| Session | Date | Track | Location | Paper | Author | Affiliation | Title | Keywords | Abstract |
|---|---|---|---|---|---|---|---|---|---|
| 1-1 | 5/19/2026 11:00 | Indoor Air Quality | SGM 123 | 26 | Bahadır Erman Yuce, Yunus Emre Cetin and Martin Kriegel | Hermann-Rietschel-Institut, Technische Universität Berlin, Marchstraße 4, 10587 Berlin, Germany; Yenişehir İbrahim Orhan Vocational School, Bursa Uludağ University, 16900, Bursa, Türkiye | Comparison of Particle Deposition under Air Curtain and Mixing Ventilation in a Negative-Pressure Two-Bed Ward | Air curtain Patient ward Cross contamination Deposition | Air curtain ventilation (ACV) has been proposed as a primary ventilation strategy for infection control in multi-bed wards, yet its influence on particle deposition relative to conventional mixing ventilation (MV) remains insufficiently studied. This work employs computational fluid dynamics (CFD) to compare deposition rates and spatial distribution of expiratory particles in a negative-pressure two-bed ward ventilated either by ACV or MV. Both patients were modeled as sources releasing particles with diameters of 1 µm and 10 µm. The results show that deposition patterns vary markedly between the two ventilation strategies. Under MV, deposited particles were more uniformly distributed across the ward, increasing the risk of cross-contamination between beds. In contrast, ACV established a more directional airflow, which confined deposition closer to the emitting patient and reduced the transfer of particles to the neighboring bed. These findings indicate that air curtain ventilation can modify both the magnitude and location of particle deposition, thereby limiting cross-contamination and offering a promising alternative for infection mitigation in negative-pressure patient wards. |
| 1-1 | 5/19/2026 11:00 | Indoor Air Quality | SGM 123 | 41 | Gerrid Brockmann and Martin Kriegel | Technische Universität Berlin | A numerical investigation about the influence of combined exhaust positions on ventilation effectiveness | air change efficiency contamination removal effectiveness CFD mixing ventilation indoor air quality | This study investigates the influence of combining multiple exhaust air positions on ventilation effectiveness in mechanically ventilated spaces using slot and swirl diffusers for the supply air distribution. By systematically testing different paired exhaust configurations, the analysis examines their impact on air change effectiveness (ACE) and contamination removal effectiveness (CRE). The results show that the ventilation effectiveness of combined exhaust configurations generally falls between the values of the individual positions, observed across tested scenarios. To simplify the analysis under a one-vortex airflow characteristic, the ACE of combined exhaust positions can be reasonably approximated by averaging the ACE values of the individual exhaust locations. CRE includes the position of the contamination source. Close distance between the source and the exhaust in line of the airflow pattern increase the CRE. The probability rises with multiple exhaust positions. Findings from this study align with prior observations by Hayashi et al., indicating that the distribution of exhaust airflow between multiple outlets has minimal influence on the airflow pattern, reinforcing the independence of ventilation effectiveness from the volume flow ratio under stable vortex conditions. These insights support the practical design of exhaust configurations in room ventilation systems by highlighting that combining exhaust positions can reduce ACE. |
| 1-1 | 5/19/2026 11:00 | Indoor Air Quality | SGM 123 | 134 | Chaimin Hong, Inseo Jeong, Sanghoon Park | Department of Architectural Design and Engineering, Incheon National University, Incheon, Republic of Korea; Division of Architecture and Urban Design, Incheon National University, Incheon, Republic of Korea | Performance Evaluation of Window-Type Ventilation Systems: A Comprehensive Methodology and Experimental Validation | Window-type ventilation system Pilot experiment Performance evaluation method Indoor air quality Airtightness | Recently, infectious diseases like COVID-19 have prioritized indoor air quality (IAQ), highlighting the critical importance of effective ventilation. Concurrently, deteriorating outdoor air quality caused by particulate matter (PM) significantly hinders natural ventilation. Window-Type ventilation systems offer a solution by mechanically introducing outdoor air while mitigating pollutant ingress via filtration. However, installation requires partial window opening, potentially compromising the original fenestration's airtightness and sound insulation. A regulatory gap exists, as current standards lack clear definitions for these systems, focusing narrowly on ventilation capacity. Therefore, this study proposes a comprehensive methodology to evaluate the multifaceted performance of window-type systems, assessed via pilot experiments. The evaluation framework covers ventilation, IAQ, airtightness, sound insulation, and view quality, adapting relevant ISO and KS standards. Performance was compared between two scenarios: a baseline without the device and an operational state with the installed system. Results confirm the system effectively accelerates CO₂ decay and improves overall IAQ. Furthermore, key metrics such as airtightness and sound insulation are largely maintained. A trade-off was observed in the reduction of transparent window area. In conclusion, this study presents a validated methodology for the integrated assessment of window-type ventilation systems. Findings underscore the need for standardization and inform the development of advanced systems balancing ventilation efficacy with critical building performance factors. |
| 1-1 | 5/19/2026 11:00 | Indoor Air Quality | SGM 123 | 427 | Saeid Chahardoli, Avijit Sarker, Mina Lesan, Yi Xiao, Andrew Z Johannsen and Arup Bhattacharya | Assistant Professor in Construction Management at LSU; Computer Science at LSU; Computer Science, South Dakota School of Mines & Technology; Construction Management at LSU | SIMOC-Inspired Mesh Sensing and Combinatorial Bayesian Optimization of Classroom Air-Purifier Placement | 1- Indoor air qualit 2- mobile robot 3- air purifier placement 4- combinatorial Bayesian optimization 5- wireless mesh | Optimizing indoor air quality (IAQ) in educational environments not only can improve occupants' health and productivity but also can provide assistance to optimize energy constraints. One of the effective strategies is the optimal placement of portable air purifiers, which can help with pollutant removal and uniform air distribution. This work presents a novel approach using SIMOC-inspired sensing and networking architecture that couples a mobile robot equipped with IAQ sensors and another set of sensors installed in a grid inside a classroom. A mesh of fixed nodes and the robot continuously measured CO₂, particulate matter, temperature, and relative humidity. Next, data was transported over MQTT and aggregated to visualize the transient changes in dynamic particulate movements. The purifiers were moved over a predefined set of locations. During each scenario of filter placement, the sensors were arranged in a grid, and the robot was used to record the data. In order to intelligently select the most promising pair of purifier locations, Combinatorial Bayesian Optimization was used. Then, the performance of the model was compared against simpler baseline strategies, such as random placements and locations typically recommended by the literature, to measure the effectiveness of the model. Using the mobile-plus-grid workflow, pollutant concentration fields were rapidly mapped across all trials. As a result, superior purifier placements were identified where both space-average and peak concentrations were reduced. Furthermore, even within a limited number of experiments, spatial uniformity could be improved compared to baseline operations. The system is readily extensible to additional robots on the same mesh to accelerate exploration, recognizing deployment time as a practical constraint. The results indicate that data-driven placement, including employing real-time data measurements, can be used to configure optimum placement for portable purifiers to improve IAQ levels in educational spaces. |
| 1-1 | 5/19/2026 11:00 | Indoor Air Quality | SGM 123 | 558 | Vincenzo Gentile and Marco Perino | Politecnico di Torino - DENERG | Low-cost & fast response multi-tracer multi-point gas sensing network for ventilation and interzonal flows measurements | tracer gas low cost sensors ventilation IAQ air interzonal exchange air flow rate measurements | The assessment of ventilation performance and interzonal airflows is essential both for ensuring indoor air quality (IAQ) and for understanding the risk of airborne cross-infection in buildings. Conventional tracer gas methods, typically relying on photoacoustic spectroscopy (PAS), remain limited by high costs, logistical complexity, and restricted temporal resolution. This study introduces a novel low-cost, fast-response sensing system designed for multi-tracer and multi-spot applications. The platform integrates Non-Dispersive Infrared (NDIR) detectors and wireless communication, enabling the simultaneous monitoring of different tracer gases—sulfur hexafluoride (SF₆), propane (C₃H₈), and carbon dioxide (CO₂)—across multiple zones. The use of multiple tracers allows the characterization of interzonal mass exchange pathways, while the distributed sensor network provides spatially resolved data with high temporal resolution (up to 50 Hz). Laboratory validation against a reference PAS confirmed measurement accuracy within ±20% for ventilation rates between 1 and 10 air changes per hour (ACH). Beyond traditional single-zone assessments, the proposed system demonstrates the capability to capture transient airflow phenomena and quantify interzonal exchange rates with a single equipment, offering a practical and scalable tool for real-time IAQ monitoring, ventilation effectiveness evaluation, and infection risk assessment in buildings. |
| 1-2 | 5/19/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 71 | Weiyu Shih, Kyosuke Hiyama, Yuya Baba and Ryosuke Kinoshita | Graduate School of Science and Technology, Meiji University, Japan; Nikken Sekkei Ltd; School of Science and Technology, Meiji University, Japan | Energy Conservation and Performance Verification of Air-Conditioning Systems in a University Building with a Large-Scale Learning Commons | University Facilities Learning Commons Air-Cooled Modular Chillers Heat Source Coefficient of Performance (COP) Water Transportation Factor (WTF) | In recent years, learning commons have been increasingly introduced into university buildings as spaces that promote active learning among students. This study reports on the operational outcomes of energy conservation strategies implemented in the air-conditioning system of a university building designed with a large-scale atrium serving as a primary circulation space and accommodating a learning commons to encourage active use. The learning commons in the target building is planned with an underfloor air distribution (UFAD) system to condition the occupied zone, thereby mitigating thermal disturbances caused by its connection to the atrium. A similar UFAD system is also applied in a high-ceiling library space. Since UFAD systems generally operate with higher supply air temperatures, the chilled water supply temperature can also be set higher. In addition, lecture rooms are equipped with a ceiling radiant air-conditioning system, which similarly requires a higher chilled water temperature to prevent condensation. Based on these characteristics, the building adopts a central heat source system utilizing high-efficiency air-cooled modular chillers. Two separate chilled water distribution systems are designed: one supplying chilled water at approximately 7 °C to outdoor air-handling units, and the other supplying chilled water at approximately 10 °C to UFAD units and related equipment. Independent heat source units are installed for each system to enhance equipment performance by adjusting the chilled water temperature according to the specific requirements of each system. Performance measurements of the heat source units during operation showed that the 7 °C chilled water system achieved a coefficient of performance (COP) of approximately 5, which is close to the rated performance under Japanese Industrial Standards (JIS) conditions. In contrast, the 10 °C chilled water system exhibited a 10–20% improvement in performance compared with the rated value, confirming the energy-saving effect of adopting two chilled water systems. Furthermore, the water transportation factor (WTF), an indicator of efficient operation, remained above the threshold value of 35, demonstrating favorable performance in secondary chilled water pumping. |
| 1-2 | 5/19/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 72 | Wei Jing, Akihito Ozaki, Yusuke Arima, Younhee Choi and Sungjun Yoo | Kyushu University | Evaluation of a Peak Cooling Load Estimation Model for Radiant Systems in Large Indoor Spaces: Validation with BES and Energy Saving Analysis | Peak cooling load Large indoor space Radiant system Building Energy Simulation | Designing energy-efficient radiant systems for large-scale indoor spaces presents unique challenges, particularly when targeting comfort in only the occupied zones. This study proposes a method for estimating the summer cooling load for peak demand of radiant systems applied in large-scale spaces. In high-ceiling environments such as gymnasiums, vertical temperature stratification frequently occurs, and air-conditioning is typically needed only in the lower occupied zone. Therefore, radiant systems are commonly installed on the floor or lower walls to concentrate the cooling effect, allowing cooled air to remain in the occupied region and reducing energy use in summer. However, estimating the cooling load during the design stage is challenging, as conventional methods that assume uniform conditioning throughout the entire space often result in substantial overestimation. To address this, a peak load estimation model is developed to support the design of radiant systems targeting the occupied zone in large spaces. The model explicitly considers the treatment of heat gains from the upper unoccupied zone, including heat transfer through walls and longwave radiation of the envelope, and their effect on the thermal conditions in the occupied zone—factors often overlooked in design-oriented calculations. Its validity is confirmed by comparing the results with those from detailed unsteady Building Energy Simulation (BES), which incorporates time-dependent thermal behavior and zoning. The proposed method demonstrates acceptable accuracy, with errors within 10% compared to detailed simulations, including separate evaluations of sensible and latent cooling loads. In terms of energy performance, the proposed method significantly reduces the estimated cooling load for unoccupied zones compared to conventional whole-space conditioning approaches, thereby bringing the total load estimation closer to actual demand and helping to avoid unnecessary overestimation. These findings offer practical reference for the energy-efficient design of radiant systems in large indoor spaces. |
| 1-2 | 5/19/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 174 | Beom-Jun Kim, Sang-Hwan Park, Ye-Weon Kim, Ye-Eun Jang, Hansol Lim and Ki-Hyung Yu | Hanbat National University; Korea Institute of Civil Engineering and Building Technology | Post-Retrofit Performance Evaluation of Heat Pump Systems Using Regression-Based Benchmarking | Heat pump Building retrofit Performance evaluation Demonstration Regression-based benchmarking | The retrofit of existing HVAC systems with high-efficiency heat pumps is increasingly recognized as an effective strategy for reducing energy use, operational costs. Yet few empirical studies have verified whether retrofitted systems actually operate in line with design capacities and intended schedules. This study reports on a field-based evaluation of a hospital in Seoul, South Korea, where two air-source heat pump chillers replaced an aging chiller. The aim of this study is to determine whether the system achieved the expected cooling performance and adhered to the planned night-time operation for chilled water storage. This study introduces a workflow for post-retrofit performance evaluation using systematic monitoring, key parameter identification, and regression-based benchmarking. This approach provides a practical methodology for avoiding oversizing and improving retrofit decision-making. Hourly operational data were collected from July 7 to August 6. Cooling capacity was calculated from water temperature differentials, while power consumption was estimated from measured current and rated voltage. The cooling coefficient of performance (COP) was adopted as the primary evaluation indicator. A two-variable quadratic regression model was developed from manufacturer tables, and measured COP values were compared with this reference. Results indicated that both heat pumps predominantly operated under part-load conditions, with COP ranging from 3.3 to 8.2. Average COPs of 5.13 for Unit A and 5.11 for Unit B were within 5% of the rated part-load efficiency of 5.3, confirming close agreement with design expectations. However, schedule analysis revealed frequent daytime operation during extreme summer conditions above 30 °C, suggesting the storage tank was undersized to cover daytime loads solely through night-time charging. These findings highlight the engineering importance of properly sizing thermal storage in retrofit projects and demonstrate a transferable approach for validating post-retrofit performance with relevance for engineers and policymakers. |
| 1-2 | 5/19/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 290 | Minyoung Choi, Soo-Jin Lee, Min-Geon Park, Suyeon Hong and Jae-Weon Jeong | Hanyang University | Performance of a Hybrid Ground Source Heat Pump System with Open-Loop and Closed-Loop Ground Heat Exchangers | Ground Source Heat Pump Standing Column Well Hybrid Part-Load Performance | With decarbonization and renewable energy trends, ground source heat pump (GSHP) systems are attracting attention as sustainable technologies for buildings. GSHP systems are generally classified into two types: closed-loop and open-loop. Open-loop systems, such as the standing column well (SCW), generally have deeper boreholes and exchange heat directly with groundwater. This allows them to support a higher heat extraction capacity per borehole and meet a given building load with fewer boreholes compared to closed-loop systems. Open-loop systems with a small number of boreholes often lack operational flexibility under part-load conditions. This limitation can cause unnecessary energy losses, mainly due to excessive pump power consumption. For this reason, this study evaluated the performance of a hybrid open-loop and closed-loop system from a part-load control perspective. In this study, three cases were compared through simulation: open-loop only, the hybrid case, and closed-loop only. Case 1 used only open-loop systems to meet the entire load. Case 2 used the hybrid system in which the open-loop system handled the base load, while the closed-loop system was controlled in response to part-load conditions. Case 3 used only closed-loop systems to meet the entire load. Simulations were conducted for each case in terms of heat pump inlet and outlet temperature, pump power consumption, and the coefficient of performance (COP). Simulation results showed that using only the closed-loop systems for part-load operation provided both operational flexibility and reduced overall system energy consumption, although long-term operation led to performance degradation due to heat accumulation around the boreholes. In contrast, the hybrid system appeared to be a more effective solution for maintaining overall thermal stability and ensuring sustained system performance. |
| 1-2 | 5/19/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 358 | Mohammad Hamid, Mohammed Assad, Walid Chakroun and Nesreen Ghaddar | American Univesrity of Beirut; Kuwait University | Pulsating Impinging Jet Ventilation with floor cooling to improve thermal comfort at enhanced system performance | Impinging jet ventilation Radiative cooling floor Pulsating jet Thermal comfort | In light of global warming and increasing outdoor temperatures of future climates, solutions for reducing energy consumption are needed for heating, ventilation and air-conditioning (HVAC) systems. The impinging ventilation system (IJV) is known as low energy consumption system compared to conventional HVAC. There is significant potential of improving performance of IJV when it is combined with cool floor to increase cooling capacity and operated with pulsating flow to reduce energy consumption. This work investigates the performance of the PIJV system coupled with radiative cooling floor (RCF) in terms of meeting the occupants’ requirements of thermal comfort and enhanced at lower energy consumption. The study aims to optimize PIJV-RCF performance and improve thermal comfort while considering the pulsating frequency of the PIJV airflow and its temperature. A 3-D computational fluid dynamics (CFD) model of the flow and thermal was developed and is validated with published experimental data of the steady IJV. More over a robust bioheat and comfort model is used to predict the transient and overall thermal comfort due to the pulsating jet compared to steady IJV system. The validated CFD model and the bioheat model are then used to simulate the PIJV-RCF conditioned room and the cooled floor to predict the performance and thermal comfort at different operational parameters for a typical office space. Recommendations for optimal operation are reported and results are compared with the steady non-pulsating IJV with and without cooled floor. |
| 1-3 | 5/19/2026 11:00 | Building Technology and Performance | SGM 101 | 45 | Rossella Cottone, Stefano Fantucci, Giorgia Autretto and Miroslav Čekon | Politecnico di Torino; Slovak Academy of Sciences; Slovak University of Technology in Bratislava | High - Performance Phase Change Material - Integrated Systems for Summer Climate Optimization | Phase Change Materials (PCM) Thermal Energy Storage Passive-Night-Time cooling | Energy retrofitting and the conversion of existing buildings into dwellings are key strategies for reducing decarbonisation in the building sector and mitigating climate change. Established energy efficiency measures, such as thermal insulation, airtightness and heat recovery, have proven effective in reducing heating demand. However, as the performance of buildings improves with these approaches, they increasingly influence the overall energy balance, particularly under warm conditions. In this context, the integration of phase change materials (PCMs) into building envelope components is a promising strategy for enhancing latent thermal energy storage (LTES) and improving indoor thermal comfort in both renovations and new constructions scanarios. This study investigates the performance of an innovative integrated PCM component based on LTES principles, aimed at improving the summer performance of buildings. The proposed system consists of a 30 mm thick panel composed of paraffinic PCM impregnated in a highly porous matrix operating in synergy with a night ventilation cooling strategy. The experimental campaign was conducted on two identical test cells where the composite PCM panel was integrated into the roof of one test cell and compared to the reference without PCM. Results show that the PCM system achieved a total heat gain reduction of 23% and a 55% average decrease in peak heat flux compared with the reference configuration. The internal surface temperature decreased by up to 4.5 °C, while the operative temperature reduction reached 1.8 °C, confirming a significant improvement in indoor comfort. The observed time-lag icreased between 1 h 45 min and 17 h, demonstrating the effective thermal buffering capacity of the PCM layer. Overall, these results confirm that the application of LTES panels, combined with night ventilation strategies, effectively shifts peak loads, improves indoor thermal comfort, and reduces dependence on active air conditioning systems. The versatility of the design allows for its effective use in both existing buildings with space constraints and new constructions, contributing significantly to the optimisation of energy efficiency and the thermal comfort of the indoor spaces. |
| 1-3 | 5/19/2026 11:00 | Building Technology and Performance | SGM 101 | 303 | Yujin Kang, Ji Hun Park, Seong Taek Kang and Sumin Kim | Department of Architecture and Architectural Engineering, Yonsei University | Exploring cross-laminated timber (CLT) applications for sustainable façade design in Korea | Cross-laminated timber Façade retrofitting Sustainable building materials Energy efficiency Carbon reduction | The transition to net-zero carbon in the built environment demands innovative strategies and the adoption of sustainable construction materials. Mass timber, particularly cross-laminated timber (CLT), offers a renewable alternative capable of reducing both operational and embodied carbon in buildings. In Korea, where timber-based construction remains limited, exploring context-specific applications of CLT could provide significant opportunities for sustainable public architecture. Retrofitting reinforced concrete (RC) façades with CLT panels represents a promising pathway to enhance building performance. Leveraging the inherent thermal properties of timber, CLT façade have the potential to lower heating and cooling energy demands while enabling thinner insulation layers, which in turn reduces the carbon footprint associated with material production. This study conceptualizes a façade substitution strategy for public buildings, investigating how CLT integration could contribute to energy efficiency, carbon mitigation, and sustainability objectives. Beyond energy and carbon considerations, CLT façades exemplify the broader potential of material innovation to support environmentally responsible design. By examining opportunities and design considerations for timber retrofitting, the research provides actionable insights for architects, engineers, and policymakers aiming to integrate sustainable materials into public building projects. Ultimately, incorporating CLT into building envelopes represents a forward-looking approach to align architectural practice with climate action goals. The study underscores the potential of mass timber to enhance building sustainability, offering a pathway for resilient, low-carbon, and innovative public infrastructure in Korea. |
| 1-3 | 5/19/2026 11:00 | Building Technology and Performance | SGM 101 | 311 | Young Uk Kim, Dongchan Jin and Sumin Kim | Yonsei Unverisity | Effect of carbon material dispersion in PCM on thermal properties of cementitious building materials | Phase change materials Carbon materials Cementitious building materials Thermal properties Heat storage | Improving the thermal performance of cement building materials is an effective way to enhance building energy efficiency and indoor thermal comfort. In this study, phase change materials (PCMs) were introduced into cement-based composites via vacuum impregnation of porous lightweight aggregates. To address the inherently low thermal conductivity of PCMs, four carbon-based materials were used: activated carbon (AC), carbon nanotubes (CNTs), exfoliated graphite nanoplatelets (xGnP), and graphene. To compare the differences in mixing methods for carbon materials, samples were prepared by dispersing the carbon materials within the PCM before the morphology stabilization process, and samples were prepared by incorporating the carbon materials into the cement matrix during mixing. The samples were evaluated by compressive strength, differential scanning calorimetry (DSC), heat of hydration, thermal conductivity, and dynamic heat transfer performance tests. Conclusively, the results demonstrated that the introduction of PCMs into lightweight aggregates provided adequate heat storage capacity. At the same time, the addition of carbon materials significantly enhanced the thermal conductivity of the composites. Among the tested additives, CNTs exhibited the most significant improvement in conductivity. Although the addition of PCM resulted in a slight decrease in compressive strength, all specimens maintained values above 20 MPa, ensuring sufficient structural integrity for building applications. In dynamic heat transfer tests, carbon/PCM-modified specimens exhibited superior thermal inertia compared to conventional cement specimens, maintaining higher temperatures during the heat release phase and exhibiting enhanced energy storage and release behavior. This study highlights that combining PCM and carbon nanomaterials in cement systems is a promising strategy for developing multifunctional building materials. The synergistic effects of enhanced thermal conductivity and heat storage capacity demonstrate the potential of these composites for energy-efficient building envelopes, flooring, and interior finishes. |
| 1-3 | 5/19/2026 11:00 | Building Technology and Performance | SGM 101 | 349 | Minyoung Kwon, Jubyung Lee, Yongsik Jeong, Youngjae Lee, Juseok Kim, Shinjae Lee and Sangeun Han | SAMOO Architects & Engineers | Plug-and-Play Cartridge Facades: Assessing Energy, Carbon, and Cost in Office Renovations | smart skin cartridge façades smart renovation office building energy simulation | Renovating existing office buildings is crucial to reducing energy demand and achieving carbon-neutral targets. Among retrofit options, building envelope renovation remains a highly effective way to improve efficiency. This study evaluates five years of measured energy use data (2020–2024) from an existing office in Seoul and compares it with simulation-based smart façade renovation scenarios that incorporate different cartridge units. The baseline model was created in OpenStudio and validated in EnergyPlus 24.1, showing only a 2.71% deviation from measured data, confirming model reliability. Two renovation pathways were examined: (1) a conventional renovation sequence involving thermal insulation, high-performance windows, solar shading, and efficient HVAC systems; and (2) a smart renovation scenario integrating façade-based solutions in a stepwise manner. Results for the conventional pathway indicate modest savings: insulation lowered energy use by 0.6% and carbon emissions by 0.4%. Window upgrades achieved 3.1% and 2.1% reductions, shading 3.6% and 2.4%, and high-efficiency HVAC 5.6% and 4.2%. Overall, the conventional sequence achieved energy savings of 0.6–5.6% and cost reductions of 0.6–4.7%. The smart renovation extended façade retrofits with advanced integration. The first stage introduced a FIT frame retrofit, resulting in a 9.6% reduction in energy use. Adding a skin cartridge with vertical louvres improved savings to 10.5%, while dynamic louvre control raised the improvement to 11.2%. The most significant impact was observed when an air-handling cartridge with a Fan Terminal Unit (FTU) system was integrated, resulting in a 22.9% reduction in total energy use. These measures also reduced carbon emissions by 7.8–14.8% and improved energy cost efficiency by 8.1–15.7%. The results demonstrate that smart façade-integrated retrofits outperform conventional measures. By combining smart envelope integration with an active system, smart renovation provides greater efficiency, reduced emissions, and long-term adaptability for sustainable building operations. |
| 1-3 | 5/19/2026 11:00 | Building Technology and Performance | SGM 101 | 355 | Yonca Yaman, Ayça Tokuç, Mehmet Akif Ezan, Gülden Köktürk, Zeliha Demirel and İrem Deniz | Department of Architecture, Dokuz Eylül University, 35390, İzmir, Türkiye; Department of Bioengineering, Ege University, 35040, İzmir, Türkiye; Department of Bioengineering, Manisa Celal Bayar University, 45140, Manisa, Türkiye; Department of Electrical and Electronics Engineering, Dokuz Eylül University, 35390, İzmir, Türkiye; Department of Mechanical Engineering, Dokuz Eylül University, 35390, İzmir, Türkiye; Dokuz Eylül Üniversity Department of Architecture | Bioreactive Skins: Evaluating Microalgae Façade Systems for Thermal and Daylighting Performance in Los Angeles | Building energy simulation building façades microalgae thermal comfort visual comfort | Façade-integrated photobioreactors are sustainable architectural elements due to their ecological, economic, and environmental benefits. Similar in appearance and application to curtain walls, their applications as green and bioreactive windows seem promising. However, challenges in modeling building physics parameters such as daylighting and thermal control often hinder feasibility studies to research their applicability. This paper aims to propose a methodological framework to evaluate the impact of different microalgae species on occupant comfort when integrated into building façades. The study focuses on Los Angeles climate and investigates the year-round total energy consumption, lighting and thermal comfort performance of two distinct microalgae strains. The method involved measuring light transmittance of algal cultures in different concentrations; then using these to calculate solar heat gain coefficients and visual transmittance levels for defining photobioreactor systems for building performance simulation using Grasshopper plugins, Honeybee and Ladybug. Three distinct façade design (FD) scenarios were optimized in terms of algae density, window-to-wall ratio, wall type and thickness, insulation thickness, and heating/cooling setpoints. Results indicate that photobioreactor façades have significant potential to enhance thermal comfort, improve daylighting performance, and reduce energy consumption throughout the year. Viable alternatives exist for both strains; however, their effects differ: Pseudanabaena sp. demonstrated 26-44% improvement in mean thermal comfort violation (TCV) across all three façade designs compared to C. vulgaris, attributed to its lower solar heat gain coefficient. FD1, consisting solely of algae-integrated windows, showed better thermal comfort while hybrid designs were sensitive to the placement of algae windows. Regarding daylighting, FD3 achieved highest mean useful daylight illuminance (UDI ~47%) for both species, though with greater spatial non-uniformity. Energy performance revealed configuration-dependent optimal species selection. Sensitivity analysis revealed hierarchical parameter influence: cooling setpoint demonstrated dominant effect on both energy and thermal comfort, while window-to-wall ratio (WWR) affected daylighting the most. Optimal solutions for Los Angeles require performance-priority-specific selections: FD1 with Pseudanabaena sp. (30-45% concentration) for thermal comfort prioritization, FD2 with C. vulgaris (30-35% concentration) for energy optimization, and FD3 for daylighting maximization. This research demonstrates a comprehensive, transferable methodology that enables comparative studies while presenting design guidelines for Los Angeles PBR façade applications. |
| 1-3 | 5/19/2026 11:00 | Building Technology and Performance | SGM 101 | 482 | Soyoen An, Minseong Kim, Taeyeon Kim, Hyokung Sung and Jae-Weon Jeong | Hanyang University | Retrofit of Thermoelectric Moule-Based Thermally Activated Insulation Panel for Apartment Buildings | Thermoelectric-Module Active Insulation Panel Retrofit Building Simulation Energy Efficiency | A large portion of multi-family housing in South Korea was constructed before 2000, and their building envelopes have experienced performance degradation over time due to material aging and the long-term decline of windows and other envelope components. This deterioration increases actual energy consumption compared with original design targets, with reduced thermal performance of insulation and windows directly contributing to higher heating and cooling loads. Conventional retrofit measures, such as insulation reinforcement and window replacement, provide proven energy savings but face limitations from extensive structural alterations, changes to building appearance, and regulatory constraints. To address these issues, this study introduces a thermoelectric module (TEM)-based thermally activated insulation panel capable of actively controlling the effective thermal transmittance (U-value) with minimal structural modification. The proposed panel employs the Peltier effect, which generates a temperature difference under electrical input, and the Seebeck effect, which generates electricity from a temperature gradient, to regulate heat transfer through exterior walls. This mechanism can theoretically reduce the effective U-value of the wall toward zero, thereby compensating for insulation degradation. Results show that, compared to the baseline building, heating loads decreased by 22.51% (1782.6 → 1381.2 kWh/year) and cooling loads by 7.14% (1390.8 → 1291.4 kWh/year). Including the panel’s electricity consumption, the total annual energy consumption was reduced by 14.45%. These findings demonstrate that the proposed system is an effective supplemental insulation technology for mitigating thermal weaknesses in existing buildings and has strong potential as a practical, scalable retrofit solution for improving energy efficiency. |
| 1-4 | 5/19/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 25 | Mar Hernandez and Roberto Alonso González Lezcano | Universidad CEU San Pablo | Methodology for determining Indoor Environmental Quality (IEQ) in residential buildings for the elderly by monitoring key environmental parameters. | Indoor environment quality acoustic comfort melanopic luxes indoor air quality occupants' habits | People spend most of their time indoors; therefore, it is essential to ensure good indoor environmental quality (IEQ), ensuring healthy, comfortable and energy-efficient conditions. This paper proposes a methodology to develop an Indoor Environmental Quality Index for housing inhabited by elderly people, considering indoor environmental factors such as lighting (photopic and melanopic), acoustics, hygrothermal comfort and indoor air quality (temperature, relative humidity, CO2, volatile organic compounds), with the purpose of helping both users and building professionals and designers to identify possible deficiencies in the indoor environment, without compromising environmental quality in favour of energy efficiency. Based on the combined effect of these environmental indicators, the aim is to develop an index that reflects a dimensionless value of the quality of indoor environmental conditions during the period monitored and surveyed, in compliance with national and international technical standards, such as ASHRAE or UNE, as well as WHO recommendations. The application of the Indoor Environmental Quality Index in multi-family dwellings for elderly people will be validated in order to demonstrate its usefulness. This index is an indoor environmental quality metric that will provide a simple and concise assessment of the indoor environment for scientists, professionals and users of the dwellings. One of the main strengths of the index is its ability to appropriately weight the different indicators of indoor environment quality. The calculations are based on actual monitoring and surveys developed specifically for multi-family residential buildings and are able to sufficiently inform both occupants and professionals about indoor environmental conditions. This study can help to avoid overshadowing other addressable indoor environmental problems. Furthermore, the proposal seeks to lay the groundwork for future research applied to other groups classified by vulnerability and/or age and other building typologies. |
| 1-4 | 5/19/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 98 | Koga Nakamura and Tatsuya Hayashi | Department of Architecture and Urban Science, Graduate School Engineering, Chiba University; Department of Architecture, Graduate School of Science and Engineering, Chiba University | Impact of Office Environmental Performance on Corporate Value: An Objective Data Analysis in Human Capital Management | Wellness office CASBEE-Wellness Real Estate Human Capital Management Corporate Value | The built environment profoundly shapes health, well-being, and human behavior. In Japan, the Ministry of Economy, Trade and Industry has elevated human capital management through its Human Capital Management Guidelines, which treat people as capital and aim to maximize their value for medium- to long-term growth. Although such investments are expensed and can weigh on near-term profits, recognition is growing that sustainable value creation depends on intangible assets. Therefore, quantitative evidence linking human capital investment to corporate value is needed. It is also necessary to demonstrate its relevance to corporate managers and investors. This study clarifies whether better office environmental performance, considered a human-capital investment, relates to workforce outcomes and corporate value. The sample covers 69 office properties used by 137 publicly listed companies as of April 2024. Office performance was assessed with CASBEE-Wellness Real Estate (trial version), part of the widely used CASBEE family. While CASBEE-Wellness Office targets new construction, the Real Estate version is a simplified tool for existing office buildings and aging stock. Data combine objective building scores with firm attributes, indicators of human-capital investment outside the office, and employee-reported outcomes from statutory disclosures and a workplace review platform. Corporate value is proxied by return on equity (ROE) and price-to-book ratio (PBR), using five-year averages (FY2019–FY2023) and growth rates. Correlation and multiple-regression models control for firm characteristics and human-capital investment factors. Results show statistically significant positive associations between CASBEE-Wellness Real Estate scores and “three-year employee retention” as well as “perceived openness of communication”, outcomes linked to mental health and organizational connectedness. However, no direct relationships were found with short-term financial indicators, suggesting that wellness-oriented upgrades first register in human and behavioral domains before affecting market valuation. These findings suggest that office environmental performance may have a certain positive effect on enhancing human capital in the context of promoting human capital management. Although short-term financial effects are not evident, workforce-related benefits, including improvements in office environments, may form part of the foundation for sustained organizational performance and, over time, could also support broader societal well-being. |
| 1-4 | 5/19/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 106 | Mateus Pedrosa Braga, Iasmin Lourenço Niza and Evandro Eduardo Broday | Federal University of Technology - Paraná (UTFPR) | The Influence of Seasonality on Indoor Environmental Quality Parameters in Brazilian University Classrooms | Indoor Environmental Quality Seasonality University Classrooms ANOVA IEQ | Indoor environmental quality is a key factor in ensuring the well-being, comfort, and optimal performance of activities carried out by occupants. In classroom environments, where high levels of concentration must be maintained for extended periods, indoor conditions play a significantly more critical role. In this way, it has become relevant to investigate indoor environmental conditions, as people spend a significant amount of time inside buildings. Indoor conditions can change significantly throughout the year, and these changes, often caused by the seasons, directly impact the well-being, learning capacity, and satisfaction of those who use the indoor space. This study analyzed classrooms at a university in southern Brazil to understand how the environment changes between summer, autumn, winter, and spring and how it can affect students. A one-way analysis of variance (ANOVA) was used to verify if there are any significant differences between the seasons throughout the year. To perform this research, a set of 100 data was collected between March 2024 and June 2025 using the equipment Aura IEQ Discoverer®. Operative temperature, relative humidity, illuminance (lux), CO₂ concentration, volatile organic compounds (VOCs) levels and noise (dB) were analyzed to identify which differences are important and how significant these variations are. Volatile Organic Compounds (VOCs) varied significantly throughout the year. At the same time, the concentration of carbon dioxide (CO₂) did not show statistically significant differences between seasons, remaining consistently high at approximately 1000 ppm throughout the year. This enables the proposal of specific seasonal strategies, such as adjusting ventilation, optimizing lighting, reducing pollutants, and controlling noise. These results can help create building management policies that bring more comfort to users, save energy and maintain air quality, contributing to healthier and more sustainable educational spaces for the development of the activities. |
| 1-4 | 5/19/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 111 | Clara Peretti, Alberto Lodovico Ghiberti and Enrico Fabrizio | Free Consultant; Politecnico di Torino, Department of Energy | Analysis and monitoring of environmental conditions and well-being in remote working environments in northern Italy | Indoor Environmental Quality (IEQ) Remote working IEQ monitoring Subjective analysis | Scientific literature highlights that remote working can help workers balance their work and personal lives while also increase their productivity, but this aspect is still a source of debate and requires further study. In addition to employees working, self-employed workers also carry out activities from their homes, which is why this issue is still of great interest today. This research focus on monitoring and analysis of indoor environmental quality (IEQ) in buildings where hybrid and remote work is carried out in mountain areas in northern Italy. The aim is to determine how the physical characteristics of remote working environments affect worker satisfaction and well-being, by researching patterns and correlations between the various variables monitored. The objectives described is studied through multi-parameters devices (thermal, lighting, acoustic environments and indoor air quality) and subjective analyses applied to seven case studies in three measurement periods: summer, mid-season and winter. The duration of monitoring depends on the time of use of the rooms and is approximately two weeks for each selected period. The environmental parameters monitored by integrated devices, such as temperature, relative humidity, CO2, radon, dust, TVOC, pressure, illuminance (lux) and noise level, are then analysed using the UNI EN 16798-1 standard, which defines four categories of IEQ. The subjective analysis through online questionnaires delves deeper into occupants' perceptions of indoor parameters and the ease with which they can modify their environment to increase comfort. The usability of multi-parameter domestic instruments for IEQ parameters is also analysed, in order to determine ease of use, data download and interpretation. This work is part of the NODES project, Spoke 4, Flagship project SMARTWEST, funded by the European Union - NextGenerationEU, Mission 4 Component 2 - ECS00000036 - CUP E13B22000020001. |
| 1-4 | 5/19/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 230 | Shunsaku Uozumi, Koga Nakamura and Tatsuya Hayashi | Department of Architecture and Urban Science, Graduate School of Engineering, Chiba University; Department of Architecture, Faculty of Engineering, Chiba University; Department of Architecture, Graduate School of Science and Engineering, Chiba University | Wellness Offices in Japan: An Empirical Analysis Based on CASBEE-Wellness Office | CASBEE-WO wellness certification ESG investment building performance resilience | In recent years, with the global expansion of environmental, social, and governance (ESG) investment, the adoption of certification systems that evaluate not only the environmental performance but also wellness aspects of buildings has gained increasing attention. While WELL and Fitwel have become widely adopted certifications focusing primarily on health and comfort, in Japan, CASBEE-WO (Comprehensive Assessment System for Built Environment Efficiency–Wellness Office) was introduced in June 2019. CASBEE-WO is distinctive in that, in addition to worker health, workplace productivity, it incorporates resilience, safety, disaster preparedness, reflecting Japan’s particularly high exposure to natural hazards. This study investigates the status of CASBEE-WO and the characteristics of certified properties, five years after its launch, when the number of certifications had reached 209 as of August 2025. Of these, 176 properties with sufficient data were analyzed. In addition to overall scores and category-specific evaluations, building attributes such as certification rank and certification pattern were examined. The results show that within category Qw.1, which measures health and comfort, “Interior planning of common space” received the highest evaluations, and the spatial and interior design categories generally scored highly. By contrast, comfort-related items such as “Smoke isolation and prohibition”, “Room temperature”, and “Natural ventilation performance” tended to receive relatively lower scores. The relationship between rank and total score indicated that many properties were concentrated near the threshold values for rank divisions, suggesting that applicants are highly conscious of rank acquisition. Scale-based analysis further revealed that large-scale buildings (over 16,529 m²) achieved higher scores than medium-scale buildings, and that most properties exceeding 150,000 m² obtained the highest rank, S. In conclusion, compared with comfort-related measures, aspects more visible to building occupants, such as interior planning, tended to be prioritized. Moreover, the findings confirm that, particularly in large-scale buildings, S-rank certification is strategically pursued as a form of brand value, indicating that CASBEE-WO has been recognized as a credible structure for assessing wellness and resilience in office buildings. |
| 1-4 | 5/19/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 397 | Shundong Li and Nan Ma | Worcester Polytechnic Institute | Large Language Models for Investigating Co-Occurrences in Multi-Domain Indoor Environmental Quality | LLMs IEQ occupant wellbeing social media text mining | Building occupants are continuously exposed to multiple indoor environmental stimuli, including thermal, visual, acoustic, and indoor air quality (IAQ) related factors. Prior research typically examines these multiple stimuli separately. However, our understanding of how problems in different indoor environmental quality (IEQ) domains frequently co-occur and the extent to which they lead to occupant dissatisfaction remains very limited. This limitation stems from the labor-intensive, costly, and time-consuming nature of collecting observational data for a substantial number of buildings and their occupants. In this study, we introduce a state-of-the-art large language modeling (LLM) approach to text-mine social media data from 12 major U.S. cities and identify multi-domain IEQ issues. Our advanced domain-adaptive LLM was developed based on the large-sized BART model and fine-tuned using a zero-shot natural language inference (NLI) corpus, complemented by a domain-specific vocabulary dictionary to enhance the integration of domain-specific knowledge. From 4.2 million collected reviews, our model identified over 230,000 occupant comments related to IEQ, among which 27,733 reviews discussed more than one IEQ topic. Analyzing the multi-domain IEQ reviews revealed that noise pollution is a dominant concern in the U.S., most frequently co-occurring with IAQ and, to a lesser extent, thermal discomfort. We also discovered that cities such as Los Angeles, Mexico City, Chicago, New York, and Miami are more prone to encounter multidimensional IEQ issues. These cities particularly show divergent sentiment scores across different IEQ domains, with one domain receiving extremely positive evaluations while others notably negative. Our findings highlight the importance of addressing co-occurring IEQ factors affecting occupant behavior and well-being. By applying LLMs to large-scale occupant reviews, we offer a new way to better understand what drives occupant satisfaction in the built environment. |
| 1-5 | 5/19/2026 11:00 | Thermal Comfort | GFS 101 | 68 | Vincenzo Costanzo, Gianpiero Evola and Michele Torrisi | University of Catania | Selecting and testing Personal Comfort Systems (PCS) in office spaces in a Mediterranean climate: first insights from in-situ surveys | Thermal comfort Personal Comfort Systems Office Building Experimental campaign | Personal Comfort Systems (PCS) can provide a quick and effective way to ensure thermal comfort for people inside buildings. This hypothesis can be duly tested in the case of office buildings, where workers spend most of their daily time in indoor conditions that can negatively impact their health, work productivity, learning performance, and well-being. The Comfort for All (COM4ALL) research project aims to demonstrate how it is possible to improve users’ comfort in office buildings while reducing energy expenditures for heating and cooling spaces through a detailed understanding of individuals' personal comfort responses and the concomitant use of PCS. This paper presents the preliminary results obtained by the project by first discussing the process of selecting and testing a series of commercially-available PCS in terms of acceptability from the users and effectiveness in improving comfort conditions for different individuals. Then, their integration in both single and shared office spaces is presented for a case study building located in the Mediterranean city of Catania (Italy), where indoor layouts, thermal conditions and HVAC systems are characterized through an experimental campaign. Results show that PCS can effectively be used for improving an individual’s comfort sensation in both individual and shared spaces without negatively affecting surrounding people and at a very small power demand (from 12 W of a tower fan up to 150 W for a heated keyboard and mouse pad). Based on these promising outcomes, activities are ongoing to test various PCS during the entire heating and cooling periods in order to estimate the potential energy savings. |
| 1-5 | 5/19/2026 11:00 | Thermal Comfort | GFS 101 | 109 | Kyoungmin Lim, Jihyun Yoo, Junseok Park, Chungyoon Chun, Sanghun Kim, Seokwon Seo and Namshin Kim | Dept. of Architectural Engineering, Hanyang University, Seoul, Republic of Korea; Dept. of Interior Architecture and Built Environment, Yonsei University, Seoul, Republic of Korea; Graduate School, Dept. of Architectural Engineering, Hanyang University, Seoul, Republic of Korea; Hyundai Motor Company, Hwaseong-si, Gyeonggi-do, Republic of Korea | Determining Optimal Local Thermal Environment for a Vehicle Passenger Using Thermal Comfort Model | Thermal comfort Heat loss Equivalent temperature HVAC system Vehicle | As in buildings, HVAC systems are essential for ensuring occupants' thermal comfort and have a significant impact on energy performance in vehicles. However, thermal comfort indices designed for homogeneous indoor environments are not suitable for the locally transient and non-uniform thermal conditions found in a vehicle cabin. Several human thermophysiological models have been developed to predict local skin temperature exposed to inhomogeneous thermal environments. The local skin temperature can be used to evaluate the thermal sensation vote (TSV) or thermal comfort vote (CSV) of human body segments. This study aims to propose optimal equivalent temperatures for local body segments of a passenger seated in a driver's seat using the thermophysiological and comfort models. The equivalent temperatures were derived by analyzing the relationship between heat loss and TSV and CSV under various combinations of thermal conditions by independently controlling air temperature from −10 °C to 35 °C, radiant temperature from −10 °C to 45 °C, and air velocity from 0.1 m/s to 1.5 m/s for each local body segment. The sensible and latent heat loss on local body segments was simulated using the 65-node model (Tanabe), and local TSV and CSV were predicted by the UC Berkeley comfort model. The optimal heat loss of each body segment was determined when TSV was neutral and CSV was maximum. The optimal heat loss over body segments ranged from 22.0 W/m² to 126.4 W/m² in the winter condition (1.2 clo) and from 18.8 W/m² to 114.8 W/m² in the summer condition (0.45 clo). The thermal environment, in which the heat was optimally lost in a body segment, was expressed by equivalent temperature from ISO 14505. The results of this study can help design HVAC systems in inhomogeneous thermal environments and contribute to improved thermal comfort and energy performance in vehicles. |
| 1-5 | 5/19/2026 11:00 | Thermal Comfort | GFS 101 | 128 | Wen-Hsuan Hsu and Yun-Shang Chiou | National Taiwan University of Science and Technology | Fishbone vs. Peripheral-Ring Air-Conditioning Layouts: Spatial Thermal Variation and Occupant Comfort in Office Environments | Air-Conditioning Layout Thermal Comfort Spatial Thermal Variation HVAC Design Occupant Behavior | This study was conducted in the headquarters office of a corporation in Taichung, Taiwan, a building enclosed with high-performance Low-E glazing and aluminum panels. Occupant thermal comfort survey was conducted in the open plan offices on 9th and 11th floor. These two floors adopt different air-conditioning layouts: a peripheral-ring system on the 9th floor and a fishbone-type system on the 11th floor. This research aims (1) to compare the effects of these air-conditioning configurations on indoor thermal environments, (2) to examine the relationship between environmental parameters and subjective thermal comfort, and (3) to investigate the moderating role of individual and seating factors in comfort evaluation. Field measurements and questionnaire surveys were conducted to assess indoor thermal conditions and occupants’ perceptions. Results indicate that the fishbone configuration produces significantly greater temperature variation, both simultaneously (approx. 2.5 °C) and throughout the day (approx. 3.5 °C), suggesting larger microclimatic variability. One-way ANOVA revealed a significant interaction between perceived wind speed and humidity: higher wind speeds led occupants to perceive drier air, while lower wind speeds were associated with dampness or air stagnation. However, measured humidity showed no correlation with subjective perception, highlighting low sensitivity to humidity among occupants. GLM analysis further showed that males and individuals aged 36–40 reported lower comfort levels, while frequent overheating/overcooling and behavioral adjustments (clothing change, seat switching) were negatively correlated with comfort. Seat location also moderated temperature sensitivity, with certain positions showing higher tolerance to temperature fluctuations. In conclusion, air-conditioning configuration strongly affects indoor thermal uniformity and occupants’ comfort. Beyond physical parameters, individual characteristics, behavioral adaptation, and localized thermal variations play critical roles in shaping subjective comfort, emphasizing the need for targeted strategies in HVAC design and workplace comfort management. Moreover, effective air-conditioning design should be considered in conjunction with the building envelope and its physical environment, as the interaction between façade performance, external conditions, and HVAC systems ultimately determines the overall indoor comfort and energy efficiency. |
| 1-5 | 5/19/2026 11:00 | Thermal Comfort | GFS 101 | 176 | Tazia Rahman, Mohamed Ouf, Joyce Kim and Kehinde Bayode | Concordia University; University of Waterloo | Comparative cooling efficiency of wearable and non-wearable personal comfort systems in office settings | Personal Comfort System Wearable fans Local cooling Thermal comfort Cooling performance | Conventional Personal Comfort System (PCS), such as desk fans, can reduce perceived warmth through elevated air movement but may cause unwanted drafts that disturb nearby occupants. As an alternative, wearable devices such as face and neck fans offer targeted cooling with negligible energy consumption. Although the face and neck account for only 5.5% of the body’s surface area, cooling these highly thermosensitive areas has been shown to significantly enhance overall thermal comfort. However, direct comparisons of their cooling efficiency against conventional desk fans in office settings remain limited. This study compares the cooling effectiveness of wearable face fan (FF) and neck fan (NF) against bladed and bladeless desk fans (DF). The evaluation was conducted in a controlled office space with energy-conscious indoor temperature setpoints (25 ± 1 °C, 40 ± 5% RH). A 23-segment adaptive thermal manikin with the JOS-3 thermoregulation model was used to measure local skin temperatures (Tsk), heat flux (P), equivalent temperature (Teq) and predicted mean vote (PMV). Results show that thermal comfort improvements from the wearables closely match the performance of the bladeless DF. Notably, a high-speed FF provided a level of thermal comfort equivalent to that of a low-speed bladed DF (PMV ~0.7). The corrected power in terms of heat loss (CPQ) was significantly improved by the wearable fans, with local heat reductions of up to 7W at the face and 4W at the neck. These findings indicate that targeted breathing-zone cooling can deliver whole-body comfort comparable to cooling from desk fans, offering a practical, energy-efficient solution for open-plan offices without affecting nearby occupants. |
| 1-5 | 5/19/2026 11:00 | Thermal Comfort | GFS 101 | 223 | Shiying Li, Yifan Wu and Borong Lin | Department of Building Science, Tsinghua University | Thermal comfort benefits using a convective–radiative Personalized Environmental Control System for intermittent heating | Personalized Environmental Control System convective–radiative thermal comfort intermittent heating corrective power | In intermittent heating scenarios, conventional terminals such as fan coil units and underfloor heating often struggle to simultaneously deliver rapid thermal response and satisfactory occupant comfort. Personalized Comfort Systems (PCS) have emerged as a promising solution to address differentiated thermal demands and improve individual comfort in indoor environments. In this study, a convective–radiative coupled Personalized Environmental Control System (C-R PECS), integrating the characteristics of rapid thermal response from convective heating and better thermal comfort from radiant heating, was proposed and prototyped to enhance occupant comfort during intermittent heating. To evaluate its performance, both thermal manikin and human subject experiments were conducted in a climate chamber under room temperatures ranging from 16 to 20 ℃, with 16 participants involved in the tests. In the experiments, the C-R PECS was operated following a convection-first and subsequently radiation strategy. Results from the thermal manikin showed that the heating rate of the C-R PECS reached 0.16 K/min, which was approximately 4 times higher than that of the single radiant mode, and the maximum whole-body equivalent temperature difference (∆teq) could reach 2.5 K. The most significant effect was observed in the lower leg region, where the ∆teq reached 4.4 K—thereby achieving the desirable "cool-head–warm-feet" effect. Subjective evaluations further demonstrated that under thermally non-neutral conditions (18 ℃), participants using the C-R PECS achieved a corrective power (CP) of 3.2 K within 10 minutes, which was maintained until the steady state, effectively enhancing thermal sensation and overall comfort.These findings confirm that the C-R PECS, as an innovative design strategy, can significantly enhance thermal comfort in intermittent heating applications, offering both rapid response and localized thermal comfort. |
| 1-5 | 5/19/2026 11:00 | Thermal Comfort | GFS 101 | 491 | Rosa Seo, Chul Kim and Kyu-Nam Rhee | Pukyong National University; Yonsei University | Impact of Thermally Activated Internal Louvers on Occupants’ Thermal Comfort | Thermally activated internal louver Subjective evaluation Thermal comfort Perimeter zone | Shading devices are widely adopted in conjunction with high-performance building envelopes to mitigate heat losses. Traditionally designed for daylight control, shading systems are currently have been attempted to integrated with active strategies to directly influence indoor thermal conditions and occupants. In this study, the performance of a Thermally Activated Internal Louver (TAIL) which is integrated into an internal daylight louver with hydronic pipes was examined based on subjective evaluation. The TAIL was installed in a test bed which simulates a private or small office. Since the test bed’s main HVAC system was a fan coil unit (FCU), to evaluate effects of TAIL, subjective evaluation was conducted with 36 occupants under two experimental cases—FCU and FCU+TAIL—at a fixed louver angle of 45° with supply water temperature 12°C. Test-bed set temperature for cooling season was set at 26 °C, while an artificial climate chamber adjacent to the perimeter zone simulated summer boundary conditions with 30 °C outdoor air temperature and solar radiation with solar simulator. Subjective thermal comfort was analysis according to thermal sensation votes (TSV), overall thermal comfort (OTC), overall thermal preference (OTP), and overall thermal acceptability (OTA), while objective parameters were assessed with air temperature and predicted mean vote (PMV). The results indicate that TAIL operation reduced the perimeter zone air temperature by up to 1.39 °C and PMV decreased by 0.43 compared to the FCU case. TSV in the perimeter zone decreased by up to 3 points, while OTC and OTP improved by 0.34 and 0.36 on average with FCU+TAIL case. OTA remained consistently acceptable at almost 1 regardless of the experimental case, confirming occupants’ acceptability. Overall, this study demonstrates that hydronic integrated louvers can satisfy not only lighting environment but also provide active perimeter zone cooling. These results highlight the potential of TAIL systems as a sustainable strategy for enhancing thermal comfort and reducing cooling energy demand in office environments. |
| 1-6 | 5/19/2026 11:00 | Smart Cities and Green Infrastructure | GFS 118 | 51 | Chao Lin, Hideki Kikumoto, Yasutomo Takakuwa and Ryozo Ooka | Institute of Industrial Science, The University of Tokyo | Optimizing Parapets for Rooftop Wind Safety Using CFD Simulations and Sensitivity Analysis | Rooftop CFD Optimization Parapet | The complex rooftop wind environment, dominated by flow separation at building edges, presents safety challenges for rooftop activities such as roof gardens and urban air mobility (UAM) operations. This study investigates the wind sheltering performance of rooftop parapets on a 40 m-high isolated building using computational fluid dynamics (CFD) simulations under a 0-degree wind direction. A total of 729 simulations are conducted, systematically varying the parapet height (0–4 m in 1 m intervals) and porosity (solid or 40%) across the upwind, two sides, and downwind edges. Configurations of the two side parapets are kept identical across all cases. CFD results for solid parapets are validated against wind tunnel measurements at a 1:200 scale, showing good agreement. Wind conditions are evaluated using volume-averaged statistics within the 0–2 m height range above the rooftop surface, corresponding to the typical occupied zone during rooftop use. Results reveal that different parapet configurations can cause rooftop wind speed to vary between a 50% reduction and a 12% increase, turbulent kinetic energy between a 72% reduction and a 2% increase, and total kinetic energy between a 60% reduction and a 10% increase. Specifically, a combination of 4 m upwind and side parapets with solid porosity and without setting downwind parapet leads to the largest decrease in total kinetic energy. Global sensitivity analysis using the Sobol method identifies the upwind and downwind parapet heights as the dominant parameters affecting wind speed, while the height and porosity of the upwind parapet primarily influence turbulent and total kinetic energies. These findings offer guidance for optimizing rooftop parapet design to enhance wind safety in rooftop usage scenarios. |
| 1-6 | 5/19/2026 11:00 | Smart Cities and Green Infrastructure | GFS 118 | 91 | Hongyuan Jia, Chao Lin, Karine Sartelet and Hideki Kikumoto | Institut Polytechnique de Paris; The University of Tokyo; University of Macau | Bayesian inference for sources of reactive gases in urban canyons based on the adjoint method | Source term estimation Chemical reaction Bayesian inference Adjoint method Urban canyon | Although various methods have been proposed for source term estimation, they mainly focus on hazardous gases behaving as passive scalars. These methods will struggle in identifying unknown sources of reactive gases, which are common in complex urban environments. Focusing on one of the most severe atmospheric pollutions in urban areas, the NOx-O3 photochemical reactive gas dispersion, this research proposed a novel source term estimation method based on Bayesian inference and the adjoint method. Utilizing sparse measurements and background concentrations, this method can effectively identify the source terms of NO and NO2 simultaneously. To evaluate the performance of the proposed method, a case of an urban canyon in Paris was studied. The NOx gases were released from the traffic, which were line sources at the central bottom of the canyon, and their strength was measured on-site. The measurements of multiple sensors were synthesized by numerical simulations validated by on-site concentration measurements. First, assuming the unknown sources are points, the proposed method was applied to estimate source terms in continuous urban canyons based on sensors on each roof. It was found that our method can identify the exact canyon where sources were located and estimate their strength with about 10% errors. Secondly, deploying sensors in the target canyon, the proposed method was coupled with a super-Gaussian function to estimate the location, shape, and strength of NOx sources. Our method successfully estimated the length and width of sources by using 4 sensors located at roadsides and roofs. When sensors increased to 7, the strength estimation errors could be controlled within 5%. The heights of sources were found to be the most difficult term because sources were close to the bottom wall and flows were strongly circulated in the canyon, making the adjoint concentration simulation biased. In addition, the conventional Bayesian approach for passive scalars has failed in both multiple and single canyon cases, demonstrating the necessity and advantages of our method. |
| 1-6 | 5/19/2026 11:00 | Smart Cities and Green Infrastructure | GFS 118 | 119 | Haruka Nishiyama and Yasuyuki Ishida | Tohoku University | Effects of Crown Shape, Leaf Area Index , and Tree-Planting Interval on Multifaceted Benefits of Urban Trees | Street trees Thermal comfort Transpiration Unsteady radiation and conduction simulation | Urban trees, such as street trees, have various effects on their surrounding environment, including solar shading, transpiration, and wind-speed reduction. Many researchers have studied the prediction and modelling of these effects. However, the relationship between the morphological parameters of tree crowns and their effects on the thermal and wind environments in pedestrian spaces has not been sufficiently analyzed and quantified. We conducted case studies based on unsteady radiation and conduction simulations by systematically varying the crown shape of trees, leaf area index (LAI), and tree-planting interval, focusing on tree transpiration and thermal radiant environment at pedestrian height. The results showed that trees with Zelkova-type crowns were more effective in mitigating the heat island effect than those with Ginkgo-type crowns. The leaves of Zelkova are concentrated at the top of the crown, leading to increased transpiration. However, Ginkgo-type crowns were better for pedestrians because they provide more shade, resulting in lower ground temperatures and mean radiant temperature (MRT). We also quantified the increase in tree transpiration that occurred with higher LAI and wider planting intervals. Moreover, the increase in latent heat conversion from LAI of 5 to 8 was more gradual than that from LAI of 2 to 5. Based on these results, the tree species whose LAI reaches five or more have better advantage in mitigating urban heat islands. Additionally, this study showed that the planting interval had a greater influence on the thermal radiant environment than the LAI. |
| 1-6 | 5/19/2026 11:00 | Smart Cities and Green Infrastructure | GFS 118 | 211 | Youmin Xu, Xu Han, Shaoxiang Qin and Liangzhu Leon Wang | Concordia University; McGill University; University of Kansas; University of Notre Dame | High Resolution Urban Microclimate Reconstruction with Generative Diffusion-Based AI | Urban microclimate Sparse measurements Generative AI Improved denoising diffusion probabilistic model | Monitoring microclimate in urban environments is critical to sustainable and resilient city design and operations, as it plays a key role in safeguarding air quality, mitigating the urban heat island effect, and enabling environment responsive infrastructure. In practice, however, the quantities of interest are often measured with a sparse sensing network in the urban context, for example, a limited number of weather stations, which makes the monitoring of high-resolution microclimate very challenging. While computational fluid dynamics (CFD) provides superior accuracy to predict the urban microclimate, its high computational cost makes real-time prediction of urban microclimate impractical with current resources. Therefore, there is a critical need to reconstruct urban microclimates from sparse measurements at relatively low computational cost. Recent advancements in deep learning have shown promise in CFD surrogate modeling, however, their tendency to oversimplify turbulent dynamics and their difficulty in capturing multi-scale spatiotemporal interactions limit their ability to generalize to fine spatial scales and constrain their suitability for complex urban-scale microclimate applications. To address this challenge, we propose an generative AI approach based on an improved denoising diffusion probabilistic model (IDDPM) together with the maximum a posteriori–gradient ascent (MAP-GA) method to reconstruct urban microclimate variables (U, V, W, and T) from sparse measurements. The IDDPM works by starting from noise and gradually denoising it to generate high-resolution, statistically consistent turbulent flow fields, without relying on measurement data as input. Meanwhile, the MAP-GA method leverages pre-trained IDDPM to reconstruct flow fields from sparse observations by optimizing the noise input of the IDDPM to match known measurements. The model will be trained and tested on a validated CFD simulation dataset. The IDDPM model has already been trained, achieving root mean square errors (RMSE) of 0.42 m/s, 0.083 m/s, 0.43 m/s, and 0.25 °C for U, V, W, and T, respectively. Further results combining IDDPM with MAP-GA will be reported in the full paper. |
| 1-6 | 5/19/2026 11:00 | Smart Cities and Green Infrastructure | GFS 118 | 275 | Yu-Cian Lin and Ying-Chieh Chan | National Taiwan University | Pareto Based Performance Framework for Urban Greening: Visualizing Trade offs between Cost, Carbon Sequestration, and Shading | Urban greening configuration Parametric environmental simulation Decision support visualization | Urban greening in construction planning often entails trade offs between cost and ecological performance. This study develops a multi-objective optimization framework that explicitly exposes and interprets the trade-offs among cost, carbon sequestration, and shading benefit. 3D parametric modeling is coupled with Wallacei evolutionary algorithms and a localized vegetation database integrating Taiwan public construction costs, species-specific carbon sequestration data, and measured canopy coverage. Across 800 solutions generated over 40 generations, 70 solutions constituted the Pareto optimal front, with the first Pareto solutions emerging at generation 17 and later generations (from generation 34 onward) consistently producing more than five Pareto solutions per generation. The optimizer identifies non dominated greening configurations under constraints on green coverage ratio and plant diversity. The Pareto front is further analyzed to identify representative solution archetypes aligned with distinct planning priorities cost oriented, carbon oriented, shading oriented, and balanced compromise strategies. Quantified marginal returns along the front reveal that advancing from the minimum cost solution ($148,469) to the carbon optimal solution ($246,750) requires a 66% cost increase, whereas moving from the carbon optimal to the shading optimal solution ($269,523) adds only 9% cost while improving shading by 14%, with a 6% reduction in carbon sequestration. Decision makers can therefore clearly understand what is gained and what is sacrificed when shifting priorities along the Pareto front. By tightly coupling evolutionary multi-objective optimization with interpretable Pareto analysis and visual decision aids, this framework bridges algorithmic results and practical design choices, enabling urban greening strategies that balance environmental benefits with economic feasibility for sustainability and climate adaptation. |
| 1-6 | 5/19/2026 11:00 | Smart Cities and Green Infrastructure | GFS 118 | 553 | Esra Tepeli | Purdue University - Construction Management Technology | Towards Sustainable Building Delivery: Synergizing LEED and Lean Approaches for Energy-Efficient, Healthy Passive House Design | Passive house LEED-Lean integration Sustainable construction Energy efficiency | The building sector faces the dual challenge of reducing energy demand while ensuring healthy indoor environments. Passive House standards, LEED certification, and Lean Construction each provide effective strategies for sustainable project delivery, yet limited research addresses how these approaches can be systematically integrated. This study develops and evaluates a conceptual framework that aligns LEED principles with Lean methods to enhance the design and delivery of Passive House projects. Adopting a case study methodology, the research examines how LEED strategies—such as high-performance ventilation, thermal comfort, and material sustainability—can be reinforced by Lean tools including value-stream mapping, workflow optimization, and waste reduction. The framework identifies synergies between LEED credits and Lean practices, creating a structured decision-making process that supports both sustainability and efficiency objectives. Data analysis highlights reductions in operational energy use, improvements in indoor air quality indicators, significant decreases in construction waste, and measurable gains in delivery timelines. The findings demonstrate how certification-based sustainability measures and process-driven efficiency methods can be operationalized together, offering a replicable model for future projects. This research contributes to bridging a critical knowledge gap and provides actionable insights for designers, contractors, and policymakers aiming to deliver low-carbon, energy-efficient buildings that prioritize occupant health and environmental responsibility. |
| 1-7 | 5/19/2026 11:00 | Generative AI in Sustainable Built Environment | GFS 207 | 17 | Wooyoung Jung, Prosper Babon-Ayeng and Kahyun Jeon | Illinois Institute of Technology; The University of Arizona | Human-AI Interaction in Large Language Model-Integrated Building Energy Management Systems: User Prompt Strategy | Building Energy Management System Large Language Models User Prompt Strategy Human-AI Collaboration Decision Support Systems Theory | This study investigates how users formulate and utilize prompts when interacting with large language model (LLM)-integrated building energy management system (BEMS), with the objective of understanding their interaction strategies. Prior studies often relied on (1) rigid or pre-scripted user input interfaces in BEMS due to the limited capabilities of early language models or (2) posed single-turn user prompts to evaluate the performance of LLM-integrated BEMS. To address these limitations, this study conducted an experiment where participants were tasked with identifying five energy-saving behavioral changes while interacting with an LLM-integrated BEMS. This experimental setup enabled us to examine how users would naturally formulate prompts throughout their interactions with the system. In total, we collected 156 prompts (comprising 252 sentences) from 20 participants and classified them via six prompt strategies derived from decision support systems (DSS) theory. Our key takeaways were the following: (1) participants intuitively understood core principles of DSS, such as goal articulation, information seeking, and solution evaluation; (2) most participants began their interactions with GPT by directly articulating their goals, without offering any analytical guidance, showing a strong reliance on GPT’s analytical capabilities; (3) participants were less engaged with solution evaluation, alternative seeking, and decision-making support, possibly owing to the domain knowledge required for such strategies. This study provides insights into the human side of human-AI collaboration by analyzing the content in prompts, demonstrating how users would communicate their needs and expectations using LLMs for building energy management tasks. |
| 1-7 | 5/19/2026 11:00 | Generative AI in Sustainable Built Environment | GFS 207 | 252 | Simona Semeraro, Francesca Vecchi, Roberto Stasi and Umberto Berardi | Polytechnic University of Bari | A Two-Phase Physics-informed Machine Learning Framework for Predicting Indoor Temperature and Cooling Energy in Present and Future Climates | Physics-Informed Neural Network Machine Learning Energy Efficiency Multi-Objective Optimization Social Housing | Climate change is expected to substantially modify the thermal behaviour and cooling requirements of residential buildings, particularly in Mediterranean regions. Accurately capturing these effects requires modelling tools capable of providing reliable short-term predictions while remaining robust under future climatic conditions. In this context, Physics-Informed Neural Networks (PINNs) offer a promising solution by embedding physical conservation laws directly into the learning process, thereby improving generalisation and physical consistency. This study proposes a two-stage PINN-based framework to predict indoor operative temperature and cooling electricity power in a multi-residential building located in Bari, Southern Italy. Typical Meteorological Year (TMY) data and future climate projections for 2050 and 2100 are employed to generate dynamic simulation datasets using EnergyPlus for training and validation. In Phase I, a single-zone energy balance PINN is used to predict operative temperature, explicitly accounting for thermal inertia and external heat gains. In Phase II, the predicted operative temperature is coupled with environmental and thermal features to estimate the hourly cooling electricity power at the next time step. The results demonstrate stable predictive performance across all climate scenarios. Operative temperature prediction achieves RMSE values ranging between 0.173 and 0.294 °C, with negligible systematic bias, while cooling electricity power is predicted with RMSE values of 0.104 kW (TMY), 0.478 kW (2050), and 0.251 kW (2100). Increased prediction errors are primarily associated with sharp cooling load peaks under future climatic conditions, particularly in the mid-century scenario, while overall temporal dynamics and peak timing are well captured. The proposed framework provides a physically consistent and scalable approach for integrating machine learning with building energy simulation, supporting future applications in building energy management, digital twins, and predictive control under climate change scenarios. |
| 1-7 | 5/19/2026 11:00 | Generative AI in Sustainable Built Environment | GFS 207 | 279 | Mahdi Bonyani, Maryam Soleymani and Chao Wang | Louisiana State University | Transformer-based Generative AI for HVAC Control with Fragmented Data Center Histories of IT Workload and Cooling Infrastructure | Generative AI HVAC Control Cooling Infrastructure Transformer Spatio-temporal Modeling | Data centers often face fragmented operational histories due to sensor upgrades or logging failures, hindering the training of robust HVAC control policies. This paper introduces the Generative Thermodynamic Graph Transformer (GTGT), a novel framework designed to reconstruct missing temporal data in Cyber-Physical Systems. By integrating a thermodynamic graph with a physics-informed Transformer, GTGT synthesizes high-fidelity operational profiles that bridge multi-year data gaps. We utilize real-world datasets from a tropical data center testbed (2018-2023) to validate our approach. Experimental results demonstrate that GTGT achieves a 42% reduction in reconstruction error compared to standard Transformers and maintains 99.8% thermodynamic consistency. Furthermore, Deep Reinforcement Learning agents trained on this augmented history achieve a Power Usage Effectiveness (PUE) of 1.08 and 15.6% energy savings in volatile transition scenarios, significantly outperforming agents trained on fragmented data. |
| 1-7 | 5/19/2026 11:00 | Generative AI in Sustainable Built Environment | GFS 207 | 506 | Xinyue Xu, Julian Wang and Xingjian Liu | The Pennsylvania State University | ResStock-LLM: A Multi-Agent Framework for Climate-Adaptive Residential Retrofit Decisions | Building retrofit Large language model (LLM) Building energy efficiency agentic artificial intelligence Automatic decision-making | Residential building retrofits are essential for improving energy efficiency and reducing greenhouse gas emissions, yet identifying effective retrofit actions for building stocks remains challenging. Current methods often compare pre- and post-retrofit simulations, thereby ignoring regional differences and the distribution of efficiency gaps. To improve automation in retrofit decision-making, this study introduces ResStock-LLM, a large language model (LLM) framework that integrates multiple agents with ResStock data to analyze household descriptions, forecast building energy-efficiency percentiles, and develop climate-specific retrofit strategies. ResStock-LLM links building energy-efficiency classifiers to assess retrofit needs and compares them against national and zone-level building-stock data from ResStock. The identified retrofit targets are directed to a report agent that generates code-compliant retrofit reports. Using the structural knowledge base and ResStock data, this approach demonstrates that LLM agents can produce reliable recommendations. Tests on a representative single-family residential building show that ResStock-LLM primarily identifies roof insulation, heating setpoint, and shading improvements as key factors influencing retrofit potential. In general, ResStock-LLM offers a scalable, climate-adaptive decision support tool that integrates building stock models and a pre-trained machine learning classifier with language model-based reasoning to facilitate efficient retrofit planning. |
| 1-7 | 5/19/2026 11:00 | Generative AI in Sustainable Built Environment | GFS 207 | 519 | Muhammad Ihza Febriyan Pagri, Dongho Lee, Junhwa Hwang and Dongjun Suh | Department of Convergence & Fusion System Engineering, Kyungpook National University | A Comparative Analysis of Fine-Tuning and Prompt Engineering for LLM-Based Automation of Building Energy Models for Rooftop Photovoltaics | Large language models building energy modeling rooftop photovoltaics machine learning | Establishing accurate building energy models (BEMs) for rooftop photovoltaic (PV) installations is essential for assessing renewable energy potential. However, this process presents substantial challenges related to design and a comprehensive understanding of building science, which limits its widespread adoption in urban planning. Adopting conventional design processes without incorporating accurate PV potential modeling can result in suboptimal energy performance and the failure to maximize opportunities for carbon emission reductions. To address these challenges, this study investigates the potential of Large Language Models (LLMs) to automate the generation of simulation-ready BEMs from natural language prompts. LLM-based automation offers a transformative solution by translating high-level inputs into the precise, complex files required by simulation engines, significantly reducing the time and expertise needed. Two primary methodologies for leveraging LLMs are investigated: fine-tuning and prompt engineering. Fine-tuning involves retraining a model on a specialized dataset of building and PV system parameters to create a domain-specific expert model. On the other hand, prompt engineering utilizes the extensive knowledge of large, pre-trained models, guiding them to generate the desired output through carefully crafted instructions and examples without requiring any model modification. Despite the potential of LLMs, their application to the specialized domain of BEMs is not straightforward. The complexity of this process stems from the necessity of accurately capturing the diverse geometries of rooftops, optimizing the layout of photovoltaic panels, and considering complex factors such as panel size and spacing. Additionally, there is a lack of clear understanding regarding the suitability of different LLM approaches for this particular task. Specifically, the question remains whether the resource-intensive fine-tuning or the more agile prompt engineering approach is preferable. This study provides critical insights into the potential to significantly accelerate the analysis of solar energy integration in urban environments, contributing to the development of more sustainable and energy-efficient buildings by making energy modeling more accessible and efficient. |
| 2-1 | 5/19/2026 13:30 | Sponsored session by KD Navien: Indoor Air Quality | SGM 123 | 180 | [Sponsor Team: KD Navien] Insoo Hwang, Junwoo Kim and Hyunbae Park | HVAC R&D Center, KD Navien | A Study on Indoor Air Quality Using a Hybrid Dehumidification Ventilation Unit | Hybrid Dehumidification System Energy Saving Indoor Comfort Zero Energy House Climate Change Adaptation | This study investigates the performance and applicability of a hybrid dehumidification–ventilation system that integrates a rotary desiccant rotor with a heat pump to improve energy efficiency and indoor comfort under hot and humid conditions exacerbated by climate change. The system replaces the conventional energy-recovery core with a low-temperature regenerable Super Desiccant Polymer (SDP) rotor and utilizes condenser waste heat from the heat pump for regeneration, eliminating the need for auxiliary heating and enabling consistent dehumidification. The primary latent load is removed at the heat pump evaporator, followed by secondary adsorption in the desiccant rotor. The regeneration heat provides mild reheat, resulting in near-isothermal dehumidification. Under KSC 9317 (aligned with AHAM DH 1-2022) standard test conditions, the hybrid unit achieved a moisture removal efficiency of 3.84 L/kWh, which represents a 30–40% improvement over conventional condensation-type dehumidifiers. In heating mode, total heat exchange (enthalpy) effectiveness reached 83%, approximately 10% higher than high-efficiency ventilation units employing enthalpy cores. At low temperatures, the unit delivered 3.10 L/kWh, exceeding the Energy Star Most Efficient criterion (2.35 L/kWh) by a substantial margin, confirming year-round applicability. When operated in coordination with a room air conditioner, the system enabled independent control of dry-bulb temperature and relative humidity. Under equivalent apparent temperature conditions, coordinated operation reduced energy consumption by approximately 14% compared to air conditioner-only operation, while maintaining RH below 60% to ensure thermal comfort. These findings highlight the potential of hybrid dehumidification–ventilation systems to support Zero Energy House (ZEH) initiatives and carbon neutrality goals. |
| 2-1 | 5/19/2026 13:30 | Sponsored session by KD Navien: Indoor Air Quality | SGM 123 | 85 | Danbi Kwon, Donghyun Kim and Taeyeon Kim | YONSEI University | CFD-based Surrogate Model for Predicting CO2 Concentration Distribution in Classrooms | Indoor Air Quality (IAQ) Computational Fluid Dynamics (CFD) Kriging Energy Recovery Ventilation (ERV) | University classrooms often experience elevated CO₂ concentrations due to high occupant density, which can adversely affect attentiveness, induce drowsiness, and impair learning performance. Conventional ventilation control systems typically rely on CO₂ measurements from a single fixed sensor, which fails to capture spatial variations arising from differences in occupant number and seating distribution. Although Computational Fluid Dynamics (CFD) can provide detailed spatial predictions of indoor airflow and contaminant dispersion, its high computational cost and long simulation times limit its applicability for real-time evaluation under diverse occupancy conditions. To address this limitation, this study develops a Kriging-based surrogate model for efficient prediction of breathing-zone CO₂ concentration distributions. CFD simulations were performed for 23 scenarios combining ventilation rates (150, 250, and 400 CMH), occupant numbers (4, 8, 12, 16, and 20), and seating patterns (Front, Back, and Random). Seat-level breathing-zone CO₂ concentrations were extracted from CFD results and used to construct the training dataset. The surrogate model is based on Gaussian Process Regression (GPR) and employs a combination of Constant, Matern 2.5 and White kernels to capture spatial correlation structures. Model performance was evaluated using the coefficient of determination (R²) and mean absolute error (MAE). The developed surrogate model successfully reproduced CFD results across various occupancy conditions and predicted breathing-zone CO₂ distributions with substantially reduced computation time. Owing to its high accuracy and low computational demand, the proposed model demonstrates strong potential as a predictive tool for real-time ventilation control and demand-controlled ventilation strategies under dynamic occupancy conditions. |
| 2-1 | 5/19/2026 13:30 | Sponsored session by KD Navien: Indoor Air Quality | SGM 123 | 86 | Yubin Cho, Donghyun Kim, Sihyeon Kim and Taeyeon Kim | YONSEI University | CFD–ML Approach for Predicting Breathing-Zone PM2.5 in Indoor Cooking Environments. | Indoor Air Quality (IAQ) Kitchen Environment Machine Learning (ML) Computational Fluid Dynamics (CFD) Particle matter | Cooking activities generate high concentrations of PM2.5, which degrades indoor air quality and increases occupant exposure. Although Computational Fluid Dynamics (CFD) simulations can accurately resolve airflow and pollutant distributions in such environments, the high computational cost makes the evaluation of multiple ventilation scenarios impractical. This study proposes a CFD–machine learning (CFD–ML) approach to rapidly and accurately predict Breathing-Zone (BZ) PM2.5 concentrations in a residential kitchen under varying supply airflow rates. A total of 49 CFD simulations were performed for different supply airflow cases during cooking, and the occupant’s BZ PM2.5 concentration was extracted from each case to construct a training dataset. Using the CFD-derived dataset, three machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), and Deep Neural Network (DNN)—were trained and compared in terms of their ability to predict BZ PM2.5 as a function of supply airflow conditions. Model performance was evaluated using R², Root Mean Square Error (RMSE), Coefficient of Variation of the RMSE (CVRMSE), and Mean Absolute Error (MAE). Although their prediction accuracy differed, all models reproduced the decreasing trend of BZ PM2.5 with increasing supply airflow rate. The DNN model exhibited the highest performance on the test dataset, achieving an R² of 0.99 and a CVRMSE of 2.65%, closely matching the CFD simulation results across the entire concentration range. In contrast, the SVM and RF models exhibited larger prediction errors—up to approximately 13.8%—particularly in higher concentration ranges and under specific airflow conditions. The average computational cost of the machine learning models was reduced by approximately 98.7% compared with CFD, demonstrating their capability to evaluate multiple ventilation cases with substantially improved efficiency. These results indicate that a DNN trained on CFD-derived data can effectively predict breathing-zone PM2.5 in kitchen environments and provide a foundation for exposure-oriented ventilation strategy assessment and ventilation control development. |
| 2-1 | 5/19/2026 13:30 | Sponsored session by KD Navien: Indoor Air Quality | SGM 123 | 401 | Avijit Sarker, Mina Lesan, Saeid Chahardoli, Yi Xiao, and Arup Bhattacharya | Louisiana State University | Real-Time Indoor CO2 Distribution Prediction Using CFD and Physics-Regularized Kolmogorov-Arnold Network | Indoor Air Quality (IAQ) CO₂ Mapping Computational Fluid Dynamics (CFD) Kolmogorov–Arnold Network (KAN) Physics-Informed Machine Learning | Indoor environmental quality (IEQ) that includes thermal comfort and indoor air quality (IAQ), has gained significant attention due to its strong link to the time occupants spend indoors and its impact on health and well-being. Carbon dioxide (CO₂) is a widely used IAQ indicator which has been shown to be a proxy to reflect ventilation performance, occupancy profile, and potential airborne infection risk. However, distribution of indoor CO₂ concentration is inherently non-uniform, influenced by room geometry, occupant profile, ventilation, and spatiotemporal airflow patterns. Getting accurate mapping of these variations is essential for occupancy detection, IAQ assessment, and energy management, which remains challenging when relying solely on CFD simulation or sparse fixed-point sensor data. This study proposes a hybrid framework combining CFD-simulated CO₂ fields with sparse sensor data leveraging a Kolmogorov-Arnold Network (KAN). The KAN learns a physics-regularized correction from residuals between simulated and measured data to produce real-time, room-wide CO₂ concentration maps with greater spatial accuracy than CFD alone while reducing sensor requirements. The workflow begins by defining the study room’s geometry, ventilation type, and other operating scenarios (e.g., ACH, supply conditions, door states, and occupancy profile). A fleet of CO₂ sensors records CO₂ concentration, temperature, and humidity, with HVAC supply data collected from the building management system. A Reynolds-averaged Navier-Stokes-based CFD model with CO₂ transport is employed to generate multiple cases under varying airflow and boundary conditions. The KAN is trained on normalized spatial coordinates, temporal variables, HVAC parameters, local velocities, and interpolated CFD values, with physics-based loss terms to enforce spatiotemporal smoothness. Leave-one-sensor-out cross validation and mobile traverses are used to assess numerical performance. The framework delivers computationally and data-efficient CO₂ concentration predictions with improved RMSE/MAE, preserves physical consistency, and supports real-time IAQ evaluation and ventilation optimization to enhance occupant health, comfort, and safety. |
| 2-1 | 5/19/2026 13:30 | Sponsored session by KD Navien: Indoor Air Quality | SGM 123 | 442 | Yi Xiao, Saeid Chahardoli, Mina Lesan, Avijit Sarker, Andrew Z Johanssen and Arup Bhattacharya | Assistant Professor in Construction Management at LSU; Computer Science, South Dakota School of Mines & Technology; Construction Management at LSU; Louisiana State University | Optimizing Ventilation Inlet and Outlet Configurations using a UQ-Informed Robotic Sensing Platform | 1- Indoor Air Quality (IAQ) 2- Ventilation Optimization 3- Robotic Sensing 4- Uncertainty Quantification 5- HVAC System Design | It is of paramount importance to provide Indoor Air Quality (IAQ) as it can improve the health, productivity, and well-being of the occupants while reducing the energy consumption. IAQ is fundamentally dependent on the strategic placement of diffusers and exhausts, which profoundly impact the airflow distribution, which, in turn, governs the ventilation effectiveness, occupant comfort, and energy consumption. Traditional designs rely on simulations with predefined locations for the inlets and outlets, and static sensor locations, often failing to capture the complex, three-dimensional nature of indoor air distribution. This can lead to a performance gap between design intent and real-world operation. To rectify this predicament, this paper introduces a novel methodology that integrates a dynamic digital twin, autonomous robotic sensing, and uncertainty quantification (UQ) to identify robustly optimal ventilation configurations. The method utilizes a simulation platform to create a digital twin of the experimental setup equipped with air inlets and outlets. A mobile robotic agent then systematically establishes a baseline for the digital twin by autonomously navigating the space to generate high-resolution, spatiotemporal maps of thermal and air quality parameters for various inlet and outlet location scenarios. These rich datasets are used not only for deterministic optimization but to drive a UQ analysis that characterizes the performance robustness of each configuration against key real-world uncertainties, such as sensor error and the impact of supply airflow location on airflow distribution. The best layout was found to be sensitive to operational variance. However, the UQ-informed layout was fundamentally robust, maintaining a comparably high average IAQ despite these real-world fluctuations. This framework provides a new paradigm for the evidence-based design and virtual commissioning of ventilation systems. It ensures that selected configurations are not only efficient but also robust and reliable under the dynamic conditions of actual building operation. |
| 2-1 | 5/19/2026 13:30 | Sponsored session by KD Navien: Indoor Air Quality | SGM 123 | 456 | Tang Lee and Anthony Santini | Red Studio Architects; The University of Calgary | Preventing the spread of airborne infectious pathogens in the next pandemic | Pathogens Coronaviruses Wildfires | Tang Lee 1, and Antonio Santini 2 1 School of Architecture, The University of Calgary, Canada, lee@ucalgary.ca 2 Red Studio Architects, 354 Davenport Ave, Suite 300, Toronto, Canada, antonio@red-studio.ca Abstract: Infectious pathogens such as coronaviruses and influenza, as well as fungi and bacteria spread throughout indoor environments. Portable desktop air purifiers are not effective in treating the full air volume capacity within rooms. The spread of airborne infectious pathogens can only be mitigated by removing airborne particulates, volatile organic compounds and irradiating all airborne microorganisms by treating the full air volume with effective technology that is only possible with high UVC irradiation dosage and adequate dwell time. Our tests have concluded that several commercially sold air purifiers do not have the capability to successfully treat the air contamination present. Insufficient air volume treatment, inappropriate filter mediums, and low levels of UVC dosage are some of the common factors associated with the lack of results. Having tested several commercially sold air purifiers, we noted that some desktop air purifiers have such low UVC dosage and dwell time that they cannot effectively irradiate microbes that pass through their device. Some devices use LEDs that currently produce low voltage (millivolts) and some even use UVB and UVA lamps instead of UVC that are ineffective to neutralize the microbes. This presentation discusses air cleaning technologies, limitations of commercially sold air purifiers, how to read so-called laboratory reports, and what technologies are truly effective. We will present guidelines for architects and engineers, building owners and managers, school boards, and healthcare facilities for specifying effective air purifiers to protect the health and safety of their clients and occupants. With increasing wildfires and vehicle emissions, air cleaning devices must address the three main air pollutants such as airborne particulates, volatile organic compounds (including MVOCs), and airborne infectious microbes. It will also present a new metric in assessing the efficacy of air cleaning technologies. |
| 2-2 | 5/19/2026 13:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 36 | Yi Zhu, Junyu Chen, Junjie Fu, Kan Chen and Peng Xu | GD Midea Heating & Ventilating Equipment Co.,Ltd.; Tongji University | An Efficient PSO-Based Approach for Optimizing Internal Gain Schedules in Building Energy Simulation | Building Energy Model Internal Gains Particle Swarm Optimization (PSO) Schedule Calibration | In the development of building energy models, accurately determining the temporal distribution of internal gains is crucial, as it directly influences both the daily and total load distribution within the building. However, the traditional method of manually adjusting parameters for each time segment in internal gain schedules is highly subjective. Furthermore, due to the large number of schedule parameters, the solution space is extremely vast during calibration, leading to a substantial and cumbersome manual workload that severely restricts the efficiency and accuracy of model construction. To effectively address these challenges, this paper proposes a novel method for rapidly determining building internal gain schedules based on the Particle Swarm Optimization (PSO) algorithm. First, we employ a single normal distribution to approximate and fit complex building internal gain schedules, thereby significantly reducing parameter dimensions. The fitted results are then input into IDF files for simulation. Building upon this, the PSO algorithm is utilized, with the R2 value between simulated results and measured energy consumption data serving as the objective function, to search the parameter space and identify the internal gain schedule parameter combination corresponding to the optimal R2 value. This method demonstrates excellent performance in test cases, with its R2 value automatically fitting up to 0.7. This research provides an efficient and reliable solution for the automated calibration of internal gain schedules in building energy models, and also offers new insights for optimizing similar complex time-series parameters. |
| 2-2 | 5/19/2026 13:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 90 | Yusuke Nagaoka, Keiichiro Taniguchi and Yasunori Akashi | Department of Architecture, Graduate School of Engineering, The University of Tokyo, Japan | Preemptive HVAC setpoint scheduling enabled by large language model-based occupancy prediction: a lecture hall case study | Occupancy Prediction Preemptive HVAC Strategy Large Language Models | In large-volume spaces such as lecture rooms, the indoor air temperature responds slowly to the cooling operation because of high thermal inertia. Additionally, feedback control based on the current temperature can introduce an additional delay in the equipment response. Together, these time lags may prevent the room from reaching the intended setpoint during occupied hours, thereby degrading thermal comfort. This challenge is exacerbated in lecture rooms, where attendance varies widely across lectures and causes substantial variations in internal heat gain and cooling load. Therefore, preemptive setpoint scheduling based on occupancy prediction is required. In this study, we evaluated a preemptive temperature setpoint scheduling strategy using a simulation framework that explicitly incorporates lecture-specific occupancy prediction. We constructed a control-oriented HVAC simulation for a university lecture room and coupled it with a simplified 5R2C room model. Occupancy was predicted from syllabus information using a large language model (LLM); in prior work, the Direct-LLM approach achieved a mean absolute error of 12.06 and root mean squared error of 15.41 in lecture attendance prediction. Candidate setpoint schedules were exhaustively simulated and screened by using a comfort criterion (indoor air temperature within 23–25 ℃ during class hours). Among the feasible schedules, the schedule with the lowest total electricity consumption was selected as the optimal schedule. Case studies compared schedules optimized using measured occupancy and with those optimized using LLM-predicted occupancy. The results indicated that schedules derived from the predicted occupancy lie near the measured optimal schedule in the setpoint-parameter space and achieve similarly low electricity consumption while satisfying the comfort criterion. These findings support the practical applicability of LLM-based semantic occupancy prediction for preemptive setpoint scheduling in lecture rooms with uncertain and highly variable attendance. |
| 2-2 | 5/19/2026 13:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 241 | Sharon Verghese and Mike Jaeger | Arup; Arup Detschland GmbH | Enhanced Deterministic Occupant Behavior Modeling Framework for Energy Efficient Conceptual Design | Occupant behavior modeling conceptual design design decision deterministic adaptive | The integration of occupant behavior (OB) into building energy modeling remains limited in practice, particularly during the conceptual design stage, despite extensive research in this field. This gap is largely driven by the complexity, computational demand, and limited interpretability associated with existing OB modeling approaches. To address these challenges, this study proposes an enhanced deterministic occupant behavior modeling framework aimed at supporting energy‑informed design decision‑making during early design stages. The proposed framework extends deterministic modeling by incorporating dynamic and adaptive occupant behavior through scenario‑based parameter variation and rule‑based behavioral responses. Non‑adaptive behaviors are varied to represent temporal dynamics, while adaptive behaviors are activated deterministically across consecutive time steps in response to changing indoor and outdoor conditions. To ensure computational efficiency and facilitate design interpretation, the framework integrates Latin Hypercube Sampling for structured exploration of the parameter space and regression‑based sensitivity analysis to identify influential occupant‑centric parameters. The framework is demonstrated through a residential building case study, illustrating its applicability in a realistic design context. Rather than prioritizing absolute behavioral prediction accuracy, the proposed approach emphasizes robustness of design decisions to occupant variability. The results highlight the ability of the framework to reduce computational effort while preserving interpretability, enabling practitioners to focus on the most impactful behavioral parameters during early‑stage design. Although developed for the conceptual design phase, the modular and parameter‑driven structure of the framework allows it to be adapted to other design stages, building types, and occupant behavior definitions, offering a scalable and practical pathway for integrating occupant behavior into energy‑optimized building design. |
| 2-2 | 5/19/2026 13:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 249 | Jeongyun Hwang and Hyunwoo Lim | konkuk university | Improving urban building energy modeling (UBEM) accuracy through shape and energy use pattern calibration factors based on representative buildings | Urban building energy model (UBEM) Representative building Calibration Energy use pattern shape index | Rapid urbanization and population concentration have increased urban energy demand, intensifying stress on urban power grids. Urban building energy modeling (UBEM) is widely used to predict urban-scale energy demand; however, its accuracy strongly depends on input data availability and model resolution. Because detailed building-level energy data are rarely available at scale, many UBEM studies rely on representative buildings to reduce data and computational burdens, which can oversimplify geometry and temporal load patterns and reduce reliability for decision-making. To address these limitations, this study proposes a two-step calibration framework for a representative building-based UBEM that accounts for differences in building geometry and monthly energy use patterns. First, we derive shape calibration factors using shape indices calculated from building height, floor area, and volume. Second, we divide energy use data into (ⅰ) heating and cooling and (ⅱ) baseload energy use intensity (EUI) [kWh/m2] and derive energy use pattern calibration factors that adjust the monthly distribution. The framework is demonstrated using UBEM simulations based on the representative buildings and a target dataset of Seoul office buildings. Compared to the uncalibrated representative building-based UBEM, the shape calibration significantly reduced end-use CVRMSE (e.g., heating: 964.60% → 427.92%, cooling: 210.97% → 103.63%, baseload: 58.69% → 35.02%). Energy use pattern calibration further improved the consistency of monthly patterns, increasing the Pearson correlation coefficient from 0.57 to 0.99 and reducing the average monthly total EUI error rate from 21.66% (before calibration) to 7.79% (after pattern calibration). This approach improves accuracy while maintaining the efficiency benefits of representative buildings, and it provides a practical pathway to more reliable UBEM for urban-scale applications such as load forecasting and retrofit prioritization. |
| 2-2 | 5/19/2026 13:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 477 | Joshua Wiens | IES Ltd. | IES: New trends in building performance modeling | Building Performance Modeling Electrification & Decarbonization Building Energy Code Compliance | This presentation will provide an update to IAQVEC about the most recent trends in Building Performance Modeling technology for the design of high-performance buildings. Five of the more recent innovative simulation workflows and trending modeling design methods will include: (1) Metrics for Electrification & Decarbonization; (2) Momentum towards more Energy Storage in Buildings; (3) HVAC Heat Recovery Systems; (4) New Building Energy Codes, Standards, and Rating Systems; (5) Data exchange between performance modeling software platforms. |
| 2-2 | 5/19/2026 13:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 576 | Sooyoun Cho and Gi Seok Kim | Center for Sustainable Buildings, Yonsei University | Development of Hierarchical Classification System for University Building Energy Influential Factors and Construction of Prediction Matrix | University Buildings Energy Influential Factors Classification System Prediction Matrix | Abstract. University campuses represent complex facilities with diverse building types exhibiting distinct energy consumption patterns from conventional buildings. Major campuses in metropolitan areas including Seoul possess dozens of high energy-consuming buildings, yet specific systems capable of evaluating each building according to its unique consumption characteristics remain absent. This study systematically classifies multi-layered factors influencing university building energy and develop prediction and evaluation matrices through factor combinations. Annual energy consumption data from 47 buildings at Yonsei University Sinchon Campus (2023) were analyzed. Building Energy Influential Factors (BEIF) were structured into a three-tier hierarchy: Tier 1 (Primary Factors)—building basic information, operation information, environmental information; Tier 2 (Integrated Factors)—energy consumption patterns, performance indicators; Tier 3 (Prediction/Evaluation Models)—integrated analysis models. Factor combinations and prediction accuracy at each tier were evaluated to construct practical utilization matrices. University buildings showed significantly different energy consumption patterns according to departmental characteristics. A novel indicator—unit energy consumption per area per operating hour (Wh/m²·h)—enabled more accurate performance evaluation than conventional methods. The impact of research activities on total energy consumption was quantified through separation of base energy (60.4%) and building energy (39.6%). The developed matrix can be applied for deriving optimal operating hours by facility type, establishing energy intensity standards by department, and predicting real-time energy demand. Tier 1 combinations enable qualitative analysis, while quantitative prediction becomes possible from Tier 2 combinations, and practical decision support is achievable at Tier 3. The research results are expected to serve as a fundamental framework for university energy management policy development and smart campus construction. |
| 2-3 | 5/19/2026 13:30 | Building Technology and Performance | GFS 116 | 75 | Miyu Matsunobu, Kyosuke Hiyama and Yutaka Oura | Sankyo Tateyama, Inc.; Meiji University | Quantifying the Trade-off between Upfront and Operational Carbon in High-Performance Building Envelopes | Office building Upfront Carbon Operational Carbon Double Skin Facade Triple Glazing | In recent years, reducing greenhouse gas (GHG) emissions over the entire life cycle of buildings has gained increasing importance. In addition to reducing operational carbon through energy efficiency during the use phase, building design must also aim to suppress upfront carbon emissions from the sourcing of materials, manufacturing, and construction. This study examines a medium-sized office building to evaluate the balance between the increase in upfront carbon and the decrease in operational carbon associated with high-performance envelope upgrades. The adaptability of various envelope specifications was examined considering Japan’s climatic characteristics and building orientations. The high-performance envelope types investigated are Low-E triple glazing and high-performance double-skin façades, compared with the commonly used Low-E double glazing in Japan. The study covers all 8 climate zones defined in Japan’s energy-saving standard. The effect of the performance upgrade is evaluated as the carbon payback time, which compares the reduction in operational carbon to the increase in upfront carbon. Orientation-specific effects on heating and cooling loads are also examined to identify façade directions that should be prioritized for performance upgrades. The results show that Low-E triple glazing achieves large reductions in operational carbon relative to the increase in upfront carbon, enabling payback within the assumed service life (30 years) across all climate zones. In cold regions in particular, payback is expected in about 5 years. Double-skin façades also showed large reductions in cold climates, with payback achievable within 20 years. In warmer climates, however, achieving payback within the service life may require additional measures such as the use of recycled materials. It was found that east and west-facing facades consistently offered the highest potential for GHG reduction in all climate zones. These orientations receive more intense solar heat, suggesting they should be prioritized for building performance upgrades. |
| 2-3 | 5/19/2026 13:30 | Building Technology and Performance | GFS 116 | 322 | Hyeonseong Yuk, Seong Taek Kang and Sumin Kim | Yonsei University | Balancing energy efficiency and conservation in historic building retrofits | Historic building conservation retrofit building energy saving | Sustainability has become a crucial concept in various industries, including construction, as a response to climate change and carbon neutrality goals. In modern construction, implementing energy-efficient technologies is relatively straightforward. However, historic buildings pose unique challenges due to their architectural and cultural significance, requiring a balance between preservation and functionality. Many historic buildings, constructed during the modern era, retain their historical value due to their association with significant figures and periods. Today, they continue to serve as museums, offices, and commercial spaces. Unlike newly constructed buildings, historic buildings often remain unchanged to preserve their original form, leading to limited improvements in building envelope performance. As a result, their energy efficiency remains suboptimal. Addressing this challenge requires tailored retrofit strategies that align with the inherent characteristics of historic buildings. This study examines heat balance and essential conservation principles to develop appropriate retrofit strategies for these structures. The heat balance analysis identified exterior walls as a primary source of heat loss and gain, contributing significantly to overall energy inefficiency. The findings indicate that applying retrofit technologies to exterior walls alone can achieve a 16% reduction in energy consumption. Additionally, windows, particularly those made of glass, play a crucial role in thermal performance, with energy savings of up to 14% when retrofitted appropriately. By optimizing retrofit solutions, this study contributes to improving the energy efficiency of culturally significant buildings while preserving their historical integrity, ensuring their continued sustainable and functional use in the future. |
| 2-3 | 5/19/2026 13:30 | Building Technology and Performance | GFS 116 | 496 | Oi-Man Hip, Simeon N. Ingabo and Ying-Chieh Chan | National Taiwan University | Evaluating the Impact of Reflective Painting on Building HVAC Performance | HVAC systems Cooling energy demand Reflective coating | Buildings are a major contributor to global carbon emissions. The International Energy Agency (IEA) reported that the building sector accounts for 34% of global energy demand and 37% of energy- and process-related CO₂ emissions. This level of consumption exacerbates challenges such as the urban heat island (UHI) effect, peak electricity loads, and climate-related vulnerabilities worldwide. In response, public sectors and organizations have attempted to develop strategies focused on improving energy efficiency in building operations, particularly in heating and cooling systems. While considerable attention has been given to HVAC equipment optimization and smart control technologies, the building envelope also plays a critical role in reducing energy demand. Reflective paint applied to building envelopes presents a low-cost, passive strategy to mitigate solar heat gain and reduce cooling loads. These coatings, characterized by high reflective, are increasingly used to combat the UHI effect by reflecting solar radiation and lowering surface and indoor temperatures. In addition to building envelopes, reflective pavement is also being considered as a complementary measure with the potential to reduce outdoor surface temperature and alleviate urban heat stress. Despite its practical appeal, the effectiveness of reflective paint in enhancing HVAC energy performance has not been comprehensively evaluated, particularly in relation to different HVAC system types. This study investigates the impact of reflective exterior paint on the cooling energy demand of buildings equipped with various HVAC systems, and explores the potential influence of reflective pavement on outdoor thermal conditions. Simulations were conducted using DesignBuilder across multiple scenarios with and without reflective paint, while maintaining consistent building geometry, materials, and orientation. Several HVAC configurations were tested, including decentralized and centralized HVAC systems. Preliminary results indicate that reflective paint reduces cooling energy consumption across HVAC types, with more pronounced effects under decentralized systems. Reflective pavement also shows promise in lowering surface heat emissions, suggesting combined benefits for both building performance and outdoor environment. |
| 2-3 | 5/19/2026 13:30 | Building Technology and Performance | GFS 116 | 532 | Kisa Fujiwara | Utsunomiya University | Thermal and Daylighting Performance of Representative Spatial Configurations in Contemporary Japanese Municipal Office Buildings | Japanese government office buildings Environmental design strategies Spatial configuration Thermal comfort Daylighting | Recent Japanese municipal office buildings commonly feature elongated floor plates, large south-facing façades, and double-height atria intended to enhance daylight availability and public transparency. Although these spatial configurations are widespread, their combined effects on indoor environmental quality remain insufficiently clarified. This study examines two representative spatial configurations extracted from a nationwide survey of contemporary municipal offices: a perimeter office with glazing on a single exterior façade and a double-height atrium connected to a south-facing façade. A computational fluid dynamics analysis was conducted to evaluate thermal behavior under representative summer and winter conditions, while a climate-based daylighting analysis assessed depth-dependent illuminance and visual uniformity in atrium-adjacent zones. The thermal results indicate pronounced summer overheating in west-facing perimeter offices, moderate warming in south-facing orientations, and relatively stable temperatures in north- and east-facing offices, with limited seasonal differences in winter. The daylighting analysis reveals clear depth-related contrasts: middle and rear zones achieved high illuminance levels but exhibited low uniformity and strong temporal variation, whereas near-façade zones maintained more stable but lower illumination. These results suggest that façade-connected atria can generate competing thermal and daylighting responses. The study provides performance-based insights for integrating façade design, shading strategies, and atrium configuration to improve indoor environmental quality in public-sector buildings. |
| 2-3 | 5/19/2026 13:30 | Building Technology and Performance | GFS 116 | 645 | In-Hwan Lee, Beom Yeol Yun, Sang Joon Lee, Chul-Ki Kim, and Hyung Woo Lee | National institute of forest science | Strategies for zero energy building certification of timber house | Timber housing Zero Energy Building (ZEB) Sustainable building design Energy efficiency Passive and active building systems Renewable energy integration | . In recent years, growing emphasis on sustainable buildings has led to increasing interest in timber housing. Timber houses are recognized as an energy-efficient building type due to their carbon reduction potential and excellent thermal insulation performance; however, achieving Zero Energy Building (ZEB) certification requires addressing various technical and institutional challenges. This study analyzes the key requirements for timber houses to obtain ZEB certification and proposes strategies for energy reduction and the integration of renewable energy systems to meet these requirements. First, domestic and international ZEB certification systems are comparatively reviewed to derive evaluation criteria suitable for timber housing. Subsequently, the applicability of passive design elements—such as high-performance insulation, enhanced airtightness, and optimized window placement—and active technologies, including photovoltaic systems, geothermal systems, and energy management systems, is examined. In addition, case studies are analyzed to assess practical feasibility, and optimal approaches for achieving ZEB certification are suggested by considering economic viability and environmental benefits. The results indicate that an optimal combination of energy-saving technologies tailored to the structural characteristics of timber housing, together with the efficient application of renewable energy systems, is a critical factor in achieving ZEB certification. This study is expected to contribute to the wider adoption of environmentally friendly timber housing and the advancement of sustainable building technologies. |
| 2-4 | 5/19/2026 13:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 118 | 50 | Seonghyuk Son and Dongwoo Jason Yeom | Clemson University | Lighting and Spatial Proportions in Virtual Reality: Patterns of Comfort and Task Performance | Virtual reality Spatial proportion Lighting condition Comfort Task performance | This study investigates how spatial configuration and lighting conditions jointly influence comfort and task performance using an interactive virtual reality experiment. Forty-two participants experienced four spatial configurations (Base, Wide, High, and Deep) under two lighting conditions (2600K and 5200K) in a within-subject design. Perceptual comfort was assessed through in-VR questionnaires, and task performance was measured using four interactive tasks targeting sensorimotor speed, inhibitory control, working memory, and problem-solving ability. Results showed that vertically expanded spaces were perceived as less comfortable, particularly under cool lighting. Task performance exhibited task-specific sensitivity to spatial and lighting conditions. Inhibitory control was reduced in vertically expanded spaces, while working memory and problem-solving performance were enhanced under cool lighting in high and deep rooms. To examine comfort and task performance simultaneously, a multidimensional analysis was conducted using standardized z-score composites. This analysis revealed systematic patterns and trade-offs across conditions, with some conditions favoring comfort and others favoring task performance. Warm lighting in deep spaces supported relatively balanced outcomes, whereas cool lighting in vertically expanded spaces enhanced performance at the expense of comfort. These findings demonstrate that no single spatial or lighting condition uniformly optimizes both comfort and task performance. By adopting a multidimensional analytical framework, this study highlights the importance of jointly considering perceptual and performance outcomes when evaluating architectural and lighting design strategies. |
| 2-4 | 5/19/2026 13:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 118 | 204 | Yanwei Jin, Yunyi Zeng, Juan Yu and Borong Lin | School of Architecture and Urban Planning, Chongqing University; School of Architecture, Tsinghua University | Health impact assessment of light and thermal environments: field research in offices with wearable monitoring | Healthy Buildings Light Environment Thermal Environment Wearable Monitoring Field Study | Light and thermal environments are important determinants of human mood, alertness, sleep, and work performance in the built environment. Although these effects have been studied in controlled laboratory settings, there is still limited understanding of how daily exposures in real workplaces shape health and wellbeing. To address this gap, this study conducted a field investigation using wearable monitoring and repeated surveys to examine the dynamic relationship between environmental exposures and human responses. Eight office workers (aged 21–31) were observed for at least three working days. Each participant continuously wore a lightweight device that measured illuminance, melanopic equivalent daylight illuminance (m-EDI), and ambient temperature at 10-second intervals. Subjective data on mood, comfort, alertness, and self-rated work efficiency were collected via digital questionnaires, while physiological indicators, including sleep-related indices from wrist-worn actigraphy and skin temperature from wearable sensors attached to each participant, were continuously recorded. The results showed that higher m-EDI levels in the half hour before survey completion were associated with more positive mood. Higher ambient temperatures were related to greater fatigue and lower work efficiency. Sleep duration tended to increase with higher morning light exposure and decrease with higher afternoon exposure. These findings suggest that light and thermal conditions have distinct and meaningful impacts on both psychological responses and sleep outcomes. This preliminary study demonstrates that combining wearable sensing with real-time subjective reporting can provide useful insights into how indoor environmental factors affect health and wellbeing. While limited by the small sample and short duration, the results highlight the value of field-based evidence for guiding healthier and more supportive workplace design, and point to the need for larger and longer studies in the future. |
| 2-4 | 5/19/2026 13:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 118 | 226 | Quanna Liao, Duo Yang, Le Ma, Hui Zhu, Hua Su, Masanari Ukai and Songtao Hu | Department of Cardiology, 1st Affiliated Hospital of the University of South China; Qingdao University of Technology; Waseda University | Cognitive performance evaluation based on physiological indicators in different sleep restrictions | Cognitive Performance Sleep Restriction Thermoneutral environment Melatonin Mean HR | Working overtime in the night has become common due to escalating competitions. During the nighttime overwork, biomarkers such as the melatonin and cortisol, as well as the electrocardiogram (ECG) feature like heart rate variability (HRV), have been reported to be closely corelated with cognitive performances of people. However, their quantitative relationships with cognitive performances remain to be further clarified. To explore the patterns of human cognitive performances under different sleep-restrictions, three different sleep-restriction conditions were devised, including the mild restriction from 23:00 to 1:20 a.m., the moderate sleep-restriction from 23:00 to 2:30 a.m., and the severe sleep-restriction from 23:00 to 3:40 a.m. During these sleep restrictions, the Deary-Liewald task, Stroop task, and Corsi block task were administered continuously to simulate the stable cognitive loads during overtime work. The overall performance index (OPI) was calculated from results of these tasks. Meanwhile, saliva melatonin and cortisol were collected during sleep restrictions, and ECG data were continuously recorded for HRV analysis. Results showed that the melatonin concentration during these three sleep restrictions elevated by 6.07 pg/mL (p<0.05), 7.17 pg/mL (p<0.05), and 7.7 pg/mL(p<0.05), respectively. SampEn kept reducing during all sleep restrictions, by 0.14 (p<0.05), 0.11 (p<0.05), and 0.15 (p<0.05), respectively. Mean heart rate (Mean HR) also reduced across all sleep restrictions, with the decrement of 5.88 (p<0.05), 9.94 (p<0.05), and 9.79 (p<0.05), respectively. Furthermore, the overall cognitive performances reduced generally with several fluctuations during all three sleep restrictions. Correlation analysis results indicated that the overall cognitive performance was positively correlated with mean heart rate (HR) (ρ=0.87, p<0.05), but negatively correlated with the melatonin concentration (ρ=-0.65, p<0.05). Based on that, an objective evaluation model for cognitive performance was proposed using the mean HR (R²=0.70, p<0.05) and melatonin concentration (R²=0.42, p<0.05). The quantitative relationships between the cognitive performance and two biomarkers (melatonin, HR) provided references for the working performance of people during the nighttime overtime. |
| 2-4 | 5/19/2026 13:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 118 | 270 | Wan-Tai Au-Yeung, Josephine Lau, Joel Steele, Nora Mattek, Zachary Beattie, Lyndsey Anderson, Allison Lindauer, Miranda Lim and Jeffrey Kaye | Architectural Engineering, Durham School of Architectural Engineering and Construction, University of Nebraska-Lincoln; Department of Neurology, Oregon Health & Science University; Indigenous Health, School of Medicine & Health Sciences, University of North Dakota; School of Nursing, Oregon Health & Science University | Associations between night-time bedroom environmental factors and objective sleep metrics of older adults | Indoor environmental quality sleep cognitive status older adults | Poor sleep quality is associated with adverse outcomes in older adults. Identifying associations between bedroom environmental factors and sleep quality could potentially provide guidance on how to control these factors to improve older adults’ sleep quality. Seventeen older adults with normal cognition (4 males and 13 females, mean [SD] age: 76.6 [8.2] years) and 12 with mild cognitive impairment or dementia (11 males and 1 female, mean [SD] age: 77.1 [8.5] years) living in Portland, Oregon were enrolled in the study. Night-time bedroom environmental factors and sleep metrics were objectively collected over a mean (SD) period of 211 (144) nights in participants’ personal residences. Mixed-effects models were constructed with six sleep metrics (duration in sleep, wake after sleep onset [WASO], sleep efficiency, toss-and-turn count, average heart rate and average respiratory rate) as outcomes and seven bedroom environmental factors (light, noise, temperature, humidity, particulate matter 2.5 [PM2.5], volatile organic compounds [VOC] and carbon dioxide [CO2]) (averaged per night) as predictors including covariates: age, sex, cognitive status, bed-sharing and season. Among all environmental factors, light level had the strongest association with duration in sleep (effect size [ES] = -0.051). Relative humidity was most strongly associated with WASO (ES = -0.101) and sleep efficiency (ES = 0.104). Temperature was most strongly associated with toss-and-turn count (ES = -0.118), average heart rate (ES = 0.052) and average respiratory rate (ES = 0.083), while PM2.5 level was strongly associated with sleep duration (ES = -0.050) and sleep efficiency (ES = -0.058). All reported associations were statistically significant according to the Bonferroni corrected p-value threshold (p < 0.0083). The results may yield insight into which environmental factors should be prioritized when attempting to optimize the sleep environment for older adults. Future work will examine whether environmental effects are different on the sleep of older adults with mild cognitive impairment or dementia vs those with normal cognition. |
| 2-4 | 5/19/2026 13:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 118 | 380 | Zhining Zhu, Ji Eun Choi, Xinbo Xu, Jiwon Park, Tobias Kramer, Hui Zhang and Stefano Schiavon | Center for the Built Environment, University of California, Berkeley, CA, USA; Department of The Built Environment, National University of Singapore, Singapore | Environmental and Physiological Influences on Sleep Quality: A Randomized Controlled Trial using Heating Pads in the Bay Area | Sleep Indoor Environmental Quality Thermal Comfort Residential Buildings | Sleep quality is a key determinant of physical health, mental well-being, and cognitive performance, yet the influence of indoor environmental factors on sleep remains insufficiently studied in real-world settings. While laboratory experiments have highlighted the effects of individual parameters like temperature, CO₂, particulate matter, and noise on sleep, multi-parameter field studies combining environmental, physiological, and subjective data are scarce. To address this gap, we conducted a pilot study with five participants (aged 21–35) to evaluate bedroom environmental conditions, their relationship to sleep quality, and the potential role of a heating pad as a thermal intervention. This within-subject weekly crossover study consisted of two phases (3 weeks each, total 6 weeks): an observational/control phase, during which participants’ bedrooms were monitored without intervention, and an intervention phase that introduced the use of an electrical heating pad. Environmental variables (temperature, CO₂, PM2.5, sound pressure level) were continuously measured alongside physiological signals from wearables (heart rate, sleep parameters). Subjective sleep quality was assessed daily using Cozie, an open-source Apple Watch survey tool. Results revealed substantial variability in environmental conditions between bedrooms, with CO₂ levels frequently exceeding recommended thresholds, typical night-time temperatures fluctuating by up to 5 K across homes, and notable differences in sound pressure level exposure. Correlational analysis suggested that higher CO₂ concentrations and elevated nighttime noise were associated with poorer subjective sleep quality, while temperature variability had mixed effects. The heating pad intervention improved subjective thermal comfort for most participants and was linked to modest improvements in self-reported sleep quality, although inter-individual responses varied. Our findings highlight the importance of considering multiple indoor environmental factors in relation to sleep and emphasize the potential of targeted thermal interventions to improve sleep quality. However, since the small sample size and short cross-over intervention period (3 weeks per condition) limit the generalizability of the results, future studies with larger and more diverse cohorts are needed to disentangle the relative contributions of environmental and physiological factors, and to assess the long-term efficacy of heating pads and other interventions in improving sleep quality. |
| 2-4 | 5/19/2026 13:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 118 | 571 | Eun Ji Choi and Joon-Ho Choi | School of Architecture, University of Southern California, Los Angeles, CA 90089 | Improving metabolic rate estimation in buildings through diffusion-based occluded pose reconstruction | Occupant-centric control Activity recognition AI-based data generation Computer vision | The importance of human integrated building systems is increasing, not only for occupant well-being and health but also for optimized building control. A critical element of such systems is the ability to detect occupant behavior. Recognizing occupants and understanding their activity context can provide key variables for thermal comfort assessment and energy-efficient HVAC control. Among these, pose-based activity recognition has advanced rapidly with the development of AI technologies. In particular, computer vision techniques using indoor images now enable real-time detection of activities and estimation of activity levels. However, vision-based methods often face significant limitations, particularly accuracy loss caused by occlusion due to varied poses, angles, or surrounding objects. To address this challenge, this study explores a multimodal inference approach that combines computer vision algorithms with AI-based data generation techniques. The proposed method aims to synthesize missing information in occluded images and improve the estimation of diverse indoor activities. To evaluate the method, over 10,000 images of five common indoor activities (standing, sitting, sleeping, walking, exercising) are collected through experiments. These data were used for training and testing the model, and error performance was analyzed to compare the proposed approach with conventional methods. Ongoing experiments will be further analyzed to demonstrate that the proposed model can generate reliable representations for occluded images, thereby improving activity estimation accuracy compared to conventional approaches. These findings are expected to confirm the potential of multimodal inference for robust occupant activity recognition in building applications. Future work will experimentally assess the applicability of this approach to real-world building environments. |
| 2-5 | 5/19/2026 13:30 | Thermal Comfort | GFS 101 | 42 | Maha Basha and Jim Uttley | School of Architecture and Landscape, The University of Sheffield, Sheffield, UK | Adaptive thermal comfort and healthy home metrics among minority households in the United Kingdom. | Adaptive Thermal Comfort (ATC) Healthy Homes Indoor Environmental Quality (IEQ) Ethnic Minority Complex-To-Decarbonise (CTD). | Ethnic minority households in the UK face compounded challenges in maintaining thermally comfortable and healthy indoor environmental conditions. Policy efforts tend to prioritise cost reduction and decarbonisation over indoor health, often assuming that achieving thermal comfort automatically ensures healthy living conditions. This assumption is questionable, especially for vulnerable and minority households who frequently live in cold, damp, and energy-inefficient homes that are Complex-To-Decarbonise. This study explores the current gap between thermal comfort and health metrics based on longitudinal real-world field measurements within one minority group in the UK, to assess whether thermal comfort metrics reflect healthy indoor conditions. Quantitative high-resolution data were collected from eleven minority households using Internet of Things (IoT) sensors recording temperature and relative humidity (RH) in the living areas over a one-year period. When looking at overheated and underheated conditions during annual occupied hours (7:00 am to 10:00 pm), all 11 cases had periods of cold stress, with temperatures below 18°C for up to 72% of annual occupied hours. Periods of overheating were observed in 8 cases, with temperatures over 26°C for up to 11% of the annual occupied hours. A dry living area was observed in one case, for up to 5% of the annual occupied hours. Excessively humid living areas with RH above 60% were identified in all cases, for up to 91% of annual occupied hours. The findings from this study demonstrate that relying on thermal comfort metrics may obscure unhealthy indoor conditions. Therefore, a combined approach linking thermal comfort and health is essential and will be beneficial for architects, academics, practitioners, and policymakers who are concerned with thermal health, inclusive and equitable approaches for home decarbonisation. The study applies a practical taxonomy to identify thermal and health stresses that may disproportionately affect minority households. |
| 2-5 | 5/19/2026 13:30 | Thermal Comfort | GFS 101 | 202 | Raimo Simson, Renate Jaanus, Martin Kiil, Karl-Villem Võsa, Endrik Arumägi, Alo Mikola and Jarek Kurnitski | Tallinn University of Technology | Balancing Cooling and Comfort: Lessons from Fan Coil Units in Estonia | Fan coil unit active cooling draught risk termal comfort indoor climate | This study examines the performance of fan coil units (FCUs) as active cooling devices during the cooling season across five case settings. Uncomfortable thermal conditions are known to impair cognitive performance, reducing concentration, memory retention, and reaction speed, whereas thermal comfort enhances productivity. Draught risk was evaluated through air velocity measurements conducted with a thermal comfort measurement kit equipped with low-air-speed probes. Measurements were performed in three open-plan offices and two control centers located in Estonia. The measured rooms were equipped with ceiling-mounted FCUs – either water-based or multi-split systems. The high-temperature cooling system demonstrated superior performance, maintaining air velocities predominantly below 0.2 m/s. Draught risk and occupant complaints were more pronounced in spaces with high ceilings. In several cases, workstation layouts were modified to avoid cold air jet zones, leading to inefficient spatial utilization. The findings underscore the need for careful FCU placement during design and performance verification during commissioning to ensure occupant comfort and space efficiency. |
| 2-5 | 5/19/2026 13:30 | Thermal Comfort | GFS 101 | 346 | Ryuichiro Yoshie | Tokyo Polytechnic University | Field Measurements in a Renovated Apartment with Underfloor Air Distribution Using a Single Mini-Split Heat Pump | Residential retrofits Underfloor air distribution Ductless mini-split heat pump | In Japan, an increasing number of households renovate condominiums after children leave home to create a lifelong residence. For such “final homes,” priorities include eliminating inter-room temperature differences to reduce heat-shock risk, using natural materials to support mental comfort and indoor air quality via low chemical emissions and moisture buffering, and minimizing HVAC energy. This study reports winter and summer 2025 field measurements in an 80 m2 apartment after a full-gut renovation. The insulation of exterior walls, floor, and ceiling was strengthened, and interior secondary windows (low-E double glazing) were added. A floor-first construction method installed the double raised floor before partitions, forming a continuous underfloor supply plenum (clear height ≈100 mm) with a floor outlet in each room. The energy-recovery ventilator (ERV) and ducts are located in the ceiling void with ceiling return and supply. The dwelling is conditioned solely by a single, low-cost, ductless mini-split heat pump (hereafter, AC)—rated 2.2 kW cooling and 2.5 kW heating. The indoor AC unit is set near the floor inside a walk-in closet, keeping living spaces free of visible equipment. The AC and ERV operated continuously (24 h/day). Hereafter, unless otherwise noted, temperature, absolute humidity (AH), COP, and ERV effectiveness are period averages. In winter 2025, inter-room ∆T was ≤ 2 °C with negligible vertical stratification. Indoor AH was 6–7 g/kg(DA) without supplemental humidification, while outdoor AH was 3.2 g/kg(DA). The ERV kept supply air near 20 °C and was ≈90/50/75 % sensible/latent/total effectiveness. Heating COP was 3.69. In summer 2025, thermal conditions were highly uniform (inter-room ∆T ≤ 2 °C; floor-to-ceiling ≈1 °C). Indoor AH was 12–13 g/kg(DA) while outdoor was 17.1 g/kg(DA). At the coldest underfloor point—directly beneath the AC discharge (minimum 12 °C)—no condensation or mold was found, and elsewhere underfloor air was warmer, so no condensation risk is expected. The ERV effectiveness was typically 60–80 % sensible and ≈70% latent/total. Cooling COP was 5.23. Overall, one standard, low-cost AC unit with an underfloor supply plenum and a ceiling-mounted ERV delivered whole-dwelling comfort with high spatial uniformity and high energy efficiency, suggesting a practical pathway for aging-friendly, low-energy retrofits. |
| 2-5 | 5/19/2026 13:30 | Thermal Comfort | GFS 101 | 567 | Ying Jiang, Yongxin Xie and Jianlei Niu | The Hong Kong Polytechnic University | Developing a physiological-parameter-based thermal sensation model for warm-biased outdoor settings: the dynamic part | Outdoor thermal comfort Thermal physiology-based model Thermal sensation Dynamic thermal environment Derivative of skin temperature | This study presents a comprehensive thermal sensation model that predicts subjective thermal sensation votes (TSVs) based on human physiological responses under dynamic warm-biased outdoor conditions. Human subject experiments were conducted in both step-up and step-down thermal environments, capturing a wide range of wind speeds (0.5–2.8 m/s) and solar radiation levels (mean radiant temperature, Tmrt: 28–63 °C). A total of 228 participants contributed to over 700 subjective surveys, which included TSV, thermal comfort vote (TCV), thermal acceptability (TA), thermal pleasure (TP), and thermal stay willingness (TSW). Environmental parameters and skin temperatures from up to 12 body regions were recorded. To address naturally occurring thermal fluctuations, two fluctuation modes were defined—highly-dynamic and weakly-dynamic—based on empirical thresholds of the derivative of local skin temperature dT_(sk,i)/dt within a 30-second window. The dynamic model comprises both step-up and step-down phases: the step-up phase uses dT_(sk,m)/dt and dT_(sk,i)/dt depending on fluctuation mode, while the step-down phase applies dT_(sk,i)/dt across both modes. The steady-state component was also refined, particularly for the abdomen, foot, and neck. A correction term incorporating a combined sun and wind index (SWI) was introduced to quantify the distinct effects of solar radiation and convective cooling on TSV. Among the thermal evaluation metrics, TSW demonstrated the strongest correlation with PET, highlighting its suitability for outdoor thermal assessment. The integration of steady-state, step-up, and step-down models enables accurate prediction of local and overall TSVs and can be coupled with thermoregulation models to support the thermal assessment of urban outdoor environments during design and renovation stages. |
| 2-5 | 5/19/2026 13:30 | Thermal Comfort | GFS 101 | 579 | Andrea Martinez-Arias, Marco Morales, Valentina Gonzalez, Maria José Peña, Daniel Canto and Isaias Navarrete | Universidad de Concepcion; Universidad de Concepción | Prototypes and on-field testing of eco-insulated modules for retrofitting building facades in public schools in Chile. | Public school Building retrofit eco-insulation Modular prototypes Monitoring. | In a context of mitigating the effects of climate change, it is essential to improve the performance of existing buildings, as the adverse effects range from the planet's health to people's well-being. Along with reducing the construction industry's carbon footprint, it is urgent to evaluate Indoor Environmental Quality (IEQ) in buildings. In schools, maintaining good indicators for IEQ, encompassing factors such as temperature, humidity, air quality, lighting, and acoustics, positively influences attendance, motivation, and academic performance in students. In a context of increasing extreme weather events driven by climate change, ensuring good IEQ in learning spaces is challenging, especially in aging buildings that most often do not comply with current standards or have not been updated to code. In vulnerable contexts, this is common, as budgets limit the postponement of good repair and maintenance when other urgencies arise. This work addresses the challenges that existing schools face in maintaining good spaces and effective facade retrofit strategies. In particular, a study on the design and testing of thermal insulation modules was conducted to mitigate thermal bridges in steel structures and in uninsulated walls of an existing school in the central-south region of Chile. The study focuses on critical areas of the thermal envelope of a modular school representative of a predominant typology in Chile, which served as a case study. To support the design, a comparative review of insulation materials available on the local market and construction strategies applied in similar contexts was conducted. Based on this, an organic-based insulation material produced locally was shown to be a compatible solution for integrating a modular solution that leveraged the existing structure in one classroom. By measuring temperatures (surface, air, and radiant) using sensors and thermal images, the impact of the designed modules was evaluated in comparison to a neighboring classroom serving as a control case. The results enable an assessment of the effectiveness and challenges of the proposed solution. Finally, this experimental study offers replicable guidelines for schools with similar conditions in other locations in Chile and other locations with similar buildings. |
| 2-6 | 5/19/2026 13:30 | Visual (Lighting and Daylighting) Quality and Accustic Quality | GFS 207 | 35 | Kuniaki Mihara, Daniel Jun Chung Hii, Hiroyuki Takasuna and Katsuhiko Sakata | Kajima Technical Research Institute; Kajima Technical Research Institute Singapore | From Simulation to Space: Impacts of Green Coverage Ratio and Spaciousness on Occupant Well-being in a Semi-outdoor Atrium | Indoor environmental quality Biophilic design Occupant well-being Post-occupancy evaluation | Our previous study explored how green coverage ratio and spaciousness influence self-reported performance and mood using a virtual reality (VR) head-mounted display. A semi-outdoor atrium was built in Singapore in the tropical climate to reflect the optimal conditions identified through VR experiments. This study aims to evaluate the effects of green coverage ratio and spaciousness on occupants’ self-reported performance and mood in the actual built environment, and to validate the prediction model developed from the VR study. A field survey was conducted in five locations within the atrium, each representing different combinations of high/low green coverage ratio and spaciousness from March to April 2024. Thirty-five occupants participated by completing a questionnaire after a 2-minute break during their working hours. We asked for their environmental satisfaction, moods, and self-reported performance such as work efficiency, mental fatigue and recovery. Temperature, relative humidity, illuminance, and noise level were measured during the experiment. The results showed that participants in high greenery spaces demonstrated higher visual comfort, concentration and more positive moods, as well as reduced mental fatigue, compared with the baseline workplace environment. Interestingly, even though air temperature was approximately 5 °C higher and noise levels were 6–8 dBA higher than in the workplace, occupants in the high greenery spaces reported feeling more comfortable both thermally and acoustically. The analysis further indicated that green coverage ratio tended to have a particularly strong effect on relaxed mood, while spaciousness tended to influence self-reported concentration and work efficiency. These findings support the notion that well-designed semi-outdoor environments with high greenery coverage ratio and sufficient spaciousness can promote psychological restoration and enhance workplace performance through strategies that optimize break intervals. |
| 2-6 | 5/19/2026 13:30 | Visual (Lighting and Daylighting) Quality and Accustic Quality | GFS 207 | 153 | Haerin Yang, Minwoo Kim and Jeehwan Lee | Myongji University; Technical University of Munich | Comparative EEG Neural Pattern Analysis of Occupant Responses to Window Configurations in Educational Environments | Electroencephalogram Neural pattern comparison Window configuration Educational environment Virtual reality(VR) | The daylight environment in educational settings plays a critical role in influencing students’ concentration, cognitive performance, and emotional well-being. This study employs EEG-derived neural activity patterns to compare how different classroom window configurations affect both cognitive and emotional responses. Rather than relying solely on conventional environmental metrics, this research applies a structured spatio-temporal-frequency analysis to determine which brain regions, frequency bands, and temporal segments exhibit changes in neural activity under varying daylight conditions. A comprehensive case study was conducted on 18 LEED-certified school buildings (Gold level or higher, Daylight Credit 2+) to identify five representative window types: i) single-sided, ii) two-sided, iii) three-sided, iv) repetitive full-height glazing, and v) combined high- and mid-level windows. Each configuration was implemented in a standardized classroom model. To ensure consistent and controlled exposure, participants experienced each modelled condition within an immersive virtual reality (VR) environment, with key daylight variables—vertical illuminance, glare probability, and view factor—meticulously regulated. EEG data were collected to capture neural patterns related to visual comfort, attention, and arousal, with a specific focus on metrics including frontal alpha asymmetry, theta/beta ratio, and P3 event-related potentials. This objective data was complemented by post-experiment surveys to record subjective comfort and preferences. Outcomes suggest that larger window configurations (three-sided and full-height glazing) will enhance frontal beta activity and frontal alpha asymmetry, indicating improved comfort and focus, whereas smaller windows (single-sided) are expected to increase alpha activity, reflecting relaxation and reduced engagement. High-level clerestory windows are predicted to elevate P3 amplitude, reducing visual distraction and supporting sustained attention, while two-sided arrangements are anticipated to stabilize occipital alpha rhythms, thereby mitigating visual fatigue. These insights elucidate the neural mechanisms linking daylight access and cognitive-emotional responses and offer evidence-based guidance for optimizing window design in educational environments. |
| 2-6 | 5/19/2026 13:30 | Visual (Lighting and Daylighting) Quality and Accustic Quality | GFS 207 | 198 | Yun-Shang Chiou and Wan-Hsin Cheng | National Taiwan University of Science and Technology | Between ClimateStudio simulations and reality – a study of glare in complex lighting workplace environments | Complex Lighting Environments Glare Daylighting ClimateStudio Post Occupancy Evaluation (POE) | The luminous environment of modern workplaces is often shaped by multiple light sources: self-luminous visual display units (VDUs), task lighting, ambient lighting, and daylight. Each source introduces different mechanisms of glare. To achieve a high-quality luminous environment, lighting simulations are typically conducted during the design phase to prevent glare. Ideally, such simulations are supported by reliable information on light sources, interior and furniture layouts, and occupant behavior patterns. In practice, however, this information is often incomplete. This paper presents a comparative study of simulated and measured glare in workplaces with complex lighting environments. The study forms part of a post-occupancy evaluation (POE) project at the global headquarters of a leading manufacturing company in Taichung, Taiwan. The headquarters, inaugurated in 2020, is a 15-story office building with extensive glass cladding. The glare study was carried out in open-plan offices on the 9th and 11th floors. Both offices are illuminated by three types of light sources: VDUs, artificial ambient lights, and daylight. Three sides of each office are lined with large window bands, and every workstation is equipped with VDUs. The layouts of the linear ambient lights differ between floors: on the 9th floor, they run orthogonal to the office furniture, while on the 11th floor, they run parallel. Field measurements were conducted in July and October 2023. High dynamic range imaging (HDRi) luminance mapping was applied to capture the impact of daylight on spatial luminance distribution. Data from the field measurements and a nearby weather station were used in ClimateStudio simulations. Because manufacturer data were unavailable, polar diagrams of the artificial lights were measured on-site. Glare analysis was performed using HDR Scope software. The results suggest that, in complex lighting environments, ClimateStudio simulations are most effective for predicting daylight glare, whereas glare from artificial light sources may be more accurately predicted by other lighting simulation tools. More than one simulation tools may be needed for a comprehensive glare prediction. |
| 2-6 | 5/19/2026 13:30 | Visual (Lighting and Daylighting) Quality and Accustic Quality | GFS 207 | 217 | Chung-Luen Cheng and Ying-Chieh Chan | National Taiwan University | Interactive Lighting Design and Simulation Interface Based on BIM and Game Engines for Smart Indoor Environments | Light Simulation Building Information Modeling Game Engine Lighting Design | With the continuous advancement of digital design technologies in the architectural field, Building Information Modeling has become a crucial technique within the architectural design process. Its strong capability for integration and scalability brings new opportunities for simulating a building's physical environment. Among those applications, indoor light design has received growing attention due to its significant impact on users' visual comfort and its increasing relevance in BIM-integrated research. Currently, most existing light simulation tools focus on quantitative analyses of static parameters, such as energy consumption calculations and daylight studies. Although some scholars have applied game engines to interactive lighting simulations, concerns remain regarding the accuracy of their simulation results. This research aims to integrate Building Information Modeling (BIM) technology, professional lighting simulation software, and game engine platforms to establish a real-time, interactive, and immersive lighting design process and develop an operational interactive interface for light environment design. The research is divided into three main components: First, a literature review examining the applications of BIM and game engines in lighting design and the impact of immersive game-engine interface on user interaction; second, the development of the research framework, including user interface design, functional modules, and lighting simulation accuracy verification under different environmental conditions; and third, the evaluation phase, which compares measured data, professional simulation software, and game engine results. The outcomes of this study are expected to balance simulation accuracy and real-time interactivity, providing a more intuitive and efficient tool for indoor lighting design and offering a reference for the future development of interactive architectural design tools. |
| 2-6 | 5/19/2026 13:30 | Visual (Lighting and Daylighting) Quality and Accustic Quality | GFS 207 | 396 | Zahra Najafi and Mehdi Ashayeri | School of Architecture, Southern Illinois University Carbondale, Carbondale, IL 62901, USA, mehdi.ashayeri@siu.edu; School of Architecture, Southern Illinois University Carbondale, Carbondale, IL 62901, USA, zahra.najafi@siu.edu | A Framework for Designing Kinetic Fabric Shading Systems Optimizing Integrated Energy, Daylight, and View Clarity Metrics | Dynamic Shading Systems Openness Factor Multi-Objective Optimization Daylighting Energy Efficiency View Clarity Index | This study addresses the gap in evaluating the performance of dynamic fabric shading systems by integrating energy, daylight, and view clarity metrics into early-stage architectural design. Few studies have simultaneously optimized these metrics, particularly in relation to the Openness Factor (OF) of fabric shading. To bridge this gap, this research proposes a comprehensive framework for the design and optimization of kinetic fabric shading systems using an evolutionary-based multi-objective optimization approach. The framework automates the exploration process, focusing on optimizing Spatial Daylight Autonomy (sDA), Annual Sun Exposure (ASE), Lighting Energy (LE), and the View Clarity Index (VCI) defined by the EN 14501:2021 standard. It is developed on open-source platforms, including Rhino 7, Grasshopper, Ladybug Tools, and Wallacei, enabling flexible parametric modeling and optimization. The study evaluates fabric materials with OFs ranging from 1% to 10% across three representative shading patterns inspired by the Al-Bahar Tower, SDU Campus Kolding, and Kiefer Technic Showroom façades. The framework is applied to the Graduate Studio at the School of Architecture, Southern Illinois University Carbondale (SIUC), where kinetic shading systems are compared with existing internal roller shades. Results demonstrate the ability of kinetic systems to balance daylight performance, energy efficiency, and view clarity more effectively than conventional shading. To strengthen reliability, the study experimentally validates simulation outcomes by employing a daylight sensing method in the Graduate Studio at Quigley Hall, SIUC. Validation compares baseline roller shade performance against simulated data, evaluated using Root Mean Square Error (RMSE) and Coefficient of Variation of RMSE (CVRMSE) metrics. By combining simulation and experimental validation, this research provides a replicable framework for assessing and optimizing dynamic fabric shading systems, contributing to the advancement of high-performance, occupant-centered building design. |
| 2-7 | 5/19/2026 13:30 | Panel Discussion | SGM 101 | 601 | Maninder Thind, Rebecca Martinez, Anushka Raut, Yu Hou | California Energy Commission | Advancing Healthy, Equitable Buildings: Integrating Research, Standards, and Decarbonization Practice | Healthy Buildings Indoor Air Quality Research Building Energy Efficiency Standards Implementation Electrification Policy | California’s transition toward healthier, low-emission buildings is driven by a combination of strengthened ventilation standards, expanding building electrification efforts, and an increasing focus on equitable implementation. Yet this transition requires integrating applied research, technology demonstration, building standards development, and community-centered program design in ways that meaningfully improve indoor air quality and protect public health. This session brings together experts across the California Energy Commission’s research, standards, and decarbonization programs to illustrate how evidence-based ventilation guidance, technology demonstration and deployment innovations, and equity-informed implementation strategies are shaping the next generation of healthy buildings. Presenters will highlight research on indoor air quality, health, and equity; discuss the evolution and rationale behind ventilation and indoor air quality requirements in the Building Energy Efficiency Standards; illustrate how advanced electrification technologies, smart controls, and deep-retrofit strategies are shaping scalable pathways to healthy, high-performance buildings; and explore how targeted incentives and program design under the California’s Equitable Building Decarbonization Program support healthier, cleaner homes—especially in under-resourced communities. Collectively, the panel provides attendees with a multi-disciplinary perspective on how California’s policies, research investments, and field demonstrations are advancing healthier, more equitable, and climate-aligned buildings. |
| 3-1 | 5/19/2026 15:30 | Indoor Air Quality | SGM 123 | 15 | Hanin Othman and Rahman Azari | Associate Professor of Architecture; Penn State University | Enhancing the Granularity of Spatial Sensing using a Low-Cost IoT-based Sensing Network | Low-Cost Sensors Indoor Air Quality (IAQ) Sensing Network Spatial Resolution | Indoor carbon dioxide (CO₂) concentration is a widely used indicator of ventilation effectiveness, occupancy-driven emissions, and indoor environmental quality, with direct implications for health, comfort, and cognitive performance. As demand increases for continuous and spatially resolved indoor CO₂ monitoring, low-cost sensing systems integrated with advanced modeling techniques offer a promising alternative to traditional, sparsely deployed reference instruments. This study presents a hybrid fixed–mobile, low-cost Internet-of-Things (IoT) sensing framework to reconstruct high-resolution spatiotemporal indoor CO₂ distributions from limited sets of sensing data collected using fixed-mobile sensing systems. After validating individual sensor nodes against reference instrumentation, a distributed sensing network was deployed in a controlled indoor environment using a combination of continuously operating stationary sensors and sequentially repositioned portable devices. A grid-based stop-and-measure protocol was adopted to ensure measurement stability while achieving full spatial coverage under sparse and asynchronous sampling conditions. To reconstruct CO₂ concentration fields from incomplete spatiotemporal observations, Gaussian Process (GP) and Random Forest (RF) models were evaluated under random, periodic, and spatial cross-validation schemes. Results show that GP consistently outperformed RF in terms of variance preservation, spatial generalization, and normalized error metrics, aligning with ASTM D5157-19 recommendations for indoor air quality model evaluation. This work demonstrates that combining low-cost hybrid sensing with uncertainty-aware spatiotemporal modeling provides a scalable and cost-effective approach for indoor CO₂ monitoring. Future work will extend the framework with autoregressive spatiotemporal formulations to better capture short-term temporal dependence and localized transient peaks under occupied conditions, varying ventilation states, and real-time digital twin integration. |
| 3-1 | 5/19/2026 15:30 | Indoor Air Quality | SGM 123 | 261 | Lu Li, Jiawei Wang, and Katie E. Angarano | University at Albany, State University of New York | Long-Term Indoor Air Quality Exposure Assessment in Academic Buildings | Indoor air quality Academic buildings Long-term monitoring Health exposure index | Indoor air quality (IAQ) assessment and control in academic buildings is an engineering challenge due to high occupant density, fixed class schedules, and prolonged daily use, which together create sustained exposure conditions not captured by short-term measurements. Most existing IAQ studies in educational environments rely on short-term monitoring and concentration-based compliance metrics, limiting their ability to quantify cumulative exposure and long-term ventilation performance. This study develops and applies a long-term, occupancy-aware exposure assessment framework for indoor carbon dioxide (CO2) based on continuous sensor data. An exceedance-based Health Exposure Index (HEI) and a Cumulative Exposure Index (CEI) are formulated using time-resolved CO2 measurements and schedule-based student occupancy weighting. HEI quantifies the intensity and duration of concentration exceedance above engineering thresholds (800, 1000, and 1600 ppm), while CEI captures cumulative exposure above background concentration. The framework is demonstrated using 5-minute resolution data collected from January 2025 to March 2025 in a historic academic building at Schreiner University (ASHRAE Climate Zone 2B). Results show clear distinctions between non-instructional and instructional operations. During winter break, indoor CO2 remains near the outdoor background (420 ppm), whereas during academic periods, concentrations increase sharply, reaching peak values of approximately 1211 ppm (63.9% increase). Daily analysis indicates that HEI can remain zero on instructional days when thresholds are not exceeded, while CEI remains positive, revealing persistent exposure not captured by exceedance metrics alone. Monthly results show HEI increasing from 159.1 in January to 427.8 in February and 1221.7 in March, indicating progressively more frequent and severe ventilation stress, while CEI increases more gradually from 162.4 ppm to 485.5 ppm. Seasonal aggregation (January-March) yields a HEI of 589.7 and a CEI of 344.4 ppm. The results demonstrate that threshold-based compliance metrics alone are insufficient for evaluating long-term IAQ performance in academic buildings. The proposed dual-metric framework provides an engineering-relevant, scalable approach for quantifying both exceedance severity and cumulative exposure, supporting improved ventilation evaluation and long-term IAQ management in educational facilities. |
| 3-1 | 5/19/2026 15:30 | Indoor Air Quality | SGM 123 | 317 | Jehyun Kim and Minki Sung | Sejong University | Estimation of the Number of Occupants Using Carbon Dioxide Concentration and Differential Pressure Data Based Machine Learning Model | Machine Learning Internet of Things CO2 concentration Differential Pressure Number of Occupants | The building sector accounts for a significant 39% of total global energy consumption, with HVAC systems consuming the largest share at 40%. Precise indoor occupancy estimation is a critical factor for demandcontrolled ventilation, which balances energy reduction with comfortable indoor air quality. While environmental data-based methods are privacy-friendly, they often face challenges such as time lags and unaccounted air leakage. This study aims to enhance estimation accuracy by utilizing differential pressure data and door/window opening status to reflect these leakage variables. Data was collected from an office laboratory using IoT sensors to monitor CO2 concentration, ventilation system power, and differential pressure between the room and adjacent spaces. Three machine learning models—Multi-Layer Perceptron (MLP), Random Forest (RF), and Long Short-Term Memory (LSTM)—were evaluated across five experimental cases. A physicsinformed approach was implemented by incorporating the CO2 mass balance equation as a specific input variable to calculate airflow rates. The results indicated that the LSTM model outperformed MLP and RF models in all scenarios. Case 5, which integrated all variables including the occupancy equation results, achieved the highest accuracy of 0.612 and the lowest Root Mean Squared Error (RMSE) of 0.981. The inclusion of door and window opening status significantly reduced estimation errors compared to the baseline case. In conclusion, incorporating real-time leakage through differential pressure and opening status into a physics-based neural network framework substantially improves the reliability of occupancy estimation for smart building control. |
| 3-1 | 5/19/2026 15:30 | Indoor Air Quality | SGM 123 | 324 | Arezoo Shirazi, Artur Grigorev, Payam Keshavarz Mirzamohammadi, Dikaia Xenaki, Brian Oliver and Adriana-Simona Mihaita | Data Science Institute, University Technology Sydney; Department of Construction Management and Architectural Studies, California State University, Fresno; School of Built Environment, University Technology Sydney; School of Life Sciences, University Technology Sydney; Woolcock Institute of Medical Research | Indoor and Outdoor Air Quality Monitoring in a Sydney Medical Research Center Using IoT and Toxicological Assessment | Indoor air quality IoT sensors particulate matter toxicological PM monitor medical buildings. | Indoor air quality (IAQ) is a critical factor in protecting health and supporting productivity in sensitive environments such as research centers. While IAQ in schools and offices has been widely studied, limited evidence is available for university-affiliated medical research facilities, particularly in the Australian context. This study reports on a four-week monitoring campaign conducted at a medical research institute in Sydney. A network of IoT-based Smart Citizen Kits was deployed across two functional floors, administrative offices (Floor 2) and PC2 laboratories (Floor 3), together with an outdoor reference node. Each unit recorded multiple environmental parameters including carbon dioxide (CO2), particulate matter (PM1, PM2.5, PM4, PM10), formaldehyde, temperature, relative humidity, barometric pressure, light, noise, and ultraviolet radiation. To ensure data reliability and explore the actual health impacts, IoT particulate measurements were benchmarked against a co-located toxicological particulate matter collector (JCH Environmental PM Sampler) capable of assessing total suspended particles and later tested for toxicology level. Preliminary analyses compare indoor and outdoor air quality and highlight differences between office and laboratory environments. Results show that while mean indoor concentrations largely remain within international guideline limits, short-term variations and room-specific differences are evident. These findings underline the importance of continuous IAQ monitoring in medical research centers and provide a foundation for strategies to maintain safe and healthy indoor environments. |
| 3-1 | 5/19/2026 15:30 | Indoor Air Quality | SGM 123 | 549 | Aaron Collins, Joseph Stam and Rob Caldow | Lean Forward Consulting; OpenAeros LLC | Evaluating and Mitigating Residential Fine and Ultrafine Particle Exposure via an Open-Source Condensation Particle Counter and Low-Cost Sensor Suite | Ultrafine particles (UFP) Condensation particle counter (CPC) Open-Source Hardware Indoor air quality (IAQ) Portable Air Cleaner (PAC) | Indoor air quality (IAQ) standards and public health guidance have traditionally relied on mass-based particulate matter metrics, most notably PM2.5. However, a growing body of evidence indicates that ultrafine particles (UFP) represent a distinct and clinically relevant exposure class that is poorly captured by mass-based measurements. UFPs contribute negligibly to particle mass yet dominate particle number concentration and surface area, properties associated with enhanced biological reactivity and systemic transport. Despite this, UFPs are rarely monitored in residential environments due to the cost and operational complexity of conventional condensation particle counters (CPCs). This study presents a two-week field deployment of the OpenCPC®, a low-cost, fully open-source CPC, in an occupied single-family home. UFP number concentrations were measured concurrently with PM2.5 mass, optical particle counts (>0.3 µm), and CO₂ using a distributed sensor network spanning two floors. A daily crossover design was used to evaluate the effectiveness of portable air cleaners (PACs) operated in alternating 24-hour periods. Results show that PAC operation reduced mean UFP concentrations by 55.5% in the primary living area and 90.7% in an upstairs bedroom, with corresponding PM2.5 reductions of 82.3% and 93.2%, respectively. Time-resolved data revealed consistent inter-floor transport of particles with a 15 to 20-minute lag, indicative of stack-driven vertical migration. Correlation analysis demonstrated strong agreement among co-located optical sensors but a marked decoupling between PM2.5 and UFP concentrations, particularly across zones. These findings confirm that mass-based metrics are insufficient proxies for UFP exposure in residential settings. The study demonstrates that accessible CPC technology enables routine UFP monitoring and that distributed portable filtration provides an effective, layered mitigation strategy for both ultrafine and accumulation-mode particles in naturally ventilated homes. |
| 3-2 | 5/19/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 334 | Heon-Min Lee, Youngsub An, Jongkyu Kim, Jae-Won Jeong and Min-Hwi Kim | Hanyang University; Korea Institute of Energy Research | Experimental and Theoretical Performance Analysis of a Building-Integrated Photovoltaic and Thermal (BIPVT) System | Photovoltaic and thermal panel building-integrated system thermal and electrical efficiency experimental validation | Building integrated photovoltaic thermal (BIPVT) systems can generate electricity and heat from building envelope areas where deploying a photovoltaic thermal (PVT) system is challenging, as this study's experimental approach investigates and validates prediction models for a frameless curtain wall liquid BIPVT system. Eight 1 m² modules were operated from September 1st to November 8th, 2025, and a set of operational data were recorded. This dataset encompasses parameters like vertical-plane irradiance, ambient air temperature, inlet/outlet fluid temperatures, volumetric flow rate, and inverter-based electrical power. The model calculates electrical power using a conventional power equation. It estimates cell temperatures with a NOCT-based linear temperature model and a physics-based cell temperature model. Thermal performance is predicted using a Hottel–Whillier model based on lossless efficiency and a first-order heat-loss coefficient, and a physics-based outlet temperature model that predicts outlet temperature from heat-transfer mechanisms. The model's validation is achieved through a comparative analysis of predicted and measured monthly power generation and heat collection. Daily root mean square error is recorded as 0.24, 1.68, and 1.37 kWh/day for electricity and 0.29, 1.28, and 1.50 kWh/day for heat in September, October, and November, respectively. Total power generation was 87.98 kWh. The closest prediction was 87.14 kWh from the physics-based cell temperature model with an error rate of -0.5%. The total heat collection was 113.08 kWh, and the closest prediction was 116.97 kWh from the physics-based outlet temperature model, with an error rate of +3.4%. The outlet-temperature correlation for the physics-based model yielded an R² value of 0.9612. The findings suggest that the physics-based cell/outlet temperature models exhibit the lowest prediction error for the target liquid-type BIPVT system by directly reflecting the multilayer conductive structure and tube–fluid heat transfer. The validated models can support performance prediction, system capacity sizing, and energy self-sufficiency analysis for future building applications of BIPVT systems. |
| 3-2 | 5/19/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 338 | Ye-Bin Shin, Jae-Won Jeong and Min-Hwi Kim | Hanyang University; Korea Institute of Energy Research | Experimental Analysis of a Building-Integrated Photovoltaic and thermal (BIPVT) Module with Detachable Phase Change Material (PCM) for Curtain Wall Applications | Building-integrated system photovoltaic and thermal system phase change material | The increase in panel temperature in a photovoltaic and thermal system (PVT) leads to a degradation of power generation performance, making it essential to suppress the module's temperature rise. This study developed a Building integrated photovoltaic and thermal system (BIPVT-PCM) module with a phase change material (PCM) attached to the rear of a BIPVT module. This module has the advantage of a detachable PCM and can be easily installed on buildings in a curtain wall form. To ensure experimental accuracy, experiments were conducted in three phases during the winter. Phase 1 compared the power generation performance between Building integrated photovoltaic system (BIPV) modules, Phase 2 compared the thermal and power generation performance between BIPVT modules, and Phase 3 applied PCM to only one module to compare the performance of each module. The analysis results showed that the average electrical efficiency for both modules was 11.5%, with no significant performance improvement observed. The thermal efficiency decreased by 14.2% with the attachment of PCM. This was because although the heat generated during module operation was transferred to the PCM, the direct attachment method to the rear of the panel caused the transferred heat to re-influence the panel's temperature. However, thermal imaging analysis showed that the PCM prevented a rapid increase in the panel's temperature. This indicates that while the PCM contributes to the temperature stabilization of the panel, its latent heat storage properties caused a delay in the heat recovery time, making it disadvantageous for real-time heat recovery. Therefore, directly attaching PCM to the rear of the BIPVT module is not effective for improving the module's thermal performance. This suggests that when applying PCM to a BIPVT, a design for an alternative attachment method is necessary. |
| 3-2 | 5/19/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 475 | Shun Okihara, Hideki Sato and Katsunori Nagano | Hokkaido University; National Institute of Technology, Tomakomai College; SANKEN SETSUBI KOGYO CO., LTD. | A study on optimal energy management with forecasting PV power generation and energy consumption for ZEB provided by GWHP and energy storage. | Energy optimization Machine learning Photovoltaic system Electrical battery Demand response | The rapid proliferation of renewable energy technologies, particularly photovoltaic (PV) systems, combined with the declining costs of energy storage, has significantly increased interest in advanced energy management strategies that prioritize the on-site use of excess electricity. Demand Response (DR) programs and Model Predictive Control (MPC) have emerged as practical approaches to balance electricity demand while minimizing objectives such as economic costs and greenhouse gas emissions. A critical requirement for these strategies is the ability to forecast both energy generation and consumption accurately. This study focused on a medium-sized office building located in a cold climate, with the objective of reducing electricity expenses. Through optimization calculations, the most efficient operational schedules for various energy systems—including photovoltaic (PV) systems, electrical batteries, thermal storage tanks, HVAC units, and heat pump water heaters—were identified. PV generation was forecasted utilizing Long Short-Term Memory (LSTM) networks. Concurrently, forecasts of electricity demand and HVAC thermal loads were predicted with Transformer models enhanced by incremental learning to augment accuracy and adaptability. These forecasts were integrated with device performance characteristics, derived through piecewise linear regression, and operational constraints to formulate optimal schedules for electrical batteries, HVAC units, and heat pump water heaters using Mixed-Integer Linear Programming (MILP). A comparative analysis was conducted against a traditional Rule-Based Control (RBC) strategy, which demonstrated that the proposed optimization-based approach effectively shifted load peaks in response to excess generation and fluctuating electricity prices. This facilitated efficient energy charging and discharging, resulting in a reduction of electricity procurement costs and overall expenditure compared to the RBC methodology. The most significant benefits were observed during the summer season when PV generation was abundant. |
| 3-2 | 5/19/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 563 | Yong You and Qiuhua Duan | University of Alabama | Multi-objective performance assessment of rear-ventilated BIPV double facade using CFD | Building-integrated photovoltaics (BIPV) PV panel double skin CFD | Rear-ventilated BIPV facades enhance both building thermal performance and PV efficiency. This study numerically investigates the cooling performance of such facades under varying cavity geometries using a single-room CFD model with a non-gray, two-band discrete ordinates (DO) radiation approach. Results show that increasing cavity depth and vent height strengthens airflow and convective heat transfer. The optimal configuration enhanced wall heat removal by approximately 37% compared to the worst-performing case. While ventilation significantly reduced PV temperatures, differences among configurations were minor due to the aluminum back sheet's high thermal conductivity, which promotes heat spreading. Notably, airflow organizations were found to govern the spatial heat flux distribution. These findings highlight the critical role of geometric design and cavity airflow organization in the development of high-performance, energy-efficient BIPV envelope systems. |
| 3-2 | 5/19/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 560 | Mohammed Nazarpoor and Huijeong Kim | University of Kansas | Challenges and Drivers of Battery Second-Use Community Energy Storage Development: Integrating Social, Techno-Economic, and Behavioral Perspectives | Battery second-use Community energy storage Mixed method research Community energy resilience | Repurposing retired electric vehicle (EV) batteries into building energy storage offers a sustainable pathway to strengthen energy resilience in under-resourced communities. Our goal is to develop Battery-Second-Use Community Energy Storage (B2U-CES) by engaging local residents in transforming retired EV batteries into affordable, sustainable infrastructure for backup power and demand flexibility. This research examines the social and techno-economic challenges and drivers of B2U-CES through a mixed-method approach that includes surveys and semi-structured interviews with key stakeholders. Data analysis involves open, axial, and selective coding to identify recurring themes and relationships, which are then cross-validated with public data sources for robustness. Key findings are organized into three themes: (1) community needs, (2) technical constraints, and (3) financial considerations. Building on these findings, discrete-choice modeling is used to model EV owners’ willingness to donate batteries and estimate potential community battery supply under different conditions, considering demographics, vehicle usage, and socio-economic characteristics. The results provide empirically grounded insights to guide technology innovation, community engagement, and mechanism design for B2U-CES development. |
| 3-3 | 5/19/2026 15:30 | Building Technology and Performance | SGM 101 | 129 | Sameeraa Soltanian-Zadeh, Shayan Mirzabeigi, Bess Krietemeyer and Jianshun Zhang | Syracuse University | Integrated Evaluation of Energy Performance, Indoor Environmental Quality and Building Envelope Performance in Retrofitted Multifamily Residential Buildings | Energy retrofit Building Envelope Indoor environmental quality Occupant behavior Post-occupancy evaluation. | Energy retrofits in residential buildings can substantially reduce energy demand while enhancing thermal comfort and indoor environmental quality (IEQ). However, the interactions between these outcomes remain insufficiently documented, particularly in occupied multifamily settings where occupant behavior plays a significant role. This study presents an integrated pre- and post-retrofit evaluation of two two-story, multifamily townhouse-style buildings (14 apartments total) in Syracuse, New York, USA, combining in-situ monitoring with occupant environmental surveys. The whole-building retrofit approach includes highly insulated prefabricated exterior building envelope panels for improved thermal performance and airtightness at the walls, roof, and foundation, and high-efficiency integrated mechanical pod solution for heating, cooling, ventilation, and domestic hot water. Energy performance was assessed through power consumption measurements, showing a normalized 76% reduction in thermal energy use during the heating season compared to pre-retrofit levels. Continuous monitoring captured indoor air temperature, relative humidity, CO2, PM2.5 concentration, and envelope surface temperatures across multiple seasons. R-value value characterization results indicated a post-retrofit mean effective R-value of 6.02 m²·K/W, representing a considerable improvement. However, blower door tests showed only marginal increase in enclosure airtightness. Occupant surveys documented self-reported thermal comfort, perceived air quality, satisfaction with retrofit outcomes, and behavioral patterns such as window operation and thermostat use. Results indicated improved thermal stability, lower CO2 levels, and reduced heating demand consistent with measured energy savings. Nevertheless, variability in reported thermal comfort highlights the continued influence of occupant activities and preferences. This study demonstrates the value of integrating quantitative building performance metrics with qualitative occupant feedback to fully assess retrofit outcomes. The findings support occupant-centered retrofit strategies that couple technical improvements with user engagement to ensure that energy efficiency gains are achieved alongside healthy, comfortable indoor environments. |
| 3-3 | 5/19/2026 15:30 | Building Technology and Performance | SGM 101 | 178 | Yuchong Qian and Jiawei Leng | Southeast University | How Digital Twin Platforms Empower the Decarbonization of Built Environments: A Case Study of a Vernacular Dwelling | Decarbonizing built environments Digital twin Digital intelligence technologies Carbon emissions measurement Multimodal perception and integration | Decarbonizing built environments is crucial to the global carbon neutrality strategy. Central to this transition are operational carbon footprint accounting and the development of zero-carbon energy supply systems, both of which depend on the integration of extensive multi-source heterogeneous data. The processes of information acquisition, performance evaluation, and optimized retrofitting are thus interconnected and mutually reinforcing, necessitating integrated tools that bridge these stages to advance systematic decarbonization research. Digital twin technology offers a structured framework for incorporating diverse digital intelligence technologies, enabling minimal-intervention yet highly efficient aggregation of multimodal data. It also provides a transparent, controllable, and manageable platform for rapid building performance assessment and coordinated energy dispatch, serving as an ideal medium for multi-module integration in the decarbonization of built environments. This paper investigates the technology roadmap and implementation methods for digital twin-enabled decarbonization of built environments through a case study of a Chinese patio-style vernacular dwelling. The process begins with intelligent multi-source information perception and correlation to provide data support for carbon footprint accounting and optimization. Subsequently, a multi-indicator coupled operational carbon footprint accounting model is established, incorporating physical parameter matrices associated with carbon emission activities to quantify spatiotemporal carbon distribution and identify optimization priorities. Finally, performance-driven design is integrated with smart control technologies to achieve energy system upgrades, all unified through a digital twin platform. Empirical results demonstrate that the platform achieves real-time carbon footprint prediction with errors below 15% through autonomous integration of multi-source data. An upgraded intelligent control system enables automated regulation based on predefined thresholds, ensuring both habitability and carbon-neutral operation aligned with pre-designed energy supply strategies. By addressing the current fragmentation among evaluation, design, and operation in building performance optimization, this research provides innovative pathways and methodological guidance for decarbonizing the built environment, while promoting the adoption of digital intelligence in sustainable building retrofits. |
| 3-3 | 5/19/2026 15:30 | Building Technology and Performance | SGM 101 | 305 | Yun-Jin Hong, Jabin Goo, Dong Hee Choi and Dong Hwa Kang | Department of Architectural Engineering, Graduate School, University of Seoul; Department of Architectural Engineering, University of Seoul; Institute of Construction and Environmental Engineering, Seoul National University | Prediction of Dehumidification Performance of a Window-Type Liquid Desiccant Ventilation System | Liquid desiccant Window-type ventilation Regression Model Moisture removal Dehumidification fulfillment | Rising summertime outdoor air humidity is leading to an increase in the dehumidification load required to maintain acceptable indoor environments. The objective of this study is to develop an empirical regression model is to predict the dehumidification performance of a window-type liquid desiccant ventilation system, which can be implemented in EnergyPlus. A prototype of the dehumidification module of the ventilation system proposed in a previous study was developed, and experiments were conducted under varying outdoor air temperature and humidity conditions to derive regression models. Based on the experimental results, empirical regression models were developed to predict the outlet air conditions as functions of the inlet air conditions, specifically outdoor air temperature and humidity, in a form compatible with implementation in EnergyPlus. The developed models achieved high predictive accuracy, with coefficients of determination of R² = 0.99 for outlet air humidity and R² = 0.98 for outlet air temperature. Furthermore, the daily dehumidification performance of the system was evaluated for a residential building during the summer season in Seoul(122days). The results show that the system satisfied 100% or more of the daily required dehumidification load on approximately 49% of the total days, while providing an average of approximately 60% of the required dehumidification load on the days when the requirement was not fully met. These results indicate that the proposed system can make a practical contribution to mitigating ventilation-induced latent cooling loads in hot and humid environments. |
| 3-3 | 5/19/2026 15:30 | Building Technology and Performance | SGM 101 | 390 | Jiwon Park, Sangjoon Lee, Jiayu Li, Kian Wee Chen, Ippei Izuhara, and Stefano Schiavon | Center for the Built Environment, University of California, Berkeley; Center for Turbulence Research, Stanford University; Global Environmental Technologies Inc. | A simulation study on condensation risk in radiant cooling panels with elevated air movement | Radiant cooling Condensation risk Computational fluid dynamics | Radiant cooling panels are an energy-efficient heating, ventilation, and air conditioning (HVAC) alternative to conventional all-air systems, as they operate with higher chilled water temperatures and rely on water as the primary heat transfer medium. However, their wider adoption has been constrained by the risk of surface condensation, which limits allowable surface temperatures and reduces cooling capacity. Elevated air movement, such as that induced by ceiling fans, has been proposed as a strategy to enhance cooling capacity and maintain thermal comfort, yet its impact on condensation behavior remains insufficiently understood, particularly under conditions where panel surfaces operate below the dew point. This study employs transient computational fluid dynamics (CFD) simulations using the interThermalPhaseChangeFoam solver in OpenFOAM to investigate the effects of air speed on condensation phenomena over a uniformly cooled radiant panel. A simplified numerical wind tunnel containing a small-scale radiant panel element is simulated to isolate airflow effects on phase change behavior with air temperatures of 22-27 °C, relative humidity levels of 50-60%, air velocities ranging from 0-3 m/s, and panel surface temperatures set 0.5-2.0 °C below the dew point. The analysis focuses on steady-state phase change heat flux and equivalent water thickness on the panel surface. Results show that increasing subcooling temperature (defined as the difference between the panel surface temperature and the dew-point temperature of the surrounding air) consistently increases both phase change heat and equivalent water thickness. In contrast, the influence of air speed on phase change heat is strongly dependent on subcooling level, exhibiting non-monotonic behavior at higher subcooling conditions. Meanwhile, the equivalent water thickness decreases monotonically with increasing air velocity across all cases, indicating enhanced removal of condensed water by airflow. These findings demonstrate that condensation risk cannot be assessed using a single metric alone and highlight the importance of jointly considering latent heat transfer and surface water retention. The results further suggest that, under appropriate subcooling and airflow conditions, elevated air movement may enable increased cooling capacity while mitigating practical condensation risks in radiant cooling applications. |
| 3-3 | 5/19/2026 15:30 | Building Technology and Performance | SGM 101 | 462 | Daisuke Ogura, Sora Nakaike, Makiko Nakajima and Masaru Abuku | Department of Architectural Engineering, Faculty of Engineering, Hiroshima Institute of Technology; Department of Architecture and Architectural Engineering, Graduate School of Engineering, Kyoto University; Department of Architecture, Faculty of Architecture, Kindai University | Investigation of Hygrothermal Control and Architectural Measures to Reduce Mold Risk in RC Detached Houses in Hot and Humid Regions | Hot and humid regions Mold Okinawa Numerical simulation RC detached houses Mold index | Mold can cause health hazards such as allergies and respiratory diseases, making it one of the significant environmental risks in the built environment. In hot and humid regions with high temperatures and humidity year-round, significant temperature differences between indoors and outdoors due to the use of air conditioning lead to summer condensation and associated mold occurrence. For these reasons, the need for humidity control measures in hot and humid regions is increasing. Okinawa Prefecture is the only region in Japan characterized by a hot and humid climate throughout the year. This paper proposes methods to suppress high humidity during the rainy season in highly ventilated reinforced concrete (RC) houses located in Okinawa from the perspectives of “occupant behavior” and “architectural measures.” For each proposal, we examined changes in temperature and humidity within the bedroom using multiple room temperature and humidity analysis simulations. We evaluated the mold suppression effect using a mold index and calculated the power consumption of the air conditioner and dehumidifier. Regarding occupant behavior, two approaches to reducing relative humidity were examined: increasing temperature via heating, and lowering absolute humidity via dehumidifier operation. It was demonstrated that both methods reduce the risk of mold growth. Furthermore, it was found that operating heating and a dehumidifier for three hours reduced the risk of mold growth to a similar level, and heating consumed less electricity than the dehumidifier. From the architectural perspective, thermal insulation and airtightness retrofitting is proposed. This proposal significantly reduced the risk of mold growth and lowered power consumption compared to heating operation or dehumidifier use. |
| 3-3 | 5/19/2026 15:30 | Building Technology and Performance | SGM 101 | 540 | Enkh-Uchral Erdenebaatar, Taro Mori, Amarbayar Adiyabat and Hisato Osawa | Graduate School of Engineering, Hokkaido University; School of Engineering and Technology, National University of Mongolia | Field Evaluation of Winter Indoor Environmental Performance of a Passive House–Level Detached House in Mongolia | Passive House Cold Climates Thermal Performance Indoor Air Quality Building Envelope | Mongolia is one of the coldest countries in the world, where nearly 70% of households burn coal and other solid fuels for heating. On average, a household consumes 3–5 tons of coal per year, resulting in severe air pollution during the long heating season. This situation underscores the urgent need to improve housing quality to reduce energy inefficiency and enhance thermal comfort. However, very few studies have addressed the housing design strategy in Mongolia. This study presents a case analysis of a newly constructed passive house–inspired detached house in Ulaanbaatar. Field measurements conducted during winter included airtightness testing, monitoring of indoor temperature, relative humidity, and CO₂ concentration, as well as solar irradiation measurements and thermal transmittance evaluations of walls and windows. Results showed that the compact-shaped envelope incorporating polyurethane foam and plywood achieved an airtightness of 0.18 h⁻¹, surpassing the passive house standard of 0.6 h⁻¹. The I-joist timber frame, filled with 300 mm of rock wool and 50 mm of PU foam, minimized thermal bridging, resulting in a wall U-value of 0.079 W/(m²·K). South-facing triple-glazed low-e windows (20 m²) performed well (U-value 0.80 W/(m²·K)). Yet, frame-related thermal bridging caused local surface temperatures to drop to 5.4°C at –19°C outdoor conditions, raising condensation risks. Between December 2, 2024, and February 1, 2025, the average indoor temperature was 22.7°C compared to an outdoor average of –20.2°C. Occupants often turned off the energy recovery ventilator due to noise concerns, and the highly airtight envelope limited air infiltration, resulting in CO₂ concentrations in the living room that often exceeded 1000 ppm and peaked at 3000 ppm. The relative humidity remained between 28–55%. These results emphasize two key considerations: Although a large south-facing window was installed in the double-height living room to enhance solar gains and reduce heating demand, it occasionally caused thermal discomfort. Design consideration in acoustic comfort is crucial in ensuring the continuous operation of ventilation systems to maintain optimal indoor air quality. Overall, this case study provides insights into both the potential and challenges of adapting passive house strategies for Mongolian and other cold-climate contexts. |
| 3-4 | 5/19/2026 15:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 49 | Seonghyuk Son, Jae Yong Suk, Kristina Knowles and Dongwoo Jason Yeom | Arizona State University; California Lighting Technology Center, University of California Davis; Clemson University | Light-Music Interaction: Modulating the Perception of Emotional Music Through Ambient Lighting | Lighting Music perception Lighting-music fit Positivity rating Emotional response | This study investigates how indoor lighting conditions influence music perception and emotional responses during music listening. Using a within-subject experiment, participants experienced eight lighting conditions varying in color, correlated color temperature (CCT), and intensity while listening to happy and sad music excerpts. Music perception was assessed through perceived lighting-music fit and positivity ratings, while emotional responses were captured using self-reported affective measures. Results showed that lighting effects on music perception were context-dependent. Perceived lighting-music fit was relatively stable during happy music but was strongly modulated during sad music, with blue and low-intensity lighting producing higher perceived fit. Positivity ratings during happy music were significantly enhanced under warm white lighting compared to blue and red lighting, whereas lighting had minimal influence during sad music. Emotional responses, extracted through principal component analysis, revealed valence and arousal as dominant dimensions shaping music perception. Higher valence predicted stronger lighting-music fit under happy music, while lower arousal supported better fit under sad music. These findings demonstrate systematic patterns in how indoor lighting conditions shape music perception through interactions with musical emotion, underscoring the importance of integrating lighting design with auditory context in music-listening environments. |
| 3-4 | 5/19/2026 15:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 193 | Shuja Rehman, Prabhjot Singh Chani, Rajasekar Elangovan and Omar Afroz | Department of Architecture and Planning, Indian Institute of Technology, Roorkee; Department of Psychiatry, All India Institute of Medical Sciences New Delhi | Thermal-Only Physiological Sensing of Stress and Boredom Detection for Occupant-Centric Control | thermal imaging stress detection boredom recognition arousal classification machine learning region importance physiological signal processing | Occupant stress and boredom have a significant impact on comfort, productivity, and safety in indoor environments, underscoring the need for scalable and non-intrusive affect sensing. This study presents a thermal-only facial sensing framework for differentiating stress and boredom using infrared thermography, without reliance on contact-based sensors or privacy-sensitive RGB imaging. Facial thermal video data were collected from 11 participants using a within-subject protocol that comprised baseline, stress-inducing, boredom-inducing, and recovery conditions. Region-of-interest (ROI)–based facial thermal signals were baseline-normalised to reduce inter-individual variability, and both static distributional features and temporal dynamic features were extracted. Feature redundancy was mitigated using Pearson correlation and Variance Inflation Factor (VIF) analysis, resulting in a compact and physiologically relevant feature set. Multiple machine learning classifiers were evaluated, including Random Forest, XGBoost, LightGBM, SVC, kNN, Logistic Regression, and MLP. Random Forest achieved the highest performance, with an accuracy of 0.82 and balanced F1-scores exceeding 0.82 using combined static–temporal features. Region-wise importance analysis identified the periorbital, forehead, and temporal regions as dominant contributors. The results demonstrate the feasibility of privacy-preserving, upper-face thermal sensing for occupant-centric building control and real-time affect-aware environmental adaptation. |
| 3-4 | 5/19/2026 15:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 466 | Yijin Zhao, Tsz Him Ian Chiu, Nan Wang, Jeffrey Mundinger and Julian Wang | Northwestern University; The Pennsylvania State University | A pilot study of the interaction between heat stress and metameric white light on occupants’ cognitive performance | Metameric white lights Indoor heat stress Core body temperature Cognitive performance | Previous studies have shown that occupants’ core body temperature (CBT) increases dynamically and cognitive performance declines under high indoor temperatures. On the other hand, light illuminance and correlated color temperature (CCT) have been explored for their potential influence on physiological responses and cognitive performance within thermal comfort zones. However, light spectral power distribution (SPD) remains underexplored. This study examined the effects of two metameric white lights (identical intensity and CCT but differ in spectral composition) on occupants’ CBT responses and cognitive performance during heat exposure, including blue-enriched white light and red-enriched white light. Seven college students were exposed to each lighting condition in a climate chamber maintained at 38 °C, with each exposure lasting 1h. Other environmental parameters were set to simulate office scenarios. Subjects wore a smartwatch to continuously monitor CBT and completed a battery of cognitive tasks assessing attention, executive function, memory, and emotion. Results showed that the increase of CBT was significantly smaller under blue-enriched white light than under red-enriched white light. This is the first experimental evidence of an association between metameric white light and CBT responses under heat stress. No significant differences in cognitive performance were observed between the two lighting conditions. However, red-enriched white light slightly indicated fewer errors, shorter response latency, higher sensitivity, and higher composite scores, possibly resulted by a systematic order effect. These findings highlight the importance of light SPD as a non-visual environmental factor for modulating physiological responses under heat stress. Future research should include larger sample sizes and counterbalance exposure orders to further validate these effects. |
| 3-4 | 5/19/2026 15:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 489 | Shintaro Ando, Misaki Miyazaki, Wataru Umishio and Toshiharu Ikaga | Institute for Built Environment and Carbon Neutral for SDGs; Institute of Science Tokyo; Nikken Sekkei Research Institute; The University of Kitakyushu | Long-Term Risk of Chronic Disease from Cold Indoor Environments: A 10-Year Cohort Study | Cold indoor environment Indoor temperature Thermal insulation Chronic disease Cohort study | Cold exposure is a well-established environmental risk factor for adverse health outcomes; however, evidence regarding the long-term health effects of sustained exposure to cold indoor environments remains limited. This study examined the association between indoor thermal conditions and the long-term incidence of chronic diseases using a 10-year prospective cohort design. The study was conducted in Yusuhara Town, a rural mountainous municipality in western Japan characterized by cold winter conditions and a predominance of detached housing. Baseline questionnaire surveys were conducted in 2013, followed by a second survey incorporating objective indoor temperature measurements in 2019 and a third follow-up survey in 2023. Objective indoor air temperature measurements were performed in early winter 2019, six years into the follow-up period, using data loggers installed in frequently occupied living spaces. Because continuous long-term monitoring was not feasible, indoor temperatures measured at mid-follow-up were used as a proxy for long-term residential thermal exposure, assuming relative stability of housing characteristics and heating practices. Incident cases of hypertension, cardiovascular disease (including stroke and heart disease), and dyslipidemia were identified based on self-reported physician diagnoses during follow-up. Missing data were addressed using multiple imputation. Propensity score analysis was applied to control for potential confounding factors, including age, sex, body mass index, smoking status, alcohol consumption, physical activity, and socioeconomic indicators. The results demonstrated that participants exposed to lower indoor temperatures or living in thermally poor dwellings had a significantly higher odds of developing chronic diseases over the 10-year period. Individuals residing in inadequately insulated homes exhibited a 2.46-fold higher odds of incident hypertension. In addition, participants with low thermal evaluation scores based on questionnaire assessments had a 2.30-fold increased odds of cardiovascular disease and a 1.83-fold higher odds of dyslipidemia compared with those living in thermally favorable environments. These findings suggest that sustained exposure to cold indoor environments may substantially elevate the long-term odds of chronic disease. Improving residential thermal conditions—particularly through enhanced insulation across the entire dwelling, including unheated spaces—may represent an important complementary approach for long-term health promotion. |
| 3-4 | 5/19/2026 15:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 538 | Shevvaa Beiglary and Julian Wang | The Pennsylvania State University | Machine Learning-Based Prediction of Circadian Lighting Exposure: A Practical Framework for Nursing Homes | circadian lighting human behavior modeling healthcare design lighting exposure assessment | Circadian lighting exposure significantly impacts patient health outcomes in healthcare environments, yet accurate assessment of individual exposure remains challenging due to complex human-lighting-space interactions. Traditional measurement approaches rely on fixed-position spectrometers that fail to capture the dynamic nature of human behavior and its effect on circadian stimulus exposure. This study addresses the critical research gap by developing a predictive model that quantifies how human-lighting interactions affect circadian lighting exposure in healthcare settings. A comprehensive field study was conducted in dementia care facilities across central Pennsylvania, collecting 460 spectral data points across varying environmental conditions. Four key parameters representing human-lighting interactions were systematically measured: distance to window, patient view direction, window blind slat angle, and artificial lighting presence. Light exposure was measured using spectrometers at eye-level heights, calculating both Circadian Stimulus (CS) and melanopic equivalent daylight illuminance (m-EDI) values. The dataset spanned measurements from 10 AM to 3 PM to capture dynamic daylight variations. Multiple machine learning algorithms were implemented and compared, including polynomial regression, random forest, and ridge regression models. The best-performing model achieved an R² score of 0.83 on the training set and 0.76 on the test set, demonstrating robust predictive capability. Applicability analysis revealed the relative importance of each architectural feature and their interactions in determining circadian exposure levels. The developed model enables real-time prediction of individual circadian lighting exposure using simple position data, eliminating the need for complex on-site measurements. Implementation scenarios demonstrate the model's ability to detect nuanced hourly variations in circadian exposure between patients with different behavioral patterns. This research provides evidence-based design strategies for optimizing healthcare lighting environments and offers a practical tool for monitoring circadian health in vulnerable populations, particularly benefiting dementia care facilities where traditional wearable monitoring approaches are impractical. |
| 3-5 | 5/19/2026 15:30 | Thermal Comfort | GFS 101 | 48 | Senta Mill, Matija Cabadaj, Nicolas März, Nicholas Müller and Normen Langner | Technical University of Applied Sciences Würzburg-Schweinfurt | How Accurate Is Low-Cost Comfort Monitoring? Validating the ComfortCube | Indoor air quality ComfortCube PMV model user perception thermal comfort user comfort | The reliable measurement of indoor climate parameters is a fundamental prerequisite for evaluating indoor climate and, consequently, user comfort. While professional measurement systems offer high precision, they are often associated with high costs, limited mobility, and restricted scalability in practice. At the same time, classical models for assessing comfort (e.g., the PMV model) focus primarily on thermal parameters and neglect the proven relevance of non-thermal factors such as lighting, acoustics, and CO₂ concentration. Against this background, the ComfortCube was developed as a compact, low-cost, and modular device designed to capture indoor environmental conditions in multiple dimensions and to bridge the gap between high-end reference systems and practical field applications. It collects real-time data on illuminance, light color, CO₂ concentration, air temperature, relative humidity, sound level, and air pressure using six integrated sensors and an ESP32 microcontroller. The aim of this paper is the empirical validation of the ComfortCube. For this purpose, an experimental field study was conducted in which parallel measurements with two professional reference systems were carried out under real conditions in various indoor spaces. Statistical comparison was performed using bias, standard deviation, root mean square error (RMSE), and Pearson correlation. The results demonstrate that air temperature, relative humidity, barometric pressure, CO₂ concentration, and illuminance lie within application-specific tolerance limits. Particularly for air temperature and relative humidity, two key factors in thermal comfort evaluation, only minimal deviations were observed. Sound pressure levels exhibit higher scatter (RMSE: 2.1 dB(A)) and do not reach Class-1 laboratory accuracy but are sufficient for trend analysis and comfort-oriented acoustic assessment. The results confirm that the ComfortCube can be used as a valid instrument for indoor climate field studies, especially in contexts requiring cost-efficient, multidimensional, and practice-oriented data collection. The paper emphasizes the potential of user-centered measurement technology to complement existing methods of assessing indoor environmental quality and to provide a data-based foundation for the further development of comfort-related evaluation models. |
| 3-5 | 5/19/2026 15:30 | Thermal Comfort | GFS 101 | 272 | Yukimasa Hirano, Masahiro Katoh, Saori Yumino and Tsubasa Okaze | Institute of Science Tokyo; Kajima Technical Research Institute | Validation of Turbulence Models used in CFD Analysis of Indoor Natural Convection with a Cold Window and a Thermal Manikin | Thermal comfort CFD RANS model Turbulence models Natural convection windows Thermal manikin | Drafts induced by cold windows deteriorate thermal comfort for occupants during winter. Computational fluid dynamics (CFD) is a practical design tool for evaluating countermeasures against drafts. To balance accuracy and computational cost, the Reynolds-averaged Navier–Stokes (RANS) approach is commonly used. In thermally driven flows, the turbulence model selection and buoyancy treatment significantly affect the accuracy of the simulation results. Previous studies suggest that low Reynolds-number k-ε models, which account for turbulence damping under stable stratification, are suitable for natural convection, whereas the SST(Shear Stress Transport) k-ω model often performs well for thermal manikins. In this study, an experiment replicating a winter room with a cold window and a thermal manikin was conducted to obtain validation data. In addition, the thermal manikin was operated in comfort control mode to simulate the heat balance of the human body. CFD simulations reproducing the thermal environment of the experiment were performed using two turbulence models: a low Reynolds-number k-ε model and an SST k-ω model. Horizontal profiles of airflow velocity and temperature at 0.5 m above the floor were analyzed. The SST model reproduced the boundary layer thickness along the cooled window more accurately than the Lien low Reynolds-number k-ε model. However, it tended to overestimate the airflow velocity near the wall. |
| 3-5 | 5/19/2026 15:30 | Thermal Comfort | GFS 101 | 276 | Cheng Zhao, Yichen Yu and Jianlei Niu | The Hong Kong Polytechnic University | Development of a dynamic heat and moisture transfer model for sweat-soaked clothing in thermal comfort assessment | Thermal comfort Clothing model Heat transfer Moisture transfer | Clothing serves as a critical medium for heat and moisture transfer between the human body and the environment, with variations in its thermal properties significantly influencing thermal equilibrium. Although several clothing models have been developed to quantify heat and mass transfer between the human body and its surroundings, the effect of liquid perspiration on heat and moisture transfer is often overlooked, limiting the applicability of such models in assessing thermal comfort. This study comprehensively evaluates the dynamics of heat and moisture transfer within the air gap between the human body and clothing system. The parameter of clothing wettedness was introduced to identify distinct heat and moisture transfer pathways in sweat-soaked clothing. Field measurements revealed the relationship between clothing moisture content and wettedness, resulting in a generalized empirical equation for this parameter. An observation platform was established to monitor skin temperature and micro-environmental characteristics of clothing under various environmental conditions, allowing quantitative analysis of the influence of different environmental variables on clothing moisture absorption and desorption rates. Based on experimental data, a clothing model was developed and validated, demonstrating robust computational accuracy under dynamic environmental conditions. Finally, the model was integrated with the JOS-3 model to simulate trends in human thermophysiological parameters under dynamic clothing thermal properties. Compared to the original model, the proposed model more accurately captures variations in physiological parameters during human sweating. Overall, the developed clothing model can effectively simulate reversible changes in thermal insulation and evaporative resistance during perspiration, providing a reliable basis for the precise evaluation of human thermal comfort across diverse thermal environments. |
| 3-5 | 5/19/2026 15:30 | Thermal Comfort | GFS 101 | 320 | Jihee Nam, Yujin Kang and Sumin Kim | Yonsei University | Influence of the thermal behavior of building envelopes on urban microclimate | Urban Heat Island Building envelope Wood Hanok Microclimate | Urban heat island (UHI) mitigation efforts have largely focused on introducing greenery—such as parks, trees, and green roofs—yet the influence of building envelope materials on microclimate remains underexplored. This study investigates the extent to which material choice can shape urban thermal environments, using Bukchon Hanok Village in Seoul, South Korea, as a case study. The area is a densely built historic district known for its concentration of traditional wooden houses (Hanok), offering a unique setting to compare the thermal impacts of wood and concrete. Field measurements of temperature and humidity were collected on-site and used to validate a high-resolution ENVI-met simulation. Two scenarios were analyzed: the current condition with wood-based envelopes and a hypothetical replacement scenario with concrete envelopes. Indicators such as ambient air temperature, mean radiant temperature, and the Physiological Equivalent Temperature (PET) were evaluated to assess microclimatic and comfort differences. The results demonstrate that wooden envelopes not only maintain cooler surface and air temperatures during peak summer but also extend the periods of pedestrian-level thermal comfort. In contrast, the concrete scenario produced higher daytime temperatures, intensified radiant heat exposure, and reduced comfort hours, increasing heat stress risk. These outcomes highlight that the selection of building envelope materials can be as influential as vegetation in shaping microclimates. Beyond preserving cultural heritage, traditional wood materials contribute to urban resilience under climate extremes. The findings call for the integration of material-sensitive strategies into broader UHI mitigation frameworks, bridging architectural design and urban climate policy. |
| 3-5 | 5/19/2026 15:30 | Thermal Comfort | GFS 101 | 510 | Meftah Uddin and Sanjeev Khanna | Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO 65211 | 3D Visualization and Spatiotemporal Analysis of Indoor Comfort Parameters | Building Energy Modeling Occupant Comfort Thermal Zone Spatiotemporal Clustering 3D Visualization | Occupant thermal comfort plays a central role in building energy modeling (BEM), as it directly influences the design and optimization of HVAC systems. Visualization of thermal comfort parameters facilitates the assessment of system performance, thermal zoning, and variations in indoor environmental quality. This study develops a custom 3D visualization method, integrating Python with the Grasshopper-Honeybee platform, to improve the interpretation of indoor thermal conditions with greater spatial and temporal resolution. Key comfort parameters, including indoor air temperature and mean radiant temperature (MRT), were evaluated on an hourly basis over a representative summer design day, enabling the identification of thermal disparities that single-value metrics often conceal. Building on the single-zone analysis, the model was extended to a two-zone configuration, which revealed that interior areas maintained more stable radiant temperatures compared to perimeter regions. Density-based spatial clustering of MRT distributions substantiated these findings and provided an evidence-based framework for refining thermal zoning strategies. While ASHRAE guidelines commonly recommend simplified zoning approaches such as core-plus-four perimeter divisions, the results underscore that optimal zoning is highly context-dependent, shaped by factors such as room geometry, building type, and window orientation. The 3D visualization enhances interpretability of simulation results, supports alignment between design intent and energy performance, and informs zoning refinements that improve occupant comfort and HVAC responsiveness. Beyond simulation, the grid-based framework also offers practical applications in experimental contexts, guiding the placement of sensors and contributing to the development of digital twin models. Collectively, the methodology demonstrates how spatiotemporal visualization can function as a critical decision-support tool in the early-stage design of energy-efficient and thermally comfortable buildings |
| 3-6 | 5/19/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 207 | 136 | Yasir Ahmed | Prince Sultan University | Toward a Just Energy Transition in the GCC: Integrating Policy, Sustainability, and Climate Leadership | energy transition renewable energy GCC climate leadership sustainable development | The Gulf Cooperation Council (GCC) countries stand at a critical juncture in redefining their energy futures, confronted by the dual imperatives of sustaining robust economic growth and transitioning toward environmentally sustainable energy systems. The GCC countries have historically been dependent on large deposits of fossil fuels; hydrocarbons exports have brought a high level of economic growth to the countries. Nevertheless, the mounting global pressure to fight climate change, along with rising demands domestically to fight inequity in energy access and long-term energy security have highlighted major loopholes and discrepancies in current energy policies. This research responds to these complex issues by offering a holistic framework of decision making that encompasses four key dimensions i.e., energy policy assessment, economic resilience, social justice and environmental sustainability. The main focus is to be able to find and prioritize the energy transition strategies that are not only technically feasible but also socio-economically inclusive and environmentally sound. The study is based on the understanding that climate leadership has become a hallmark of global climate crisis mitigation efforts. The GCC is progressively dependent on visionary leadership to help close the gap between fossil fuel dependence and sustainable energy invention. To accommodate the complexity, uncertainty, and subjectivity inherent in energy policy decisions, the study employs a Fuzzy Analytical Hierarchy Process (AHP) approach. Policy evaluation holds the greatest significance with a weight of 0.4904, highlighting the paramount importance of aligned, clear, and enforceable energy policies in steering the GCC’s energy transition. Economic Resilience follows with a weight of 0.2641, emphasizing the critical role of economic diversification and market stability in supporting a sustainable transition. Environmental sustainability and social justice receive weights of 0.1318 and 0.1137 respectively, reflecting their essential contributions to ensuring ecological responsibility and social inclusiveness in energy reforms. The analysis identifies that diversified energy portfolio for the GCC to achieve a just and sustainable transition. |
| 3-6 | 5/19/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 207 | 175 | Zahra Khashei and Sandeep Langar | School of Civil and Environmental Engineering, and Construction Management | Integrating Circular Strategies into Post-Disaster Rebuilding: Pathways to Resilient and Resource-Efficient Recovery | Circular Economy Post-Disaster Recovery Disaster Reconstruction BBC Framework Resilience | Abstract. The increasing frequency and severity of natural disasters pose significant challenges for the built environment, especially during post-disaster recovery and reconstruction phases. Traditional rebuilding practices often focus on rapid implementation and cost reduction, sometimes at the expense of sustainability, resource efficiency, and long-term resilience. These methods typically result in linear construction models that generate substantial amounts of waste, deplete limited resources, and increase vulnerability to future climate-related events. In recent years, the circular economy (CE) has emerged as a promising and innovative approach to addressing these systemic issues. By prioritizing resource loops through reduction, reuse, recycling, and designing for adaptability, CE offers a more regenerative and resilient model for rebuilding. However, despite its potential, a consistent and comprehensive Build Back Circular (BBC) framework specific to post-disaster contexts is still underdeveloped. This study explores how circular economy principles can be integrated into post-disaster recovery to support sustainable, adaptable, and future-ready rebuilding practices. Using a qualitative analysis of academic literature, recent case studies, and existing CE and disaster recovery frameworks, the research highlights key circular interventions that could guide the creation of a BBC framework for disaster-affected areas. These interventions include material recovery, modular design, stakeholder collaboration, and adaptive reuse strategies. The results indicate that circular strategies not only boost resource efficiency and lower environmental impact but also promote healthier, more durable, and energy-efficient built environments. This study adds to the ongoing discussion on sustainable reconstruction by proposing a systems-based approach that aligns environmental, social, and economic goals in the wake of disasters, ultimately aiding long-term community resilience and sustainability. |
| 3-6 | 5/19/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 207 | 237 | Min Zong | US Green Building Council CA | From the source ensuring IAQVEC meet people's new expectations for a better life | Source Ensuring IAQVEC Meet Expectation | Abstract. People's aspirations for the better life and future depend on improved architectural environments, including Indoor Air Quality, Ventilation, and Energy Conservation (IAQVEC). The most fundamental and effective way to solve this problem is to do a good job from the four key sources of the IAQVEC—society, nature, architecture, and the IAQVEC systems themselves—in the process of the green building design according to the green architectural policy and green building standards represented by LEED v5, etc. The architectural policy has evolved from the original three-dimensional space of "Firmness, Utility, Aesthetics" to "Firmness, Utility, Green, Aesthetics" four-dimensional space’s the green architectural policy including the essential factors of safety and durability, resilience improvement, low carbon and decarbonization, quality of life, ecological protection and restoration, social value and equity, and nature-based design, etc. The essences are to realize the harmonious coexistence among architecture, people and nature, which are the cornerstone and fundamental of green building design, moreover a magic cudgel, an anchor, and a guiding beacon to ensure the performance of the IAQVEC systems to improve environmental quality, to enhance energy efficiency, and to promote the healthy, green, high-quality and sustainable development of the building and real estate industry. Therefore, started from the sources, the comprehensive researches on the IAQVEC system structure, technological advancement, model breakthroughs, system integration, and path innovation, etc. are required to create a better built environment meeting people's new expectations for a better life. |
| 3-6 | 5/19/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 207 | 344 | Ryuta Tsurumi and Takahiro Yoshida | Center for Spatial Information Science, the University of Tokyo; Nikken Sekkei Research Institute | Spatiotemporal analysis of major CO2 emission sources in the Japanese building sector | Building decarbonization district heating and cooling Spatio-temporal analysis Energy consumption efficiency Geocoding | Understanding greenhouse gas emissions from the building sector is crucial for climate change countermeasures. In Japan, a law was enacted in 2006 requiring corporations that emit greenhouse gases above a certain level to report to the national government. Furthermore, under this law, information on business locations (geographical bases) has been publicly available since fiscal year 2021, making it possible to grasp the actual spatiotemporal greenhouse gas emissions of cities based on real data, which was previously difficult to obtain from publicly available information. The purpose of this study is to conduct a spatiotemporal analysis of emission locations and emissions, focusing specifically on the building sector, using publicly available information for fiscal years 2021-2022 under Japanese Mandatory GHG Accounting and Reporting System, a Japanese law, to clarify the actual emissions of Japan's building sector. Furthermore, in the building sector, total floor area is an important variable for evaluating energy consumption efficiency. However, building total floor area is generally not available from publicly available information. Therefore, in this study, a separately obtained database of building floor area (building name and latitude/longitude) was integrated with publicly available information from the reporting system by geocoding building names and latitude/longitude information, enabling a spatiotemporal analysis of energy use intensity. The results of the spatiotemporal analysis make it possible to understand area-wide energy use (e.g., district heating and cooling) and locations where the community energy management system is most effective. These results are expected to enable the formulation of effective climate change mitigation measures in cities. |
| 3-6 | 5/19/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 207 | 357 | Max Ruffo | Terabee | Why Energy per Person Is the Metric the Future Demands | People Counting BMS Energy Saving co2 reduction Smart Buildings Metrics | As the world moves toward zero-emission buildings and radical energy efficiency, it’s time to rethink how we measure energy performance. The conventional energy-per-square-meter metric fails to reflect real building usage, especially in the context of hybrid working and fluctuating occupancy. Instead, energy per person offers a more accurate, actionable standard. This new metric is made possible by people counting technologies, which are evolving beyond space optimization to play a central role in intelligent energy management. By integrating people counting systems with Building Management Systems (BMS) via protocols like BACnet, HVAC and lighting can adapt in real time to occupancy, significantly reducing waste. With hybrid working now the norm, spaces designed for dozens of people, like meeting rooms, communal areas, restrooms, often sit underused. People counting infrastructure can dynamically manage and reorganize space usage, closing off unnecessary areas and directing occupants more efficiently. This article calls for a shift in both mindset and policy. Heating or cooling empty spaces, even with efficient systems, is no longer acceptable. Energy per person must become the new standard for sustainable, intelligent buildings. |
| 3-6 | 5/19/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 207 | 546 | Caribay Godoy-Rangel, Emanuele Giorgi and Viviana Barquero | Tecnologico de Monterrey, School of Architecture, Art and Design, Mexico | Evaluating the Thermal Resilience of PCM-Retrofitted Housing under Heat Waves and Climate Change in Mexico | Thermal Resilience Passive Strategies PCM Residential Building Future Scenarios | The increasing frequency and intensity of heat waves, and the projected rise in temperatures due to climate change, pose a significant challenge for the thermal adaptation of residential buildings. This research aims to evaluate the thermal resilience of existing social housing by assessing thermal comfort and overheating through six retrofit strategies generated using Phase Change Material (PCM) to roofs and thermal insulation. Using transient simulations, the scenarios were evaluated under three schemes: historical climate, the 2024 heat waves, and a future climate scenario (2050). The study focuses on three Mexican cities with different climates: Mexico City, Chihuahua, and Tuxtla Gutiérrez, for which the optimal melting temperature of the PCM was determined by evaluating its potential to improve thermal comfort in each one. Key findings include a decrease in average annual thermal comfort in the baseline case for temperate climates (Mexico City and Tuxtla Gutiérrez), while the more extreme climates with very cold winters and very hot summers (Chihuahua) show improvement, demonstrating the need for retrofitting in most cases. When only PCM was applied, an improvement in thermal comfort was observed in all cases by 2050, with Mexico City standing out with an 18% increase. When combining PCM and insulation, only Chihuahua showed an improvement, with a 13% increase by 2050. When the overheating is studied dramatic results were observed, with temperatures exceeding 25°C and 28°C reaching 93% and 51%, respectively, for Chihuahua, and 97% and 59%, respectively, for Tuxtla Gutiérrez. These results indicate that implementing retrofit strategies increases thermal resilience in future climate scenarios by enhancing thermal comfort during a warmer year in the future but does not guarantee a significant reduction in overheating during extreme heat waves over a short period (e.g. two weeks). |
| 3-7 | 5/19/2026 15:30 | Generative AI in Sustainable Built Environment | GFS 118 | 82 | Jung Min Han | Yonsei University | Quantum Computing for Wind Pressure Data Prediction | quantum computing wind pressure prediction quantum machine learning natural ventilation | Accurate prediction of unexpected turbulence remains a persistent challenge in atmospheric sciences, aviation safety, and building design, particularly when dealing with sparse wind pressure and speed data. In the context of sustainable architecture, the growing adoption of natural ventilation systems further amplifies the importance of precise pressure coefficient estimation and turbulence modeling, as these factors directly affect both energy efficiency and indoor air quality. Conventional machine learning models often face significant limitations in capturing the high-dimensional, nonlinear dynamics of turbulent flows, especially when available measurements are irregular or limited in resolution. This study presents a quantum embedding framework that leverages quantum computational principles to enhance prediction accuracy in sparse-data environments. The method employs quantum feature maps to encode classical wind measurements into high-dimensional Hilbert spaces, preserving complex correlations and nonlinear structures that are frequently lost in classical embedding methods. Experimental validation is performed using real-world datasets from meteorological stations, aircraft-mounted sensors, and building facade pressure sensors, with a focus on conditions characterized by sparse temporal and spatial resolution. The proposed framework demonstrates notable improvements over classical baselines, achieving a 23% increase in turbulence prediction accuracy, a 31% performance gain in sparse data scenarios, and a 28% improvement in pressure coefficient estimation. The approach is particularly effective at identifying rapid pressure gradient changes, wind shear signatures preceding turbulence, and complex pressure distributions across building facades. With computational requirements suitable for operational deployment, the method exhibits robust generalization across diverse climates, geographic contexts, and building configurations. These results highlight the potential of quantum-enhanced feature representation to address the curse of dimensionality in turbulence prediction while providing actionable insights for both aviation safety and sustainable building design optimization. |
| 3-7 | 5/19/2026 15:30 | Generative AI in Sustainable Built Environment | GFS 118 | 181 | Po-Yen Lai, Xinyu Yang, Jian Cheng Wong, Derrick Low and Huizhe Liu | Institute of High Performance Computing (IHPC), Agency for Science Technology and Research (A*STAR) | Agentic AI-Enabled Framework for Thermal Comfort and Building Energy Assessment in Tropical Urban Neighborhoods | agentic AI surrogate modelling physiological equivalent temperature (PET) envelope thermal transfer value (ETTV) tropical urban environments | In response to the growing challenges of urban heat island effects and building energy demands in Singapore, this study proposes an agentic AI-enabled reasoning framework that integrates large language models (LLMs) with deep neural network (DNN) surrogate models to evaluate the microclimate and energy impacts of urban design schemes. The LLMs autonomously interpret urban design tasks, extract relevant environmental policies and planning guidelines, and strategically select and trigger appropriate DNN surrogate models for evaluation, forming a closed-loop reasoning-action process. These DNN models, trained on high-resolution multi-physics simulation datasets generated in-house, can rapidly predict urban microclimate variables such as building surface temperature, ground radiant heat, and airflow conditions, thereby enabling the estimation of thermal comfort indices (e.g., physiological equivalent temperature (PET)) and building energy usage (e.g., cooling loads approximated via envelope thermal transfer value (ETTV)). This framework allows users to explore a variety of climate-resilient building surface strategies (e.g., green facades and cool paint applications) that improve thermal comfort while reducing wall heat gain and energy demand. By combining the autonomous reasoning capacity of agentic LLMs with the rapid quantitative evaluation of DNN models, the proposed system demonstrates significant potential for cross-disciplinary applications in sustainable urban design, indoor-outdoor environmental integration, and climate adaptation planning. |
| 3-7 | 5/19/2026 15:30 | Generative AI in Sustainable Built Environment | GFS 118 | 565 | Saba Imani and Yun Kyu Yi | School of Architecture, University of Illinois at Urbana-Champaign | GenAI for Human–Building Interaction: Consistency, Reproducibility, and Automation in Post-Occupancy Evaluation | Generative AI Small Language Models Reproducibility Post-Occupancy Evaluation Human–Building Interaction | Generative AI (GenAI) models are increasingly applied in the built environment, from analyzing occupant feedback to supporting building energy assessments. However, concerns remain about their reliability, including consistency, reproducibility, and the risk of hallucination when identical inputs yield divergent or inaccurate outputs. This study presents a systematic framework to evaluate GenAI reliability in the building domain, focusing on human–building interaction data from Post-Occupancy Evaluation (POE) surveys, building energy reports, and HVAC operations data. Two representative text tasks are designed: (1) classification of occupant comfort feedback and HVAC-related descriptions into categories such as thermal comfort, lighting, air quality, noise, and system operation, and (2) summarization of energy audit reports and POE responses into concise insights. Three different versions of ChatGPT (3.5, 4, and 4o) are tested, with multiple independent runs per input to quantify variability across tasks. To enhance reliability, we introduce two strategies: aggregation (majority voting across multiple runs) to mitigate random variation, and retrieval-augmented generation (RAG), which grounds outputs in building-specific knowledge bases (e.g., HVAC taxonomies, POE survey archives, and equipment metadata). The framework is designed to assess consistency within models, reproducibility across experimental setups, and the potential of these strategies to support more trustworthy automation. In addition, the role of Small Language Models (SLMs) is considered, as they can be fine-tuned with domain-specific data for more efficient and contextually reliable deployment in building workflows. By establishing a methodological foundation and highlighting the value of domain-specific supplemental data, this study contributes to advancing the use of GenAI in energy research, HVAC operations, and occupant-centered building analysis, offering guidance on how to integrate GenAI responsibly into building system workflows where reproducibility and trust are critical. |
| 3-7 | 5/19/2026 15:30 | Generative AI in Sustainable Built Environment | GFS 118 | 572 | Le Sun, Xinyue Xu and Julian Wang | Builder Supply Link LLC; The Pennsylvania State University | Bridging Construction and AI: Computer Vision-Based Floor Plan Analysis for Real-Time Cost Estimation | Construction cost estimation Drawing recognition Computer vision YOLO Automation | Timely and accurate cost estimation is a critical determinant in fast-paced engineering construction projects. Traditional methods are usually time-consuming and error-prone, relying on human interpretation of architectural drawings. With the assistance of computer vision, the ability to provide early and reliable quotes can be accelerated for fast, secure construction projects. In this study, we propose an automated computer vision framework that leverages multiple computer vision models to identify and quantify building components directly from floor and unit plans. The final database will calculate the cost of detected components. Unlike existing methods that require engineers to interpret drawings, our approach establishes an end-to-end pipeline from drawing recognition to cost estimations, minimizing human efforts and turnaround time. The proposed pipeline can process large construction drawing sets, automatically identify and extract relevant sheets such as floor plans, enlargement drawings, schedules, and detect key building components like doors, windows, walls, and floors. The results are expected to achieve an accuracy of 95%. Beyond immediate recognition of building components, this pipeline lays the groundwork for broader applications, such as material calculations and integration with building information modeling (BIM). In conclusion, the proposed method allows contractors to streamline human interpretation, secure a competitive advantage, and motivate the development of an AI-driven construction industry. |
| 3-7 | 5/19/2026 15:30 | Generative AI in Sustainable Built Environment | GFS 118 | 573 | Ana Sofia Graça and Xiang Zhang | Arizona State University | Early-stage shading design evaluation for buildings: A workflow accessing energy performance on AI-generated 3D geometry | Early-stage design optimization Façade shading Building energy modeling Generative artificial intelligence Performance evaluation | This study presents a simplified and controllable workflow for the early-stage evaluation of self-shading building façade designs. Early design decisions strongly influence long-term building energy performance; however, façade shading strategies are often defined through qualitative guidelines rather than quantitative assessment, largely due to the time-intensive nature of energy modeling and the limited simulation expertise among architects. The proposed workflow addresses this limitation by enabling a rapid transition from conceptual design ideas to quantitative feedback on building operational performance, while preserving architectural intent. Using text-based design inputs derived from initial abstract ideas, AI-based tools are employed to generate biomimetic façade shading geometries inspired by the saguaro cactus, tailored to a hot-arid climate context in Tucson, Arizona. The AI-generated façade geometries are then integrated into a standardized DOE Medium Office reference building using a Grasshopper–Honeybee–EnergyPlus workflow. This workflow enables consistent comparison across multiple shading design alternatives, supporting rapid decision-making in early-stage design optimization. Three self-shading scenarios with shading depths of 1, 2, and 3 meters are evaluated against an unshaded baseline. The results indicate that the extension of shading depth reduces annual cooling demand but may increase annual heating demand, revealing diminishing returns of overall building performance beyond certain shading depths. The early-stage quantitative performance evaluation feedback enabled in this study informed early-stage design decision-making without significantly increasing modeling complexity. While Large Language Models (LLMs) have been used to support model integration and result interpretation in this work, future efforts will focus on further simplifying modeling complexity empowered by LLMs. |
| 3-7 | 5/19/2026 15:30 | Generative AI in Sustainable Built Environment | GFS 118 | 574 | Soo Jeong Jo | Louisiana State University | Application of AI and Building Performance Simulations to the Early Stages of Building Design | AI (artificial intelligence) environmental performance early design Forma Insight | The present study investigates how recent advancements in artificial intelligence (AI) can enhance the environmental performance of buildings during the early design stages. A total of 36 community center designs were developed through three architectural design studio courses. The study simulated environmental performances such as expected annual energy demand, peak demand, natural lighting conditions, and the environmental experiences of users in these proposed designs employing various AI platforms, including Gemini, Insight, and Forma. The AI-powered simulation and optimization processes helped minimize the buildings' energy consumption while optimizing natural lighting and other environmental conditions. This approach facilitated the identification of environmentally friendly building orientation, form, and façade design. Furthermore, it encouraged designers to focus more on environmental issues, leading to multiple design iterations aimed at improving environmental performance. Ultimately, the study compared the proposed designs before and after interactions between designers and AI to assess how accurately the environmental context and the quality of experience users may have were represented. While the application of AI tools showed positive effects on high-performance building design, some misleading results were also noted. This highlights the importance of designers possessing fundamental knowledge to interact with AI effectively and to carefully evaluate and selectively adopt feedback from these tools. The significance of this study lies in demonstrating AI as a powerful assistive tool that enhances building performance from the initial design phase. The findings underscore the impact of AI in the early stages of building design and indicate how building professionals can prepare to effectively use this new technology and practice to promote sustainable design. |
| 3-8 | 5/19/2026 15:30 | Online Session | VHE 206 | 67 | Mahdieh Adib, Fariborz Haghighat and Fuzhan Nasiri | Concordia University | Continuous-Time Neural Surrogate Models for Simulation and Scheduling of Compressed Air Energy Storage Systems | Compressed Air Energy Storage (CAES) Neural Controlled Differential Equations (Neural CDEs) Renewable Energy Integration Energy Storage Optimization | Long-duration energy storage technologies play a critical role in supporting electric grids with growing shares of renewable generation. Among these, Compressed Air Energy Storage (CAES) offers the potential for large-scale energy shifting. Operational scheduling for CAES is computationally demanding because it relies on frequent evaluations of optimization routines and thermodynamic models that account for off-design component performance. This study introduces a Neural Controlled Differential Equations (Neural CDEs) based surrogate framework designed to emulate CAES behavior. Because Neural CDEs learn state evolution as continuous trajectories, they align naturally with the dynamic processes governing CAES. Given the path-dependent nature of CAES, driven by variations in demand, renewable supply, and nonlinear physics, Neural CDEs are well-suited to represent its evolving behavior. In this study, two distinct Neural CDE surrogate models are developed, a thermodynamic CAES model that learns the internal physical behavior of the storage system, including stage-by-stage compressor, turbine, and heat exchanger pressures, temperatures, and mass flow rates, and an operational scheduling surrogate that learns optimal charge, discharge, and decision trajectories. The thermodynamic surrogate reproduces detailed off-design behavior. Combined with the operational surrogate, the framework accurately replicates optimal scheduling patterns, maintains physically consistent storage trajectories, and generalizes robustly to unseen operating days, all while operating with significantly reduced computational cost. Based on these results, Neural CDEs provide a fast, physically informed, and scalable alternative to conventional CAES simulation and scheduling approaches in renewable-rich power systems. |
| 3-8 | 5/19/2026 15:30 | Online Session | VHE 206 | 287 | Zhao Dong, Jian Ge, Jiaqi Wang, Kang Zhao and Isabelle Y.S. Chan | The University of Hong Kong; Zhejiang University | The impact of tangible and intangible factors on occupants’ satisfaction with the indoor environment: A machine learning-driven analysis | Intangible factors Machine learning Indoor environment SHAP | Indoor environmental quality (IEQ) exerts a significant influence on occupants’ comfort, health, and cognitive performance. A comprehensive understanding of IEQ encompasses both tangible factors—such as thermal environment, air quality, lighting environment, and acoustic environment—and intangible factors, such as space design. Despite their importance, intangible factors have received far less scholarly attention than tangible ones. The present study aims to examine how both categories of IEQ factors affect occupants’ satisfaction with the overall indoor environment. A questionnaire survey was administered to dormitory residents, resulting in 921 valid responses. Prior to analysis, the data were preprocessed using the Synthetic Minority Oversampling Technique (SMOTE) and Tomek links. Subsequently, the dataset was analyzed with XGBoost and other machine learning models (e.g., Gradient Boosting, Decision Tree, K-Nearest Neighbors). Among these models, XGBoost achieved the highest classification accuracy at 93.2%, whereas Logistic Regression yielded the lowest at 81.6%. To further interpret the model outputs, Shapley Additive Explanations (SHAP) were employed to evaluate the relative contribution of each factor to the overall satisfaction. The results clearly revealed that three intangible IEQ factors—space design, personal environmental control, and maintenance and cleanliness—were among the top four most influential predictors. Importantly, space design emerged as the single most influential factor. These findings strongly underscore the pivotal role of intangible factors in shaping occupants’ satisfaction with the overall indoor environment and provide a novel perspective for advancing IEQ research. Overall, the study offers practical implications for the evidence-based design and effective management of more satisfying indoor environments, particularly in dormitory settings. |
| 3-8 | 5/19/2026 15:30 | Online Session | VHE 206 | 471 | Zeinab Deldoost Fattahi, Fariborz Haghighat and Fuzhan Nasiri | Concordia University | A Superposition-Based Method for Rapid Estimation of Indoor Airflow Fields Under Occupant Movement | Pathogen dispersion Real-time simulation Indoor air quality Moving infection source | Indoor air quality is strongly affected by the behavior of airborne pollutants such as pathogens dispersed in circulating air. The dispersion of these particles depends heavily on the airflow field and the vortices generated within an enclosed space. While predictable factors—such as ventilation configuration and furniture layout—can be investigated through one-time numerical simulations, unpredictable factors, particularly occupant movement, remain a major challenge. Previous studies have attempted to simulate airflow under specific movement scenarios; however, their results are case-specific, lack generalizability, and require extensive computational resources. To address this limitation, the present study introduces a novel method for rapidly estimating airflow fields influenced by occupant movement. The approach is based on a dataset generated from computational fluid dynamics (CFD) simulations of a moving person at different speeds. These simulations capture the vortical structures created around the body, represented by distributions of velocity vectors at computational nodes. When occupant movement occurs in a ventilated domain, the stored velocity vector distributions can be superimposed onto the baseline airflow field of the empty room. By combining these two components—the airflow induced by the ventilation system and the flow generated by occupant motion—the method reconstructs the overall velocity field around a moving person in a ventilated environment. This superposition technique substantially reduces computational cost by avoiding the need for repeated CFD simulations for every new movement scenario. At the same time, it provides timely and reliable predictions of airflow dynamics under occupant-induced disturbances. The proposed method therefore offers a practical and efficient tool for assessing pollutant transport and infection risk in real indoor environments where human activity introduces inherently uncertain airflow conditions. |
| 3-8 | 5/19/2026 15:30 | Online Session | VHE 206 | 500 | Maria Isabel Rivera, Tamara Ugarte-Aviles, Patricia A. Huerta and Marcela Palma-Troncoso | Departamento de Arquitectura, Universidad de Concepción; Departamento de Currículum e Instrucción, Universidad de Concepción; Departamento de Kinesiología, Universidad de Concepción; Departamento de Salud Pública, Universidad de Concepción | The Effect of Air Purifier Use in Classrooms on the Pulmonary Function of School-Aged Children: A Pragmatic Controlled Trial in Primary Schools in Central-Southern Chile | Air Purifiers Particulate Matter Pulmonary Function Indoor Air Quality Children | Poor air quality adversely affects children's respiratory health, yet few interventions have been reported to improve classroom indoor air quality (IAQ). Air purifiers can remove particulate matter (PM), and, by reducing airway inflammatory response, potentially enhancing pulmonary function. This study aimed to evaluate the effectiveness of low-cost air purifiers on students' pulmonary function during winter. The study involved 97 students from 6th to 8th grades in Concepción, Chile. A pragmatic controlled trial was implemented using two types of air purifiers (A and B) filtering PM, with B being self-designed and built. Students served as their own controls. Indoor air quality was assessed over four weeks: the first week without intervention, followed by two weeks of alternating purifiers A and B, with washout periods of 2 to 7 days. Peak expiratory flow (PEF) was measured weekly, conducted by physiotherapists and trained students. A survey was also administered to guardians to identify confounders such as health status and tobacco smoke exposure. Data were analyzed using generalized linear mixed models. Multivariable analysis revealed that air purifiers significantly improved students' PEF compared to the mean without intervention. For purifier A, the improvement was 3.1 percentage points (95% C.I. 0.6 to 5.9), and for purifier B, it was 4.0 percentage points (95% C.I. 1.8 to 6.1). In students with chronic respiratory conditions, purifier B enhanced PEF by 6.2 percentage points (95% C.I. 0.31 to 12.01), while purifier A showed a non-significant improvement of 5.23 percentage points (95% C.I. -0.62 to 11.07). The washout period (7 days or less) was non-significant and did not confound the purifiers' effect on PEF. Implementing air purifiers in classrooms effectively PEF and overall respiratory health among school-aged children, particularly those with chronic conditions. Continued research on classroom environmental conditions and their health impact is essential, as fewer respiratory illnesses lead to reduced absenteeism. |
| 4-1 | 5/20/2026 11:00 | Sponsored Session by ERC (Engineering Research Center) at Chung-Ang University, Korea | SGM 101 | 47 | Seungwon Seo, Dajeong Choi, Yujin Choi, Seongkyun Ahn and Choongwan Koo | Department of Architecture, Incheon National University; Division of Architecture & Urban Design, Incheon National University | Toward Carbon-Neutral Construction: Clustering-Based Analysis of Site Electricity and Abnormal Use | Carbon neutrality Construction-site electricity consumption Time-series clustering Anomaly detection | Amid the rapid rise in global average temperatures—now framed not only as “global warming” but increasingly as “global boiling”—the Intergovernmental Panel on Climate Change (IPCC) set out concrete pathways in its 2018 special report to limit warming to 1.5 °C. In alignment, Korea has pledged carbon neutrality by 2050, with an interim 40% reduction in greenhouse gas (GHG) emissions by 2030 relative to 2018. Within this context, the construction sector manages site-level annual emissions under the Greenhouse Gas Target Management System; yet electricity consumption (Scope 2) accounts for over 85% of total site emissions while, in practice, most sites still rely on monthly utility bills. This billing-level monitoring obscures end-use loads, temporal patterns, and savings opportunities for key facilities (e.g., tower cranes, hoists, site offices), and prevents detailed analysis by trade, season, or time of day. Leveraging residential construction project data from major contractors via the Korea Real Estate Board (KREB), this study extracts representative load profiles by facility type through time-series clustering, establishes energy calendar maps to visualize daily and seasonal dynamics, and conducts benchmarking to identify underperforming sites. Anomaly detection then flags unusual energy use and estimates potential savings from operational or scheduling improvements. The proposed framework provides site-specific, detailed insights and enables early detection of inefficiencies without expensive submetering, thereby translating directly into actionable GHG monitoring and reduction strategies. Ultimately, the proposed approach provides a scalable analytical foundation for data-driven energy management in construction, supporting national carbon-neutral commitments through targeted, verifiable, and cost-effective interventions at the project level. |
| 4-1 | 5/20/2026 11:00 | Sponsored Session by ERC (Engineering Research Center) at Chung-Ang University, Korea | SGM 101 | 101 | Hae Won Lee, Ji Young Yun and Jin Woo Moon | Chung-Ang University | Development and Applicability Evaluation of an Image-Based BMI Estimation Model for Occupant-Centric Thermal Environment Control | Body Mass Index Occupant-centric control Thermal Comfort Occupant information | This study develops a face image–based Body Mass Index (BMI) estimation model for occupant-centric thermal environment control and experimentally evaluates its applicability. To overcome the limitations of conventional continuous regression approaches, a categorical classification scheme was introduced and additional Asian facial image data were used for fine-tuning to enhance the model’s generalization performance. The proposed model achieved accuracies of 0.9979 and 0.9555 on the training and validation datasets, respectively, and an overall estimation accuracy of 81.8% in experiments conducted under realistic indoor conditions. These results demonstrate that the proposed BMI estimation model can serve as an enabling technology for thermal environment control systems that explicitly account for occupants’ BMI. |
| 4-1 | 5/20/2026 11:00 | Sponsored Session by ERC (Engineering Research Center) at Chung-Ang University, Korea | SGM 101 | 161 | Sarath Raj, Da-Eun Jung, Ji Hwan Jeong, Kanghee Lee and Geun Young Yun | Kyung Hee University | Machine-Learning Based Downscaling of GK-2A Land Surface Temperature: A study of Seoul, South Korea | Land Surface Temperature GK-2A Satellite Downscaling Machine Learning Climate adaptation | Downscaling Land Surface Temperature (LST) data from geostationary satellites is crucial for high-resolution city-scale environmental monitoring and localized applications. However, the accuracy of such downscaling is often hindered by spatial heterogeneity in land cover and topography. In this study, we present, to our knowledge, the first machine-learning based downscaling of GK-2A LST from 2 km to Landsat-like 30 m resolution over complex Korean terrain. Our framework trains models using Random Forest (RF) and eXtreme Gradient Boosting (XGB) with predictors drawn from the GK-2A LST, Landsat NDVI, and terrain variables like DEM-derived slope and aspect. Model performance was then evaluated against Landsat-derived LST. We analyze 40 cloud-free Landsat dates spanning 2022–2025 in the Seoul metropolitan region. Across all dates, RF achieved RMSE = 1.10–5.27 K, MAE = 0.83–3.93 K, and R² = 0.43–0.85; XGB was similar with RMSE = 1.09–5.31 K, MAE = 0.83–4.01 K, and R² = 0.43–0.85. Performance was typically strongest in spring/early summer scenes with clear conditions. For comparison, we implemented a thermal sharpening (TsHARP) downscaling approach. TsHARP showed markedly lower performance, with R² generally 0.00–0.36, RMSE = 1.70–8.01 K, and MAE = 1.28–6.32 K across the same dates, reflecting limitations of a purely linear NDVI–LST relationship in heterogeneous urban–mountain area. The proposed ML framework reliably produces 30 m LST grids from 2 km GK-2A inputs using widely available ancillary data (NDVI and DEM). Compared with the TsHARP, RF/XGB consistently yield lower errors over diverse Seoul, while remaining computationally practical for routine production. These downscaled LST data provide actionable inputs for urban heat-risk assessment and climate-adaptation planning in Korea and can be integrated into energy modeling approaches for improving efficiency and thermal comfort. |
| 4-1 | 5/20/2026 11:00 | Sponsored Session by ERC (Engineering Research Center) at Chung-Ang University, Korea | SGM 101 | 194 | Jun Kyu Kim, Se Hyeon Lim and Jin Chul Park | School of Architecture and Building Science, Chung-Ang University, Seoul 06974, South Korea | Analysis of the Lifecycle Carbon Reduction Effects of Public Daycare Centers through Green Remodeling | Public Daycare Center Green Remodeling Life Cycle Assessment Life Cycle Inventory Carbon Emission | In the Republic of Korea, 42.6% of buildings are 30 years old or older. Most were constructed before the strengthening of energy-saving design standards, making improvements in energy performance essential to meet carbon-neutrality targets. “Green remodeling” refers to environmentally friendly retrofits of aging buildings to improve energy performance and efficiency and enhance indoor comfort. Accordingly, the Korean government is promoting green remodeling for aged public buildings, prioritizing facilities for vulnerable groups such as children. In green remodeling, the before-and-after energy-saving effect is critical, and current policy in Korea recommends achieving at least 30% energy savings. However, achieving carbon neutrality requires whole-building life cycle assessment (LCA) of carbon emissions, whereas most domestic efforts still focus only on reducing operational energy use. Therefore, this study analyzes emission-reduction effects not only during operation but across the entire life cycle of a green-remodeled building. A public daycare center over 30 years old was selected, and passive measures, including thermal insulation, low-emissivity glazing, and airtight insulated doors, were applied. The embodied carbon of the materials used was calculated using the national LCI database, and life cycle assessment across production, transportation, construction, and demolition stages was performed in accordance with ISO 14040 and ISO 21930. The operational effects of the green remodeling were analyzed using the DesignBuilder program. According to the results, the carbon emissions generated by the green remodeling works for a public daycare center over 30 years old were 32.078 tCO₂eq, and during the operational stage the emissions decreased from 12.558 tCO₂eq to 11.225 tCO₂eq, representing a reduction of approximately 10.6%. These results indicate that carbon payback begins 24.1 years after the green remodeling, and that full offset can be achieved at 48.2 years. Therefore, the findings suggest that energy savings are feasible for green-remodeled buildings not only during operation but also from a whole life-cycle perspective, and they are expected to serve as a basis for future carbon-reduction analyses and policy development. |
| 4-1 | 5/20/2026 11:00 | Sponsored Session by ERC (Engineering Research Center) at Chung-Ang University, Korea | SGM 101 | 242 | Jiwoo Jang, Taejune Song, Hansol Kim, Chaewon Lee, and Hanseung Lee | Department of Architectural Engineering, Hanyang University; Department of Smart City Engineering, Hanyang University | An Experimental Study on a Paper-Based Sensor for Chloride Ion Measurement in Fresh Concrete | Chloride ion Silver nitrate titration Paper-based sensor Fresh concrete | The chloride ion (Cl⁻) content in concrete strongly affects reinforcement corrosion and durability, and recent increases in the use of alternative fuels in cement manufacturing have raised concerns regarding unintended chloride introduction. This study proposes a simple paper-based sensor for rapid on-site chloride quantification in fresh concrete. The sensor was fabricated by sequentially impregnating filter paper with AgNO₃ and K₂Cr₂O₇ solutions to form a silver dichromate (Ag₂Cr₂O₇) reactive layer. When exposed to chloride-containing solutions, AgCl precipitates form along the strip through capillary-driven transport, and the precipitation length is used as a quantitative indicator. Sensors prepared with AgNO₃ and K₂Cr₂O₇ concentrations ranging from 0.005 to 0.5 N were evaluated using chloride solutions of 30–1000 ppm. Lower reagent concentrations (≤ 0.05 N) resulted in significantly enhanced sensitivity, enabling clear visual detection even at 30 ppm Cl⁻. Time-dependent measurements showed that more than 84% of the final precipitation length formed immediately after immersion, with reaction equilibrium reached within approximately 20 minutes. These results demonstrate that the proposed paper-based sensor enables rapid, equipment-free, and visually interpretable chloride measurement, showing strong potential for practical on-site application in fresh concrete quality control. |
| 4-2 | 5/20/2026 11:00 | Indoor Air Quality | SGM 123 | 132 | [Sponsor team: ERC] Hye In Kim, Kang Woo Bae, Ji Yeon Hyun and Jin Woo Moon | Chung-Ang University | Evaluating the Scalability of a PM2.5 Indoor Concentration Prediction Model using Transfer Learning | Indoor air quality PM2.5 prediction model Transfer learning Deep Neural Network | Indoor air quality (IAQ) directly affects occupant health and productivity, with fine particulate matter (PM2.5) recognized as a major cause of respiratory and cardiovascular diseases. This study aims to enhance the efficiency of IAQ management by analyzing the performance variations and adaptability of an indoor PM2.5 concentration prediction model, originally trained at an established test site (Site A), when applied to a different environment (Site B). Furthermore, a transfer learning-based self-learning framework is proposed to minimize user intervention. Using data from Site A from January to April 2025, including indoor/outdoor PM2.5 concentrations, indoor humidity, air handling unit (AHU) airflow rate, damper opening ratio, occupant count, and air purifier status, a Deep Neural Network (DNN) model was developed to predict indoor PM2.5 concentrations 10 minutes ahead. The model was deployed for two weeks across four AHU zones at Site B, employing transfer learning and self-learning techniques. The initial Site A model achieved a mean absolute error (MAE) of 0.5 μg/m³, a coefficient of variation of the root means square error (CvRMSE) of 10.21%, and a coefficient of determination (R²) of 0.98. At Site B, prediction accuracy declined temporarily due to variations in outdoor damper operation but improved as the model adapted through continuous retraining. Results showed high accuracy in certain zones, with performance differences influenced by occupant density and activity levels. This research establishes the basis for a real-time, adaptive PM2.5 prediction system applicable to diverse indoor spaces. Future work will evaluate scalability across multiple sites to enhance model generalization and support the development of fully automated IAQ management systems. |
| 4-2 | 5/20/2026 11:00 | Indoor Air Quality | SGM 123 | 260 | Renate Jaanus, Kristin Taru, Alo Mikola and Jarek Kurnitski | Tallinn University of Technology; Tallinn Univesity of Technology; Tallinn Univesity of Technology / Aalto Univesity | Experimental Evaluation of CO₂ Tracer Gas Dosing Methods for Reliable Ventilation Effectiveness Measurements with a Point Source | Ventilation efficiency Tracer gas CO2 dosing Indoor air quality | Reliable evaluation of ventilation effectiveness is essential to ensuring healthy, energy-efficient indoor environments. Tracer gas methods are widely used to assess air distribution performance and contaminant removal. However, little attention has been given to how the tracer gas should be released to describe a human point source and how the tracer gas flow rate influences the reliability of these measurements. This study experimentally investigates the effect of CO₂ dosing method and concentration level on the measured contaminant removal effectiveness (CRE) under mixing ventilation. Experiments were conducted in a mock-up classroom using several tracer gas dosing methods, including human metabolic CO2, and controlled injection approaches such as thermal dummies, a table tennis ball and a heated manikin. A range of dosing flow rates was applied to achieve different steady-state CO2 concentrations. The results show that CRE values depend on the achieved CO2 steady-state concentration. Low dosing rates, including human metabolic CO2, produce concentrations close to outdoor levels, resulting in large variability and systematically lower CRE values. In contrast, higher dosing rates lead to more stable and reproducible CRE values. These findings demonstrate that tracer gas steady-state concentration above the outdoor concentration level plays a key role in determining the reliability of CO2-based ventilation effectiveness measurements and highlight the importance of selecting dosing strategies and rates. |
| 4-2 | 5/20/2026 11:00 | Indoor Air Quality | SGM 123 | 415 | Neelima Geetha Archana Madasu, Sanand Maddipati and Elham Fini | Arizona State University | The Role of Bio-Based Wall Insulation in Enhancing Indoor Air Quality and Human Performance | Volatile organic compound (VOC) Joggle research Cognitive performance Building decarbonization | People spend approximately 90% of their time indoors, making indoor air quality (IAQ) a critical factor in overall health. Indoor pollutant concentrations are often 2–5 times higher than outdoor levels, and many toxic compounds are colorless and odorless, complicating their detection. Chronic exposure to these pollutants has been associated with adverse neurological outcomes, including accelerated cognitive aging, impaired memory, reduced academic performance, and symptoms consistent with Sick Building Syndrome (SBS). Modern energy-efficient building designs emphasize airtight construction and the use of various insulation materials to meet decarbonization goals. While these measures reduce energy consumption, they may also contribute to the accumulation of indoor pollutants, particularly through emissions from insulation and other building materials. Insulation, typically concealed within walls, plays a critical yet often overlooked role in IAQ. Different insulation materials, such as polyurethane, fiberglass and bio-based alternatives, emit varying levels of harmful volatile organic compounds (VOCs) and other pollutants. This study evaluates the impacts of bio-based, polyurethane, and fiberglass insulation on both environmental quality and cognitive performance. Controlled experiments were conducted to assess sound absorption, moisture permeability, and IAQ parameters, including VOCs, PM, and CO₂ concentrations. Cognitive performance was measured using the standardized Joggle test, focusing on reaction time and memory recall. The resulting data provide an integrated understanding of how insulation material choice influences indoor environmental quality and cognitive health. This is particularly relevant considering previous studies suggesting that petroleum-based insulations may emit VOCs associated with neurological effects, whereas bio-based alternatives tend to have lower emissions and have a smaller carbon footprint. These findings offer valuable insights for promoting both sustainable construction practices and occupant well-being. |
| 4-2 | 5/20/2026 11:00 | Indoor Air Quality | SGM 123 | 521 | Yunus Emre Cetin, Zihao Wang, Gerrid Brockmann and Martin Kriegel | Hermann-Rietschel-Institut, Technische Universität Berlin, Marchstraße 4, 10587 Berlin, Germany | Ventilation Effectiveness in a Test Room: Experiments and CFD Validation | Ventilation effectiveness Mixing ventilation Tracer gas measurements CFD | Ventilation effectiveness is often evaluated under the assumption of fully mixed conditions, yet this assumption may not hold for point-source emissions relevant to infection risk. To investigate this, experiments were conducted in a test room (5.2 m × 4.4 m × 2.85 m) using thermal dummies to simulate occupancy. Air velocities were measured with omnidirectional anemometers, while tracer gas experiments with calibrated CO₂ sensors captured concentration dynamics under different inlet and outlet configurations. These data were used to validate computational fluid dynamics (CFD) simulations, which enabled the assessment of additional source scenarios. The findings demonstrated reasonable agreement between CFD and experiments, although discrepancies were observed for certain source locations. Both measurements and simulations confirmed that ventilation effectiveness varies considerably with source position and that mixing ventilation does not ensure uniform conditions when emissions are localized. These results underline the importance of explicitly accounting for spatial variations in ventilation effectiveness in infection-risk-based design and highlight the need for further studies on ventilation strategies that more reliably support infection mitigation in shared indoor environments. |
| 4-3 | 5/20/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 130 | Akihiro Imaizumi, Hideki Tanaka, Hideharu Komoda and Takeshi Watanabe | Campus Planning & Environment Management Office, Nagoya University; Graduate School of Environmental Studies, Nagoya University; Kajima Corporation | Cooperative control method for Distributed Energy Resources using air conditioning heat source systems in multiple buildings | demand response distributed energy resources cooperative control centralized heat source systems multiple buildings | In recent years, the expansion of renewable energy adoption has accelerated the introduction of demand response (DR) to balance electricity supply and demand, necessitating the securing of power resources from all distributed energy resources (DERs). Among these, the use of DR from centralized air-conditioning heat source systems, whose adoption has been delayed owing to their operational complexity, is a critical consideration. In this study, energy management methods for power demand and supply were examined to achieve target goals through the "cooperative control" of multiple buildings. The central air-conditioning heat source system is assumed to be a DER resource. A DER-coordinated-control is proposed for three buildings: Buildings A and C have a combined gas and electric heat source system, and Building B has a water thermal energy storage system. During DR operation, a target power consumption was set for each building. Based on system simulation, the influence of applying this control on the negawatt-power status of each building and the achievement of the required negawatts for the entire building group was verified. During DR operation, negawatt target achievement was assessed every 30 min. Based on the operation plan established the previous day, when the system was activated at the start of DR operation, periods occurred in which the negawatt target could not be achieved. To address this issue, the target power consumption was reset based on the range of predicted power consumption. This control determines the target power consumption and the number of heat sources to operate during demand response by simulating outdoor conditions and air-conditioning heat load 30 min prior to DR commencement. Using this proposed control, it was confirmed that the DR negawatt targets requested for multiple buildings were achieved and that negawatt power could be supplied stably. |
| 4-3 | 5/20/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 148 | Mao Serikawa, Seiichi Kashihara, Junta Nakano, Takashi Akimoto, Toshiharu Ikaga and Shuzo Murakami | Asahi Kasei Homes Corporation; Hosei University; Institute for Built Environment and Carbon Neutral for SDGs; Kanagawa University; Shibaura Institute of Technology | Economic and environmental benefits of using batteries and heat pump water heaters to effectively utilize daytime electricity | CO2 emissions Electricity charge Home Energy Management System Simulation | Addressing climate change is an urgent global concern. One promising avenue is the generation of renewable energy such as solar power. Among major energy consumers, houses have significant potential for the installation of solar power generation systems and self-consumption of the electricity generated. Effective self-consumption of electricity generated in houses is crucial to expanding renewable energy use and reducing carbon dioxide (CO2) emissions. However, in many houses with solar power generation systems, the electricity generated and sold exceeds the household’s self-consumption. This study analyzes Home Energy Management System (HEMS) data and simulations to assess how charging storage batteries and operating water heaters during the day can improve self-consumption and to evaluate impacts on CO2 emissions and electricity charges. HEMS data from 262 households were analyzed to estimate the effects of implementation and battery charging timing. Within realistic electricity-rate ranges, daytime storage increased self-consumption by approximately 25% and reduced annual bills by roughly 20,000 JPY, although the savings remain small relative to battery installation costs. Simulations of a modeled house equipped with solar and storage systems examined CO2 emissions under various emission factors, storage battery-linked systems, and storage battery control methods. Assuming wider adoption of solar generation in the future, the emissions were calculated under the condition that the emission factor changes according to the amount of solar radiation. The results revealed that daytime charging generally reduced emissions, although selling electricity was more advantageous, depending on emission settings. These results highlight the need to enhance residential self-consumption rates to accommodate the future growth of solar power generation. Furthermore, they emphasize the importance of communicating the non-economic benefits of installing storage batteries to residents, such as enhanced disaster preparedness, in addition to the economic benefits. |
| 4-3 | 5/20/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 222 | Junlang Zhu, Hao Tang, Xiangzhe Xi, Yang Geng and Borong Lin | Institute of Smart City and Intelligent Transportation; Institute of Smart City and Intelligent Transportation, Southwest Jiaotong University, Chengdu 611756, China; School of Architecture, Tsinghua University, Beijing 100084, China | Planning High-PV Penetration Park: Enhancing Local PV Utilization and Economic Efficiency through Multi-Energy Storage | Photovoltaic Energy Storage Airport Planning Carbon Neutrality Local Coordination | Large airport parks have substantial energy consumption demands while possessing significant spatial resources for photovoltaic (PV) development. However, addressing the mismatch between PV generation and airport electricity demand to achieve efficient local consumption and optimal energy utilization remains a critical research challenge. This study investigates energy planning strategies for high-PV-penetration parks under net-zero development, using a major Chinese airport terminal expansion as a case study. The proposed bi-level optimization framework jointly determines installed capacities and annual hourly operation of multi-energy systems, integrating cooling, heating, and electricity with flexible resources including battery storage, chilled/hot water storage, and uni/bi-directional EV charging. A net-zero carbon constraint through carbon trading ensures environmental alignment while minimizing annualized costs. Results demonstrate local PV utilization improves from 33.6% without flexible storage to 73.0% with optimized configuration, accompanied by 30.2% cost reduction. Battery storage gains greater importance under high PV penetration due to unconstrained flexibility, while thermal storage serves supplementary roles. The system follows daytime charging and nighttime or off-peak discharging patterns. Beyond internal optimization, the study explores strategies for incorporating external resources such as adjacent buildings and surrounding EV fleets. Results show that these measures further raise PV utilization to 81.6% and reduce the levelized cost of electricity by 6.5%. Integrating surrounding buildings enhances source-load matching and reduces storage demand, while staff vehicles and external vehicle fleets substitute partial battery capacity. The findings highlight that high-PV parks require both internal multi-energy flexibility and external resource integration for efficient PV absorption, cost-effectiveness, and carbon reduction. This research establishes a paradigm for zero-carbon park planning under policy constraints, offering transferable insights for transport hubs and urban districts maximizing local PV consumption while improving economic performance. |
| 4-3 | 5/20/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 564 | Qiuhua Duan and Christy Ponnan | University of Alabama | Closed-Loop Digital Twins for Building-Integrated Photovoltaics: A Focused Review | Building Integrated Photovoltaics (BIPV) Closed-Loop Digital Twin (CLDT) Cyber-Physical Systems Urban Energy Management Predictive Maintenance | The decarbonization of urban environments relies on Building Integrated Photovoltaics (BIPV) to turn structures into active energy prosumers. However, traditional "Digital Shadows" utilize unidirectional data flows that fail to address real-time performance losses from urban shading, soiling, and degradation. This review explores closed-loop digital twins (CLDTs), which shift BIPV management from passive observation to autonomous, cyber-physical synchronization. By synthesizing 12 core studies (2013–2025), this paper maps a technological stack integrating Building Information Modeling (BIM), IoT sensing, and AI engines like LSTM and CNNs. Key findings highlight feedback mechanisms such as UAV-based robotic maintenance and multi-objective optimization (ANN-MOGA) to balance energy yield with occupant comfort. While CLDTs can reduce cooling energy and improve self-absorption, deployment is challenged by 5G or 6G latency, cybersecurity risks, and model drift from biological corrosion. We conclude with a roadmap for blockchain-secured, interoperable protocols to enable self-adaptive, resilient energy infrastructure. |
| 4-3 | 5/20/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 578 | Wooyoung Jung | The University of Arizona | Chain-of-Thought Prompting for Human-Centered Home Energy Management | Home Energy Management Systems Large Language Model Human-Centered Engineering Prompt Engineering Chain-of-Thought Prompt | This study aimed to demonstrate the effectiveness of a chain-of-thought (CoT) prompt tailored to generate personalized energy-saving strategies for households. Energy eco-systems grow increasingly complex on both demand and supply sides, but households often lack clear guidance on how to adjust their energy usage patterns in response to dynamic pricing structures and variable consumption patterns. While recent studies have indicated the potential of integrating large language models (LLMs) into building energy management (BEM) tasks, these efforts have primarily focused on technical and analytical applications, with limited attention to human-centered approaches that directly support occupants in managing their energy use. To address this gap, this study systematically assessed the performance of a LLM-integrated building energy management system (BEMS) in generating personalized, data-driven, and behavior-oriented energy-saving recommendations for an actual household located in Austin, Texas. The proposed CoT prompt, incorporating advanced analytical and step-by-step reasoning processes – was compared against a concise, dialogue-type prompt to evaluate the effectiveness of structured reasoning in enhancing the accuracy and contextual relevance of AI-generated recommendations. Results show that the CoT prompt achieved a mean accuracy of 71.3%, significantly outperforming the concise, dialogue-type prompt (29.3%). It indicated that structured reasoning enabled the LLM to generate appliance-specific, data-driven, and context-aware interventions rather than generic, surface-level solutions. This study advances the understanding of how LLM-integrated BEMS can foster more intuitive, informed, and data-driven home energy decisions. |
| 4-4 | 5/20/2026 11:00 | Building Technology and Performance | GFS 116 | 244 | Sim-Cheon Yuk, Seo-Yeon Jo, In-Beom Jo and Han-Seung Lee | Department of Architectural Engineering, Hanyang University ERICA; Department of Smart City Engineering, Hanyang University | Evaluation of Resistance to Chloride Attack of Concrete Repair Method Using a Combined Application of Silicone-Based Water Repellent | Concrete repair method Silicon-based water repellent Surface coating material Repair mortar Chloride attack resistance Durability | This study aims to evaluate the effectiveness of combined repair methods in improving the durability of reinforced concrete (RC) structures exposed to chloride-induced deterioration. The hydrophobic performance of the applied repair systems was quantified through contact angle measurements, while chloride penetration resistance was evaluated using the non-steady-state chloride migration test (NT-BUILD 492). The results showed that the application of a silicon-based water repellent significantly enhanced hydrophobicity and reduced chloride ingress, and that these effects were further improved when combined with inorganic–organic hydrophobic materials. Chloride-induced durability analysis demonstrated that the combined application of surface coating, patch repair, and surface impregnation systems markedly improved long-term performance. In particular, the predicted service life increased to 287 years, and the chloride content at a reinforcement depth of 40 mm after 30 years of simulated exposure was reduced to 0.6 kg/m³, confirming the high effectiveness of the combined repair strategy in mitigating chloride-induced deterioration |
| 4-4 | 5/20/2026 11:00 | Building Technology and Performance | GFS 116 | 37 | Indra Permana, Alya Penta Agharid, Fu Jen Wang, Zulvi Alfiqri Hidayatulloh and Chu-Cheng Wei | National Chin-Yi University of Technology | Enhancing Biotechnology Cleanroom Performance through Field Recovery Testing and CFD-based Airflow Optimization | Biotechnology cleanroom Recovery Test CFD Field Measurement Energy saving | Cleanroom recovery performance is essential in biotechnology facilities to ensure rapid removal of airborne particles after contamination events. This study aims to assess the recovery performance and pressurization condition of a Grade D biotechnology cleanroom and to determine whether airflow optimization can reduce energy use while maintaining required cleanliness and pressure levels. A field particle recovery test was conducted by generating airborne particle concentrations approximately 10 times higher than the Grade D limit and monitoring the decay of ≥ 0.5µm particles over 20 minutes. Diagnostic measurements, including airflow distribution and room-to-room pressurization, were performed to identify low-performance zones. In addition, a CFD model replicating the actual HVAC configuration was developed to analyze airflow patterns, pressure gradients, and the causes of reduced recovery or pressurization imbalance. The cleanroom successfully restored particle concentrations to Grade D limits within 10-15 minutes, achieving removal efficiencies of 98–99% across most rooms. However, field diagnostics revealed significant airflow and pressurization imbalance, particularly in the printing area, where differential pressures dropped below 10 Pa and recovery times approached the 20-minute threshold. CFD analysis confirmed the presence of low-velocity zones, recirculation, and elevated Age of Air. Simulation results demonstrated that restoring pressurization alone requires increased airflow, which raises fan power consumption. In contrast, optimizing airflow distribution through diffuser repositioning improved air mixing, reduced Age of Air by 33-38%, and re-established the required pressurization and lowered fan power by 12-17%. This demonstrates that airflow pattern optimization is more effective than increasing airflow for achieving both performance and energy efficiency in cleanrooms |
| 4-4 | 5/20/2026 11:00 | Building Technology and Performance | GFS 116 | 113 | Kätriin Onemar, Raimo Simson and Jarek Kurnitski | Tallinn University of Technology | Dynamic Modeling and Experimental Validation of Floor Cooling Systems for Overheating Assessment and Condensation Risk Considerations in Residential Buildings | Underfloor cooling Hydronic cooling systems Condensation risk considerations Dynamic thermal simulation Residential cooling performance | This study presents the development and experimental validation of a dynamic underfloor cooling system model aimed at improving the understanding of system-level thermal behavior in residential buildings. In the context of increasing summer heatwaves and overheating problems, a robust cooling solution is needed, particularly for dwellings with large glazed areas. Many new residential buildings are already equipped with hydronic underfloor heating systems, making them suitable for adaptation to cooling without major modifications. Unlike conventional supply temperature control, the proposed modeling approach considers cooling output in relation to floor surface temperature and indoor air conditions, providing a physically consistent basis for assessing condensation-related constraints. Experimental data were collected from a full-scale nearly zero-energy (nZEB) residential building equipped with a hydronic underfloor cooling system. Measurements included return water temperature, cooling power, and floor surface temperature under varying operating conditions and supply temperature levels. The measured data were used to calibrate and validate the dynamic simulation model. Primary emphasis was placed on return water temperature and cooling power as robust system-level indicators, while floor surface temperature was used as a secondary reference for qualitative comparison. Performance was evaluated across different floor surface configurations and operating points. The results demonstrate that the calibrated model is able to reproduce the key thermal responses of the underfloor cooling system at the system level. This work provides experimental support for the use of dynamic simulation models in the analysis of residential underfloor cooling performance and forms a basis for future studies addressing advanced control concepts and condensation-safe operation. |
| 4-4 | 5/20/2026 11:00 | Building Technology and Performance | GFS 116 | 155 | Minzhi Ye, Masashi Momota, Aoto Kumagai, Hajime Ogata and Hyo Ogawa | Tokyo Denki University | Post-construction evaluation of building envelope thermal performance using neural networks | Building envelop performance Building thermal performance BACS Neural network | The thermal performance of buildings is usually evaluated only at the design stage, whereas post-construction evaluation has received limited attention. Existing frameworks, such as the Perimeter Annual Load (PAL*) in Japan or the Overall Thermal Transfer Value (OTTV) applied in Hongkong and Singapore, also rely primarily on design values and are evaluated by climate-zone-defined standards. However, it is generally difficult to evaluate the thermal performance of specific rooms or zones within a building, or to compare buildings in different climates. Furthermore, thermal performance evaluations are also required in practice to identify issues caused by the deterioration of building envelopes over time. On-site measurements are necessary to obtain accurate results of building thermal performance. However, the measurements require cost, time, and skilled professionals to implement. At present, most newly constructed buildings are equipped with Building Automation and Control Systems (BACS). Although BACS measurement data are typically used for system control to maintain comfortable indoor conditions, they could potentially be extended applied for the automated evaluation of building thermal performance. In this paper, a methodology is proposed to evaluate the thermal performance of building envelopes based on indoor and outdoor temperature measurements. A neural network model was first trained to predict indoor temperature variations in the early morning using data collected by BACS during the non-air-conditioned and unoccupied period. The data from this period are free from solar radiation and internal gains caused by occupant activities, leaving only the influence of the building envelope. The model was validated against recorded room temperatures in a university campus in Tokyo, Japan. Then, the predicted temperature variations in three different types of rooms were compared to examine whether the proposed methodology can capture the performance characteristics associated with different building envelope types. Finally, different climate datasets were applied to investigate how the thermal behavior of various room types may differ and change under diverse climatic conditions. |
| 4-4 | 5/20/2026 11:00 | Building Technology and Performance | GFS 116 | 457 | Nasim Ildiri and Mark Hernandez | University of Colorado | Effects of HVAC Duct Cleaning on Indoor Air Quality Parameters: A Multi Season Demonstration of Exposure Assessment in Occupied Public School Classrooms | Building hygiene HVAC cleaning PM air exchange aerosol exposure | Abstract. Modern building hygiene practices have received increased attention in response to updates in ventilation performance guidelines for high occupancy indoor environments. In this context, the Centers for Disease Control and professional architectural engineering societies (e.g., ASHRAE) have recently issued updates (2024) for air exchange rate guidelines (minimum 5 hr-1), notably including recommendations for educational settings. The primary drivers for increased air exchange are to lower occupant exposures to respirable particulate matter (PM) and carbon dioxide (CO2). However, increased air exchange requires sustained mechanical energy input over baseline conditions and there is a paucity of systematic PM and CO2 observations to confirm exposure reduction benefits in response to engineering interventions, including building hygiene practices. Recent research has reported energy consumption and ventilation performance benefits associated with systemic HVAC system cleaning in commercial office and educational environments, yet concomitant reductions PM exposure potential associated with these practices have not been systematically studied. In response, this demonstration study was designed to observe patterns of respirable PM and CO2 levels before, and after certified HVAC cleaning in public school classrooms, during heating and cooling modes, through an academic year. We also compared indoor air quality parameters from classrooms connected to cleaned air handling units (AHU) in temporal parallel to those classrooms connected to uncleaned AHUs within schools containing similar architectural features, occupancy, and grade levels. As judged by continuous real time air quality monitoring (1 minute resolution), results from this pilot study (4 schools) suggest that certified HVAC cleaning can significantly reduce respirable PM levels and improve ventilation performance during typical classroom occupation periods |
| 4-4 | 5/20/2026 11:00 | Building Technology and Performance | GFS 116 | 646 | Beom Yeol Yun, In-Hwan Lee, Sang-Joon Lee, Chul-Ki Kim, Hyung Woo Lee and Tae-Ik Hwang | Wood Engineering Division, National Institute of Forest Science | Field Application of EMC-Based Temperature–Humidity Monitoring for Durability Risk Assessment in Timber Buildings | Timber buildings moisture monitoring durability design equilibrium moisture content risk assessment | Timber buildings are increasingly applied to mid- and large-scale construction, which intensifies the need for durability strategies against moisture-driven deterioration. This paper proposes a durability-oriented moisture monitoring and risk assessment framework integrating (i) a review of durability design requirements in leading regions, (ii) degradation case analysis from existing timber buildings, and (iii) a smart monitoring workflow for temperature–humidity measurement and equilibrium moisture content (EMC)–based alerts. Domestic field surveys identified recurring moisture pathways including window/joint leakage due to timber shrinkage, inadequate drainage and waterproofing details, insufficient ground separation at timber bases, and leakage from aged building services. A distributed monitoring system was implemented using embedded and ambient sensors with RS-485/MODBUS communication. EMC was estimated via the Hailwood–Horrobin model, and risk was classified using duration-based exceedance criteria (e.g., EMC > 20% sustained for > 6 h). Results show that cumulative high-humidity exposure governs moisture accumulation more strongly than short-term peaks. The framework supports proactive maintenance and detailing improvements (drainage, airtightness continuity, ventilated cavities) and provides an operational basis for long-life management of timber buildings in humid climates. |
| 4-5 | 5/20/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 101 | 78 | Kensuke Watanabe, U Yanagi, Yoshiki Shiraishi and Koichiro Asano | Kogakuin University; Tokai University | Mycobiome of air purifier filters in allergic bronchopulmonary mycosis patients' homes | ABPA/ABPM Indoor air quality Air purifiers Fungal communities Next-generation sequencing (NGS) | In recent years, the number of patients diagnosed with allergic bronchopulmonary mycosis (ABPM), a chronic disease caused by fungal colonization in the bronchi, has increased. ABPM has been associated not only with Ascomycetes such as Aspergillus fumigatus and A. niger from the Aspergillus genus, but also with Basidiomycetes, including Schizophyllum commune. However, long-term investigations of indoor mycobiome in the homes of ABPM patients remain limited. Therefore, the objective of this study was to ascertain the extent of microbial contamination in the homes of ABPM patients. In this study, air purifiers were installed in the living rooms and bedrooms of 10 ABPM patients for a two-month period. Fungi adhering to the collected filters were analyzed by next-generation sequencing (NGS) to targeting the ITS1 region, and the fungal communities were analyzed in a total of 16 samples. The results demonstrated that Basidiomycetes accounted for at least 60% of all samples, with an average of over 82%. Conversely, Ascomycota accounted for an average of 2.9% or less, indicating a substantial imbalance between both groups. Analysis of the genera Schizophyllum revealed species identified as potential causative agents of ABPM. Furthermore, β diversity analysis revealed that the fungal communities inhabiting the living rooms and bedrooms within each residence were similar. This finding suggests shared characteristics among fungal communities within a single residence, despite functional differences among rooms. |
| 4-5 | 5/20/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 101 | 105 | Iasmin Lourenço Niza, Mateus Pedrosa Braga and Evandro Eduardo Broday | Federal University of Technology - Paraná (UTFPR) | Assessment of Indoor Environmental Quality (IEQ) in university classrooms by periods of the day through discriminant analysis | Indoor Environmental Quality Discriminant Analysis University Classrooms IEQ | Indoor Environmental Quality (IEQ) is fundamental in any environment, as it directly influences occupants' health, comfort, well-being, and productivity. In educational environments, inadequate conditions can impair cognitive performance and learning. This research aimed to analyze university classrooms located in Southern Brazil, using Discriminant Analysis to classify environmental conditions considering four periods of the day: (1) early morning (7:30–9:59 a.m.), (2) mid/late morning (10:00–11:59 a.m.), (3) early afternoon (12:00–02:59 p.m.), and (4) mid/late afternoon (03:00–05:59 p.m.). This classification will be based on data collected from 150 on-site measurements taken between 2024 and 2025. Data were collected using Aura IEQ Discoverer equipment, which covers the tangible aspects of IEQ, including thermal comfort (operative temperature and relative humidity), visual comfort (illuminance), acoustic comfort (noise), and indoor air quality (carbon dioxide concentration and volatile organic compounds). The results indicated that operative temperature, relative humidity, and CO2 concentration were the variables with the greatest discriminatory power between periods. The discriminant model achieved a 50.7% accuracy rate in classifying environmental variations throughout the day, revealing identifiable temporal patterns in environmental conditions, which can help develop strategies for ventilation, lighting control, pollutant, and noise reduction in educational environments. This information can support the implementation of building management policies that promote greater energy efficiency, thermal and acoustic comfort, and improved air quality. All of these benefits contribute to good indoor conditions for users and also for the building’s sustainability. |
| 4-5 | 5/20/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 101 | 139 | Toby Cheung and Eikichi Ono | General Manager; Senior Researcher | Occupant Environmental Satisfaction in a Semi-Outdoor Workspace versus Air-Conditioned Offices in Singapore | Post-Occupancy Evaluation Satisfaction Semi-Outdoor Workspace Tropical Climate | In Singapore, the hot and humid climate has made air conditioning the default design strategy for commercial office buildings. However, it comes at a cost with cooling demand up to 60% of total electricity consumption. Strategy of higher temperature setpoints combined with elevated air speed has been shown to improve both energy efficiency and occupant comfort in tropical conditions. Yet, the central question remains: is it possible to work without air conditioning in a modern workspace? This study investigates occupant satisfaction with environmental conditions in a purpose-built semi-outdoor, naturally ventilated workspace in Singapore. A Post-Occupancy Evaluation (POE) survey was used to assess occupants’ satisfaction across 19 environmental parameters. These parameters include temperature, humidity, air movement, overall thermal comfort, air freshness, scent, overall IAQ, lighting, light color, window views, overall visual comfort, noise, privacy, communication, furnishings, available space, personal control, cleanliness, and overall environment. Thereafter, satisfaction performance of 14 common parameters from the semi-outdoor workspace were compared against thirteen conventional air-conditioned (AC) offices extracted from the literature. The findings were unexpected. The semi-outdoor workspace showed either higher satisfaction or lower dissatisfaction with temperature, air freshness, scent, window view, available space, and noise level when compared with AC offices. This outcome suggests that occupant expectations in semi-outdoor settings could be different from those in fully controlled indoor environments. The results also indicate that maintaining optimal air speed is a key factor in achieving higher overall thermal satisfaction in semi-outdoor workspaces. On the other hand, satisfaction with humidity, lighting, personal control, cleanliness, and privacy was lower than in AC offices, largely because of the dynamic and less controllable outdoor weather conditions. These results based on user feedback demonstrate that semi-outdoor workspaces are not an impossible option in tropical climates. The study offers valuable insights that can inform the design and operation of future naturally ventilated workspaces in the tropics. By adopting appropriate design strategies, it is possible to reduce energy-intensive reliance on air conditioning while maintaining acceptable levels of occupant satisfaction. |
| 4-5 | 5/20/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 101 | 146 | He Wu, Hisato Osawa and Taro Mori | Hokkaido University; Hokkaido Universiy | Investigation of Legionella Transmission Using CFD Simulation Coupled with GIS | Legionella outbreak GIS CFD Bioaerosol Urban dispersion | Legionella is a pathogenic bacterium that can cause severe pneumonia, known as Legionnaires' disease, with a death rate ranging from 5% to 10%. Warm and humid environments promote the proliferation of Legionella. As a result, places and facilities where Legionella is likely to grow should be managed under strict rules. However, in 2023, a Legionella outbreak originated from a cooling tower at a hospital in Ōsaki City, Miyagi, Japan. This case is considered one of the most severe in modern Japanese history, resulting in 23 infections and 2 deaths. During this incident, the concentration of Legionella in the cooling tower reached approximately 680,000 times the normal value (about 68,000,000 CFU/100mL), far exceeding the safety standard of 100 CFU/100mL. In this case, while inhalation of Legionella from the cooling tower is suspected, the exact transmission pattern remains unclear. Therefore, this study integrates meteorological data from the outbreak period and inputs the GIS data of Ōsaki City into CFD software to investigate the spread situation of Legionella within a 5 km radius from the source and conduct a quantitative analysis of the extent of risk. The simulated scenario consists of a 10km×10km area centered on the particle source building. The simulation is conducted under time-varying wind conditions, using local meteorological data from JMA to change the wind velocity every 10 minutes. A particle decay system is introduced into the simulation, referencing existing literature on the survival time of bioaerosols in the atmosphere under the effects of humidity and UV exposure. Given that particles are subject to different environmental conditions at different locations, such as reduced UV sterilization efficacy for aerosols in shaded areas, the model applies a spatially dependent, comprehensive particle decay rate, thereby enabling a more accurate representation of Legionella dispersion under real world conditions. Comparison of CFD results with infection records from the outbreak can demonstrates that the CFD system can reproduce Legionella dispersion in urban environments. When combined with GIS data, this system can be used to assess potential risks in other regions. |
| 4-5 | 5/20/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 101 | 187 | Amanda Quarshie and Cristina Poleacovschi | Iowa State University | Residential Cooking and Kitchen Ventilation Behaviors in Alaska Native Households: Foundations for Indoor Air Quality Assessment | IAQ Occupant Behaviors Kitchen Ventilation Alaska Native communities | Occupant behaviors particularly cooking contribute significantly to the emission of pollutants such as particulate matter (PM) in households, worsening indoor air quality (IAQ) and adversely impacting health and wellbeing. However, systematic characterization cooking and kitchen ventilation practices in Alaska Native (AN) communities, and how they are shaped by seasonal conditions remains limited. Understanding these behavioral patterns is essential for interpreting IAQ exposure pathways and designing effective interventions. This study addresses the research question: What are the seasonal and temporal cooking and kitchen ventilation behaviors in AN households? Survey data (n=50) were collected across two AN communities in the Norton Sound region between August and September 2025, with participants reporting behaviors separately for summer and winter. Descriptive analyses revealed similar cooking patterns across seasons, with frying, roasting and grilling dominating as high-emission methods. This study provides the first systematic documentation of cooking and ventilation behaviors in AN households, revealing three novel insights: (1) evening hours (5-9pm) consistently exhibited the highest concentration of cooking activities, accounting for 37% and 35% of potential daily pollution exposure risk in summer and winter respectively, creating predictable temporal windows of heightened exposure; (2) seasonal shifts in ventilation practices from window opening in summer (63%) to exhaust fan use in winter (64%). However, 25-34% of households do not ventilate despite using high-emission methods; and (3) open floor plans (71% of households) combined with limited ventilation may enable pollutant emissions throughout living spaces during peak periods. This characterization provides essential groundwork for future research linking cooking and kitchen ventilation behaviors to measured IAQ outcomes and developing culturally appropriate, seasonally feasible intervention strategies for AN communities. |
| 4-5 | 5/20/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 101 | 239 | Houda Er-Retby, Myriam Bahrar, Mohamed Oualid Mghazli, Mostafa Benzaazoua and Mohamed El Mankibi | ENTPE – University of Lyon, LTDS; Geology and Sustainable Mining Institute (GSMI), Mohammad VI Polytechnic University (UM6P) | Experimental Assessment of Indoor Air Quality and Thermal Comfort Performance Using Fuzzy Logic Control for Natural and Mechanical Ventilation Systems | Fuzzy logic control Natural ventilation Mechanical ventilation Indoor air quality Thermal comfort CO₂ dynamics | Ventilation strategies embody a fundamental compromise between human comfort, indoor air quality, and the responsiveness of building systems to dynamic occupancy. As modern buildings become increasingly airtight, the ability of ventilation systems to adapt in real time has become essential. This study presents an experimental comparison of natural ventilation (NV) and mechanical ventilation (MV) operated under an identical two-level hierarchical fuzzy logic control, coupling thermal comfort assessment (temperature and relative humidity) with CO₂-based ventilation decision-making. Experiments were conducted in a four-room testbed under equivalent occupancy profiles, aligned over 24 hours to ensure comparability. Indoor air temperature, relative humidity, and CO₂ concentration were monitored to evaluate thermal stability, indoor air quality performance, and ventilation effectiveness. Both strategies maintained indoor temperatures close to setpoints (tracking errors < 2.5 °C), but NV produced larger short-term fluctuations in temperature and humidity. MV achieved better indoor air quality control, limiting CO₂ peaks to typically below 1200 ppm, whereas NV reached higher peaks (up to ~1400 ppm in higher-occupancy rooms). Post-occupancy CO₂ decay analysis revealed faster and more consistent pollutant removal under mechanical ventilation, compared to lower and more variable decay rates under natural ventilation. Further exposure analysis showed that mechanical ventilation increased the proportion of time spent below 1000 ppm by up to 60% across rooms. Overall, the results indicate that applying a common fuzzy decision logic allows both ventilation strategies to operate effectively, while mechanical ventilation provides more stable and predictable indoor environmental control. Natural ventilation, although viable, exhibits greater variability and stronger room-dependent behavior, highlighting the potential of hybrid strategies that combine both approaches. |
| 4-6 | 5/20/2026 11:00 | Smart Cities and Green Infrastructure | GFS 207 | 150 | Ryoma Okuda, Hideki Tanaka, Hiroaki Tanaka and Fuminori Nishiyama | Nagoya University; NIKKEN SEKKEI LTD | Optimal control method for HVAC heat source system based on operational data utilizing machine learning | Machine Learning Optimization Method Random Forest District Heating and Cooling | In large-scale air-conditioning heat supply systems, such as district heating and cooling (DHC), multiple heat source units are typically operated, with manual control based largely on operator experience. This study aims to develop an energy management system that optimizes operational planning for such facilities. Central to this initiative is the construction of a high-fidelity energy consumption estimation model for each heat source unit, leveraging actual operational data within a machine learning framework. To enhance model accuracy, the learning process systematically addresses operational biases, enabling precise characterization of unit-specific performance even when historical data are limited or unbalanced. Beyond predicting gas consumption based on cooling water temperature and part-load ratio, the proposed methodology explicitly quantifies the sensitivity of these variables and incorporates a simulation-driven data augmentation strategy. This approach expands the effective learning domain, allowing the machine learning model to capture operational characteristics across a broader spectrum of conditions, including those infrequently observed in practice. By integrating the developed performance model with forecasts of cooling water temperature and heat demand, this study introduces a method for estimating future energy consumption and generating optimized operation schedules that account for anticipated system dynamics. The application of the proposed framework to real plant data revealed that conventional manual operations often favored less efficient units, whereas the proposed approach achieved a potential reduction in energy consumption of approximately 22.7%. These results highlight the significant impact of accurate performance modeling on subsequent optimization. |
| 4-6 | 5/20/2026 11:00 | Smart Cities and Green Infrastructure | GFS 207 | 163 | Doyun Lee, Young Jik Youn and Wonseok Oh | Hanbat National University; Kyushu University | Microclimate heterogeneity and operational strategies in indoor vertical farm | indoor vertical farm climate uniformity computational fluid dynamics(CFD) transpiration operational strategies | This study employed a high-fidelity computational fluid dynamics (CFD) framework to investigate microclimate heterogeneity and evaluate operational strategies for its mitigation. The CFD model integrates a plant transpiration model to resolve coupled heat, moisture, and airflow transport at the microscale, enabling detailed representation of crop–environment interactions. Unlike experimental approaches constrained by sensor density, the CFD analysis provides continuous spatial and temporal data, capturing complex gradients across layers and zones of an indoor vertical farm. Baseline simulations reveal pronounced stratification, with temperature differentials exceeding 3 °C and differences in relative humidity (RH) exceeding 8%, which directly influence transpiration, climate regulation, and energy demand. To improve the climate uniformity, three operational strategies were evaluated: (1) adaptive airflow control through optimized local fan speed and canopy-level configurations, (2) sensor-driven dynamic HVAC control, and (3) combined strategies integrating both airflow and climate system optimization. The evaluation utilized canopy-level temperature and humidity data to assess thermal uniformity at local cultivation points. Unlike conventional centric control that regulates overall space conditions, this framework emphasizes whether crop-level environments remain within optimal growth ranges. Results show that adaptive airflow effectively mitigates stratification near canopies, while dynamic HVAC control improves overall uniformity. The combined strategy achieved the highest consistency, ensuring local crop microclimates aligned with growth requirements. This research highlights the value of CFD-based simulation with plant physiological coupling for analyzing microclimate dynamics in vertical farms. Beyond methodological contribution, it offers practical insights for deploying vertical farms within urban buildings, where integration with energy systems can enhance sustainability and resilience in future cities. |
| 4-6 | 5/20/2026 11:00 | Smart Cities and Green Infrastructure | GFS 207 | 177 | Jeonghoon Choi, Muhammad Ihza Febriyan Pagri and Dongjun Suh | Kyungpook National University | Sensor-Only Occupant-Centric Ventilation Control with LLM-Augmented Decision Support for Human–Building Interactions | Occupant-centric ventilation control Large language model Human building interactions Model predictive control Sensor-based occupancy estimation | A sensor-only occupant-centric ventilation control framework augmented with large language model based decision support is proposed to address human–building interactions in smart building operations. The system uses low-cost environmental sensors including carbon dioxide concentration, temperature, humidity, passive infrared motion detection, door state, and smart meter data to preserve privacy while capturing occupant presence and activity patterns. Occupancy is inferred using a carbon dioxide mass-balance inversion model with Bayesian filtering, incorporating motion and door state signals for accuracy. Short-term forecasts of indoor air quality and thermal conditions are generated using time-series models such as long short-term memory networks or gradient boosting. These predictions are applied by a model predictive controller to optimize ventilation and cooling setpoints under air quality, comfort, and equipment constraints while minimizing energy consumption. The large language model module acts as a supervisory layer that reviews control proposals, detects potential violations or inefficiencies, incorporates contextual factors such as scheduled events, and recommends adjustments. The module also generates human-readable, context-aware explanations linking each control decision to predicted occupancy, air quality trajectories, and energy trade-offs, enhancing operator trust and enabling human-in-the-loop interactions. The framework is evaluated using real-building sensor datasets and EnergyPlus or CONTAM simulations, with performance compared against fixed-schedule control, threshold-based demand-controlled ventilation, and predictive control without decision support. Results show reductions in air quality exceedance hours and ventilation or cooling energy use, while maintaining stable actuation and providing clear decision rationales. This integration of predictive control and large language model based decision augmentation offers a practical, adaptive, and explainable approach for occupant-centric and privacy-preserving ventilation management, advancing research in human–building interaction and sustainable smart building practices. |
| 4-6 | 5/20/2026 11:00 | Smart Cities and Green Infrastructure | GFS 207 | 364 | Chanuk Lee and June Young Park | The University of Texas at Arlington | Deep reinforcement learning for citizen-centric building retrofit decision making under behavioral uncertainty of a series game scenario | Deep Reinforcement Learning Building Energy Retrofit Proximal Policy Optimization Serious Games Portfolio Optimization Bounded Rationality | Residential buildings account for a significant portion of global energy consumption, and energy retrofits represent a crucial pathway toward achieving carbon neutrality. However, homeowners often make retrofit decisions under bounded rationality, influenced by social factors, limited information, and random opportunities rather than optimal economic calculations. This study proposes a novel framework that models citizens' inherent decision-making randomness through a serious game environment (Net-Zero Home Race Game, NZHR) integrated with EnergyPlus building simulation and derives optimal retrofit strategies using Proximal Policy Optimization (PPO), a deep reinforcement learning algorithm. The NZHR game uses a representative single-family residential building from the NREL ResStock database located in the Dallas-Fort Worth metropolitan area of Texas, providing realistic baseline energy consumption data. Drawing inspiration from financial portfolio management theory, we conceptualize retrofit decision-making as an investment problem where homeowners allocate limited capital across various retrofit assets to maximize long-term portfolio value. The trained PPO agent achieved an average reward of 8.51 (±0.95) across 30 test episodes, with mean energy savings of 12,692 kWh (26.4% reduction) and final capital of $49,647. The agent learned a phased investment strategy: prioritizing insulation measures in early game stages, followed by HVAC improvements mid-game, and deferring high-cost solar PV installation until late game when sufficient capital was accumulated. This research bridges the gap between idealized optimization models and real-world behavioral uncertainty in retrofit decision-making. |
| 4-6 | 5/20/2026 11:00 | Smart Cities and Green Infrastructure | GFS 207 | 431 | Hongzhi Liu, Takumi Tanabe, Bozhou Dang and Katsunori Nagano | Faculty of Engineering, Hokkaido University; National Institute of Technology, Tomakomai College | Implementation of an Optimized Control Strategy for Energy Storage Systems in HEMS (Home Energy Management System) in Cold Climate | Energy management systems Optimization Energy storage system Data predication. | As the global warming issue is gathering much more attention than ever before, the major countries in the world have set goals of achieving carbon neutrality in decades. The movement has been promoting the development of renewable energy utilization and energy-saving technologies. In ZEBs (Zero Energy Buildings), in addition to achieving a net zero annual primary energy balance, maximizing energy self-sufficiency is also important. In this case, the introduction of energy storage systems such as batteries and thermal storage is essential, and accurate solar radiation forecasting is indispensable for controlling such energy storage systems. Therefore, this study examined the impact of solar radiation forecasting methods on energy self-sufficiency and purchased electricity costs in a building equipped with PV and battery. The forecasting methods used were: a closed-loop type that performs daily predictions with an LSTM (Long Short-Term Memory) after clustering by weather conditions; an open-loop type that updates predictions every hour using measured values; and a hybrid model combining CNN (Convolutional Neural Network) and LSTM. Among these, the results obtained with the CNN-LSTM approach showed the highest predication accuracy. Mixed-Integer Linear Programming (MILP) algorithm uses constraints to find the minimum or maximum value of the objective function, including some variables with integer values to reduce calculation time, which is suitable for the situation in this research for optimization calculation. Renewable thermal energy is fully utilized by applying optimal operation schedules to energy storage facilities and heating and cooling appliances to adjust flexible electrical and thermal loads. The operation schedule is calculated based on prediction data and advanced optimization algorithms. As a result, the CNN-LSTM approach provided the best overall performance. Furthermore, a lab-scale experimental setup—including a PV panel, load simulator, battery, and power conditioner—was constructed to validate the control strategy. |
| 4-6 | 5/20/2026 11:00 | Smart Cities and Green Infrastructure | GFS 207 | 551 | Nan Wang and Giorgia Chinazzo | Department of Civil and Environmental Engineering, Northwestern University | An Immersive VR-Based Workflow for Evaluating Automated Shading Control and Visual Aging Effects within Smart Cities | Immersive daylighting visualization occupant experience human-centric design visual aging automated shading control | Smart cities increasingly rely on automated building control systems to regulate indoor environmental conditions. However, the experiential impacts of such automated strategies on occupants, particularly across different age groups, are costly and challenging to evaluate prior to real-world deployment. Virtual reality (VR) technology provides a means for occupants to engage with simulated environments in an immersive and controlled way. This paper presents the design of a VR-based workflow for experiencing automated daylighting and shading control scenarios, incorporating illustrative age-related visual characteristics. A representative indoor space with a south-facing window and automated roller shading was modeled in Rhinoceros. Daylighting conditions were simulated in Radiance at selected representative time points under clear-sky conditions to capture daylight scenarios relevant to shading control. A rule-based shading strategy was implemented using vertical eye-level and horizontal workplane illuminance thresholds to determine shading states (open, partially open, and closed). To account for age-related visual changes, illustrative perceptual aging profiles were applied during VR visualization to qualitatively represent differences in visual sensitivity, without altering the underlying physical lighting simulations. The resulting shading transition animations and aging comparisons were illustrated to demonstrate the proposed VR-based workflow, showing how automated shading behavior and daylighting scenarios could be visualized in an immersive environment. The proposed VR-based workflow enables occupants and designers to experience and assess automated daylighting control strategies prior to physical installation and can be extended to broader applications in human-centered residential design and smart-city planning. By explicitly considering age-related visual decline, this approach supports more inclusive evaluation of daylighting strategies and highlights the value of integrating daylighting performance, automated control, and occupant perception within building science research. |
| 4-7 | 5/20/2026 11:00 | Sustainable Building Materials and Circular Economy | GFS 118 | 210 | Todd Walsh, Yumna Kurdi, Tharique De Silva and Bruce Haglund | University of Idaho | Overcoming Construction Barriers to Mass Timber Adoption in the Inland Northwest: A Case Study of the ICCU Arena | Mass Timber Construction Challenges Supply Chain Resilience Workforce Development Inland Northwest | This study investigates the construction-related challenges facing the adoption of locally sourced mass timber in the Inland Northwest, with particular focus on the Idaho Central Credit Union (ICCU) Arena in Moscow, Idaho. While mass timber offers environmental and logistical advantages through prefabrication, digital fabrication, and reduced on-site labor, its implementation in rural and semi-rural regions reveals a complex set of barriers that limit its viability at scale. Using a mixed-methods approach, this research integrates a literature review, construction-phase documentation, and stakeholder interviews with architects, engineers, and contractors involved in mass timber projects. The goal is to identify specific barriers, including workforce skill gaps, design coordination challenges, cost predictability, and supply chain volatility, that affect mass timber’s construction efficiency in the region. A central case explored is the closure of Katerra’s Spokane Valley CLT facility in 2021. Despite its advanced technology and significant financial investment, the facility’s failure exemplifies the fragility of emerging supply chains for engineered wood products in the Inland Northwest. This disruption, coupled with a lack of regionally trained labor in timber construction methods, highlights the need for targeted workforce development, resilient business models, and cross-sector coordination. The findings from this study will contribute to a regional framework for overcoming construction-phase barriers to mass timber implementation. The results aim to support designers, policymakers, and manufacturers seeking to scale timber construction through more reliable and resilient pathways in similar post-industrial and rural markets. |
| 4-7 | 5/20/2026 11:00 | Sustainable Building Materials and Circular Economy | GFS 118 | 299 | Dongchan Jin, Young Uk Kim and Sumin Kim | Yonsei University | Development and performance evaluation of recycled insulation materials from waste firefighting suits for fire-resistant building pipes | Recycled insulation materials Waste firefighting suits Building pipe Thermal performance Underground fire safety | With the increasing frequency of fire incidents due to the expansion of underground spaces and the growing adoption of electric vehicles, the safety of building piping systems and ventilation ducts has become a critical concern. Pipes and ducts installed in underground areas often act as pathways for rapid fire spread, increasing the risk of flashover and exposing building occupants to severe casualties and property damage. To address these issues, this study focuses on the development and evaluation of recycled insulation materials derived from waste firefighting suits to enhance fire resistance in building piping and duct systems. Thermal conductivity tests revealed promising results, with the recycled materials achieving a value of 0.04499 W/m·K at 20 °C, demonstrating superior performance compared with conventional insulation and findings from previous recycling studies. To enhance external durability and improve thermal stability, the specimens were packed using materials derived from firefighting suits. Experiments conducted in a controlled temperature and humidity chamber, simulating virtual plenum spaces in buildings, showed enhanced insulation efficiency compared with poly-wool, with an average temperature difference of 13.5 °C at elevated temperatures and 2.4 °C under low-temperature conditions. Further assessments using flexible ducts revealed temperature differences ranging from 0.9 °C to 2.1 °C higher than those observed with poly-wool, indicating superior insulation capability. Additionally, cone calorimeter tests were conducted to evaluate the fire resistance and combustion behavior of the recycled insulation materials. Results demonstrated significantly reduced peak heat release rates and delayed ignition times compared with conventional poly-wool insulation, confirming the potential of these materials for applications requiring enhanced fire safety. Overall, this study highlights the viability of utilizing recycled firefighting suits as high-performance insulation materials, offering both thermal efficiency and improved fire resistance. These findings suggest strong potential for their integration into sustainable building systems as an alternative to conventional insulation solutions. |
| 4-7 | 5/20/2026 11:00 | Sustainable Building Materials and Circular Economy | GFS 118 | 302 | Won Duk Suh, Jihee Nam and Sumin Kim | Yonsei University | Aging of indoor finishing materials under long-term temperature exposure: Focus on surface degradation and chemical oxidation | Accelerated experiment Indoor finishing material Surface oxidation Building material aging Degradation | The aging of building materials leads to material damage, reduced thermal performance and energy efficiency, and increased economic burdens due to replacement. While studies have investigated the degradation of insulation materials and paints, limited research has focused on the aging of indoor finishing materials. The primary factors influencing the aging of indoor building materials are temperature, humidity, and UV exposure; among these, indoor finishing materials are most affected by temperature. Therefore, study conducted accelerated experiments to analyze the long-term temperature-induced aging of indoor finishing materials. Using the Arrhenius equation, the experimental temperature conditions were set to replicate the equivalent of 5 and 10 years of natural aging within shortened exposure periods. The selected materials were artboard, profile, tex, and wood, which are commonly used as indoor finishing materials. Microstructural analysis of the aged specimens revealed the formation of cracks and overall surface deterioration. Quantitative evaluations of oxidation, based on elemental composition and carbonyl index, indicated an increase in both O/C ratios and carbonyl indices with longer exposure times. After the equivalent of 10 years of aging, the O/C ratios of artboard, profile, tex, and wood increased by 20.52%, 11.83%, 32.77%, and 61.18%, respectively, compared with unaged specimens, and the carbonyl indices increased by 23.46%, 9.81%, 333.76%, and 78.24%, respectively. To assess the impact of surface degradation on thermal performance, the thermal conductivity of each material was measured. The results showed an increase in thermal conductivity for artboard and wood with extended aging, whereas tex exhibited a decrease owing to dehydration of its gypsum core. Overall, the findings confirm that longer periods of temperature exposure intensify both surface degradation and oxidation in indoor finishing materials, thereby verifying that thermal aging is a critical factor in their aging. Future studies should propose strategies to mitigate temperature-induced aging of indoor finishing materials. |
| 4-7 | 5/20/2026 11:00 | Sustainable Building Materials and Circular Economy | GFS 118 | 326 | Jae Hyuck Jung, Young Uk Kim and Sumin Kim | Yonsei University | Thermal performance of lightweight concrete with a novel aggregate from cement-coated recycled polyurethane foam impregnated with phase change material | Lightweight concrete Phase change material (PCM) Polyurethane foam Thermal energy storage Recycled aggregate | The trend towards high-rise buildings has increased structural self-weight, escalating the demand for lightweight aggregates. Concurrently, improving building energy efficiency and ensuring sustainability have become critical challenges, highlighting the importance of technologies like phase-change materials (PCM) and waste recycling. To address these complex demands, this study proposes a novel multifunctional aggregate based on recycled polyurethane foam (PUF) that possesses both lightweight properties and thermal energy storage performance. The aggregate was fabricated by impregnating porous PUF with PCM, followed by a cement paste coating primarily to prevent PCM leakage and secondarily to enhance the interfacial bond with the surrounding cement matrix. Concrete specimens were prepared by replacing conventional fine aggregate with the developed aggregates at various volume fractions. To evaluate their performance, the mechanical properties of density and compressive strength were measured, and the thermal properties of thermal conductivity, latent heat storage capacity via differential scanning calorimetry (DSC), and dynamic heat transfer behavior were assessed. As a result, the cement paste coating was found to effectively mitigate the strength reduction associated with using polymer aggregates. The concrete incorporating the coated, PCM-impregnated aggregate showed a clear trend of decreasing thermal conductivity and significantly increasing latent heat storage capacity as the replacement ratio increased. Dynamic heat transfer tests confirmed a distinct thermal time lag, indicating the aggregate's effectiveness in buffering indoor temperature fluctuations. In conclusion, this study validates the use of recycled polyurethane foam as a high-performance carrier for PCM and presents a promising multifunctional aggregate for non-structural applications where both weight reduction and improved thermal comfort are required. |
| 4-7 | 5/20/2026 11:00 | Sustainable Building Materials and Circular Economy | GFS 118 | 421 | Najah Majouri, Mohamed El Mankibi and Jalila Sghaier | ENIM / LRTTPI; ENTPE / LTDS | Sustainable Fired Clay Composites with Root Palm and Diss Fibers for Energy-Efficient and Healthy Indoor Environments | Thermal Performance Fired Clay Composites Natural Fibers Sustainable Construction IAQ | This work presents a low-impact building material designed for hot arid climates, combining traditional fired clay with natural fibers derived from root palm and Diss plants native to southern Tunisia. The objective is to enhance thermal performance while promoting indoor environmental quality (IEQ). Clay mixtures containing 4% fiber content (by weight) were fabricated and tested for thermal conductivity, mechanical strength, bulk density, and water absorption. Results show that incorporating 4% Diss fibers reduced thermal conductivity to 0.281 W/m·K, while 4% root palm fibers reduced it to 0.352 W/m·K, offering notable insulation gains. Mechanical performance of the root palm fibers reaches 3.2 MPa in compressive strength. Hygric properties improved through reduced porosity and increased vapor permeability, supporting effective moisture buffering and potentially reducing risks of dampness and mold key factors for healthy indoor air. By utilizing locally available agricultural residues, these composites offer a climate-responsive, resource-efficient alternative to conventional masonry. The findings indicate strong potential for use in passive design strategies that simultaneously lower energy demand, regulate indoor humidity, and improve occupant well-being. |
| 4-7 | 5/20/2026 11:00 | Sustainable Building Materials and Circular Economy | GFS 118 | 536 | Tannaz Afshar Bakeshloo, Azadeh Sawyer and Joshua Lee | Carnegie Mellon University | Life Cycle Assessment of Building Deconstruction: Insights from Ten Projects | CircularEconomy SustainableBuildingMaterials LCA EmbodiedCarbon | In 2018, the United States generated more than 600 million tons of construction and demolition (C&D) waste, of which 143 million tons were landfilled. Demolition alone accounted for 94% of this total. In Pittsburgh, nearly 1,700 condemned properties are slated for removal, representing a substantial source of future waste. While the U.S. Environmental Protection Agency estimates that 90-95% of C&D waste could be recycled or reused, demolition practices rarely realize this potential. Deconstruction–carefully dismantling buildings for material recovery–offers a pathway to reduce landfill waste, conserve resources, and lower embodied carbon. Although life cycle assessments (LCA) have been applied to deconstruction, most focus on single projects or specific materials, limiting their broader relevance. To address this gap, we conducted a standardized LCA (ISO 14040/44) study on ten documented deconstruction projects using publicly available data. Three scenarios–standard, good, and best practice– were modeled with varying salvage rates to quantify material recovery and associated greenhouse gas emissions reductions. A sensitivity analysis of transport distance was also included to test the influence of transportation distance and to strengthen decision-making insights. The results demonstrate that deconstruction can avoid substantial CO2 emissions by reducing demand for virgin resources and diverting waste from landfills. Beyond environmental benefits, salvaged materials expand access to affordable, low-carbon building supplies and support healthier communities. By comparing the results across multiple cases and contexts, this study provides robust evidence for decision-makers, municipalities, and designers on how deconstruction can accelerate circular economy transitions and sustainable material strategies worldwide. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 570 | [Sponsor Team: ERC] Chan Hyeok Kang, Bo Kyung Jung, Tae Kyu Lee, Young Cheol Kwon, and Chang Ho Choi | EnergyX Inc.; Halla University; Kwangwoon University | Automated IFC Generation and Machine Learning-Based λ- Correction for Embodied Carbon Estimation of Buildings | Building Attributes Industry Foundation Classes Machine Learning Embodied Carbon Life Cycle Assessment | This study proposes a practical framework for estimating embodied carbon in buildings by integrating automated generation of Industry Foundation Classes (IFC) models with λ-correction techniques. Six minimal building attributes—gross floor area, number of floors, floor height, structural type, year of completion, and building use—were used to automatically generate simplified IFC models. Preset values for material thickness, density, and surcharge rates were applied, and Environmental Product Declaration (EPD) data were linked to calculate baseline emissions. The baseline IFC results, however, accounted for only 5–20% of actual embodied carbon, confirming systematic underestimation. To address this limitation, three correction methods were evaluated: global scaling with an average λ, cohort-based correction using K-nearest neighbors, and machine learning regression with Light Gradient Boosting Machine (LightGBM). A dataset of 304 buildings, including 260 for training and 44 for testing, was used for validation. Results showed that scaling and cohort approaches provided limited accuracy, while the machine learning model achieved the best performance (R²=0.803, MAPE=23.3%). These findings demonstrate that even with minimal inputs, reliable embodied carbon estimation is feasible for existing buildings lacking design documents. The proposed framework supports BIM–LCA integration and contributes to data-driven strategies for carbon-neutral building design and retrofitting. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 19 | Jong-Il Bang and Minki Sung | Department of Architectural Engineering, Sejong University | Disinfection Effectiveness of UR-UVGI for Airborne Bacteria Based on Equivalent Air Change Rate in a Multi-bed Patient Room | Upper-Room Ultraviolet Germicidal Irradiation Multi-bed Patient Room Airborne Bacteria Equivalent Air Change per Hour Disinfection Effectiveness | The prevention of airborne infectious disease transmission in indoor spaces is closely linked to maintaining healthy environments and indoor air quality (IAQ) for occupants. In particular, multi-bed hospital rooms require special attention, as they present higher risks of cross-contamination through bioaerosol dispersion. Ultraviolet Germicidal Irradiation (UVGI) has been recognized as an effective method for microbial inactivation, and its application in healthcare settings offers potential for both infection control and IAQ management. This study evaluates the disinfection performance of Upper-Room UVGI systems in a four-bed patient room mock-up. Bioaerosols were released from a 6-jet nebulizer at one bed to simulate a localized source. Airborne bacteria were sampled at three other beds (representing patient breathing zones) and at the terminal of the mechanical ventilation system (AHU). Experiments were conducted under two ventilation rates (2 and 6 ACH) and three UR-UVGI operational conditions (off, one system on, two systems on). To quantify the UR-UVGI performance, the equivalent air change rate (eACH) was calculated based on the decay of airborne bacterial concentrations over time. In the AHU terminal, the eACH under UV off conditions was found to be higher than the set ventilation rate, with values of 7.35/h (set 6 ACH) and 4.85/h (set 2 ACH). UR-UVGI operation increased eACH by approximately 1/h at the AHU. In the patient room, UR-UVGI operation led to more significant eACH increases. For the 6 ACH condition, eACH rose from 6.3/h (UV off) to 8.5–9.0/h (UV on), and for the 2 ACH condition, from 3.7/h to 5.4–5.5/h. These results confirm the disinfection effect of UR-UVGI within the room; however, discrepancies at the AHU terminal suggest potential influences from surface deposition and duct-related losses. Additionally, variations in eACH were observed depending on the sampling and UR-UVGI locations, suggesting that airflow distribution and environmental factors should be considered. This highlights the need to assess local ventilation and infection risks near each patient. This study suggests that eACH estimation based on airborne bacterial decay is a valid method for evaluating UR-UVGI effectiveness and can be improved further by accounting for bioaerosol behavior and airflow characteristics. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 27 | Jaekyoung Kim, Donghyun Koo, Taeyoon Kim, Dasom Hur and Seungkwon Jung | Formerly with Gangneung-Wonju National University; Infra Disaser Navigation Agency; International Center for Urban Hydroinformatics Research & Innovation; Konkuk University; Pukyong National University | Development and Application of a Spatiotemporal Validation Method for CFD-based Analysis of Urban Heat Island and Thermal Comfort | CFD Thermal Comfort UHI Spatiotemporal Validation LST | This study presents the development and application of a spatiotemporal validation methodology for computational fluid dynamics (CFD) models used in analyzing urban heat island (UHI) effects and thermal comfort, particularly in the context of climate change adaptation. As extreme weather events become more frequent, there is growing demand for accurate high-resolution simulation models to assess urban heat risk. CFD modeling has emerged as a widely adopted approach to analyze UHI phenomena; however, most prior validation efforts have relied solely on point-based, time-series meteorological observations. While such methods can confirm temporal trends at specific locations, they fall short in evaluating spatial consistency and performance across broader urban areas. To address this gap, this study proposes a novel spatiotemporal validation framework that integrates satellite-derived land surface temperature (LST) data, artificial intelligence-based mapping, and CFD simulation outputs. This method was applied to Gwacheon City, South Korea, covering a 2 km x 2 km urban area. The analysis focused on August 19, 2024 - a day with clear sky conditions and reliable satellite thermal imagery. To ensure consistency in spatial resolution, the domain was discretized into 4,489 grid cells at a 30-meter resolution for both CFD and Landsat-based data. Results indicate an R2 of approximately 0.73 between the CFD-simulated surface temperatures and satellite-derived LST values, demonstrating the feasibility of high-resolution spatial validation over a large urban domain. Additionally, an ensemble-based approach was developed to simultaneously evaluate spatiotemporal agreement, further enhancing the robustness of the validation process. This method strengthens the reliability of CFD models and offers a scalable basis for evaluating various climate adaptation strategies to support evidence-based urban planning. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 46 | Chun Han Li | Department of ERAC Engineering, National Kaohsiung University of Science and Technology | Evaluation of Membrane-Based Dehumidification Systems: Pressure Permeance of Dry Air in Commercial and Composite Membranes | Membrane dehumidification Dry-air permeance Energy efficiency Indoor air quality HVAC membranes | Air conditioning typically represents 40% to 50% of a building’s overall energy consumption, making it a significant area to target for energy efficiency improvements. As a result, finding ways to reduce the energy use of air conditioning systems has emerged as a critical challenge in the built environment. In response, researchers have recently focused on developing advanced technologies that allow for the independent control of temperature and humidity, which is essential for enhancing occupant comfort and improving indoor air quality. Among these innovations, membrane-based dehumidification has garnered considerable attention due to its potential for passive, energy-efficient moisture control. An effective dehumidification membrane should possess low permeance to dry air and high permeance to water vapor, allowing selective mass transfer. Measuring dry air permeance is essential to evaluate the membrane’s gas separation capability and predict its performance in practical systems. If dry air permeance is too high, excessive air from the supply side may leak to the permeate side, reducing airflow delivery and increasing operational demands. To offset this, more supply air would be needed, increasing fan power, equipment sizing, and energy consumption. This study evaluated the pressure permeance of commercial Nafion 212, Nafion 117, and a custom-made Carboxyl PI composite membrane under controlled vacuum recovery conditions. The findings indicated that the pressure recovery rates followed the order Nafion 212 > Nafion 117 > Carboxyl PI, with all membranes exhibiting acceptable gas barrier performance. These results support the application of composite membranes in energy-efficient HVAC systems and highlight the importance of dry air barrier properties in membrane design. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 52 | Jaekyoung Kim, Donghyun Koo, Taeyoon Kim, Samuel Park and Soonchul Kwon | Formerly with Gangneung-Wonju National University; Gangneung-Wonju National University; Korea Socio-Hydrology Institute; Pukyong National University; Pusan National University | Development of a predictive Model for Urban Cooling Blue Infrastructure using Integrated CFD and U-Net CNN | Urban Cooling Blue Infrastructure Computational Fluid Dynamics Cooling Fog Attention U-Net Urban Heat Island Mitigation | As urban heat island (UHI) effects intensify in densely populated cities, the need for effective and scalable climate adaptation technologies is becoming increasingly urgent. This study proposes a predictive decision-support framework that integrates Computational Fluid Dynamics (CFD) with deep learning-based U-Net Convolutional Neural Networks (CNN) to evaluate and forecast the effectiveness of urban blue infrastructure, specifically cooling fog systems. The research was conducted in Gwacheon, South Korea, where a real-scale cooling fog system was installed and analyzed under various environmental scenarios. Air temperatures ranging from 25°C to 35°C, relative humidity levels between 50% and 90%, one wind directions, and wind speeds were simulated using CFD. Results demonstrated a linear increase in cooling performance with rising ambient temperatures, while higher wind speeds significantly reduced the cooling fog’s effectiveness due to mist dispersion. The CFD-generated high-resolution surface temperature data were used to train both standard U-Net and Attention U-Net models. The prediction accuracy achieved was notably high, with MAE = 0.32 and R² = 0.93 for the U-Net model, and MAE = 0.29 and R² = 0.95 for the Attention U-Net model. These models allow for rapid evaluation of cooling interventions in near real-time, providing decision-makers with a powerful tool to assess the necessity and performance of urban climate adaptation measures under varying microclimatic conditions. The study highlights the potential of integrating CFD and AI for data-driven, climate-resilient urban planning. Cooling fog systems are evaluated as an effective urban cooling strategy that can be actively managed and optimized using the proposed AI-CFD hybrid framework. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 53 | Suji Choi and Jaehun Jo | Inha university | Operational Performance Indicators Based on Temporal Energy Use Patterns for Enhancing EUI | Operation management indicators Energy use intensity (EUI) Temporal Energy Use Patterns | Energy performance evaluation of existing buildings is commonly based on annual energy consumption or Energy Use Intensity (EUI). While EUI effectively represents the magnitude of energy use, it has limitations in capturing differences in operational and management performance. Detailed equipment-level or control data required for operational assessment are rarely available for most existing buildings, necessitating alternative approaches based on publicly accessible data. This study proposes a set of supplementary indicators for the relative diagnosis of operational and management performance in existing residential apartment buildings using publicly available electricity consumption data in Korea. Instead of focusing on absolute energy use levels, the proposed approach analyzes temporal energy use patterns to infer operational characteristics. Three indicators are introduced: the Operational Stability Index (OSI), which evaluates monthly consumption variability; the Seasonal Suitability Indicator (SSI), which assesses the appropriateness of seasonal operation; and the Abnormal Signal Index (ASI), which quantifies the frequency of statistically significant anomalies in hourly energy use. These indicators were applied to government-leased apartment buildings where data availability was limited. The results show that buildings with similar EUI values can exhibit different levels of operational stability and seasonal consistency. While ASI values exhibited limited variation among the analyzed buildings, this finding suggests operational homogeneity rather than low indicator effectiveness. The proposed indicators are not absolute performance metrics, but rather diagnostic tools that complement conventional EUI-based evaluations. By revealing temporal usage patterns and variability that are not captured by aggregate energy indicators, the framework provides foundational information for relatively identifying buildings with atypical or potentially inefficient operational behavior under current public data constraints. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 56 | Katalin Fülep, Claudia Kopic and Martin Kriegel | Technical University of Berlin | Balancing Infection Risk and Energy Consumption in Hospitals: A Data-Driven Ventilation Strategy | Infection risk Energy efficiency Hospital setting Digital twin Sensor network | Healthcare-associated infections (HAIs) are infections that patients acquire within 48 to 72 hours of hospital admission, which were not present before their arrival. According to the Global report on infection prevention and control (2022) published by the WHO, seven patients out of 100 will acquire at least one HAI during their hospital stay in high-income countries. One out of 10 affected patients will die from their HAI. Maintaining high indoor air quality (IAQ) in hospitals is crucial to protect patients, healthcare workers and visitors from nosocomial infections. Main strategies for maintaining IAQ include ventilation, humidity control, and cooling. Yet, these processes are highly energy intensive, where a hospital bed in Germany can consume as much energy as up to four average households, creating a challenge in balancing infection risk reduction with energy efficiency in hospital settings. This study proposes a method for the assessment of infection risk and energy efficiency simultanously. Furthermore, it investigates how infection risk control and energy efficiency can be jointly addressed by integrating four components: (1) a real-time IAQ sensor network in a hospital ward, (2) a digital building energy model predicting IAQ and energy use, (3) an airborne infection risk model embedded in the simulation framework, and (4) an initial intervention analysis targeting reduced energy consumption while maintaining infection risk at baseline levels. The study was conducted in an intensive care unit in Germany using sensor data collected from January to September 2025 and found that patient-room CO2 levels remained close to outdoor concentrations, indicating very high air change rates and associated ventilation energy demand. To explore an optimization potential, a scenario analysis is evaluated, replacing constant ventilation with demand-controlled ventilation (DCV), showing that DCV can markedly reduce energy use while keeping IAQ within standard limits and dynamically increasing ventilation where initial measurements indicate suboptimal air quality. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 57 | Ali Moazzeni Khorasgani , Ghazal Asadi Eskandar | Architectural Instructor at South Dakota State University; Assistant Professor of Architecture at South Dakota State University | Sustainable Mycéliums Composites for Building Construction | Mycelium bricks sustainable construction bio-based materials | In response to the urgent need for sustainable construction practices, this research explores the potential of mycelium-based bricks as an eco-friendly and regenerative alternative to conventional building materials. Mycelium, the root-like structure of fungi, has emerged as a promising biomaterial due to its rapid growth, biodegradability, and ability to bind with agricultural waste to form lightweight yet structurally viable composites. This project focuses on the development, testing, and architectural application of mycelium-based bricks, using locally available organic waste and environmentally conscious fabrication processes. The research employs an interdisciplinary methodology that integrates experimental material science, architectural design, and performance engineering. The process begins with the cultivation of mycelium in controlled environments, combining it with agricultural byproducts to produce testable brick units. These units undergo rigorous structural and thermal analysis to evaluate their load-bearing capacity, insulation properties, fire resistance, and environmental durability. In parallel, the project explores innovative interlocking systems that improve construction efficiency while reducing reliance on adhesives and mechanical fasteners. To demonstrate real-world applicability, a small-scale architectural prototype will be constructed using the developed mycelium bricks. This proof-of-concept structure will be used as a platform to assess performance under realistic environmental conditions and to engage stakeholders in sustainable design, including architects, engineers, researchers, and material manufacturers. Furthermore, the project includes public outreach components such as workshops, seminars, and exhibitions, aimed at promoting awareness of bio-based materials and fostering dialogue on low-carbon architectural solutions. By advancing the scientific understanding and architectural potential of mycelium-based construction materials, this research contributes to the global movement toward climate-resilient, circular, and regenerative design. It offers an innovative pathway to reduce the ecological footprint of the built environment and supports the transition to more sustainable urban development practices. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 58 | Milad Jafari and Ehsan Mousavi | Associate Professor and Endowed Chair, Nieri Department of Construction and Real Estate Development, Clemson University; Nieri Family Department of Construction and Real Estate Development, Clemson University | Data-driven approach for studying MRI units’ energy consumption | MRI Electrical Load Hospitals Probability Energy Management | Understanding magnetic resonance imaging (MRI) machines' operational patterns and energy usage is critical for optimizing electrical infrastructure, improving energy efficiency, and ensuring reliable performance in healthcare facilities. Using energy consumption data, a data-driven framework was applied to analyze MRI machines' energy profile. Energy consumption data from 12 MRI machines were collected at one-minute intervals from various healthcare facilities across the United States at different periods. Inherently, these data included a few phases, such as hibernation and active scanning. MRI events were detected by a computer code based on the deviation from background loads. Energy and duration distributions of MRI events were reported. To evaluate the electrical demands of each MRI machine under realistic operating conditions, momentary load data, the peak power drawn by a machine or subsystem over a short duration, were extracted from manufacturer-provided cutsheets. A novel parameter called the probability of exceedance (PoE) for passing the momentary load was defined and calculated for the operation of one to four MRI machines. It was shown that the electrical design criteria can be reduced by about 5% for two concurrent MRI machines, and by more than 20% when three or four machines operate simultaneously. In contrast with Montecarlo method, the proposed approach is more precise and accounts for all feasible real-world scenarios. The current study's findings provide insights into machine usage patterns, support the foundation for electrical load demands prediction, and contribute to optimizing facility energy management strategies in healthcare facilities. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 77 | Chih-Hao Chen | Industrial Technology Research Institute | New Ionic Liquid for Liquid Desiccant Air Conditioning system | liquid desiccant air-conditioning Ionic liquid Low regeneration temperature | Independent temperature and humidity control technology has been demonstrated to reduce energy consumption by 10–30% in a high-temperature and high-humidity environment. Among the available solutions, liquid desiccant air-conditioning (LDAC) systems are recognized for their high energy efficiency. Beyond dehumidification, LDAC systems can also sterilize and purify the air, making them a promising candidate for next-generation air-conditioning applications, particularly in climates where both temperature and humidity control are essential for comfort and indoor air quality. Despite these advantages, the practical adoption of LDAC systems has been constrained by the properties of traditional absorbents. Lithium chloride (LiCl), the most common liquid desiccant, is effective at moisture removal but exhibits strong corrosiveness toward metals. This characteristic increases maintenance requirements, limits material compatibility, and restricts widespread application. Ionic liquids, a new class of absorbents, present a viable alternative to conventional salt-based desiccants. They are non-corrosive to metals, possess high chemical stability, and can be regenerated at low temperatures. These properties reduce system corrosion risks, lower operating costs, and enable greater flexibility in heat source utilization, including the potential use of low-grade waste heat or renewable thermal energy. In this study, a small-scale LDAC system with an air-handling capacity of 300 CMH was constructed to evaluate the performance of a newly developed ionic liquid. Experimental results indicated that the ionic liquid achieved dehumidification performance comparable to that of LiCl, while eliminating the issue of metal corrosion. Given these findings, ionic liquids can effectively replace traditional absorbents, thereby facilitating the broader adoption of independent temperature and humidity control technology and enabling substantial energy savings in air-conditioning systems. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 112 | Maciej Danielak and Patrick Warzecha | Kampmann GmbH & Co KG | Natural Convection Cooling for Indoor Thermal Regulation in Buildings | HVAC systems cooling indoor comfort natural convection passive cooling | Natural processes offer an effective means of regulating a building’s indoor environment, providing both hygienic ventilation and thermal conditioning while reducing primary energy use. Unlike mechanically driven systems—which require electricity and incorporate complex components such as fans—natural convection relies on buoyancy forces generated by air density differences, enabling passive air movement. Although mechanical convection remains the prevailing approach for cooling, practical evaluations comparing it with natural convection are scarce, and documented real-world applications are limited. Moreover, existing studies tend to focus on temperature distribution alone, neglecting broader aspects of indoor environmental quality. This research addresses these gaps by analyzing the vertical and horizontal distribution of indoor parameters in a building hall that employs both gravity-based and mechanically forced convection cooling. The results contribute applied knowledge for the design of low-carbon buildings that integrate energy efficiency with occupant comfort. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 142 | Jinkyun Cho, Jongwoon Song, Wonseok Oh, Sangwoo Byun, Jihyuk Ahn and Haram Kim | E-SOLTEC Co., Ltd; Hanbat National University | Engineering resilient ventilation systems for rapid-deployment medical isolation units | Negative pressure isolation room. Ventilation. Infection control. Tracer gas test. CFD. | Infectious disease outbreaks, such as COVID-19, have emphasized the need for rapidly deployable isolation facilities that ensure infection control and protect healthcare workers. This study presents the design and performance evaluation of a modular negative pressure isolation room (MNPIR) for emergency use. A full-scale prototype was tested using SF₆ tracer gas, and results were compared with computational fluid dynamics (CFD) simulations. Airflow patterns, contaminant removal, and pressure differentials were analyzed at six sampling points. CFD results closely matched field data, with concentration deviations typically within ±10%. The ventilation system successfully maintained negative pressure and minimized cross-contamination risks. These findings validate the proposed system as a practical solution for mobile isolation and highlight its potential application in future public health emergencies involving airborne transmission. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 151 | Jyun-De Liang and Cheng-Kai Hung | National Sun Yat-sen University | Design and Study of a Vapor Compression Cycle Household Dehumidifier Using Ionic Liquid Solution | Ionic Liquid Household Dehumidifier Energy-efficient Dehumidification Energy Factor | Taiwan is located in a subtropical climate zone with high ambient humidity throughout the year; consequently, dehumidifiers are widely used in both residential and commercial buildings. However, the performance of conventional dehumidifiers is often limited under low-temperature conditions, leading to reduced efficiency and, in some cases, an increased risk of frost formation. In addition, in recent years, heightened public awareness of indoor air quality has emerged due to the impacts of seasonal influenza and the COVID-19 pandemic. To address these challenges, this study proposes a novel vapor compression cycle household dehumidifier integrated with an ionic liquid solution, which combines absorption and condensation dehumidification mechanisms to enhance overall system performance. This hybrid approach effectively mitigates the performance degradation commonly observed in conventional dehumidifiers under fluctuating ambient conditions. Experimental results demonstrate that the proposed system can operate stably under four typical climatic conditions representative of Taiwan, confirming its technical feasibility. Compared to a conventional dehumidifier, the proposed system achieves an improvement in the energy factor of approximately 17–48%. The system exhibits high operational flexibility and is capable of effectively regulating indoor humidity across a wide range of environmental conditions. Furthermore, the ionic liquid employed in the system exhibits antibacterial and air purification properties, providing dual benefits of humidity control and indoor air quality enhancement. These characteristics make the proposed system particularly suitable for offices, hospitals, clinics, and classrooms, providing tangible benefits in the post-pandemic era and during periods of influenza outbreaks. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 188 | Yan Lu, Xinyi Zhang, Soroush Neyestani, Ling Jin, Lu Zhang, Rima Habre and Jiachen Zhang | Department of Civil and Environmental Engineering, Viterbi School of Engineering, University of Southern California; Energy Analysis and Environmental Impacts Division, Lawrence Berkeley National Laboratory; Keck School of Medicine, University of Southern California | Assessing Indoor Versus Outdoor PM2.5 Concentrations During the 2025 Los Angeles Fires Using the PurpleAir Sensor Network | PurpleAir data indoor air quality wildland–urban–interface (WUI) fire PM2.5 2025 Los Angeles Fires low-cost sensors | In January 2025, a series of fast-moving wildland-urban-interface (WUI) fires swept through the Los Angeles (LA) metropolitan area, causing severe air pollution. While the impacts of WUI fires on outdoor air quality have been extensively studied, indoor exposure remains less understood, despite most people sheltering indoors during WUI fires. This study investigates the spatial and temporal patterns of indoor and outdoor PM2.5 concentrations across the South Coast Air Basin, with a focus on Los Angeles County during the LA fires. Using high-resolution data from co-located indoor and outdoor PurpleAir sensors, we analyze hourly PM2.5 levels and indoor/outdoor ratios. Outdoor PM2.5 concentrations spiked sharply during the fires, reaching unhealthy levels. Indoor concentrations increased concurrently but to a lesser extent, reflecting the partial shielding effect of indoor environments from outdoor air pollution. The mean daily indoor/outdoor PM2.5 ratio was 0.50 during LA fire days, lower than that ratio (0.81) during non-fire days. Indoor/outdoor PM2.5 ratios across sensors showed a wide distribution, reflecting differences in building characteristics and occupant behavior, such as the use of air purifiers. These findings emphasize the need for guidance and interventions to reduce indoor PM2.5 exposure and protect public health during extreme WUI fire events. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 200 | Yi Chun Chu, Jia Kun Chen, Yan Cheng Chiang and Tzu I Tseng | National Applied Research Laboratories; National Taiwan University | Impact of Inlet Flaps on Ammonia Distribution in a Water-Pad Layer House: A Case Study in Yunlin, Taiwan | Indoor air quality Closed-type water-pad cooling poultry house Ammonia distribution Occupational health Porous media model | To reduce the risks of extreme climate and avian influenza to laying hen houses, the Taiwanese government has vigorously promoted the reconstruction of open-type laying hen houses into closed-type water-pad cooling laying hen houses. This has led to problems for laying hen houses, such as a high humid environment that is more conducive to ammonia generation, and the accumulation of pollutants like ammonia and particulates indoors, which negatively impacts worker health and laying hen productivity. This study used Computational Fluid Dynamics (CFD) to simulate the effect of two geometric configurations—with or without a guide baffle at the air inlet—on ammonia distribution in the worker walkways' breathing zones and the laying hen activity areas. This study constructed a Porous Media model of the chicken cages through a numerical wind tunnel, applying it to the overall simulation of ammonia distribution in the laying hen house. Ammonia sampling was simulated at 6 worker breathing zones (H = 1.5 m) in each of the two rows of walkways, and at 4 laying hen activity areas in each of the two rows of chicken cages. The results of this study show that adding a baffle at the air inlet significantly affects the ammonia distribution inside the laying hen house. When the rear fans were on, the average ammonia concentration in the overall worker walkways' breathing zones for the "with baffle" model was 2.6 ppm, which was higher than the 1.8 ppm of the "without baffle" model (an increase of 31%). In the laying hen activity areas, the average ammonia concentrations were similar between the models. However, while the "without baffle" model frequently exceeded 20 ppm (up to 27.1 ppm) at single-point simulation sampling points at the far end of the laying hen house, all simulation sampling points in the "with baffle" model were below 20 ppm. Adding a guide baffle at the air inlet of a closed-type evaporative cooling laying hen house increases worker exposure in the walkways can suppress the ammonia peaks in the terminal laying hen activity areas. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 234 | Shunsuke Fujitsubo, Yasuyuki Shiraishi, Yoshiaki Ushifusa and Masayuki Watanabe | Kyushu Institute of Technology; The University of Kitakyushu | Optimization of Annual Operation of a PV-HPWH-BT Cooperative System in an All-Electric House to Achieve Maximum Electricity Self-Sufficiency | optimal control MILP carbon neutral PV–HPWH–BT coordinated system self-sufficiency | In recent years, the introduction of renewable energy in Japan has been increasing to promote carbon neutrality and reduce greenhouse gas emissions. Among them, the spread of photovoltaic systems (PV) has been remarkable in the residential sector, as installation is relatively easy. However, since PV power generation fluctuates significantly depending on weather conditions and time of day, ensuring a stable and reliable electricity supply is extremely challenging. To address this issue, the combined use of distributed energy resources (DER) such as battery storage (BT) and heat pump water heaters (HPWH) has attracted attention. Furthermore, by coordinating and optimizing the operation of these resources, it is expected that electricity generated by PV can be utilized more effectively. Therefore, this study models an all-electric house equipped with PV, BT, and HPWH, and proposes an optimal operation method for a PV-HPWH-BT coordinated system with the objective of maximizing electricity self-sufficiency. The optimization method was formulated as a mixed-integer linear programming (MILP) problem and implemented in MATLAB. To evaluate the effectiveness of the proposed method, a case study in Japan was conducted and compared with the following four scenarios: (1) without DER control, (2) with rule-based control, (3) optimization with the objective of minimizing operating costs, and (4) optimization with the objective of maximizing electricity self-sufficiency. As a result, it was shown that rule-based control promotes effective utilization of PV generation and improves self-sufficiency. Furthermore, MILP-based optimization achieved improvements depending on the objective function, and optimization for maximizing self-sufficiency realized further enhancement of self-sufficiency. These findings demonstrate the effectiveness of operational strategies that emphasize reducing environmental impact and propose new guidelines for the realization of a decarbonized society. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 307 | Dong Yoon Park | Chonnam National University | Individual thermal comfort prediction using ensemble transfer learning and physiological signals under different physical characteristics | Thermal comfort Physiological signals Transfer learning Machine learning | Thermal comfort models often suffer from low accuracy at the individual level due to their reliance on population-based statistics and environmental factors. While physiological signals offer a personalized alternative, data collection across diverse demographics remains a significant challenge. This study proposes an ensemble transfer learning (TL) framework to predict individual thermal comfort by transferring knowledge between different gender groups. A hybrid model integrating 1D-convolutional neural networks (1D-CNN) for feature extraction and support vector machines (SVM) for classification was developed. The model was pre-trained on data from male subjects in their 30s (source domain) and fine-tuned for female subjects in their 20s (target domain) using a bagging-based ensemble strategy. The experimental results showed that the ensemble TL model outperformed other approaches, achieving a thermal comfort prediction accuracy of up to 97% for the female target group. This approach demonstrates that high-performance personalized thermal comfort models can be established even with limited data from specific demographic groups, providing a scalable solution for intelligent building energy management and occupant wellbeing. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 312 | Sung Won Cho, Ji Hyun Yoo, Seung Rim Lee, Yi Zhou Wang and Jun Seok Park | Hanyang University | Determining the Minimum Monitoring Period for Predicting Occupant behaviors related to manual control of Windows in Residential Buildings | Occupant behavior manual control of windows machine learning algorithms Residential Buildings | Occupant behaviors related to the manual control of indoor environmental systems, such as thermostats, windows, and air conditioners, play a critical role in influencing both energy consumption and indoor environmental quality. In residential buildings, occupants prefer manual control of windows for natural cross ventilation. These behaviors significantly affect both the indoor thermal environments and indoor air quality in their homes. Previous studies have demonstrated that machine learning models are more accurate in predicting occupant behavior than logistic regression models. Furthermore, it was found that the determinants of the behaviors are the seven indoor and outdoor parameters, including outdoor temperature, indoor temperature, humidity, and carbon dioxide. Accordingly, mechanical ventilation systems and HVAC systems installed in homes can be predictively controlled through the occupants’ behaviors. In this study, the effects of monitoring period on predicting occupants’ behaviors were analyzed using field monitored data for the application of occupant centric control of the ventilation and HVAC systems in home. The monitoring data sets gathered from sample homes, which were field monitored for more than six months, were used to evaluate how monitoring periods affect the predictions of occupant behaviors. Random Forest (RF) and k-Nearest Neighbors (KNN) algorithms were used to predict manual window control. The environmental variables, such as outdoor temperature, indoor temperature, indoor relative humidity, indoor CO2, outdoor PM10 and PM2.5, PMV, ΔT, and Window Operation Condition (WOC) were used as input features. The models were trained using datasets of one week, two weeks, and one month, respectively, and predicted window status for five randomly selected days. The predicted results were compared with the actual observed data, and model performance was assessed using precision, recall, F1-score, and accuracy. The results showed that that a minimum of one week of monitoring is required to accurately predict occupants' window-opening behavior in homes. These results can be applied to monitor occupants’ behavior for the occupant centric control of mechanical ventilation systems and HVAC systems in homes. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 339 | Ye-Bin Shin, Deuk-Won Kim, Wangje Lee, Jae-Won Jeong and Min-Hwi Kim | Hanyang University; Korea Institute of Energy Research | Comparative Analysis of PCM- and Water-Based Thermal Energy Storage Units in a Photovoltaic and Thermal System for Residential Applications | photovoltaic thermal systems phase change material thermal storage capacity | Photovoltaic thermal (PVT) systems, which may be incorporated into buildings, can generate both electricity and heat. When utilized in residential structures with limited space, the miniaturization of thermal energy storage (TES) units becomes crucial. This study compares the performance of a water-based TES tank with a PCM-based thermal storage unit that uses latent heat for energy storage, offering high energy storage density per unit volume. The study was conducted on a BIPVT system installed on the Korea Institute of Energy Research's KePSH-2 building. Two types of PCM-based thermal storage units, each with a storage capacity of 7.71 L, and a water-based TES tank with a capacity of 500 L, were installed in a real-world BIPVT system where the solar collection varied in real time. We observed the instantaneous changes in the charging rate from April 18 to June 30, 2025, over three months. The operational performance of the storage units, including the energy storage density, was evaluated by comparing the heat collected by the PVT modules and stored in the water heat transfer fluid versus the PCM-based units. The average solar collection by the PVT system was 16.4 kWh. The average energy storage densities were 102.5 kWh/m³ for PCM 1, 138.5 kWh/m³ for PCM 2, and 28.2 kWh/m³ for the water-based TES. This suggests that the PCM storage units can store more energy per unit volume than the water-based TES. However, the average charging rate was 0.5 kW for PCM 1, 0.6 kW for PCM 2, and 8.3 kW for the water-based TES, indicating that the water-based TES is 16.3 and 13.2 times greater than that of the PCM units, respectively. The average discharging rates for PCM 1 and PCM 2 were each 1 kW, while the rate for the water-based TES was 2.6 kW. This indicates that while PCM-based units can be miniaturized due to their high energy storage density in BIPVT systems, there is a need for improvement in their charging rate. The implementation of both TES and PCM storage units was analyzed to be an effective method for thermal energy storage in multi-family residential buildings with significant space limitations. Since the charging rate of PCM-based storage units is slow, an optimized design combining both TES and PCM units is necessary for practical application in residential buildings. Further research is needed to develop an integrated system that utilizes the high charging rate of the TES tank and the high energy storage density of the PCM, creating an optimal thermal storage solution for residential buildings. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 384 | Krzysztof Grygierek and Joanna Ferdyn-Grygierek | Silesian University of Technology | Impact of ventilation stacks on airflow in naturally ventilated buildings: simulation vs. measurements | natural ventilation stack effect gravity chimneys building simulation | Modeling of mass and energy flows in naturally ventilated buildings enables the prediction of indoor thermal conditions and the evaluation of ventilation performance under different operational scenarios. However, the accuracy of simulation results strongly depends on the quality of the airflow model, which must be validated against experimental data. The greatest discrepancies typically arise from difficulties in capturing rapidly changing outdoor conditions and unstable airflow patterns. Model validation is therefore essential, as it improves the reliability of predictions and provides a basis for optimizing ventilation strategies, reducing heat losses, and enhancing the overall energy efficiency of buildings. This study investigates a mixed-use office and educational space located on the second floor of a five-story building at the Silesian University of Technology, Poland. The rooms are naturally ventilated, with outdoor air entering through infiltration and being exhausted via grilles connected to vertical stack ventilation ducts. The building is of reinforced concrete frame construction with ceramic brick infill, and its envelope has been thermally retrofitted with insulation. Three simulation approaches were compared: (1) co-simulation between EnergyPlus and CONTAM, where mass flows are calculated in CONTAM and exchanged with EnergyPlus at every timestep, (2) the Airflow Network model in EnergyPlus, and (3) the simplified Leakage Area and Wind and Stack Open Area airflow model in EnergyPlus. The models were validated using measurements of CO2 concentration in room, airflow rates through the ventilation grille, and local meteorological data from the nearest weather station. Both calibration of input parameters and validation of simulation outcomes were carried out for each modeling approach. The results demonstrate that simplified infiltration models can provide acceptable agreement only under limited and highly specific conditions, while the Airflow Network model fails to realistically represent airflow in the presence of vertical ventilation chimneys. In contrast, the EnergyPlus–CONTAM co-simulation achieved good agreement with measurements across different window operating scenarios. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 385 | Krzysztof Grygierek, Joanna Ferdyn-Grygierek, Stanisław Kocik and Aleksandra Lipczynska | Silesian University of Technology | Assessment of solar radiation distribution in indoor spaces for local thermal comfort evaluation | shortwave solar radiation building performance simulation EnergyPlus Radiance thermal comfort | Shortwave solar radiation significantly influences local thermal comfort in indoor environments, particularly in spaces with large glazed areas. Although building performance simulation tools such as EnergyPlus accurately predict solar gains at the room and surface level, they do not provide information on the spatial distribution of solar radiation incident on the human body. Conversely, ray-tracing tools such as Radiance enable detailed spatial resolution of solar exposure but require high computational effort and complex model setup. This study proposes a hybrid methodology for estimating spatially resolved shortwave solar radiation incident on individual human body segments by combining standard EnergyPlus simulation outputs with geometric analysis. Beam solar radiation is computed using a mesh-based human body model that accounts for solar position, body orientation, surface normal vectors, and self-shading effects. Diffuse solar radiation transmitted through the window is redistributed to body segments using precomputed area view factors. The method was validated against detailed Radiance simulations employing climate-based sky models. A case study of a typical office room in a temperate Central and Eastern European climate with a southwest-facing window was analyzed. Four study cases included two distances of the human body from the window (0.5 m and 1.5 m) and two body orientations toward the window (facing the window or sideways to it). A simplified human body model divided into seven representative segments was adopted. The results show good agreement between the proposed approach and Radiance simulations. Beam solar radiation exhibits strong spatial non-uniformity and is predicted with high accuracy. For diffuse radiation, minor discrepancies were observed, mainly due to differences in sky anisotropy treatment, although high correlations were maintained across all cases. The proposed EnergyPlus-based approach provides a reliable and computationally efficient alternative for estimating local solar radiation exposure on the human body, enabling advanced occupant-level thermal comfort analyses and supporting the evaluation of solar-related discomfort and façade or shading design strategies. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 399 | Kotoha Shin, Yasuyuki Shiraishi, Yoshiaki Ushifusa and Masayuki Watanabe | Kyushu Institute of Technology; The University of Kitakyusyu | Optimization of Distributed Energy System Operation in All-Electric Districts with Electricity Sharing | optimal control MILP carbon neutral electricity sharing | In recent years, as renewable energy has been increasingly deployed in pursuit of a decarbonized society, photovoltaics (PV) have become particularly widespread in the residential sector owing to their ease of installation. However, because PV output fluctuates with solar irradiance, it is difficult to ensure a stable power supply with PV alone. It is therefore effective to configure a distributed energy system (DES) that combines PV with energy storage equipment such as battery (BT) and heat pump water heater (HPWH). In addition, electricity sharing among households has attracted attention as a means of maximizing the utilization of PV-generated electricity. Furthermore, comprehensive control of the operation of these systems is expected to improve the electricity self-sufficiency of individual households and the district as a whole, thereby reducing environmental impact. In this study, we consider a district model composed of multiple dwellings equipped with a DES integrating PV, HPWH, and BT, and introduce electricity sharing by numerical simulation while optimizing the operation schedules of the system. The target region is assumed to be Japan, and two optimization objectives are defined (1) minimization of primary energy consumption and (2) minimization of running cost and the corresponding results are compared. System optimization is performed using a mixed-integer linear programming (MILP) formulation. As a result, in scenario (1), the introduction of electricity sharing reduces weekly primary energy consumption by approximately 5%. In scenario (2), it is shown that the control outcomes, including how PV-generated electricity is utilized, change significantly depending on given conditions such as the selling price of exported electricity. These findings clarify both the potential of DES and electricity sharing to reduce environmental impact and the effectiveness and limitations of the proposed optimization method. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 429 | Jeongil Kim, Takashi Kurabuchi, Sihwan Lee and Hayato Kiyosuke | DAI-DAN Co., Ltd.; Tokyo University of Science; University of Hyogo | Experimental Evaluation of Particle-Based Tracers for Indoor Ventilation Performance Assessment | Age of air Tracer particles Indoor air quality | Reliable evaluation of ventilation performance and age of air is essential for improving indoor environmental quality and reducing airborne infection risks. Traditionally, tracer gas methods using CO2 have been employed, but these experiments require specialized equipment, are relatively costly, and cannot represent particle removal processes by devices such as air cleaners. As a potential alternative, this study experimentally investigates the applicability of aerosol particles as tracers for measuring ventilation and age of air in indoor environments. Experiments were conducted in both a controlled laboratory and field settings, where artificially generated droplets of different solution compositions were sprayed and their concentration decay was monitored with a particle counter. Several solutions, including tap water, calcium carbonate solution, and mixtures containing glycerin, were compared to identify suitable tracer properties. The influence of gravitational settling on indoor particle concentration and its impact on ventilation rate estimation were analyzed, and comparative measurements using CO2 gas as a reference tracer were also performed. The results highlight three main findings. First, particles containing glycerin and other impurities are effective for generating sufficiently high and stable tracer concentrations. Second, differences between gas- and particle-based experiments can be largely explained by gravitational settling, which becomes more significant with particle diameter. Third, focusing on particles in the 0.3–0.5µm size range yields ventilation and age of air values that correspond well with those obtained from CO2 experiments, while larger particles tend to result in measurement differences due to deposition losses. These results indicate that particle tracers can be applied as practical substitutes for gas tracers and also allow evaluation of equivalent ventilation performance of air-cleaning devices by considering particle removal efficiency. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 494 | Yi-Pin Lin, Tzu-Ling Huang, Chi-Ming Lai and Rong-Horng Chen | Department of Architecture and Interior Design, Cheng Shiu University, Taiwan; Department of Creative Design, National Yunlin University of Science and Technology, Taiwan; National Cheng Kung University; National Cheng Kung University, Taiwan | Numerical investigation of a PV-assisted hybrid ventilation strategy for monitor roofs | ventilation natural ventilation monitor roof photovoltaic | This study aims at improving the ventilation performance of a monitor roof by integrating renewable energy applications. Photovoltaic-powered fans are incorporated into the design, and Computational Fluid Dynamics (CFD) simulations are employed to systematically evaluate their impact on natural ventilation efficiency. The monitor roof is 1.2 m wide and 1.2 m high, with an eave overhang length of 0.3 m. Twenty inner fans are installed on the central axis of the horizontal opening of the monitor roof. The flow area of each inner fan is set to be 0.3 × 0.3 m or 0.6 × 0.6 m. The fan operates with outlet wind speeds of 0.5 m/s and 2 m/s. A power-law exponent of 0.143 is applied to represent the approaching wind profile over open terrain. The prescribed velocity range (0.01–3 m/s) corresponds to the reference wind speed at a height of 10 m. The results show that, under low wind speeds or no wind conditions (such as sweltering summer mornings or nights), the installation of inner fans on the monitor roof can enhance ventilation. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 509 | Soroush Samareh Abolhassani, Alimohammad Sedaghat, Mojtaba Parsaee, David J.Sailor and Sami G. Al-Ghamdi | KAUST Climate and Livability Initiative, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia; School of Architecture, Mississippi State University, Mississippi State, MS, USA; School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ, USA | Building and Census-Tract-Scale Validation of a Coupled Urban Energy–Microclimate Digital Twin (CityDigitalTwin): Mobile Traverse Observations and Utility-Billing Benchmarking | Urban Building Energy Modeling (UBEM) CityDigitalTwin microclimate validation utility-billing benchmarking | Urban Building Energy Modeling (UBEM) is increasingly used for planning in hot cities, yet validation commonly focuses on either building loads or microclimate, rarely both, and seldom at multiple spatial scales. Prior studies are often set in temperate climates, rely on fixed-station weather data, and provide limited, reproducible protocols for aggregating model outputs to utility service areas. This work addresses these gaps by validating CityDigitalTwin under hot-arid summer conditions (June–August) in Phoenix at two scales and across energy–microclimate domains. For 20 buildings, hourly simulations based on DOE/NREL archetypes are compared to Salt River Project (SRP) meters using CVRMSE and NMBE. At the census-tract scale, simulated loads are aggregated and benchmarked against tract-level SRP billing. The coupled microclimate is evaluated with repeated mobile traverses (air temperature, reported via RMSE/MAE, bias, and spatial correlation of along-route temperature gradients. To demonstrate modeled responsiveness without expanding scope, we apply enhanced glazing, heat-pump conversion, and urban greening and summarize directional impacts. CityDigitalTwin reproduces building loads and spatial thermal patterns with accuracy suitable for building- and tract-scale decision support; residuals align with occupancy-schedule uncertainty and vegetation/shading representation. The study contributes a dual-scale, dual-domain validation protocol with standardized metrics and alignment workflows, enabling consistent comparisons and future citywide applications. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 511 | Namchul Seong, Daeung Kim and Kyungmo Kang | Cheongju University; Daejin University | Energy Saving of HVAC System Using Integrated Machine Learning Algorithm (IMLA) | Integrated Machine Learning Algorithm(IMLA) HVAC system Energy Saving | Heating, Ventilation, and Air Conditioning (HVAC) systems account for a substantial portion of building energy consumption, making their efficient operation a critical issue for energy conservation and carbon reduction. Conventional HVAC control strategies are generally based on static rules or predefined schedules, which often fail to respond effectively to dynamically varying thermal loads, occupant behavior, and outdoor conditions. To overcome these limitations, this study proposes an Integrated Machine Learning Algorithm (IMLA) that unifies short-term load prediction and global optimization within a single HVAC control framework. The proposed IMLA combines an Artificial Neural Network (ANN) and a Genetic Algorithm (GA). The ANN is employed to predict cooling and heating loads at the next time step (t+1), providing anticipatory information on future thermal demand, while the GA determines optimal HVAC control variables by minimizing total energy consumption. By integrating predictive and optimization modules, the proposed framework enables proactive and coordinated control of air-side and water-side HVAC systems. The IMLA was applied to a Medium Office Reference Building, where the HVAC system was modeled as a variable air volume (VAV) air-side system coupled with a chilled-water-based plant. Its performance during the cooling period was evaluated and compared with conventional rule-based control and GA-based optimization without load prediction. Simulation results demonstrated that the proposed IMLA consistently outperformed the benchmark strategies. Compared with conventional control, the IMLA reduced fan energy consumption by approximately 13.4%, chiller energy by 8.0%, and pump energy by 7.0%. When total HVAC energy consumption was considered, the proposed approach achieved an overall energy reduction of approximately 8.2%, exceeding the performance of optimization-only control. These results indicate that incorporating short-term load prediction into the optimization process provides additional system-level energy savings by enabling more proactive and demand-responsive HVAC operation. The proposed IMLA offers a practical and extensible solution for improving HVAC energy efficiency under dynamic operating conditions and shows strong potential for application to various HVAC system configurations and seasonal operating modes. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 550 | Zhuoying Lin, Yi Fang, Marcus Young, Qin Xia, Caleb Kwon, Catherine Banach, Haoran Zhao, Tim Tyner, Stephanie M. Holm, Anabelle Garza, Arlette Garcia-Ramirez, Briseida Vasquez, Debra Manzo Garcia, Jesus Rivera, Amy Dryden, John R. Balmes, Brett C. Singer and Suzanne E. Paulson | AEA Clean Energy; Central California Asthma Collaborative; Lawrence Berkeley National Laboratory; Stephanie Holm Consulting; UCLA; University of California, San Francisco | Measured indoor particulate matter, black carbon, and oxidative potential before and after replacing gas with induction electric cooking in homes with a child with asthma | CEVICA study Air Pollution Exposure Randomized Controlled Trial | Cooking is a major source of fine particulate matter (PM) in homes and evidence to date is inconclusive about the impact of cooking fuel on measures of residential PM exposure. The Cooking Energy and Ventilation Impacts on Children’s Asthma (CEVICA) study measured cooking frequency, range hood use, indoor air quality (IAQ) and respiratory health indicators of children with asthma living in homes with gas stoves in California’s San Joaquin Valley. Intensive measurements occurred over three 2-week intensive periods: at baseline and at the end of two consecutive 3-month study phases. Participants were randomly assigned to have their gas stoves replaced with electric induction at the start of Phase 1 or Phase 2. As part of the IAQ assessment, we collected particulate matter on Teflon filters using ultrasonic personal air samplers (UPAS). The filters were analyzed to quantify time-integrated PM₂.₅ mass concentration, black carbon (BC) oxidative potential (OP). OP was measured using the SLF-OH assay, an acellular chemical assay that quantifies production of OH radicals in simulated lung fluid (SLF). Across all comparisons, PM₂.₅ mass tended to be higher during gas cooking than induction electric cooking, although only one transition (Baseline to Phase 1) was statistically discernible at p<0.05. BC and mass normalized OP showed no measurable differences across stove types or across phases. These preliminary findings suggest that cooking fuel is less important than factors such as cooking style and frequency, food and oil type, kitchen ventilation use, and outdoor infiltration in determining indoor particle levels and oxidative potential. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 561 | Anders Bjork, Ella Tucker and Charlie Thornton | Thunderhead Engineering | Bridging New Air Cleaner Measurement Standards and Indoor Air Quality Simulation: An In-Progress Method in CONTAM | Indoor Air Quality CONTAM Air Cleaner contaminants Ultrafine Particulate | This paper describes an in-progress method to translate air cleaner byproduct emissions data from the 2025 standard testing procedure by ASTM International, developed with the United States National Institute of Standards and Technology (NIST), into contaminant source characterization in contaminant modeling software. Contaminant transport can be modeled with the NIST multi-zone modeling tool, CONTAM. Desired is a method such that air cleaner chemical and particle byproduct emission behaviors can be precisely represented in an indoor air quality (IAQ) analysis project file. Once in CONTAM, the transport and leakage of contaminants can be simulated within the context of the built environment. Homes, workplaces, and schools can be quickly modeled. Currently, CONTAM model contaminant characterization methods are not directly associated with expected byproduct emissions data from the Standard Test Method for Chemical Assessment of Air Cleaning Technologies. Additionally, it is challenging to model the transient concentrations of gases and particles without a chemistry and aerosol physics background. Thus, this paper aims to bridge the gap between expected measured data and available IAQ simulation. Building professionals who can appropriately model the byproduct emissions of air cleaners can efficiently design healthy environments and communicate risks to the public. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 569 | Hye-Gi Kim, Hye-Ry Shin, Han-Gyeong Chu, Doo-Sung Kim and Deuk-Woo Kim | Korea Institute of Civil Engineering and Building Technology; SQI Soft | Stepwise Address Matching Methodology for National-Scale Building Energy Database Integration | Data integration Stepwise address matching National building database Carbon neutrality Administrative data linkage | Achieving carbon neutrality in the building sector requires comprehensive, evidence-based policy making, yet building-related data remains fragmented across multiple government ministries in South Korea. With approximately 7.3 million buildings nationwide and small buildings (under 1,000㎡) comprising over 90% of the total stock, integrating these dispersed datasets is critical for inclusive energy management policies that have historically overlooked this majority segment. The DataNet project (2023-2026) aims to establish a national data framework by integrating 17 administrative datasets from various ministries including Land Infrastructure and Transport (MOLIT), Interior and Safety (MOIS), Education (MOE), Health and Welfare (MOHW), and Culture, Sports and Tourism (MCST). The project addresses Korea's unique challenge of dual address systems—land lot-based addresses and road name addresses—alongside complex meter-building relationships where single lots contain multiple buildings and meters rarely correspond one-to-one with registry entries. Currently in its third year, the project has successfully integrated 13 of the planned 17 datasets, achieving an average matching rate of 94.96%. We are employing a hierarchical matching methodology that combines code-based matching for datasets with standardized identifiers and text-based matching for those without. The National Building Energy Database (NBED) serves as the reference point, containing dual address codes for each building. The methodology includes comprehensive lot-building verification to capture all spatial relationships and systematic preprocessing that addresses temporal alignment, non-building consumption exclusion, and quality control through multi-dimensional anomaly flagging. The ongoing integration is enabling unprecedented nationwide analyses by linking building registry data, monthly energy consumption from 50 million meters, business permits, meteorological data, and facility-specific operational information. These achievements are establishing the foundation for evidence-based carbon neutrality policies and providing valuable methodological insights for similar national initiatives globally. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 628 | Saemi Shin and Joung Ryeul Sohn | Korea University | Measurement of Fine Particulate Matter Concentrations and Time-Series Outlier Analysis at a Korean Screen golf course | particulate matter screen golf course time-series outlier | In Korea, a significant number of public-use facilities that fall below the size standards or are not included in the managed facility group are outside the legal management network, and information on their concentration status and influencing factors is lacking. Screen golf courses are also unmanaged facilities in Korea. The PM-2.5 concentration in the screen golf course was confirmed to be 12.8±9.2 (2.5-18.9) μg/m3, with time-series outliers observed in four locations. Measures to prevent or recovery should be considered. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 629 | Joung Ryeul Sohn and Saemi Shin | Korea University | Comparative Analysis of Health Risks Associated with the Operation of Ventilation Systems in a School Kitchen | particulate matter school kitchen cooking fume | This study analyzed whether there was a difference in fine dust concentration depending on the operation of existing school kitchen ventilation equipment. The concentration of ultrafine dust was 38.9±8.8 (24.3~69.3) μg/m3 when the air purification equipment was not in operation, and 37.9±4.9 (27.9~74.8) μg/m3 when it was in operation. The difference in fine dust in school kitchens depending on the operation of the air purification equipment was significant, and the hazard level greatly exceeded the permissible level regardless of the operation of the air purification equipment. To reduce fine dust in kitchens and protect the health of food service cooks, school kitchen managers need to manage the installation and operation of air purification equipment in the kitchens appropriately. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 640 | Jieun Han, Jeong Hoon Lee, Yoonhee Lee, Minjung Kim, Dongryul Park and Hyungho Park | Air Science Lab, Eco Solution Company, LG Electronics | Real-time Personalized Comfort Control Algorithm utilizing User Location and Machine Learning-based PMV Prediction | Thermal comfort control PMV prediction Machine learning User location detection | This study proposes an automated comfort control algorithm that predicts the Predicted Mean Vote (PMV) in real-time and optimizes thermal comfort using only existing air conditioner operation data and radar-based user location information, without requiring additional environmental sensors or wearable devices. Based on data from 66 experimental cases collected in a residential environmental chamber, a linear regression model was developed to correlate air conditioner operating states with the local thermal environment of the occupant. The model predicted local temperature and air velocity with Root Mean Square Errors (RMSE) of 0.72°C and 0.067 m/s, respectively. The developed prediction model is utilized to estimate the occupant's thermal load in real-time, facilitating a multi-phase control logic consisting of 'Rapid cooling' and 'Comfort cooling’ modes. Environmental chamber experiments confirmed that the proposed algorithm significantly reduces the time required to reach the comfort zone (PMV ±0.5) and enhances occupant thermal satisfaction compared to conventional control methods. This approach presents a practical solution for smart buildings, simultaneously improving energy efficiency and occupant comfort by enabling cost-effective, personalized control. |
| 5-1 | 5/20/2026 13:30 | Poster Session | VHE Courtyard | 647 | Kuo-Hsiung Lin, Tzu-Jui Huang, Jyun-Hao Jhu and Hung-Lung Chiang | Fooyin University; National Yunlin University of Science and Technology | Assessment of Volatile Organic Compound Emissions from Liquid Cleaners and Personal Care Products | Consumer products VOCs Emission factors Ventilation strategies Health risk assessment | Consumer products represent a significant and growing source of volatile organic compounds (VOCs) in indoor environments, contributing to poor indoor air quality (IAQ) and potential health risks for occupants. This study investigates the VOC content, emission characteristics, and health implications of common consumer products in Taiwan, with a specific focus on two high-usage categories: liquid cleaners and personal care products. The total VOC content was determined using the gravimetric and gas chromatographic techniques specified in CARB Method 310, while dynamic emission behaviors were assessed using a standard 0.036 m³ environmental chamber. The results revealed a dramatic disparity in VOC content based on product formulation. Liquid cleaners, particularly solvent-based adhesive removers, contained up to 98.9% VOCs, whereas personal care products such as facial cleansers and body washes contained approximately 0.1%. Furthermore, field experiments on ventilation strategies demonstrated that natural ventilation significantly accelerates pollutant decay, whereas closed environments lead to the accumulation and prolonged persistence of VOCs. A screening-level health risk assessment indicated that while the lifetime carcinogenic risk (1.12×10-8) and non-cancer hazard index (0.76) were within acceptable limits under standard usage, the margin of safety is narrow for acute exposures in unventilated spaces. These findings underscore the critical need for source control and active ventilation management. |
| 6-1 | 5/20/2026 15:30 | Indoor Air Quality | SGM 123 | 127 | Kiriti Sahoo, E V S Kiran Kumar Donthu and Siva Rama Krishna Evani | Indian Institute of Technology (BHU), Varanasi; National Institute of Technology, Calicut; The Energy and Resources Institute | Role of portable-mechanical air ionisers on indoor air quality in Indian office buildings | Office building Filtration Ionisers IAQ Health | Maintaining adequate indoor air quality is specifically important in urban areas with high levels of outdoor air pollution, as poor air quality can contribute to a range of short- and long-term health issues. Ventilating indoor spaces with fresh air either naturally or mechanically can help dilute indoor pollutants. However, when outdoor air contains elevated concentrations of particulate matter (PM), filtration becomes essential. One effective strategy for enhancing indoor air quality involves the use of high-efficiency filtration systems incorporating Plasma cluster technology. This approach targets not only particulate matter but also volatile organic compounds (VOCs) and biological contaminants. The paper presents the findings of an experimental study conducted in two Indian cities, focusing on both naturally ventilated and air-conditioned office buildings. The aim was to assess the effectiveness of portable ionizers in reducing indoor air pollution. Indoor pollutants include PM10, PM2.5, PM1, Carbon monoxide (CO), Carbon dioxide (CO2), ammonia(NH3), formaldehyde (HCHO) and NO2 were monitored along with indoor temperature and relative humidity as per the guidelines and protocols set by the Central Pollution Control Board (CPCB) and Bureau of Indian Standards (BIS). The study demonstrated that the use of mechanical ionizers could reduce concentrations of PM10, PM2.5, and PM1 by approximately 24-51%, 31-62%, and 36-54%, respectively. Regarding gaseous pollutants, reductions of 15%, 23–35%, 18%, and 33% were observed for CO, CO2, NO2, and HCHO, respectively, with the use of air purifiers. Although limited research exists on the relationship between gaseous air pollutants and asthma in India and globally, some studies have identified a strong positive correlation between NO2 exposure and asthma-related hospitalizations. Therefore, the long-term use of air purifiers could significantly reduce indoor concentrations of NO2, potentially benefiting respiratory health. However, further scientific investigation is needed to confirm the associations between other pollutants such as CO, HCHO, and asthma-related health outcomes. |
| 6-1 | 5/20/2026 15:30 | Indoor Air Quality | SGM 123 | 159 | Elham Hasani Alavy and Clifford B. Fedler | Department of Civil and Architectural Engineering and Mechanics, University of Arizona, Tucson, AZ, USA; Department of Civil, Environmental, and Construction Engineering, Texas Tech University, Lubbock, TX, USA | Safety Evaluation of Air Cleaner Technologies in the Building Sector | Air Cleaner Indoor Air Quality Healthy Buildings Indoor Environment Indoor Safety | Indoor environments account for most of human daily exposure, making indoor air quality (IAQ) a critical determinant of health. Fine particulate matter, volatile organic compounds (VOCs), and airborne pathogens in high-occupancy spaces pose severe risks to respiratory and cognitive health. While numerous air-cleaning technologies exist, their real-world performance is shaped not only by pollutant removal but also by safety, maintenance, energy use, and lifecycle costs. A persistent barrier in the field remains the absence of a standardized certification framework for air cleaners. In the absence of such guidance, users face uncertainty in selecting technologies that are both effective and safe. To address the absence of a standardized evaluation framework, this study applies a multi-criteria decision-making approach that integrates removal efficacy, byproduct risks, operational requirements, and economic feasibility into a unified scoring system. It proposes a comprehensive evaluation framework that ranks technologies across three core dimensions: removal efficacy, operational safety, and practical demands. The results offer evidence-based guidance for selecting air cleaning solutions in environments such as schools, offices, and healthcare settings. More broadly, this framework lays a foundation for informed indoor air quality policy, paving the way for healthier, more resilient buildings in the post-pandemic era. |
| 6-1 | 5/20/2026 15:30 | Indoor Air Quality | SGM 123 | 354 | Yonca Yaman, Ayça Tokuç, Seda Nur Apdik, İrem Deniz, Azize Ayol, Gizem Tuna Tuygun, Tunahan Akış and Mehmet Akif Ezan | Department of Architecture, Dokuz Eylül University, 35390, İzmir, Türkiye; Department of Bioengineering, Manisa Celal Bayar University, 45140, Manisa, Türkiye; Department of Environmental Engineering, Dokuz Eylül University, 35390, İzmir, Türkiye; Department of Mechanical Engineering, Dokuz Eylül University, 35390, İzmir, Türkiye; Dept of Architecture & Energy Research and Application Center, Dokuz Eylül Uni, 35390, İzmir; Electric and Energy Department, İzmir Vocational School, Dokuz Eylül University, 35360, İzmir, Türkiye | Beyond Filters: Evaluating Biotechnological Indoor Air Purification with Microalgae Systems | Air purification biofiltration carbon capture indoor air quality sustainable buildings | Managing indoor air quality is crucial to avoid the harmful impacts of contaminated indoor environments on building occupants. Prominent strategies are controlling the source of emissions and pollutants, effective design of ventilation systems, and active reduction technologies. The various air purification methods range from conventional physicochemical techniques to sustainable biological treatments. Among these, biofiltration technologies stand out due to their environmental, economic, and social benefits. Additionally, emerging systems such as microalgae technologies offer carbon capture potential, while also retaining other pollutants, and contribute to improved quality of life, human health, and productivity of occupants. This review explores microalgae-based air purification systems, their impact on environmental sustainability and economic efficiency, the long-term effectiveness and practical applicability of microalgae systems in buildings and their contribution to indoor air quality. Hence, it evaluates the advantages and disadvantages of conventional physicochemical air purification methods and microalgal biotechnological solutions. In recent years, the potential benefits of microalgae on indoor air quality have attracted significant attention. However, the limited scope of existing literature and the need for deeper research into the potential effects of microalgae systems are the motivations of this study. In conclusion, carbon capture and indoor air quality improvement through microalgae have become a significant research area for sustainable energy development. Although microalgal air purifiers are not widely used on the market, they stand out as a promising alternative for future air purification technologies due to their lower environmental impact, higher efficiency, and effectiveness across a broader range of pollutants. Their indoor use also potentially creates positive impacts on building occupants. However, pilot-scale studies and standardized evaluations are essential to advance and validate these technologies. This work was supported by Research Fund of the Dokuz Eylül University. Project Number: FBA-2025-3655. |
| 6-1 | 5/20/2026 15:30 | Indoor Air Quality | SGM 123 | 408 | Semi Park and Insung Kang | University of Texas at Arlington | A state-of-the-air review and laboratory experiments of do-it-yourself (DIY) air cleaners | Indoor air quality do-it-yourself air cleaner air filtration | Evidence linking exposures to air pollutants and a range of acute and chronic adverse health effects has been well-established. Vulnerable populations are particularly susceptible to the adverse health effects of indoor air pollution as they spend more time in the home environment, where levels of air pollutants are typically 2 to 5 times higher than those outdoors. A substantial body of literature has reported that portable air cleaners equipped with high-efficiency particulate air (HEPA) filters can indeed reduce particulate matter (PM) concentrations and improve health outcomes or biomarkers. In recent years, do-it-yourself (DIY) air cleaners have emerged as low-cost alternatives to commercially available PACs, especially during the COVID-19 pandemic and wildfire events. These DIY air cleaners can be typically made from a box fan and furnace filter(s). Although DIY air cleaners have been proven effective in reducing PM in several experimental studies, research has not yet examined the interactions among design parameters such as configuration, filter and fan selection, shroud, and more. We reviewed the literature to date on the performance of DIY air cleaners across different design parameters and found out that more filters, higher ratings, and the presence of a shroud generally improved clean air delivery rate (CADR). Additionally, among the various designs, the 5×1 configuration demonstrated the highest CADR and cost-effectiveness, although the available data remain limited. Therefore, we conducted experiments on 5×1 DIY air cleaners with different filter combinations (e.g., 4 particle filters with 1 carbon filter, or 3 particle filters with 2 carbon filters) and evaluated their removal efficiency for both particulate and gaseous pollutants. |
| 6-1 | 5/20/2026 15:30 | Indoor Air Quality | SGM 123 | 424 | Wenfeng Huang, Tong Lin and Jianshun Zhang | Syracuse University | Modeling and Simulation of Indoor Aerosol Particle Behavior under Bipolar Ionization-Based Air Cleaning | CFD simulation ionization ion-particle interaction particle deposition | Particle removal has been demonstrated to be enhanced under bipolar ionization-based air cleaning technologies. With ion generation, aerosol particles acquire electrical charges, leading to agglomeration and subsequent deposition. Understanding the ion-particle interactions and increased deposition is essential for evaluating the overall effectiveness of ionization in indoor environments. Existing modeling studies often simplified species interactions by tracking a single representative particle concentration, whereas this study explicitly tracks each species concentration, uniquely defined by charge and diameter. In this study, a computational fluid dynamics (CFD) framework was developed to explore species concentration distribution under ionization conditions. The Eulerian approach was applied to simulate particle behaviors, as it facilitates detailed tracking of species concentrations by charge and size, while explicitly accounting for ion-particle interactions. A deposition model was incorporated for each species as a permanent sink to indoor surfaces, where deposition rates strongly depend on particle charge and particle diameter. The CFD framework was constructed based on a species transport model that emphasized particle charging, agglomeration, and deposition processes in previous work. Early CFD trials revealed localized regions of elevated particle concentration in the downstream area of the air cleaning box in the absence of a filter, suggesting critical regions where ion–particle interactions were intensified, and deposition was most pronounced. The model provides a foundation for systematically evaluating particle transport and removal under varying environmental and operational conditions including realistic ventilation scenarios. Future simulations will investigate the influence of different ventilation strategies, airflow patterns, and ion generation rates on particle distribution and deposition. This work is expected to provide valuable insights into the mechanisms governing ion-induced particle removal and support the optimization of ionizer design, placement, and operation for improved indoor air quality. |
| 6-1 | 5/20/2026 15:30 | Indoor Air Quality | SGM 123 | 649 | Kuan-Lun Pan, Pei-Yun Shih, Zhen-Shuen Choo and Jo-Chen Hsu | Industrial Technology Research Institute | Removal of isopropyl alcohol (IPA) in a semiconductor facility using ozone catalytic oxidation | Volatile organic compound (VOC) Isopropyl alcohol (IPA) Acetone Ozone (O3) Catalysis | Isopropyl alcohol (IPA) is a widely used organic solvent in the semiconductor industry and is commonly detected as an indoor volatile organic compound (VOC) that poses potential risks to both manufacturing processes and human health. In this study, ozone catalytic oxidation (OZCO) was investigated as an effective technology for IPA removal through laboratory-scale experiments and real field tests conducted in a semiconductor manufacturing facility. The laboratory results demonstrated that IPA removal efficiency was strongly dependent on ozone dosage, achieving up to 97% removal at an ozone generator power of 80 W under ambient temperature conditions. Carbon balance analysis indicated effective oxidation of IPA, with the majority of carbon converted to CO₂, confirming the strong oxidative capability of the OZCO process. Field-scale evaluations further demonstrated stable and effective removal of IPA and acetone, with removal efficiencies of 87–89% and 80–85%, respectively, over repeated tests under actual operating conditions. The results confirm the reliability and applicability of the OZCO system for continuous VOC control. Overall, this study highlights the potential of OZCO as a promising and practical technology for VOC abatement in semiconductor manufacturing facilities. |
| 6-2 | 5/20/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 38 | Alya Penta Agharid, Indra Permana, Fujen Wang and Chu-Cheng Wei | National Chin-Yi University of Technology | Energy Audit and Modeling for a Bank Management Office under Hot-Humid Climate | Energy audit energy modeling on-site survey energy efficiency low-cost energy measures | Bank management office buildings consume significantly more energy than typical offices due to continuous data server operation. This study focuses on improving energy efficiency in a bank management office in Northern Taiwan (ASHRAE Climate Zone 2A, Hot-Humid). Energy audits were conducted to identify inefficiencies and develop improvement strategies. The methodology combined ASHRAE Level 2 and Level 3 audits, including on-site surveys, field measurements, and energy modeling. Field measurements assessed indoor environmental conditions (temperature, humidity, airflow, and illumination), the performance of HVAC systems, server-room cooling, lighting, and plug loads. Findings show that the building’s Energy Use Intensity (EUI) consistently exceeds 300 kWh/m2/year, well above the ASHRAE 90.1 office benchmark of 179.86 kWh/m2/year, indicating significant inefficiencies. Three energy‐saving measures were proposed, including no-cost and higher-cost options. For no-cost option, raising the air-conditioning set point from 21°C to 24°C can reduce total energy use by 9%, saving about $67,898 TWD/year. For a higher-cost measure, replacing 35.5 W recessed LED fixtures with 25 W LED fixtures lowers lighting demand from 7.95 kW to 6.13 kW, saving roughly $10,992 TWD/year. Overall, integrating field audits with energy modeling provides a solid basis for identifying inefficiencies and developing effective recommendations, particularly for office buildings in hot-humid climates. |
| 6-2 | 5/20/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 218 | Hyun-A Ko and Jongwon Lee | Keimyung University; Sungkyunkwan University | Building Energy Performance Evaluation of Public Institutions Using the Korean Green Button System | Green button Building energy performance evaluation Public building energy monitoring Energy benchmarking ESG Indicators | The building sector accounts for approximately 30% of global energy consumption and 28% of energy-related CO2 emissions, making the establishment of systematic energy monitoring and assessment systems essential for achieving carbon neutrality targets. At this critical juncture where public sector leadership is paramount, this study explores the potential applications of the Korean Green Button system launched in 2025 and presents a comprehensive building energy performance assessment methodology for Korea. This research develops a performance evaluation framework through real-time monitoring of public institution electricity consumption data, centered on the Korean adaptation of the U.S. Green Button Initiative. The research methodology is composed of three core components: The first is a comparative analysis of public building energy monitoring systems and evaluation indicators from advanced economies including the United States, the EU, and Japan. The second is a descriptive statistical analysis and K-means clustering for building typology classification utilizing the electricity consumption data collected from approximately 500 public institutions during the 2022-2024 period. The third is the establishment of an EUI-based normalized benchmarking framework that enables objective performance comparisons across buildings. The findings of this study elucidate the characteristics of energy consumption patterns by building size, function, and region through the first systematic big-data analysis of energy consumption in Korean public institutions. The research provides quantitative indicators directly applicable to public institution ESG management evaluation systems which offer policymakers practical tools to establish data-driven energy efficiency targets and monitor carbon reduction progress. This methodology can be extended to the private building sector going forward and is expected to evolve into core infrastructure for national building energy management policy. |
| 6-2 | 5/20/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 251 | Youssef Benmoussa, Joud Al Dakheel, Nassim Sebaibi and Mohamed El Mankibi | BUILDERS Ecole d'ingénieurs, Unité de Recherche "Builders Lab", ComUE NU, Campus Caen, Epron, France; BUILDERS Ecole d'ingénieurs, Unité de Recherche "Builders Lab", ComUE NU, Campus Lyon, Vaulx-En-Velin, France; ENTPE - University of Lyon, LTDS, 3 rue Maurice Audin, Vaulx-en-Velin 69120, France | Enhancing Building Energy Flexibility Through Demand Response-Enabled Heating and Ventilation for Flexible IEQ Management | Mechanical Ventilation Energy Flexibility Rule-based control Demand Response Indoor environmental quality | With increasing investments in renewable energy, driven by climate change and its impact on global energy security, the volatility of the energy supply-demand has grown. Energy flexibility strategies, especially within the building sector, are crucial for bridging this gap. However, the use of ventilation to achieve energy flexibility and demand-side management remains underexplored in the scientific community. Energy flexibility is the capacity of a building to manage its generation and consumption according to grid requirements, user needs, and climate conditions. This paper investigates ventilation‑driven flexibility in smart retrofitted buildings using a novel Economic Rule-Based Control (ERBC) framework that modulates outdoor air and supply airflow setpoints in response to grid signals while enforcing indoor environmental quality (IEQ) constraints within the experimental setting of “HYBCELL”, an in-situ testing facility at ENTPE, France. The ERBC methodology, developed in LabVIEW, integrates real-time sensor data (indoor temperature, CO2 concentration), weather data, and dynamic hourly electricity pricing signals from the French day-ahead market. Building energy flexibility is achieved through load shifting by the ERBC framework and quantified using a flexibility factor (FF) that ranges from -1 (operation exclusively during high-price periods) to +1 (operation exclusively during low-price periods). Across six monitored days in December 2025, the proposed control achieved load shifting primarily in heating, reaching a flexibility factor (FF) of up to 0.84 during high-price periods, while maintaining acceptable indoor air quality (CO2 80% of occupied hours). Results demonstrate that heating loads are more flexible than ventilation and that economic savings are influenced by both climatic conditions and price volatility. The findings confirm that ventilation-driven control can serve as a viable short-term flexibility measure without compromising comfort, supporting the transition toward grid-adaptive buildings. |
| 6-2 | 5/20/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 288 | Kentaro Suga and Ryozo Ooka | Kyoto Institute of Technology; The University of Tokyo | A Study on the Comfort and Energy Effectiveness of Passive Design Method - Case Studies using Detached House Model | Passive Design Thermal Autonomy Global Sensitivity Analysis SHAP Standardized Regression Coefficient | Passive design, which harnesses natural forces such as sunlight, ventilation, and thermal mass, is increasingly seen as a key strategy for decarbonizing buildings. Conventional evaluations often assume continuous HVAC use and focus on annual energy demand, overlooking the original goal of achieving comfort without mechanical systems. To address this gap, the Thermal Autonomy (TA) metric has been proposed, quantifying the share of occupied hours that remain comfortable without active conditioning. TA provides a complementary perspective to HVAC-based assessments and highlights alternative design priorities. In this study, an extensive parametric analysis was carried out with EnergyPlus for detached houses in three representative Japanese climates—Sapporo, Tokyo, and Naha—by systematically varying insulation thickness, thermal mass, solar shading, and window-to-wall ratios. Building performance was assessed from both active (HVAC loads) and passive (TA) perspectives, enabling a comparative understanding of energy demand and inherent thermal resilience. To examine the relative influence of these parameters, we conducted a Global Sensitivity Analysis (GSA) using two complementary approaches: standardized regression coefficients (SRCs) from multiple regression and SHAP (SHapley Additive exPlanations) values derived from random forest models. While both methods consistently identified the most influential factors, differences in predictive accuracy led to variations in the resulting sensitivity rankings. Importantly, SHAP extended beyond linear correlations by highlighting nonlinear and interaction effects among variables, enabling more precise and interpretable insights. The analyses revealed that passive design strategies can have seasonally opposing impacts. For example, in Okinawa’s hot-humid climate, high insulation and thermal mass improved indoor comfort during winter but were disadvantageous in summer by retaining excess heat. In contrast, building orientation had limited influence on HVAC energy demand but significantly affected TA during colder periods, illustrating how the importance of design strategies depends on the chosen evaluation metric. Overall, the results demonstrate that SHAP-based sensitivity analysis, combined with building performance simulation, offers a robust and transparent framework for evaluating passive design strategies. This approach provides both global and local interpretability, supports evidence-based decision-making, and contributes to the advancement of climate-responsive, energy-efficient residential design. |
| 6-2 | 5/20/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 562 | Yizhou Yang and Qiuhua Duan | University of Alabama | Predictive Control of Kinetic BIPV Fins for Comfort-Efficient Building Operation | Building-integrated photovoltaics (BIPV) kinetic facades predictive control daylight thermal comfort | Kinetic building-integrated photovoltaic (BIPV) fins can simultaneously influence solar gains, daylight availability, glare risk, and on-site generation. However, their net benefit depends on how façade optics, thermal loads, lighting demand, and PV yield interact. This paper establishes a reproducible simulation workflow in EnergyPlus (DOE medium office prototype) to quantify these coupled tradeoffs for a semi-transparent PV insulating glass unit and rotatable exterior fin states. We first compare the baseline glazing against the BIPV glazing at the whole-building level. The BIPV case reduces total annual end-use electricity by 7.9% (from 521,763 kWh to 483,595 kWh) while producing 35,027 kWh of PV electricity. Cooling electricity decreases by 6.7% (−6,359 kWh), while heating increases by 8.6% (+2,406 kWh) and interior lighting increases by 1.4% (+1,437 kWh), reflecting the reduced visible transmittance of the PV glazing. Daylight and glare at a representative perimeter reference point show lower illuminance (average 3,400 lux to 2,200 lux) and a modest reduction in average glare index (25 to 22). We then evaluate three static fin tilt angles (0°/45°/90°) to illustrate energy–comfort–PV tradeoffs: 45° yields the highest PV generation (45,033 kWh) and the lowest cooling energy (95,059 kWh), while other angles shift the balance between heating, cooling, lighting, and glare exceedance time. These baseline results motivate the need for predictive fin control and provide decision-ready performance sensitivities for future occupant-centric kinetic BIPV operation. |
| 6-3 | 5/20/2026 15:30 | Building Technology and Performance | SGM 101 | 145 | Meng-Chieh Jeffrey Lee, Yi-Chun Kuo, Liu Shu Han and Tien-Chun Cheng | Department of Interior Design, National Taichung University of Science and Technology, Taichung City, Taiwan; Department of Interior Design, Shu-Te University, Kaohsiung City, Taiwan; Departments of Neurology and Occupational Medicine, Chi Mei Medical Center, Tainan City, Taiwan; Interior Design, National Taichung University of Science and Technology, Taichung City, Taiwan | Impact of CO2 concentration on Elderly residential by EEG& ECG | Indoor Air Quality Combined Environmental Conditions Carbon Dioxide EEG Heart Rate Variability Elderly Neurophysiological Load Subjective–Objective Discrepancy | Abstract This study investigates the impact of combined indoor environmental conditions, specifically carbon dioxide (CO₂) concentration, and ventilation states, on the psychophysiological responses of elderly and young populations. A controlled experimental design was adopted to measure electroencephalography (EEG) and electrocardiography (ECG) indicators alongside subjective environmental assessments. Participants were categorized into healthy elderly and young adult groups to examine age-related physiological differences. The results indicate that healthy elderly participants exhibited greater neurophysiological sensitivity to elevated CO2 and combined environmental stressors, as reflected by altered EEG band activity (e.g., increased theta and beta bands, and decreased alpha band). In contrast, young adults demonstrated comparatively stable physiological responses across similar environmental conditions. Notably, while subjective perceptions of the environment remained largely neutral or acceptable among the elderly, objective EEG measurements indicated increased neurophysiological load. These findings highlight the limitations of relying solely on subjective perception for indoor environmental evaluations in aging populations and demonstrate the critical value of integrating objective psychophysiological indicators. The results provide empirical support for developing health-oriented residential ventilation strategies tailored to older adults. |
| 6-3 | 5/20/2026 15:30 | Building Technology and Performance | SGM 101 | 258 | Jialiang Guo, Ngoc Dung Ngo Hoang and Hilde Breesch | Hanoi University of Civil Engineering; KU Leuven | Outdoor Microclimate Variations and Indoor Thermal Stress: Summer Field Measurements in an Elderly Care Facility | Indoor thermal stress Outdoor microclimate Field measurement Elderly care facility | Rising temperatures driven by climate change degrade both indoor and outdoor thermal conditions in cities. This challenge is particularly critical for vulnerable populations, such as older adults in care facilities, where combined indoor and outdoor heat exposure may pose serious risks. This study presents a summer field campaign at an elderly care facility in Ghent, Belgium, where indoor and outdoor thermal environments were monitored synchronously to evaluate recent heat stress in the built environment. Four representative urban microclimate locations (canyon, courtyard, semi-shaded park, exposed park) and seven resident rooms with different neighbouring microclimate contexts were selected. Rooftop and pedestrian-level weather stations, together with HOBO loggers, were used to record outdoor and indoor environmental variables. Physiological Equivalent Temperature (PET) and Standard Effective Temperature (SET) were applied to quantify outdoor and indoor heat stress, respectively. Tukey tests were used to assess significant differences in heat stress between sites and rooms, while SHapley Additive exPlanations (SHAP) were employed to identify key driving factors. The results showed that the exposed park (EXP) experienced the highest outdoor heat stress, with Exceedance Degree-hour (ED-h) of 600–1100 °Ch, whereas the semi-shaded park (SDP) showed roughly half this value, demonstrating the effectiveness of tree cover ratio in mitigating outdoor heat stress. Canyon (CAN) and courtyard (COY) showed similar heat stress with ED-h ranging from 280 to 740 °Ch. SHAP results indicated that air temperature and solar radiation (during daytime) are two key drivers of outdoor heat stress at pedestrian levels. For indoor results, all top-floor rooms exhibited higher heat stress than ground-floor rooms, particularly those facing the canyon and courtyard, with ED-h of 136 °Ch and 75 °Ch, respectively. Moreover, rooms with same east-facing orientation but different surrounding microclimates (COY and SDP) showed a significant difference in ED-h, with maximum delta SET reaching around 1.42 °C. Beyond orientation, the surrounding microclimate may be a key driver of indoor thermal stress. These findings highlight the importance of outdoor morphology (e.g., tree and impervious cover) in shaping local temperatures and should be considered in indoor heat mitigation strategies. Future work will assess these influences using coupled building–microclimate simulations. |
| 6-3 | 5/20/2026 15:30 | Building Technology and Performance | SGM 101 | 499 | Mohammad Saleh Nikoopayan Tak and Yanxiao Feng | New Jersey Institute of Technology | The Naturalness Effect: Open-Database Analysis of Ventilated and Mechanically Cooled Spaces | Natural ventilation Mechanical cooling Adaptive comfort Open-database analysis | Indoor thermal comfort is a critical factor in sustainable building design and occupant well-being, yet much of the existing evidence is limited to small-scale or region-specific studies. A key but insufficiently examined phenomenon is the naturalness effect, the observed tendency for occupants to perceive naturally ventilated environments as more comfortable than mechanically cooled ones under similar thermal conditions. To investigate this effect on a global scale, we conducted an open-database analysis using the ASHRAE global thermal comfort data, supplemented with metadata identifying building type and cooling strategy. This integration produced a diverse dataset covering multiple climates, continents, and building categories. We analyzed thermal sensation ratings on a categorical scale from −3 to +3, applying Chi-squared tests for independence to compare distributions between naturally ventilated and mechanically cooled environments across 3°C temperature bins within the 10-40°C range. Results revealed consistent evidence of the naturalness effect in moderate temperatures: between 22-25°C, naturally ventilated spaces showed significantly more neutral responses, with similar patterns observed in the 19-22°C and 25-28°C ranges. At higher temperatures (28-34°C), naturally ventilated environments displayed broader distributions and higher neutrality, challenging the assumption that mechanical cooling always ensures superior comfort. By contrast, differences were not significant at the cooler (13-16°C) and hotter (34-37°C) extremes, indicating boundary conditions where the effect diminishes. These findings align with the adaptive comfort framework, suggesting that occupants in naturally ventilated buildings employ behavioral adjustments, such as clothing changes, window use, or fan operation, to sustain comfort. Overall, this study provides cross-climatic evidence that cooling strategy systematically influences thermal perception and demonstrates the value of natural ventilation as both a sustainable and occupant-centered design approach. |
| 6-3 | 5/20/2026 15:30 | Building Technology and Performance | SGM 101 | 502 | Tsz Him Ian Chiu, Yijin Zhao and Julian Wang | Department of Architectural Engineering, Pennsylvania State University, University Park | Thermal Sensitivity and Biomarkers as Predictors of Individual Heat-Stress Vulnerability in Indoor Environments | Indoor Environmental Quality Heat Stress Vulnerability Thermal Sensation Predictive Model Wearable Sensors | Heat-related illness remains a critical public health concern, yet individual vulnerability to heat stress in everyday indoor environments is not well characterized. While prior research has identified physiological thresholds of heat strain and data-driven models have improved prediction of thermal sensation, these approaches often fail to capture heat vulnerability because subjective comfort metrics and physiological responses are rarely integrated. This study investigates thermal tolerance as a physiologically grounded indicator of individual heat-stress vulnerability during sedentary indoor work. Experiments are conducted in a controlled indoor environment with gradually increasing thermal exposure. Subjective thermal tolerance is assessed alongside continuous physiological monitoring, including core and skin temperature, heart rate variability, and electrodermal activity. Results show that thermal tolerance is strongly associated with both environmental heat metrics and physiological regulation. Higher tolerance is associated with greater parasympathetic activity and smaller changes in core and skin temperature, whereas lower tolerance is associated with elevated environmental heat stress and autonomic imbalance. Clear physiological differentiation is observed between bearable and unbearable tolerance states. These findings demonstrate that thermal tolerance integrates subjective perception with physiological heat strain, providing a meaningful indicator of individual heat vulnerability in indoor environments. Combining tolerance-based assessment with wearable physiological sensing supports more reliable monitoring of heat stress and enables adaptive, personalized indoor climate control strategies that improve both comfort and safety. |
| 6-3 | 5/20/2026 15:30 | Building Technology and Performance | SGM 101 | 525 | Guancong Ren and Zheng Tan | The Hong Kong Polytechnic University | Evaluating Walking Thermal Comfort in Urban Spaces Using Machine Learning: The Role of Physiological and Microclimate Factors | thermal walks skin temperature high-density urban environment very hot weather machine learning | Outdoor walking supports active mobility and well-being, yet outdoor thermal comfort is increasingly challenged under warmer climate. Existing outdoor thermal comfort indices are primarily developed for steady-state conditions and is limited in representing dynamic walking experiences. This study investigates the use of machine learning to predict thermal sensation during outdoor walking under transient microclimatic conditions. Field experiments were conducted in a high-density public housing estate in Hong Kong under hot and humid weather conditions (mean air temperature: 32.7 °C; mean relative humidity: 68.3%; mean wind speed: 0.50 m/s). Microclimatic parameters, body temperatures, and thermal sensation votes were collected from 25 participants. Four classification models, Random Forest, Support Vector Machine, Extreme Gradient Boosting, and k-Nearest Neighbors, were trained to predict thermal sensation using microclimatic variables and physiological variables separately. The results indicate that models based on physiological measurements outperform those relying solely on microclimate conditions, achieving higher overall predictive accuracy. Feature importance analysis using SHAP reveals that solar radiation and air temperature dominate microclimate-based predictions, while forearm and tympanic temperatures are key physiological predictors. These findings suggest that integrating physiological responses with data-driven models provides a promising pathway for the prediction of outdoor thermal sensation in dynamic walking scenarios. |
| 6-4 | 5/20/2026 15:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 164 | Shaymaa Hussain Al Marzouqi, Dongwoo Jason Yeom, Kamil Kaloush and Elham Fini | Arizona State University; Clemson University | Daylight Timing, Natural Scent, and Outdoor View on Cognitive Performance in Office Settings | Indoor Environmental Quality (IEQ) Daylight Scent Outdoor View Cognitive Performance | The role of multisensory environments in supporting human performance has become a growing focus in indoor environmental quality (IEQ) research. This study investigates the combined effects of daylight timing, natural scents, and access to an outdoor view on cognitive performance in office settings. A controlled experiment exposed participants to morning and afternoon daylight conditions combined with rosemary or frankincense scent while also providing an outdoor view of natural elements. Environmental variables such as illuminance, color temperature, indoor air quality, and thermal conditions were continuously monitored to ensure stable indoor conditions. Physiological responses were tracked using wearable sensors measuring heart rate, heart rate variability, skin conductance, skin temperature, and brain activity (EEG). Cognitive performance was assessed through validated digital tasks targeting attention, memory, and executive function, alongside surveys on comfort and well-being. The study explores whether rosemary in the morning and frankincense in the afternoon provide cognitive benefits when combined with natural daylight and an outdoor view, compared to using scents without regard to timing. Preliminary trends suggest that the timing of scent use may influence cognitive outcomes, with certain scent–time combinations being more effective in supporting cognitive performance than random use. Moreover, access to an outdoor view appeared to further strengthen positive effects on cognitive outcomes compared to conditions without a view. These results highlight the importance of combining sensory factors, daylight, natural scent, and an outdoor view in workplace environments. By demonstrating how these factors interact to enhance cognitive performance, this study provides new insight into multisensory IEQ strategies. The findings may inform workplace design practices aimed at improving productivity and well-being through optimized combinations of daylight, natural scent, and outdoor view. |
| 6-4 | 5/20/2026 15:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 173 | Mehmet Furkan Özbey, Dolaana Khovalyg, Neşe Alkan and Cihan Turhan | Atılım University, Türkiye; École polytechnique fédérale de Lausanne (EPFL), Switzerland & Atılım University, Türkiye; École polytechnique fédérale de Lausanne (EPFL), Switzerland | Effect of Mood States on Thermal Sensation: Cultural and Gender Differences in Türkiye and Switzerland | Adaptive Thermal Comfort Occupant Behavior Profile of Mood States Cross-Cultural Analysis | Thermal comfort is a multidimensional phenomenon governed not only by environmental parameters but also by physiological, behavioral, and psychological factors. Within the adaptive framework, while behavioral influences have been extensively studied, the role of human psychology remains relatively underexplored. This study examines the influence of mood states on thermal sensation, with particular attention to cultural and gender differences. Data were collected from participants in Türkiye (n=1159) and Switzerland (n=125), where mood was assessed using the Profile of Mood States (POMS) questionnaire and thermal sensation was measured with a 13-point scale. Correlation analyses revealed striking quantitative differences: while the dataset from Switzerland exhibited thermal independence with only 4 significant correlations (1 for females and 3 for males) out of 65 items, the magnitude of these few associations was notably higher (0.26 ≤ |r| ≤ 0.30) compared to the widespread but lower-strength correlations observed in the dataset from Türkiye (|r| < 0.20). In addition, contrary to traditional models, this study identified a significantly more widespread psychological influence among males. Specifically, male participants exhibited a considerably higher number of significant correlations compared to females. These results highlight the complex interplay between mood states and thermal perception, suggesting that cultural and gender-specific factors play a critical role. |
| 6-4 | 5/20/2026 15:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 248 | Taketo Suzuki and Tatsuya Hayashi | Chiba University | The relationship between worker's work style and wellness in activity-based working (ABW) offices | ABW TMS Wellness Communication Psychological motivations | Following the COVID-19 pandemic, Japanese companies increasingly adopt Activity Based Working (ABW) to achieve employee well-being and innovation acceleration through enhanced communication, but previous research relied primarily on subjective worker perceptions to measure ABW effectiveness without objective validation methods. This study objectively evaluates ABW implementation by examining complex relationships between worker attributes, communication patterns, organizational culture, Transactive Memory Systems (TMS), and wellness (combining health and intellectual productivity) in a Technology Innovation Center specifically designed with ABW principles to foster collaborative innovation. The comprehensive methodology combined detailed questionnaire surveys achieving a robust 76.1% response rate with advanced indoor human sensing technology, establishing four objective ABW indicators: average annual movement frequency, area changes, contact frequency, and number of contacts systematically linked to individual employee IDs for precise behavioral tracking. Survey results revealed exceptionally strong workplace communication and supportive organizational culture, with average scores consistently exceeding 70% of maximum points across all measured dimensions. Binary logistic regression analysis using odds ratios as the primary statistical measure demonstrated several statistically significant relationships with practical implications: CASBEE-OHC environmental satisfaction scores correlated strongly with communication support metrics (odds ratios >2.0), workers who changed locations based on psychological rather than architectural factors showed measurably higher contact rates and significantly better external relationships, increased interpersonal contact frequency correlated with improved psychological health as measured by Wfun scores, and strong supportive relationships consistently enhanced organizational understanding, TMS effectiveness, work engagement measured by UWES scales, and innovative behavior outcomes. The study conclusively suggests that workers who strategically utilize office spaces based on psychological motivations and personal preferences tend to build substantially better interpersonal relationships across hierarchical levels, leading to measurably improved intellectual productivity and overall wellness outcomes, thereby providing robust objective evidence for ABW effectiveness that transcends traditional subjective assessment limitations. |
| 6-4 | 5/20/2026 15:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 360 | Negar Salahi and June Young Park | The University of Texas at Arlington | Investigating personal thermal comfort for wheelSession chair users using a non-intrusive wheelSession chair-based sensing | Thermal Stress Personal Thermal Comfort Metabolic Equivalent of Task Disability Studies | Individuals who use wheelchairs face unique and often overlooked challenges related to thermal stress in the built environments. While accessibility standards such as the Americans with Disabilities Act (ADA) has improved physical access, there is a limited attention regarding wheelchair users’ actual interaction and satisfaction in buildings. The main purpose of this research is to investigate personal thermal comfort of wheelchair users using a wheelchair-based sensing. We installed an integrated sensing platform (WheelCom) on a wheelchair using low-cost sensors interfaced with Raspberry Pi 4. The temperature sensors recorded seat, backrest, handrim, and ambient conditions, while the motion sensors captured propulsion dynamics to quantify mechanical work, which was then converted to estimate metabolic equivalent of task (MET). Our results showed clear captures on differences between ramp and non-ramp segments for MET estimation by WheelCom. Non-ramp propulsion for both participants produced mean and median MET values within the moderate-intensity range whereas ramp propulsion resulted in substantially higher metabolic demand. Additionally, elevated MET values during ramp segments were accompanied by increased seat and backrest temperatures, indicating a consistent relationship between metabolic intensity and localized thermal responses. |
| 6-4 | 5/20/2026 15:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 439 | Xin Guo, Emanuel Boutros, Bing Guo, Sameeraa Soltanian-Zadeh and Jianshun Zhang | Syracuse University | Occupant Interactions and Perceptions of Personal Environmental Control Systems under Different Ambient Temperatures in Summer Conditions | Occupants’ Behavior Thermal Comfort Thermal Sensation Floor Heating Desk Heating/Cooling | Personal environmental control systems (PECS) allow office occupants to regulate their immediate environment, yet there remains a limited understanding of how users actually interact with such systems under changing thermal conditions. This study aimed to investigate how occupants respond to different room temperatures and a gradual decrease in temperature during winter months. The experiments were conducted in a full-scale office laboratory consisting of 12 workstations, each equipped with a PECS that provided desk cooling, desk heating, floor heating, and adjustable fan speeds. Before the test day, participants received comprehensive training on how to operate the PECS. During the experiment, participants were allowed to freely adjust the PECS settings, thereby simulating realistic office conditions. The tests’ temperatures ranging from 70°F to 66°F, and they consisted of two sessions. The first session maintained a temperature of 70°F for 40 minutes, followed by a 30-minute transition to 66°F, while the second session lasted 40 minutes at 66°F. Objective data on PECS settings and environmental conditions were continuously recorded, while subjective responses, such as thermal sensation, thermal comfort, perceptions of indoor air quality (IAQ), and feedback on the PECS, were also collected. The results reveal how occupants adapt to temperature changes through different control strategies and indicate preferences for specific functions in cooler environments. These findings provide new insights into the interaction between occupants and PECS, which can inform the design of systems that are more practical, energy-efficient, and responsive to user comfort. |
| 6-4 | 5/20/2026 15:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 116 | 534 | Neda Ghaeili Ardabili and Julian Wang | The Pennsylvania State University | Spectral Drivers of Circadian Daylight Performance in Architectural Glazing as a Function of Gaze Direction | Circadian daylight Spectral properties sCDA Melanopic daylight Gaze direction | Windows play an important role in building performance by affecting thermal behavior, visual comfort, and non-visual (circadian) light exposure. Standard performance metrics, such as U-factor, Solar Heat Gain Coefficient (SHGC), and visible transmittance (Tvis), are widely used to evaluate window systems; however, each metric reflects only one aspect of performance. As circadian light has become an increasing focus in building design due to its impact on occupant health, the limitations of these conventional metrics have become more evident, particularly in their ability to describe how glazing spectral properties influence circadian daylight performance. In this research, the spectral properties of glazing systems are examined to determine which parts of the visible spectrum most strongly influence circadian daylight performance. The spectral properties of glazing are examined to determine which parts of the visible spectrum most strongly influence circadian daylight performance. The transmitted spectra of glazing are divided into nine wavelength bands, corresponding to the blue, green, and red regions. Circadian performance is assessed using Spatial Circadian Daylight Autonomy (sCDA) under north- and south-facing orientations and across eight occupant gaze directions. Consequently, correlation analysis and the best subset model are used to evaluate how individual spectral bands and gaze direction affect circadian light exposure at each gaze direction. The results show that circadian daylight performance is strongly affected by specific wavelength ranges, particularly in the blue (460–498 nm) and green (550–586 nm) portions of the spectrum. In contrast, visible transmittance alone does not reliably predict circadian outcomes. Gaze direction also plays an important role, with indirect viewing directions showing greater sensitivity to glazing spectral properties than direct window-facing views. Overall, this study highlights the need to consider spectral characteristics alongside conventional window metrics when designing glazing systems to support circadian health. |
| 6-5 | 5/20/2026 15:30 | Thermal Comfort | GFS 101 | 33 | Anwar Ibrahim, Ahmed Freewan and Majd Momani | Al Yamamah University , Jordan University of Science and Technology; Jordan University of Science and Technology | Exploring Factors Influencing Occupant Behavior and Thermal Perception in Apartment Buildings: Irbid/Jordan as a case study | Occupant Behavior Thermal perception Energy use Simulation. | This study explores the factors affecting occupant behavior and thermal perception in apartment buildings, specifically examining aspects such as window status, curtain use, cooling system functionality, thermal sensation, and timing patterns. These elements were combined into a new composite measure called the Summer Thermal Convenience Factor (STCF) to assess their overall effect on energy consumption and thermal comfort. Data was collected through a detailed field study in Irbid, northern Jordan, where participants maintained eight-hour daily journals over three consecutive days in July, August, and September, recording adaptive behaviors and thermal sensations using the ASHRAE scale in conjunction with environmental monitoring. Principal Component Analysis was utilized to create the STCF framework, while energy simulations under consistent cooling loads evaluated the predictive abilities of the metric. The analysis showed that the five components of STCF have varying influences, with certain adaptive behaviors closely linked to thermal perception. Statistical models revealed significant correlations (p<0.01) between STCF scores, outdoor conditions, and building characteristics, while energy simulations highlighted a 12–18% variation in energy consumption for similar thermal loads based on STCF-derived behavioral patterns. By introducing STCF as the first standardized metric of its kind, this study enhances building energy modeling by quantitatively connecting occupant behavior clusters to energy outcomes and provides a solid framework for incorporating behavioral considerations into building design in Mediterranean climates. |
| 6-5 | 5/20/2026 15:30 | Thermal Comfort | GFS 101 | 44 | Wataru Umishio, Naoki Kagi, Isao Yamada, Lisa Yumae and Tomohiro Konda | AI Solution Department, Azbil Corporation; Department of Architecture and Building Engineering, School of Environment and Society, Institute of Science Tokyo | Thermal Comfort and Productivity under Air Conditioning Control Based on Metabolic Rate Estimation from Thermal Images | Thermal comfort Productivity Thermal image AI Air conditioning | Conventional air conditioning (AC) control does not account for human factors such as metabolic rate—a key factor affecting thermal sensation—and therefore cannot meet individual thermal comfort needs. However, recent advances in thermal imaging sensors and AI-based image analysis have opened up the possibility of AC control that more closely aligns with individuals’ thermal states. Therefore, we proposed an AC control system based on metabolic rate estimation using thermal images and conducted a subject experiment comparing it with conventional AC control. We evaluated its effects on thermal comfort and productivity. Since continuous measurement of metabolic rate is difficult, we estimated it non-invasively using average surface temperature obtained from thermal images. Human body regions were extracted in real time through AI-based image analysis, and surface temperature was used to estimate individual metabolic rates due to its linear relationship with metabolism. The estimated values were then applied to air conditioning control using Predicted Mean Vote (PMV) as the control target. The subject experiment was conducted in September 2024 during the summer season in the climate chamber. Six participants took part in each session, with a total of 12 participants across two sessions. Three cases were tested in the experiment. In Case 1, the room temperature was kept constant at 26°C, representing conventional AC control. In Case 2 (room temperature control to prevent overcooling), the room temperature was lowered when the minimum PMV among the six participants exceeded +0.5. In Case 3 (room temperature and airflow control), building upon Case 2, individual airflow was added using personal fans to adjust each participant’s PMV closer to ±0. For each case, participants performed tasks for 6 hours per day—2 hours in the morning and 4 hours in the afternoon. The results showed that thermal comfort votes were significantly higher and requests for room temperature adjustment were significantly fewer in Case 3 compared to Cases 1 and 2. Furthermore, alertness, as an indicator of productivity, was significantly higher in Case 3. These findings indicate that air conditioning control using thermal images is more human-centered and could improve thermal experience while enhancing productivity. |
| 6-5 | 5/20/2026 15:30 | Thermal Comfort | GFS 101 | 348 | Taeyeon Kim, Seheon Kim, Yingdao Nan and Jae-Weon Jeong | Hanyang University | Data-Driven Estimation of Occupant Thermal Preferences from Air Conditioner Control Behavior in Residential Units | Thermal comfort Air conditioning Autonomous control Artificial Intelligence Residential building | Autonomous control of building cooling systems represents an effective strategy to reduce energy consumption by preventing excessive cooling, thereby achieving both energy efficiency and thermal comfort for occupants. Conventional autonomous control methods have typically relied on fixed setpoints determined by PMV–PPD-based thermal comfort models. However, thermal preferences differ substantially among individuals, particularly in residential environments where personal characteristics strongly influence system operation, which complicates the application of statistical comfort models. Accounting for these differences would require extensive monitoring of both personal and environmental parameters, but such an approach is difficult to implement in practice due to the complexity of monitoring infrastructure and concerns over privacy. To address these challenges, this study proposes a method that derives occupant-preferred thermal conditions from cooling device control histories data, thereby minimizing the need for additional sensing parameters. Environmental data and operation logs of air conditioners were collected from each residential unit, and an artificial neural network (ANN) model was developed to predict household-specific preferred temperatures. For each residential unit, the upper boundary of the derived preferred temperature range was adopted as the setpoint for autonomous air conditioner control. In cases where manual adjustments by occupants occurred during autonomous operation, these control interventions were additionally incorporated into the learning process, and an updated model was subsequently applied. Case studies conducted on four residential units demonstrated that, compared with manual control, the proposed method reduced energy consumption while maintaining comparable levels of occupant satisfaction. This study presents a data-driven framework for developing residential unit–specific thermal preference models and contributes to the practical implementation and advancement of autonomous air conditioner control systems. |
| 6-5 | 5/20/2026 15:30 | Thermal Comfort | GFS 101 | 447 | Kai Chen and Ali Ghahramani | National University of Singapore | Demonstrating Challenges in Predicting Occupant Temperature Setpoints: A Comparative Evaluation of Traditional and Transformer-Based Machine Learning Models | Thermal Preferences Modelling Personal Thermal Comfort (PCM) Transfer Learning Adaptive | Heating, Ventilation, and Air Conditioning (HVAC) system stands as an essential components of modern building infrastructure, which is widely used to regulate indoor thermal conditions. Among the control parameters, the temperature setpoint stands out as one of the key variables in its operation, determining when and how heating or cooling is delivered. Accurately predicting occupant preferred temperature setpoints has the potential to improve HVAC energy efficiency and achieve comfortable indoor conditions by ensuring that heating and cooling are delivered precisely when and where they are needed. This can be achieved through the use of predictive machine learning (ML) algorithms, which learn the relationship between occupant preferences and environmental or physiological parameters. However, the application of ML algorithms in modeling thermal preferences remains limited due to consistently low prediction accuracy. This study identifies three key challenges underlying these limitations: (1) Difficulty predicting under unseen environmental conditions, (2) Lack of adaptability to changing preferences over time, and (3) Poor performance with limited training data. This paper aims to systematically demonstrate these key challenges and guide the selection or development of more effective thermal preference models for real-world HVAC operation. In this study, ten widely-used ML algorithms are selected for thermal preference modeling, and their predictive performance compared against a novel transformer-based architecture which we previously developed to address these three key challenges. We utilize the data derived from ECOBEE Donate Your database for performance evaluation, which comprises over 100,000 air-conditioned building thermostat users in North America. Results show that all models suffer a 20–30% drop in accuracy when predicting for previously unseen data. However, the transformer-based architecture, which leverages pre-trained models to capture diverse thermal preference patterns, outperforms the best widely used algorithm (R² of 0.63 vs. 0.49). Additionally, we demonstrate that the performance of ML algorithms often stagnates or declines with the increase of training set and how employing a transformer mechanism helps to continuously improve the predictive performance. Furthermore, with sparse training data, ML architecture leveraging pre-trained models achieve an R² of 0.67 by the 25th data point, outperforming the best widely used machine learning algorithm, which reaches an R² of 0.62. |
| 6-5 | 5/20/2026 15:30 | Thermal Comfort | GFS 101 | 469 | Yijin Zhao and Julian Wang | The Pennsylvania State University | How heat stress impairs cognition: A review of cognitive performance in indoor passive hyperthermal environments | Indoor passive hyperthermal environment Heat stress Cognitive performance Cognitive test | Hyperthermal environments have gained increasing attention in indoor conditions due to the growing frequency of extreme heat events and the urban heat island effect. Under these conditions, heat is trapped indoors, and the resulting heat stress can adversely affect cognitive performance, acute health, productivity, and safety. This review focuses on indoor passive hypothermal environments, defined as indoor air temperature of 30 °C or higher, where occupants engage in low-intensity activities, as is typical in office and residential buildings. Prior studies have reported inconsistent cognitive outcomes under heat stress. For example, the inverted-U curve explains that performance increases with rising temperature before declining; whereas the extended-U curve argues that performance remains stable within acceptable temperature ranges due to human adaptation but deteriorates rapidly at extreme temperatures. Despite the growing body of research in this field, reviews reflecting recent advances in understating the cognitive impacts of heat stress remain limited. To address this gap, this review examined 10 experimental studies published after 2000 and analyzed the potential contributors to the inconsistencies. The results indicate that: 1) a speed-accuracy trade-off occurs under heat stress, likely driven by psychological responses; 2) heat intensity and exposure period interact to influence cognitive performance; 3) performance outcomes vary with task complexity, with more complex tasks being more susceptible to heat stress than simpler tasks under identical conditions; and 4) human factors, such as age, gender, expectation and motivation, mental condition, and heat acclimation, may modulate the heat stress effects. Accordingly, future research should examine both underlying brain activity and task performance, identify safe exposure periods for certain temperature levels, conduct real-world evaluations, and explore energy-efficient solutions to mitigate heat stress effects. |
| 6-6 | 5/20/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | GFS 118 | 88 | Keisuke Kurobe and Hideki Tanaka | Campus Planning & Environment Management Office; Graduate School of Environmental Studies, Nagoya University | Simulation Analysis of District Heat Source Water Supply System Configuration for Urban Areas in Warm Climates | heat source water water-source heat pump district heat source water supply system cooling tower borehole | This study investigates the feasibility of introducing a district heat source water supply system in urban areas of warm regions from the perspective of energy performance. The demand side of the building includes three buildings: a hotel, an office building, and a commercial facility. Each building is equipped with water-source heat pumps and chillers that use the district heat source water as a heat source/sink to meet cooling, heating and D.H.W. loads of each building. The district heat supply plant is assumed a two-pipe heat source water distribution system. The heat source water is supplied to each building via the supply pipe from the plant, used as a heat source/sink by individual heat source equipment, and then returned to the plant via the return pipe. Heat source equipment such as air-source heat pumps are installed in the plant to maintain the supply temperature within the range of 13-28 degrees celsius. This paper investigates the energy performance of the heat source water supply system when cooling towers and geothermal heat utilization are combined. In this study, cases where the cooling towers and borehole heat exchangers are connected in series or parallel to the heat source water supply/return piping were examined. To achieve this objective, a heat source system and models are constructed using the LCEM tool, and annual simulations are performed. Boundary conditions include hourly outdoor air temperature and relative humidity, as well as hourly loads of average days on weekdays, Saturdays, and holidays, calculated based on building usage-specific heat loads. These results confirm that the use of cooling towers reduces energy consumption in the plant with particularly significant reductions during the intermediate season. Furthermore, when combining cooling towers and geothermal heat, the use of parallel connection system can be expected to result in greater energy consumption reductions. |
| 6-6 | 5/20/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | GFS 118 | 108 | Soowon Chae, Yeonju Kang, Hyunmoon Cho, Kwonye Kim and Yujin Nam | Department of Architectural Engineering, Pusan National University; Energy System Research Cell, Research Institute of Industrial & Technology; Research Institute of Industrial Technology, Pusan National University | Study on Reinforcement Learning-Based Control for PVT-Heat Pump Integrated Thermal Storage | Photovoltaic-thermal Heat Pump Thermal Storage Utilization Efficiency Reinforcement Learning Control Hybrid Renewable Heating Systems | This study proposes a reinforcement learning (RL)-based control strategy to enhance the utilization efficiency of thermal storage systems integrated with photovoltaic–thermal (PVT) collectors and a heat pump (HP). The hybrid system was modeled to include dynamic interactions among the PVT unit, the HP, and the stratified thermal storage tank, using experimentally validated component models. The RL agent was trained in a simulation environment built from one-year weather and load data for a commercial office building, with the objective of maximizing system utilization efficiency defined as the ratio of useful thermal output to the sum of thermal storage charging and discharging potentials. State variables included solar irradiance, outdoor air temperature, storage tank temperature stratification, and instantaneous heating demand, while action variables represented HP operation mode and flow rate control. A Proximal Policy Optimization (PPO) algorithm was implemented and compared against a baseline rule-based control (RBC) and a deep neural network (DNN)-based predictive control. Results showed that the proposed RL strategy improved annual utilization efficiency by 9.6% and 6.3% compared to RBC and DNN control, respectively, while also reducing daily operation cost by 7.8% on average. Seasonal analysis revealed that efficiency gains were most pronounced during mid-season periods with moderate solar availability and fluctuating loads. These findings demonstrate that RL-based operation can effectively coordinate PVT generation, HP operation, and thermal storage usage to achieve both higher efficiency and economic benefits in hybrid renewable heating systems. |
| 6-6 | 5/20/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | GFS 118 | 143 | Jinkyun Cho, Joo Hyun Moon, Sangwoo Byun and Jikyum Kim | Hanbat National University | Sustainable cooling solutions for high-density data centers: A numerical analysis of liquid cooling optimization | Data center Liquid cooling Computational Fluid Dynamics Energy performance Coolant supply temperature PUE | With the increasing demand for high-density IT equipment, data center cooling systems face a critical need for both high energy efficiency and effective thermal management. This study addresses this challenge by focusing on liquid cooling methods, specifically cold plate and immersion cooling, which offer superior heat transfer and support for higher coolant supply temperatures. We conducted a matrix-based analysis of 15 different system configurations to evaluate their energy performance. Our analysis considered key factors like coolant supply temperature (S-class), coolant properties, and system design. Our findings reveal that the S-class standard, originally for cold plate cooling, can also be applied to immersion cooling systems. We showed that several dielectric fluids performed stably between 40°C and 50°C. As S-class levels rise, conventional chillers are replaced by cooling towers, which cuts system power by up to 75%. Pump energy consumption is heavily influenced by the coolant's density and thermal properties; low-viscosity, high-conductivity fluids significantly reduce energy use. Under a 6 MW IT load, higher S-class configurations achieved a design cooling PUE below 1.04. This research underscores the critical importance of selecting optimal temperature set-points, coolant types, and system architecture from the initial design phase to achieve maximum cooling efficiency. |
| 6-6 | 5/20/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | GFS 118 | 166 | Chi Ling Liu and Yaw-Shyan Tsay | Department of Architecture,National Cheng Kung University | Development of an Integrated Decision-Support Platform for WBLCA in Early-Design Stage | Whole Building Life-Cycle Assessment Structure analysis building energy modelling decision making | To achieve the goal of 2050 net-zero goal in Taiwan, the Architecture and Building Research Institute (ABRI) of the Ministry of the Interior has implemented two labeling systems, Building Energy-Efficiency Rating System (BERS) for Operational Carbon (OC) and Low Embodied-carbon Building Rating System (LEBR) for Embodied Carbon (EC), to bring the Whole Building Life-Cycle Assessment (WBLCA) into the building and construction sector. Architectural design is inherently a step-by-step decision-making process, with the early design stage playing a critical role in effective carbon reduction strategies. In this study, a Rhino–Grasshopper-based integrated platform was developed to support decision-making during the early design stage by combining structural analysis and energy simulation. The authors first created a new plug-in, Hagfish, for structure analysis via seismic design code in Taiwan, and Honeybee was then integrated in to the platform for building energy modelling. The results demonstrated that the system could complete WBLCA in few minutes, providing a significant improvement for decision-making in the early-design stage. |
| 6-6 | 5/20/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | GFS 118 | 267 | Mohamed Dardir and Ali Khorasgani | South Dakota State University | Integrated Phase Change Materials and Solar Energy Generation for High-Performance Buildings in Extreme Weather | phase change materials energy generation high-performance buildings building performance extreme weather | Extreme weather conditions create significant challenges for energy efficiency considerations, both passive strategies and energy generation, impacting indoor environmental quality in high-performance buildings (HPBs). Traditional passive design strategies are often limited by insufficient thermal storage capacity and non-optimal energy generation performance, particularly during periods of intense heat, cold, wind, and variable solar exposure. Phase change materials (PCMs) building applications have been applied to regulate building thermal loads and as cooling media for photovoltaic (PV) modules. By addressing these challenges, this research introduces an investigation into the performance of an advanced integrated system combining PCMs and PV solar energy generation, designed to maximize energy performance and occupant comfort in extreme climates. The paper aims to identify pathways for coupling these domains to create hybrid PV-PCM-envelope systems that deliver both electrical and thermal performance benefits in two contrasting climatic zones: continental cold climate and hot desert climate. The proposed method develops comprehensive energy balance modeling and multi-objective optimization, employing MATLAB, Simulink, TRNSYS, and DesignBuilder platforms. Numerical modeling are built to evaluate annual system and whole-building performance, with parameters such as PCM panel thickness, PV panels integration, and operational schedules optimized using the Reference Point Non-dominated Sorting Genetic Algorithm II (R-NSGA-II) model. In this paper, a PCM-PV integrated building envelope system is designed, and the anticipated impacts on system and whole-building performance are discussed. Preliminary results demonstrate that strategic integration of multiple PCM types enhances year-round thermal energy storage, while innovative PV deployment maintains energy generation even under extreme weather disruptions. This combination reduces heating and cooling loads, boosts energy production, and supports indoor environmental quality and occupant well-being. Future work will include experimental prototypes, capturing real-time performance, thermal storage efficiency, and system effectiveness metrics. Experimental data will be used to validate simulation results, ensure model reliability, and inform practical system implementation. This research establishes a data-driven framework for HPB design, highlighting new pathways for resilient, sustainable, and energy-efficient buildings, contributing to climate adaptation and operational quality in diverse extreme climates. |
| 6-6 | 5/20/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | GFS 118 | 547 | Wanyu Rengie Chan, Bijay Sharma, Brandon Bilzman, William Delp and Brett Singer | Lawrence Berkeley National Laboratory; Richard Heath & Associates, Inc. (RHA, now part of Resource Innovations) | Methane Emission Measurements and Occupant Survey of Gas Appliances in California Homes | Residential Gas appliances Methane emissions Field sampling Occupant activity | The California Residential Methane Emission Characterization (CARMEC) is an ongoing research study funded by the California Energy Commission to gather data from a diverse sample of homes with natural gas appliances. The study included measurements of methane leaks from the gas infrastructure present in homes to usage of a wide range of gas appliances. We also surveyed occupants of the sampled homes to understand their usage patterns and opinions about their gas appliances. This paper represents a preliminary analysis of methane measurements made in a sample of 61 California homes from Redding, Chico, Merced, Fresno, and the San Francisco Bay Area. Measurements include whole house quiescent leaks and from the meter set assemblies, and emissions from gas appliances pilot light (if present), sustained combustion and transient emissions from ignition and extinguishment. For the analysis on any associations between methane measurements and occupant survey responses, we focus on the measurements of whole house quiescent leaks and emissions from cooking appliances. While our field team did not observe any significant gas leaks or combustion safety issues with any of the gas appliances measured, about 20% of occupants report smelling gas inside their home or near gas appliances. Kitchens and garages are the common locations where gas smell was reported. We found that a higher percentage of occupants reported needing to replace one or more of their gas appliances in older homes built pre-1980. We found an association between higher whole house quiescent leaks in older homes and homes with a crawlspace. In some cases, the responses from occupant survey were helpful in explaining the variations in methane emissions measured. |
| 6-7 | 5/20/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 207 | 63 | Yasuyuki Ishida, Shuhei Fujita, Wang Zheng, Miguel Yamamoto, Yusuke Hiraga and Ryotaro Tahara | Former Tohoku University; Hebei University of Technology; Tohoku University | Development of LCZ Mapping Method Combining GIS with Machine Learning | Local Climate Zones GIS Machine Learning Mesoscale simulation Satellite imagery | Local Climate Zones (LCZ) have been used worldwide in the field of urban climate. In most previous studies, LCZ maps, which are zoning maps for LCZ categories, were generated using the WUDAPT Level 0 method using satellite images and machine learning techniques. Since this method could generate maps without using geometric information on urban morphology, it is useful for urban climate analysis using LCZ maps in cities where such numerical information is not publicly available. However, this method involves the subjectivity of the map generator, resulting in different threshold values between LCZ categories for different map generators, and making it difficult to compare and analyse urban climates for the same category across multiple cities generated by different researchers. Although one solution to this problem is to use Geographic Information System (GIS) data to determine the LCZ category of each location, some LCZ categories could not be determined based on the numerical information. This study proposed a method of generating LCZ maps that allows all LCZs to be classified according to their actual conditions and matched to the correct urban morphological values by combining GIS and machine learning techniques. Based on the proposed method, LCZ maps were generated for Tokyo, Hong Kong, and Singapore. As a result, the consistency of average building height and building coverage ratio with the reference values was verified. For all form-based categories (LCZ 1-6, 9) in the three cities, ABH and BCR were found to be within the range of reference values. Additionally, WRF simulation incorporating the map for multiple Asian cities showed that the closer a city is to the equator, the greater the effect of sea breezes in reducing temperatures in the future and extracted the influence of different latitudes on future changes in open high-rise areas. |
| 6-7 | 5/20/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 207 | 104 | Subin Lin, Jason Leong, Boo Cheong Khoo and Hee Joo Poh | Department of Mechanical Engineering, College of Design and Engineering, National University of Singapore; Department of the Built Environment, College of Design and Engineering, National University of Singapore; Institute of High Performance Computing, Agency for Science, Technology and Research (A*STAR) | Aerodynamic Response and Ventilation Enhancement in Urban Street Canyons through Building Porosity: A Comparative Numerical and Experimental Study | Urban Aerodynamics Building Porosity Street Canyon Ventilation Reynolds-Averaged Navier-Stokes Pedestrian comfort | Building porosity is increasingly adopted in urban design to improve natural ventilation and mitigate the urban heat island effect. However, the influence of pore geometry and vertical positioning on pedestrian-level wind conditions remains not fully understood. This study investigates the impact of three different building porosity configurations, specifically standard rectangular, circular, and rotated rectangular openings, on the airflow within urban street canyons. A systematic approach combining reduced-scale wind tunnel experiments and Computational Fluid Dynamics (CFD) simulations was employed. The numerical model (RANS SST k-omega) was validated against experimental pressure coefficient measurements, achieving a Pearson correlation coefficient of over 0.97, confirming the accuracy of the model. The study focused on pedestrian-level velocity magnitudes (at 1.5 m height) and the associated flow field structures within two successive street canyons. The results reveal a significant dependence of ventilation performance on the vertical location of the opening. The rotated rectangular configuration, which features a vertical slot extending down to approximately 2 m above ground, produced a normalized pedestrian velocity (U/U_{ref}) of 0.91. In contrast, the standard rectangular and circular openings, positioned at the building mid-height, resulted in much lower velocities ranging from 0.10 to 0.15. Flow visualization demonstrates that elevated openings create a skimming flow regime where the ventilation jet passes above the pedestrian zone. Conversely, the vertically extended slot allows the high-momentum jet to penetrate the near-ground layer, effectively flushing out stagnant air. These findings indicate that the vertical proximity of the opening to the occupied zone is a more critical design parameter than the specific geometric shape of the pore. The study provides quantitative evidence that lowering the base height of void decks is essential for enhancing pedestrian-level ventilation in dense urban environments. |
| 6-7 | 5/20/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 207 | 263 | Mana Nemati Aghdam and Manish Dixit | Department of Construction Science, Texas A&M University, 400 Bizzell St, College Station, Texas. | Empirical Fragility-Based Adjustment of Embodied Carbon Using Machine-Learning-Derived Post-Hurricane Fragility Data | Climate change adaptation Hazard-adjusted life cycle assessment Climate resilience Machine learning fragility model Embodied greenhouse gas emissions | Climate mitigation and hazard resilience are often treated as separate goals, even though storm-driven repairs can add substantial embodied greenhouse gas emissions over a building’s lifetime. This paper presents a data-driven workflow that links post-disaster field observations (StEER), site-specific wind fields (ARA), and machine-learning fragility models to support hazard-adjusted embodied carbon assessment. A pooled dataset of 979 residential buildings inspected after Hurricanes Laura (2020) and Michael (2018) was harmonized to a common schema and assigned peak 3-second gust wind speed using nearest-neighbor geospatial matching. Gradient boosting classifiers estimate the probability of roof and wall replacement from gust intensity and building attributes. The models achieve AUC = 0.75 (roof) and AUC = 0.92 (wall). Gust speed is the main driver, with roof age and wall cladding group acting as key modifiers. These fragility outputs can be combined with regional hazard frequency and component-specific repair carbon factors to estimate expected repair-related emissions over a service life. The framework treats resilience as an emissions-reduction strategy by translating replacement risk into lifecycle CO₂e consequences. |
| 6-7 | 5/20/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 207 | 291 | Kanxuan He and Hongshan Guo | The University of Hong Kong | Data-driven cross-national climate zone classification for building codes: a future-compatible framework | climate zone building resilience building energy simulation climate projection CORDEX | Climate zone classification (CZC) provides a foundational layer for building energy codes and performance standards. However, nation-specific classification schemes pose challenges to cross-border building design and construction, as well as to the alignment of performance criteria in fields such as thermal comfort and energy efficiency. Traditional climate classification systems, exemplified by the Köppen–Geiger (KG) scheme, are mainly derived from ecological and environmental characteristics, and are therefore not tailored to the requirements of building regulations. Accelerating climate change further challenges the static nature of traditional schemes with higher variability and more intensive and frequent extremes. This study proposes a data-driven, spatial-temporal-compatible CZC framework that enables both historically grounded and future-oriented climate zoning. The framework constructs a unified weather feature space using long-term historical sequences consolidated from ISD, ERA5-Land, and NSRDB datasets. From these sequences, we derive both Typical Meteorological Year-based features that characterize mean climatic conditions and extreme-event-based features that captures variability and tail risks. These features are then clustered through K-means to identify climate groups. Cluster quality is evaluated using a suite of EnergyPlus-simulated metrics, ensuring that zones reflect not only climatic similarity but also performance relevance for building design. Across simulated energy metrics, the proposed framework demonstrates substantially improved clustering performance relative to the KG system, as reflected by an over threefold increase in the average F-statistic (7.20 vs. 2.14). Using CORDEX-derived future weather projections calibrated to the historical feature space, we further show that the framework supports trajectory-based analysis of climatic momentum. Among ten cities in North and South America, six are projected to shift into different climate zones in future periods (2025-2045, 2046-2070, 2071-2095), highlighting the material impact of climate change on building code applicability. Overall, the framework provides a scalable and future-compatible basis for climate zoning, enabling more consistent building energy modeling and supporting regulatory adaptation under evolving climate conditions for more targeted improvement in occupant-centric indoor environmental quality and energy efficiency. |
| 6-7 | 5/20/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 207 | 325 | Ilaria Pigliautile, Douaa Al-Assaad, Ongun Berk Kazanci, Joon-Ho Choi, Yanghao Cui, Yu Dong, Wooyoung Jung, Dolaana Khovalyg, Joyce Kim, Bjarne Olesen, Mariya Petrova Bivolarova, and Jun Shinoda | KU Leuven; Technical University of Denmark; University of Arizona; University of Perugia; University of Southern California; University of Waterloo | A classification scheme for exploring the role of wearable personalized environmental control systems (PECS) in a changing climate | wearables Personal Environmental Control Systems personalized comfort outdoor comfort climate change resilience | Global warming due to climate change is increasingly challenging human thermal comfort in both indoor and outdoor environments. Extreme weather events, such as heatwaves and cold snaps, are expected to become more frequent and intense, posing serious threats to human well-being and health. These impacts are particularly critical for vulnerable populations, including outdoor workers and low-income households. This highlights the need for occupant-centric, energy-efficient, and resilient solutions that are both accessible and practical for everyday use. Wearable Personal Environmental Control Systems (PECS) for thermal management represent a promising solution to simultaneously mitigate indoor and outdoor thermal stress and reduce energy demand for indoor heating or cooling. By targeting the personal microenvironment, wearable PECS can address individual thermal preferences while relying on relatively low power capacity. Moreover, as portable systems, wearable thermal PECS can seamlessly accompany individuals across indoor, outdoor, and transitional spaces. When equipped with physiological and/or environmental sensing capabilities, wearable thermal PECS not only enhance comfort under dynamic conditions but also offer unique opportunities for the development of advanced Personal Comfort Models by capturing individual responses in real-world settings. In the framework of IEA EBC Annex 87 which overarching goal is supporting the development and market uptake of wearable thermal PECS, this contribution presents a preliminary attempt to establish a coherent classification scheme for such technologies. The proposed scheme is structured around key dimensions identified in the literature, including energy requirements, sensing capabilities, controllability, durability and invasiveness. These dimensions are discussed in relation to their potential to guide technology design, enable cross-comparison among solutions, and foster standardization within the field. Ultimately, this study contributes to a structured understanding of wearable thermal PECS, highlighting their role as a flexible, low-energy strategy to enhance human resilience against climate change while opening new avenues for research in personalized thermal comfort. |
| 6-8 | 5/20/2026 15:30 | Online Session | VHE 206 | 61 | Enlian Zhang, Jin-Bin Im, Lijing Xu, Seo-Young Park and Ju-Hyung Kim | Hanyang University | The Influence of Window Characteristics on Occupant Well-Being and Perception in Indoor Environments: A Review | Window Indoor environment Mental health Well-being Perception | Windows serve as critical interfaces between indoor and outdoor environments, shaping occupants’ visual comfort, cognitive performance, and psychological well-being, particularly in workplace environments. This paper reviews recent interdisciplinary research across architecture, environmental psychology, and building science to examine how physical window attributes, such as size, window-to-wall ratio (WWR), fenestration, and shaping, and their resulting environmental performance, such as visual openness, daylight, and view composition, affect human perception, emotion, and stress recovery in both real and virtual settings. Well-designed windows introduce natural light and landscape views, enhancing psychological comfort, reducing stress, and increasing overall satisfaction with indoor spaces. Advances in immersive virtual simulations, visualization techniques, and physiological measurement tools have enabled more precise and objective evaluations of these effects. However, current research still lacks standardized quantitative measures and longitudinal evidence. Therefore, this paper proposes a multi-stage impact model to link specific window design features, their underlying psychological and physiological mechanisms, and their contribution to occupants’ overall well-being through mental health outcomes such as stress recovery and emotional regulation. This review emphasizes the need for integrative and multisensory approaches to better understand how window design influences psychological restoration, emotional regulation, and overall well-being in contemporary built environments. |
| 6-8 | 5/20/2026 15:30 | Online Session | VHE 206 | 220 | Fahad Iqbal and Shayan Mirzabeigi | State University of New York College of Environmental Science and Forestry, Syracuse, NY, USA | Comprehensive IoT-based Monitoring of Air Quality and Thermal Comfort: An Indoor-Outdoor University Campus Case Study | IoT air quality thermal comfort indoor and outdoor air monitoring environmental quality sensors | Indoor environmental quality is a critical determinant of human health, comfort, and productivity, yet systematic and continuous monitoring in large, multipurpose buildings such as university campuses remains limited. This study addresses this gap through a comprehensive Internet of Things (IoT)-based monitoring campaign, investigating air quality and thermal comfort across both indoor and outdoor spaces at the State University of New York College of Environmental Science and Forestry. The objective was to evaluate spatial and temporal variations in environmental parameters and assess how different indoor spaces perform under different occupancy and outdoor climatic conditions. The system integrated 26 low-cost and in-house-developed devices, including sensors for Particulate Matter (PM), carbon dioxide (CO2), temperature, humidity, Total Volatile Organic Compounds, noise, light, plus globe temperature and wind speed for outdoor, connected via microcontrollers to enable continuous data logging. Indoor and outdoor locations were selected to capture a diverse range of use types and exposure conditions. Data analysis revealed that indoor environments exhibited elevated levels of CO2 and PMs during peak occupancy, whereas outdoor conditions were more strongly influenced by diurnal and seasonal temperature and humidity fluctuations as well as city-wide factors such as adjacent highway construction. Indoor thermal comfort, estimated using a Simplified Predicted Mean Vote (sPMV) model, indicated that some classrooms and offices frequently experienced conditions outside the optimal comfort range, particularly during afternoon hours and summer periods. Outdoor comfort was assessed using the Universal Thermal Climate Index. These results highlight the value of IoT-enabled environmental monitoring in identifying trends that are often missed through spot measurements or occupant surveys. The findings highlight opportunities for targeted interventions, including optimized indoor ventilation schedules and outdoor shading or landscaping strategies. Overall, the study demonstrates that IoT-based monitoring provides a scalable, cost-effective approach for assessing environmental quality, supporting sustainability goals, facilities management, and occupant well-being. |
| 6-8 | 5/20/2026 15:30 | Online Session | VHE 206 | 227 | Naja Aqilah, Sheikh Ahmad Zaki, Noor Alam and Fitri Yakub | Malaysia-Japan International Institues of Technology (MJIIT), University Technology Malaysia | Environmental, Physiological, and Subjective Assessments of Thermal Comfort in a School Classroom | Indoor environment Thermal comfort survey Physiological School classroom | Thermal comfort is crucial for students’ concentration, health, and academic performance, yet classrooms in hot and humid climates often suffer from poor ventilation, overcrowding, and limited cooling systems. Existing standards such as ASHRAE 55 and ISO 7730, which are largely derived from adult office environments, may not adequately reflect the needs and adaptive behaviors of school-aged children in tropical classroom settings. To address this gap, the present study investigates thermal comfort in a Malaysian secondary school classroom by integrating environmental, physiological, and subjective measurements. All data was collected across three classroom sessions (8:00 a.m., 10:00 a.m., and 1:00 p.m.), capturing the progression of indoor temperature throughout the day under different cooling strategies. Environmental parameters, including indoor temperature, relative humidity, globe temperature, air velocity, and carbon dioxide (CO₂) concentration, were continuously monitored. Simultaneously, heart rate data were recorded using a Polar H device from five students and one teacher per session. A questionnaire survey was also administered to assess students’ thermal sensation vote (TSV), thermal preference (TP), and thermal acceptability (TA). Two phases were conducted at which a pre-installation phase to establish baseline conditions with only existing ceiling and exhaust fans, followed by a post-installation phase to evaluate improved or alternative cooling strategies. By combining objective measurements, physiological data, and subjective assessments, the study provides a comprehensive perspective on classroom thermal comfort dynamics under various cooling strategies. The findings are expected to highlight time-dependent variations in comfort perception and physiological responses, offering valuable insights into optimizing ventilation strategies, and classroom design. Ultimately, this research contributes to the growing of knowledge on thermal comfort in educational settings and supports the creation of more conducive learning environments in hot and humid climates. |
| 6-8 | 5/20/2026 15:30 | Online Session | VHE 206 | 448 | Ashraf Ragheb | Lawrence Technological University | Indoor Thermal Comfort Evaluation of an Office Space in the Southeastern United States. | Office Buildings Thermal Comfort Indoor Climate Hot Tropical Climate | Commercial and office buildings often have problems with aspects of indoor thermal environment and energy performance. The actual performance of these types of buildings, most likely, is different from the desired performance. The possible causes can be described as follows: excessive capacity in space, inappropriate operation of mechanical system, less internal heat generation, etc. This paper aims to discuss actual vs desired indoor climate and energy consumption in a medium-size building in the extreme Southeast of the United States. Data collection was conducted in an office space measuring environmental performance and indoor thermal quality parameters. A typical fully air-conditioned office space was chosen for the evaluation. To measure and evaluate the actual performance of the building, five parameters were measured: outdoor climate, indoor climate, energy consumption of the building, occupants’ sensation, and building management. For parameters 1-3, a continuous measurement was conducted. However, a survey through questionnaire was conducted to measure occupants’ sensation. By collecting and analyzing this data, it was possible to evaluate the comprehensive actual performance of this office space which represents one floor of the building. The measurement of the thermal condition shows that most measured points across the office space are at the colder side of the comfort zone. This finding is supported by the survey results where about 63% of occupants voted for “slightly cool”, “neutral” and “slightly warm” and about 22% of occupants showed “cold” related symptoms on their extremities and body at the end of working hours. Despite these numbers, more than 90% of occupants accepted the thermal condition, however, only 20% of them liked to have the space warmer. These findings show that the occupants have adapted to the cold temperature conditions in this office space. |
| 6-8 | 5/20/2026 15:30 | Online Session | VHE 206 | 480 | Sadia Israt Anam and Fan Zhang | Griffith University; Griffithu University | Heart Rate Variability as a Marker of Cognitive Workload: Influence of Temperature and Task Complexity in Office Settings | Heart rate Heart Rate Variability (HRV) Cognitive workload Task Complexity Office environment | This study investigates the relationship between temperature, cognitive task complexity, and HRV features to determine their reliability as physiological markers of mental workload in office environments. Forty-eight participants completed six cognitive tasks at two complexity levels across four controlled temperatures (22°C, 25°C, 28°C, and 31°C) in a climate chamber. HRV was continuously recorded using a Polar H10 chest strap, and subjective workload was assessed using the NASA Task Load Index (NASA-TLX). Correlation analysis identified RMSSD, pNN50, and Total Power as the most sensitive HRV indicators. RMSSD and pNN50 consistently showed negative associations with subjective workload, while Total Power demonstrated a positive association. These relationships strengthened at higher temperatures, with additional associations observed for LF power, HF power, and SDHR at 28°C and 31°C. A three-way repeated measures ANOVA revealed significant effects of task type on multiple HRV features, particularly pNN50, IBI, and Total Power, while temperature showed moderate effects, and task complexity had limited influence. Paired-samples t-tests revealed task-specific physiological responses, including a reduced IBI during PASAT and an increased HF power with a decreased LF/HF ratio during Match to Sample. These findings highlight the importance of HRV-based workload monitoring and underscore the role of thermal conditions and cognitive task design in supporting office worker performance and well-being. |
| 6-8 | 5/20/2026 15:30 | Online Session | VHE 206 | 651 | Shuyi Chen, Yihu Zhang, Jun Xiao, Ziliang Wei, Hao Zhou, Yang Geng and Borong Lin | Institute for Urban Governance and Sustainable Development, Tsinghua University, Beijing 100084, China; School of Architecture, Tsinghua University, Beijing 100084, China | Seasonal and spatial differences of building occupancy profiles: Evidence from mobile data | Occupancy mobile data building simulation building energy modeling multi-city comparison | Building occupancy is a critical determinant of building energy consumption, yet it is often represented by typical, deterministic patterns that overlook potential spatiotemporal variations. Using large-scale mobile data, this study provides an initial examination of how building occupancy varies across seasons, cities, and intra-city locations. Occupancy profiles were generated for over 440,000 buildings across Beijing, Chongqing, and Zhengzhou, of which the core analysis focused on five representative building types: residential, office, retail, hotel, and cultural. Results show that intra-city differences are the most pronounced, exhibiting a clear ‘center–periphery’ pattern. For example, retail and cultural buildings in Beijing’s 2nd Ring display cumulative occupancy density 2.4 times higher than those in the 4th–5th Ring. Inter-city variations display complex patterns potentially associated with urban morphology and economic context. Seasonal differences are most evident in cultural buildings, with spring weekend afternoon occupancy reaching 1.9 times winter levels. The findings reveal significant variability in occupancy, highlighting the limitations of uniform assumptions in building simulations. Accounting for this can enhance the accuracy of occupancy representation, facilitate more precise building energy modeling, and support cross-scale carbon reduction interventions. |
| 7-1 | 5/21/2026 11:00 | Sponsored session by LG: Thermal Comfort | SGM 101 | 329 | [Sponsor Team: LG] Jae-Hee Lee, Peter Schild, Moon Keun Kim, Saikee Oh, Sanghun Lee, Donghan Kim, Beomsoo Seo, Eunjun Cho and Trygve Eikevik | LG Electronics Inc.; Norwegian University of Science and Technology; Oslo Metropolitan University | Field Evaluation of Multiple R290 Air-to-Water Heat Pumps in Cascade Operation Adapted to Nordic Climates | Multiple air-to-water heat pumps Cascade operation Propane as refrigerant Field performance evaluation Nordic climate applications | Air-to-water heat pumps (AWHPs) using propane (R290) as a refrigerant have drawn attention as energy-efficient and environmentally friendly space heating solutions. However, their limited heating capacity and reduced energy performance in cold climates—especially in Nordic regions characterized by low ambient temperatures and high humidity during winter—remain critical challenges. To address these limitations, this study introduces a cascade-operation approach using multiple AWHPs, enabling alternate or concurrent operation to provide continuous, sufficient, and energy-efficient space heating. Multiple R290 AWHPs, equipped with cascade-control logic, are installed in a test building in Oslo, Norway, to evaluate its advantages compared to a conventional non-cascade operation. The cascade case consistently achieves higher target water temperature attainment rates, averaging 96.9%, with advantages becoming more pronounced under colder and more humid outdoor conditions, especially during frequent defrosting. Moreover, the cascade case can operate under deeper partial-load conditions at lower compressor frequencies compared to the non-cascade case. This results in higher energy efficiency in the cascade case, with improvements increased by up to 0.35 as outdoor temperature increases and humidity decreases, favoring partial-load operation. Under more extreme weather conditions, the non-cascade case approaches full-load operation, whereas the cascade case remains under partial-load conditions, leading to markedly improved seasonal performance factors. Consequently, the cascade operation of multiple AWHPs highlights practical advantages in both heating and energy performance throughout the entire winter season, offering a viable space-heating solution for Nordic climate applications. |
| 7-1 | 5/21/2026 11:00 | Sponsored session by LG: Thermal Comfort | SGM 101 | 29 | Kertu Kund, Raimo Simson, Alo Mikola, Kätriin Onemar and Jarek Kurnitski | Tallinn University of Technology | Analysis of Circuit Connections and Control Strategies for Residential Air-to-Water Heat Pump Systems | buffer tank connection schemes dynamic simualtion heat pump performance seasonal performance factor | This study investigates the impact of secondary circuit hydraulic connection schemes and control strategies on the performance of residential air-to-water heat pump systems providing space heating and domestic hot water (DHW). Five configurations (parallel-connected 200L buffer tank; 200L buffer tank with return bypass; direct connection; 50L buffer on supply; 50L buffer on return) were analyzed with inverter, on-off, and degree-minute heat pump controls. Dynamic simulations using IDA ICE software for a detached house model and moderate climate conditions (Estonia) evaluated Seasonal Performance Factor (SPF), indoor temperature stability, and auxiliary heating. Inverter-controlled systems with larger buffer tanks yielded the highest heating SPF; a 200L buffer with return bypass achieved a SPF of 3.90 with no auxiliary heating. On-off controls performed similarly (SPF 3.86 with bypass). Direct connections resulted in lower SPF values (e.g., 3.55 for inverter) and significantly higher auxiliary heating across all control logics, largely influenced by DHW priority operation. Degree-minute control led to the lowest SPFs and substantial auxiliary heating, attributed to its operational logic, especially after non-heating periods. The defrost cycle reduced overall system SPF by approximately 7.0%. Optimal performance, characterized by high SPF and minimal auxiliary heating, was achieved with an inverter-controlled heat pump using a 200L buffer tank with a heating circuit return bypass, particularly when the system is configured to maintain supply temperatures with auxiliary support. |
| 7-1 | 5/21/2026 11:00 | Sponsored session by LG: Thermal Comfort | SGM 101 | 64 | Lorenzo Croci, Francesco D'Oria and Maria Francesca Talamo | RSE SPA; RSE Spa | Hybrid Heat Pump: Enabling Efficient Decarbonization of Existing Buildings | Energy efficiency retrofits hybrid heat pumps flexibility building energy management systems | The EPBD Directive (EU) 2024/1275 establishes a gradual abandonment of the installation of fossil fuel-based boilers and the removal of financial incentives as early as 2025, except for hybrid systems. In this context, the study analyzes the effectiveness of bivalent systems that combine a condensing gas boiler with a high-temperature electric heat pump. These solutions are particularly suitable for retrofitting existing buildings equipped with radiator-based heating systems, as they do not require major structural modifications while offering enhanced energy flexibility. As is well known, boilers and radiator emission terminals represent the most widespread system solution in Italy. The analysis highlights that bivalent systems, especially when integrated with Building Energy Management Systems (BEMS), can achieve a significant reduction in CO₂ emissions (up to 60% compared to a traditional gas boiler), improved energy efficiency, and increased penetration of renewable energy sources. In optimized configurations, the heat pump can cover over 90% of the thermal demand while maintaining high overall efficiency, with only a limited reduction (6–8%) in the share of renewables compared to fully electric solutions. Additionally, bivalent systems can provide auxiliary services to the electricity grid, contributing to its stability through ancillary services and flexible load management. Their ability to respond dynamically to grid conditions makes them a strategic asset in the evolution of the energy system. From an economic perspective, the achievable energy savings make this solution viable in the long term. The study suggests that future incentives could be proportional to the actual share of renewable energy used by the hybrid system. In conclusion, bivalent systems emerge as an easily applicable technology for the decarbonization of residential heating, in line with the need to address a large stock of inefficient and outdated existing buildings and in accordance with European climate policies. |
| 7-1 | 5/21/2026 11:00 | Sponsored session by LG: Thermal Comfort | SGM 101 | 297 | Sangmin Lee and Hyunwoo Lim | Konkuk University | Optimal Load Shift Control Strategy for CHPWH system Based on Load Separation Method | Load shift Load separation Central heat pump water heater Domestic hot water | As global electrification accelerates, the central heat pump water heater (CHPWH) system has attracted increasing attention as an efficient and sustainable alternative for domestic hot water supply. However, the conventional CHPWH system experiences performance degradation because the introduction of recirculation return water increases the heat pump inlet temperature, thereby lowering its operational efficiency. To address this issue, a swing-tank-based load separation strategy has been proposed for the CHPWH system, in which the primary water heating load that heats cold water is separated from the temperature maintenance load that processes recirculation return water. By introducing this load separation method, the system enables load shift, which is a control strategy that reduces operation during periods of high demand and increases operation during periods of low demand in order to achieve energy load leveling and improve overall efficiency. Nevertheless, detailed modeling studies and systematic validation of the effects of load shift in such systems remain limited. Therefore, this study proposes and optimizes a load shift control strategy, and to achieve this a swing-tank-based CHPWH system is modeled using TRNSYS. The analysis results indicate that the developed model reproduces the on-off operation pattern of the heat pump with a normalized mean bias error (NMBE) within 10%. Furthermore, the proposed demand-responsive load shift control strategy reduces electric energy consumption by approximately 10% compared to conventional operation. These findings demonstrate that the load shift–based control strategy can enhance the energy efficiency of the CHPWH system. In addition, they suggest that the developed TRNSYS-based model provides a foundation for future research on advanced control strategies, such as machine learning–based load forecasting or tank size optimization, which could further improve the performance and flexibility of the operation of the CHPWH system. |
| 7-1 | 5/21/2026 11:00 | Sponsored session by LG: Thermal Comfort | SGM 101 | 335 | Yujin Lee and Dae Uk Shin | Kunsan national university | System configuration and control process of a combined convective cooling and radiant floor heating system | Simultaneous heating and cooling Heat pump Radiant floor heating Thermal comfort Energy saving | Radiant floor heating and convective cooling systems are widely adopted in residential buildings in Korea due to their respective advantages in thermal comfort and cooling performance. However, these systems are typically operated independently. This study proposes a novel simultaneous heating and cooling system that combines convective cooling with radiant heating to improve energy efficiency while maintaining high thermal comfort in residential buildings. The proposed system recovers waste heat generated during cooling operation through a heat exchanger and reutilizes it for radiant floor heating. The system consists of an air-source heat pump, a refrigerant–water heat exchanger, a hot water storage tank, and a boiler-based radiant floor heating system. A suitable system configuration was developed based on a comprehensive review of previous studies. The cooling control process determines cooling demand based on indoor air temperature and prioritizes waste heat recovery, while the heating control process is designed to prioritize thermal comfort based on floor surface temperature. As a result, four representative operating modes are defined: a simultaneous heating and cooling mode, a cooling-only mode, a heating-only mode, and a non-operational mode. In future work, the proposed system will be implemented in a simulation environment to quantitatively evaluate energy-saving potential and thermal comfort performance under various operating scenarios and climatic conditions. |
| 7-1 | 5/21/2026 11:00 | Sponsored session by LG: Thermal Comfort | SGM 101 | 504 | Won-Jong Choi, Jae-Won Jeong and Min-Hwi Kim | Department of Architectural Engineering, College of Engineering, Hanyang University, Republic of Korea; Renewable Energy System Laboratory, Korea Institute of Energy Research, Republic of Korea | Operational optimization of fifth-generation district heating and cooling systems with thermal energy storage for energy autonomy | fifth-generation district heating and cooling(5GDHC) self-consumption self-sufficiency bidirectional thermal network decentralized heat pump | Achieving carbon neutrality requires a paradigm shift from isolated technologies to integrated, community-scale energy systems. While conventional District Heating (DH) systems are a cornerstone of urban energy, legacy systems (3rd and 4th generation) exhibit inherent limitations, including significant thermal losses from high-temperature distribution, restricted integration of renewables, and fossil fuel dependency. As a promising alternative, fifth-generation district heating and cooling (5GDHC) systems have emerged, characterized by low-temperature networks that minimize heat loss and enable bidirectional thermal exchange, allowing for the integration of diverse renewable sources and the recovery of low-grade waste heat. This study aims to enhance energy self-sufficiency in a 5GDHC system utilizing photovoltaic (PV) generation as its primary energy source. The optimization targets two key variables: the thermal network's operating temperature and the charging/discharging schedule of the Thermal Energy Storage (TES) system. A dynamic simulation model was developed in Python to quantitatively evaluate an operational strategy that schedules heat pump operation during peak PV generation periods to store surplus thermal energy. While existing research has focused on the technical feasibility of 5GDHC, limited attention has been paid to operational optimization that accounts for renewable energy variability and TES integration. The simulation results indicate that the proposed strategy substantially improves system performance, as reflected by the Self-Consumption Ratio (SCR). With an increase in PV capacity from 25 kWp to 100 kWp, the SCR improves from 25% to 71%. This outcome suggests that a PV-driven operational strategy is effective in enhancing energy self-sufficiency and offers a practical basis for future empirical validation. Such strategies are pivotal for realizing smart energy districts and advancing the transition toward nearly Zero Energy Districts (nZEDs). |
| 7-2 | 5/21/2026 11:00 | Indoor Air Quality | SGM 123 | 107 | Chai Yoon Um, William Delp, Rowan Blacklock, Stefano Schiavon and Brett Singer | Lawrence Berkeley National Laboratory; University of California, Berkeley | Measured influence of supply airflow rate and supply air temperature on air mixing time in a room with overhead mixed system | Ventilation effectiveness Air distribution Airborne transmission Infectious aerosol Germicidal ultraviolet irradiation | Air mixing and movement are often driven by the design and operating conditions of the heating, ventilation, and air conditioning (HVAC) system, and are influenced by occupants and thermal gradients at windows and walls. Air mixing affects the indoor-generated pollutant dispersion and thus influences the effectiveness of ventilation and within-room air cleaning systems, including upper-room germicidal ultraviolet disinfection (GUV). In rooms with a ceiling exhaust and/or upper-room GUV, upward airflow from occupants can enable faster pollutant removal compared to well-mixed conditions. We used pulsed ethanol as a tracer and measured concentration at 2 s time resolution using fast-response metal oxide sensors at three levels: near the floor at 0.1–0.4 m, mid-height at 1.1–1.4 m, and 0.3 m from the 2.74 m ceiling. Test conditions included: HVAC off; supply air at ~380 (low) or ~1200 m3 h-1 (high) at neutral, cooling, or heating temperatures with 20% or 100% outdoor air; and added mixing fans. Air mixing times were determined from the start of ethanol release until the relative standard deviation of the concentrations fell below 20%, indicating an approximately well-mixed condition. We found that the air mixing time was longest with the HVAC off, followed by conditions with a low total supply airflow rate at all temperatures, and was fastest under high airflow at neutral/cooling temperatures or when mixing fans were added. The outdoor airflow rate (20% or 100%) did not significantly affect spatial heterogeneity or air mixing time. Under poor mixing conditions (HVAC off or low airflow rate) and with releases associated with heaters simulating occupants, several upper-room sensors peaked after the release, and mixing into the upper room and occupied space was slow. Under good mixing conditions (high airflow rate with neutral/cooling settings or added fan), air reached and mixed in the upper room more quickly and spread faster in the occupied zone. |
| 7-2 | 5/21/2026 11:00 | Indoor Air Quality | SGM 123 | 201 | Karl-Villem Võsa, Martin Kiil, Raimo Simson, Alo Mikola and Jarek Kurnitski | Tallinn University of Technology | Evaluating perceived stuffy air complaints through tracer gas experiments in a modern educational building in Estonia | Ventilation effectiveness contaminant removal effectiveness ventilation indoor air | This paper investigates ventilation-related complaints concerning stuffy air and inadequate air distribution in a modern educational building in Estonia. Insufficient ventilation performance has been associated with reduced well-being and productivity among students, whereas adequate ventilation supports improved learning outcomes. Ventilation effectiveness was assessed using CO₂ tracer gas measurements in a classroom, an office, and two halls. The results highlight key issues related to both the ventilation system design and its control parameters. The classroom and halls demonstrated adequate, though suboptimal, ventilation effectiveness (0.8–0.9), indicative of performance below ideal mixing conditions. In contrast, the office exhibited pronounced short-circuiting, where supply air largely bypassed the occupied zone by flowing between the structural slab and suspended ceiling to the extract terminal. Across all spaces, ventilation effectiveness declined when air change rates were reduced, reflecting partial occupancy conditions. This reduction led to uneven supply air distribution within the occupied zone, confirming the complaints of the occupants. |
| 7-2 | 5/21/2026 11:00 | Indoor Air Quality | SGM 123 | 215 | Wenhao Chen, David Moore, Rosemary Castorina, McKenna Thompson, Kyle Peerless and Kazukiyo Kumagai | Environmental Health Laboratory Branch, Center for Laboratory Sciences, California Department of Public Health; Intrinsic Environment, Health and Safety; Occupational Health Branch, California Department of Public Health; Office of Environmental Health Hazard Assessment, California Environmental Protection Agency | Comparison of Field Approaches for Characterizing Classroom Ventilation Rates (VRs) and Equivalent VRs for PM2.5 – A Case Analysis | Indoor air quality ventilation assessment carbon dioxide particulate matter | Ventilating classrooms with clean outdoor air is essential for reducing exposure to indoor-generated pollutants and maintaining good indoor air quality (IAQ). Routine assessments of ventilation rates (VRs) are necessary to ensure that classroom ventilation systems are operating as designed and delivering adequate outdoor air. Practical approaches available to characterize classroom VRs include direct airflow measurement, controlled release of tracer gas (and/or particles) followed by decay measurement, and estimation based on CO2 concentrations measured during school hours. In addition, the concept of equivalent clean outdoor airflow rates, or "equivalent VRs", for removal of fine particulate matter (PM2.5) has become increasingly relevant. “Equivalent VRs” refer to the total amount of “clean” air introduced by any combination of central mechanical ventilation, natural ventilation, and air-cleaning devices such as HVAC filters and portable air cleaners (PACs). This paper presents a case study conducted in two classrooms at a K-8 school in Stockton, California, to compare VRs and “equivalent VRs” for PM2.5 using three field-based approaches. Results indicate that although the three methods produced similar results in that they all showed lower VRs in the same classroom as compared to the other, the absolute VR values varied substantially across the different methods. These discrepancies highlight the need for caution in selecting a method and interpreting data, as the assumptions underlying each method, such as no leakage in HVAC ducts or sufficiently long stable occupancy periods during school hours, may not always be valid under real-world conditions. The controlled release of tracer gas (e.g., CO2) provided the most reliable results for VR estimation in this study because the classrooms met the required assumption for this method (i.e., well-mixed single zone) reasonably well. For PM₂.₅ removal, the “equivalent VRs” (estimated from tracer particle) were higher than the outdoor VRs (estimated with tracer gas), which suggests that air filters (i.e., MERV 13 filter and PAC) increased the total amount of “clean” air and further lowered indoor PM levels. Additionally, results indicate that the MERV 13 filter contributed more to PM₂.₅ reduction than the PAC in the mechanically ventilated classrooms that were studied. |
| 7-2 | 5/21/2026 11:00 | Indoor Air Quality | SGM 123 | 402 | Aysha Siddika and Aysegul Demir Dilsiz | University of Wyoming | Linking Global IAQ and Thermal Comfort Trends in Educational Spaces to LEED and AASHE STARS Ratings | Indoor Environmental Quality Thermal Comfort Sustainability Certifications AASHE | Green building certifications promise healthier learning spaces, but do they actually deliver better indoor environmental quality for students? As climate change and post-pandemic realities reshape building priorities, understanding indoor environmental quality (IEQ) in educational spaces has never been more critical. This study systematically reviewed 122 peer-reviewed papers to map global trends, identify research gaps, and chart future directions in IAQ and thermal comfort for educational buildings. Publication activity has grown steadily over the past two decades, peaking in 2023 with 15 studies; a surge likely driven by heightened sustainability awareness, updated performance standards (ASHRAE, LEED, BREEAM), and ventilation priorities following COVID-19. Universities dominate literature (48.4%, 59 papers), followed by middle schools (18.0%), elementary schools (16.4%), and high schools (8.2%). Classrooms remain the most studied indoor space (47.5%, 58 papers), underscoring their centrality to daily student life, while support spaces, such as offices, dormitories, laboratories, and reading rooms, are severely underrepresented. Research has primarily focused on indoor air quality (IAQ) and thermal comfort, while behavioral responses and performance outcomes remain understudied. This gap highlights the need for more human-centered investigations that directly link environmental conditions with occupant behavior and performance in work and study contexts. Geographically, research is concentrated in regions such as Oman, China, the UAE, Italy, and the UK, with notable gaps in South America, Africa, and parts of Asia. We integrate these literature insights with AASHE STARS data on sustainability-rated universities, including building-level details of LEED-certified facilities and square footage. By bridging academic literature with institutional performance metrics, this research aims to identify paths that help achieve both environmental sustainability and human well-being. The findings provide useful insights for designers and administrators, supporting evidence-based approaches to improving comfort, health, and energy use in educational environments. |
| 7-2 | 5/21/2026 11:00 | Indoor Air Quality | SGM 123 | 513 | Yi Fang, Haoran Zhao, Tim Tyner, Stephanie M. Holm, Brett C. Singer, Marion L. Russell, Anabelle Garza, Arlette Garcia-Ramirez, Briseida Vasquez, Debra Manzo Garcia, Jesus Rivera, John R. Balmes and Amy Dryden | AEA Clean Energy; Central California Asthma Collaborative; Fielding School of Public Health, University of California Los Angeles; Lawrence Berkeley National Laboratory; Lawrence Berkeley National Laboratory,; University of California San Francisco; University of California, San Francisco | Measured Indoor Nitrogen Oxides in Homes with a Child with Asthma and Gas or Induction Electric Cooking | Indoor Air Quality Real-Time Monitoring Air Pollution Exposure Randomized Controlled Trial Asthma | The Cooking Energy and Ventilation Impacts on Children’s Asthma (CEVICA) study is a randomized control trial investigating the effects of replacing gas with induction electric ranges in the homes of children with asthma in California’s San Joaquin Valley. Indoor air quality parameters and respiratory health indicators were measured over 2-week intensive at Baseline and after consecutive 3-month study phases, with half getting electric cooking at the start of Phase 1 and others in Phase 2. Indoor air measurements included time-integrated NO₂ and NOX by passive sampler and time-resolved NO₂ by electrochemical sensors. In the first 40 homes, data were collected during 61 intensives for gas cooking and 55 for induction. Cooking was identified using temperature sensors above the cooktop. Pollutant events were identified from sharp rises in concentrations Time integrated NOX species were lower with electric cooking, with mean differences of 14.2 ppb for NO2 (95% CI: 9.6, 18.7; p < 0.001), 55.6 ppb for NOX (95% CI: 30.4, 80.9; p < 0.001), and 41.5 ppb for derived NO (95% CI: 19.7, 63.2; p < 0.001). A paired, within home analysis showed larger reductions in Group 2 (gas to induction) than Group 1 that remained electric across Phase 1 and Phase 2, for NO2 (mean difference in Δs of 10.5 ppb; 95% CI: 5.6, 15.4; p < 0.001), NOX (32.3 ppb; 95% CI: 10.0, 54.5; p=0.007), and derived NO (21.8 ppb; 95% CI: 3.6, 40.0; p=0.022). Compared to electric cooking, gas had much higher rates of associated NO2 events, and larger above-baseline NO2 peaks. These preliminary results are consistent with prior findings that shifting to induction cooking can substantially lower indoor NO₂ compared with gas cooking. |
| 7-3 | 5/21/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 195 | Alex Nwosu and James Hunter | Morgan State University | “Standard Retrofit First: Scalable Energy Efficiency Strategies for Legacy Row Homes” | Energy efficiency retrofit row homes affordability resilience Lifecycle cost thermal comfort | Vacant and aging housing stock in shrinking U.S. cities presents a persistent barrier to equitable energy transitions. Deep Retrofits (DR) have demonstrated strong performance in reducing energy demand, but their high capital costs and long payback periods limit feasibility in low- and moderate-income communities. This study develops and validates the Standard Retrofit (SR)—a mid-tier, value-engineered framework designed to balance energy performance, affordability, and scalability in legacy row homes. Benchmarking against a LEED Platinum retrofit case in Baltimore, SR substitutes high-cost systems with cost-optimized alternatives while retaining core efficiency and resilience outcomes. DesignBuilder/EnergyPlus simulations of middle and end-unit row homes showed that SR achieved 34% reductions in energy use intensity (EUI), approaching the 44% reductions of DR, while maintaining indoor thermal comfort and survivability during simulated five-day outages. Lifecycle cost analysis demonstrated SR’s payback in 10–12 years, compared to over 20 years for DR, positioning SR as more accessible for households facing affordability constraints. By aligning with Baltimore Green Building Standards (LEED Silver equivalent), SR demonstrates both regulatory compliance and replicability potential. Scaling SR across 15,000 legacy row homes could yield significant reductions in urban energy demand and greenhouse gas emissions, while enhancing housing resilience under climate stress. This work contributes a novel, cost-effective retrofit pathway that bridges the gap between baseline conditions and deep retrofits, offering a replicable model for legacy housing stock in shrinking cities worldwide. |
| 7-3 | 5/21/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 203 | Yi-Ting Lai and Yaw-Shyan Tsay | Department of Architecture, National Cheng Kung University | Embodied Carbon Benchmarks for Residential Buildings in Taiwan | Whole Life-Cycle Assessment Embodied Carbon Benchmarking | While embodied carbon (EC) research in buildings has been extensively conducted over the past decades, practical benchmarking of Embodied Carbon Intensity (ECI) remains relatively limited compared to the well-established Energy Use Intensity (EUI) standards in building policies. This gap between academic research and practical implementation highlights the need for more comprehensive ECI benchmarking studies to support evidence-based policy making. In this study, we conducted a benchmarking project for Embodied Carbon Intensity (ECI) of residential buildings through calculations from 35 multi-family residential buildings in Taiwan. The results show that ECI ranges approximately from 434.1 to 514.4 (kgCO₂/m².60yr). Furthermore, among all life cycle stages, the manufacturing and transportation stages (A1~A4) account for the highest proportion at approximately 72.9%~88.7%, while among sub-projects, the main structure accounts for the highest proportion at approximately 43.1%~68.1%. |
| 7-3 | 5/21/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 293 | Muhammad Asim, Muhammad Furqan Siddiqui and Farooq Riaz Siddiqui | The Hong Kong Polytechnic University; The Hong Kong UNiversity of Science and Technology | Retrofit Pathways for HVAC Decarbonization: A sustainable solution for harnessing ultra-low-grade waste heat for energy efficiency and net-zero buildings | HVAC retrofit Ultra low grade Net-zero transition Waste heat recovery 4E analysis | Buildings are responsible for nearly one quarter of global energy consumption, with 30-50% of this demand arising from Heating, Ventilation and Air-Conditioning (HVAC) systems. While essential for ensuring indoor comfort, conventional vapor compression cycle (VCC) units reject a substantial share of ultra-low-grade heat (<80 °C) to the urban environment. This not only represents a significant loss of useful energy but also contributes to local temperature rise and intensifies urban heat island effects, thereby driving further cooling demand. In this work, a retrofit-based strategy is proposed to integrate a single-stage organic Rankine cycle (SS-ORC) with the condenser of a conventional VCC system. A novel desuperheating-driven waste heat recovery approach, combined with an Adaptive Pinch Point (APP) method, is used to maximize the recoverable work potential under varying operating conditions. Multiple working fluid (WF) combinations are assessed, including low-GWP fluids (R1233zd (E), R1234ze (E), R1336mzz (Z)) for the VCC and zeotropic mixtures (R600/R600a and R365mfc/R152a) for the ORC. A comprehensive energy, exergy, economic and environmental (4E) analysis is conducted to evaluate the performance and sustainability of the proposed system. Among the selected working fluid candidates, R1234ze (E) in the VCC with R365mfc/R152a (0.1/0.9) in the ORC delivered the most favorable outcomes. This pair achieved a 3.76% enhancement in overall COP, ORC exergy efficiency of 52.5%, and the lowest levelized cost of electricity (0.061 US$/kWh). From an economic standpoint, the system yielded a high net present value (US$ 22.80 million) with a discounted payback period of only 3.8 years. Environmentally, the retrofit achieved an annual reduction of 70×106 kg/yr. of CO2 emissions, corresponding to carbon credit benefits of nearly US$ 0.83million per year. Beyond technical and economic viability, the integration reduces heat rejection, indirectly lowering surrounding cooling loads and improving the sustainability of indoor environments. The findings establish the proposed system as an effective and economically feasible retrofit method for enhancing energy efficiency and minimizing the carbon footprint of HVAC systems to support the energy conservation, net-zero transition and the sustainable built environment. |
| 7-3 | 5/21/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 389 | Fatemeh Yazdandoust, Siddhartha Sen and Kamalesh Panthi | Morgan State University | Energy Efficiency Solutions for Baltimore Housing | Energy efficiency Passive design Renewable energy Sustainable housing | Energy burden, poor indoor air quality, high levels of poverty and vacancy rates are among the major challenges facing Baltimore City. These challenges have negative impacts on residents’ health, community and environmental sustainability. Energy-efficient housing can address these interconnected issues to improve energy preservation and quality of life for Baltimore residents. A research project at Morgan State University investigates strategies to propose practical solutions using an on-campus tiny house as a sample model. The study aims to develop cost-effective interventions that residents can realistically implement in their residential units. The methodology involves investigating potential passive and active sustainable strategies, conducting comprehensive energy simulation and analysis, and proposing the most appropriate solutions for implementation by residents. The research prioritizes solutions based on affordability, ease of implementation, and maximum energy savings potential. The project focuses on both active and passive energy-efficient strategies, including daylighting and lighting improvements, natural ventilation application, renewable energy integration, building envelope and glazing enhancements, green wall incorporation, and CO₂ reduction measures. Energy modeling software evaluates the performance of different strategies under Baltimore's specific climate conditions. The tiny house demonstration model serves as a testing ground for various interventions, allowing researchers to quantify potential energy savings, cost reductions, and indoor air quality improvements. This hands-on approach ensures that proposed solutions are practical and achievable for typical Baltimore housing stock. The on-campus tiny house also serves as a demonstration model for community outreach and as a hands-on learning laboratory for students studying sustainable building practices. This research contributes to addressing Baltimore's housing challenges by providing evidence-based, accessible solutions that residents can adopt to improve their living conditions while reducing energy costs and environmental impact. |
| 7-3 | 5/21/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 394 | Mohammad Hamdan, Hamed Moradi, Paria Saadatjoo and Parham Mirzaei | Department of Architecture, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran; Department of Architecture, Faculty of Engineering and Design, Middle East University, Amman, Jordan; Department of Civil and Architectural Engineering - Building Science, Aarhus University, Aarhus, Denmark; Department of Construction, Faculty of Architecture and Urban Planning, Shahid Beheshti University, Tehran, Iran | Microclimate Building Energy Retrofitting: Assessing Urban Morphology Impacts on Cooling Demand and Carbon Emissions | Urban Heat Island Microclimate Modelling Urban Morphology Building Retrofit Cooling Energy Performance. | Urban microclimate conditions created by the Urban Heat Island (UHI) phenomenon substantially impact building energy consumption and carbon footprint, yet conventional building retrofit practices frequently neglect these localised environmental complexities. This research investigates energy performance and CO2 emissions of residential buildings across varying urban environments before and after implementing retrofit measures. The study utilises an integrated simulation methodology that combines urban environmental parameters with building performance evaluation. The approach integrates computational fluid dynamics (CFD) through ENVI-met 5.8 for urban microclimate modelling with building energy simulation via DesignBuilder for energy and emissions assessment. Conducted in Amman, Jordan, a city experiencing intensified UHI effects due to rapid urbanisation and climate change, the investigation examines a representative two-story residential building (450 m2) positioned across five distinct urban locations, each characterised by different morphological and density configurations. During peak summer conditions, cooling energy constitutes the predominant energy demand, with greater proportions observed in high-density urban environments. The simulation approach incorporates regional building standards and examines various retrofit interventions, including thermal envelope enhancements, HVAC system modifications, and passive cooling technologies. The research analyses how urban context influences both initial energy performance and retrofit intervention effectiveness through variations in consumption patterns and related carbon emissions across different urban densities. Expected results indicate that identical buildings will experience significant energy consumption variations across different urban densities, primarily attributed to microclimate-driven changes in wind patterns and ambient temperatures that influence cooling requirements. |
| 7-3 | 5/21/2026 11:00 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 446 | Min-Gyu Shin, Hye-Jin Kim, Soo-Hwan Park and Dong-Hyun Seo | Department of Architectural Engineering, Chungbuk National University | Development of Detailed EUI Benchmarks for South Korea’s Residential Building Stock | 1. residential buildings 2. energy benchmarks 3. household energy survey 4. energy use intensity | In South Korea, residential buildings account for approximately 60% of total building energy consumption, making efficiency improvements in this sector critical for meeting national carbon reduction goals. The government introduced Zero Energy Building Certification (ZEBC) and Building Energy Efficiency Rating Certification (BERC) programs to promote energy efficiency, but their simplified criteria have notable shortcomings. For example, energy use intensity (EUI) tends to decrease with increasing building size, consumption varies across climate zones, and these certifications cover only five end uses (heating, cooling, ventilation, hot water, and lighting) instead of accounting for total energy consumption. In contrast, countries such as the United States, United Kingdom, and Australia employ large-scale household energy surveys to develop benchmarks that reflect actual usage. Similarly, recent studies in Korea have utilized microdata from the national Household Energy Panel Survey (HEPS) to refine benchmarks and address these limitations. Building on this approach, this study uses HEPS microdata from 2017–2019 (approximately 8,000 households nationwide) to develop more realistic residential energy benchmarks. Homes are grouped by housing type, net usable area (NUA), year of construction, and climate zone, resulting in 54 distinct categories. For each category, typical annual and monthly energy use intensities are calculated to serve as benchmarks. Multi-year averaging and degree-day normalization are applied to mitigate year-to-year fluctuations and weather-driven variability, ensuring that the resulting baseline values are robust and representative of typical usage. To further improve accuracy, this study proposes a regression-based adjustment to refine these benchmarks based on a dwelling’s floor area (NUA) and household size. The adjusted benchmarks closely approximate actual consumption patterns and significantly improve upon current certification baselines. These benchmarks provide practical targets for energy-efficient building design and serve as reference points for evaluating the energy performance of existing homes. |
| 7-4 | 5/21/2026 11:00 | Building Technology and Performance | GFS 116 | 83 | Tatsuya Miyata, Tatsu Kishida, Hiroki Ikeda, Yasuaki Kaneko, Shohei Miyata and Yasunori Akashi | DAI-DAN CO., Ltd.; Mitsubishi Heavy Industries, Ltd.; Taikisha, Ltd.; The University of Tokyo | Development of a High-Resolution Dynamic Emulator for a Chiller Plant and Its Application to Control Improvement | Smart Building Dynamic Modeling Emulator Module Chiller One-Second Interval Data Fault Diagnosis Control Optimization | With the rise of smart buildings enabling the scalable deployment of applications for environmental and energy system, a verification platform is essential to validate their effectiveness, advantages, and safety. However, conventional energy simulations, typically using 1-hour intervals, fail to capture transient behaviors like hunting and overshoot, leaving risks of instability. To address this, this paper developed a high-fidelity dynamic "emulator"—a detailed simulation reproducing physical phenomena and control logic—using OpenModelica. Based on 1-second interval data from an actual building, the model incorporated chiller transients, specific control logic with deadbands, and piping thermal delays. The emulator successfully reproduced the system's dynamic behaviors and revealed actual sensor errors and control deficiencies. Furthermore, through a case study on control improvement to determine appropriate parameters for system stabilization, we demonstrated that optimizing staging thresholds could eliminate hunting and stabilize temperatures. In the future, this emulator serves as a critical testbed for developing and verifying smart building applications, enhancing both energy efficiency and system stability. |
| 7-4 | 5/21/2026 11:00 | Building Technology and Performance | GFS 116 | 84 | Myeongwon Chae, You-Jeong Kim and Yun Kyu Yi | School of Architecture, University of Illinois Urbana-Champaign | Data-Driven Assessment of Air-Conditioning System Sizing Using Runtime and Indoor Humidity Performance | HVAC sizing Energy efficiency Humidity control Smart thermostat Indoor thermal comfort | Oversized air conditioning (AC) systems often consume excess energy due to frequent on-off cycling and reduced efficiency, leading to higher costs and environmental impact. While such systems cool spaces quickly, they often perform poorly in controlling indoor humidity, which can promote mold and bacterial growth, degrading indoor air quality. Thus, evaluating AC sizing and performance during operation is critical. However, in large-scale housing stocks, nameplate capacity information is rarely available. While short cycling can offer a general indication of improper sizing, it may not be a reliable standalone metric, as factors such as open windows or internal heat gains can also affect cycle duration. To address these limitations, this study examines the relationship between AC runtime characteristics and dehumidification performance using real operation data. The goal is to assess the potential of runtime and humidity data as indicators of oversized AC systems in existing housing. Data were collected at 5-minute intervals from the ecobee smart thermostats in 300 homes across Florida, Michigan, and Louisiana. Instead of relying solely on compressor cycle duration, we introduce the compressor-fan runtime ratio (CFR), defined as compressor runtime divided by fan runtime, to better represent the behavior of oversized AC systems. For assessing dehumidification performance, we use the difference between indoor and outdoor relative humidity, assuming that a larger differential indicates more effective dehumidification. Preliminary results show a moderate correlation (average coefficient: 0.34) between the CFR and humidity differential. Homes with a low CFR tended to have smaller humidity differentials, indicating poor dehumidification. This likely results from fans continuing to run after the compressor shuts off, allowing re-evaporation of moisture from the coil into the indoor air. These homes also exhibited shorter compressor cycles, supporting the oversizing hypothesis. These findings demonstrate the potential of using smart thermostat data to identify dehumidification issues caused by oversized AC units. As part of the full study, we will generate synthetic datasets to systematically test the effects of oversizing under controlled conditions, thereby improving the robustness of the analysis by isolating confounding factors. We will also expand the analysis from three states to all 50 U.S. states. |
| 7-4 | 5/21/2026 11:00 | Building Technology and Performance | GFS 116 | 95 | Flavia Barone, Loubna Ait Lahsen, Myriam Bahrar and Mohamed El Mankibi | ENTPE – University of Lyon, LTDS, 3 rue Maurice Audin, Vaulx-en-Velin 69120, France | Hybrid control strategies for energy efficiency, thermal comfort and indoor air quality in residential compact HVAC–DHW systems | compact HVAC–DHW systems heat pump hybrid control strategy thermal comfort indoor air quality | To address the growing challenges of energy efficiency in buildings while ensuring indoor thermal comfort and air quality, advanced and sustainable energy systems are being developed. Among them, multifunctional compact systems integrate ventilation, space heating, cooling, and domestic hot water production into a single device. These systems are particularly well-suited for highly energy-efficient buildings due to their compactness and ease of installation. However, their overall performance critically depends on the implementation of control strategies capable of managing trade-offs between thermal comfort, indoor air quality, and energy consumption. This study proposes a numerical modeling approach coupling a compact system model with a dynamic building energy model to evaluate and compare the effectiveness of different control strategies. The compact system model replicates the behavior of an experimental prototype composed of a preheating coil, a heat exchanger, a heat pump, a post-heating coil, and a domestic hot water storage tank. System performance is assessed under representative winter and summer conditions based on predefined occupancy schedules, domestic hot water draw profiles, thermal comfort targets, and indoor air renewal criteria. Several hybrid control strategies are explored, including hierarchical multi-criteria control — prioritizing supply airflow rate, supply air temperature, or hot water supply — as well as weighted multi-objective control and adaptive seasonal control. The performance of the compact system is benchmarked against a conventional setup using electric resistance heaters for space heating and a residential split air conditioner for cooling. Results show that strategies prioritizing air renewal target tend to increase energy use and peak loads, while those focusing on thermal comfort may compromise ventilation performance. Hybrid strategies can achieve a more balanced outcome depending on operating conditions and user-defined priorities. Overall, the compact system demonstrates strong potential for energy savings compared to the conventional systems, owing to its capability to operate under a unified control strategy and its inherently higher efficiency, particularly when combined control logic is applied. This work highlights the critical importance of combined control strategies to maximize the performance of integrated compact systems and supports their broader adoption in future building designs. |
| 7-4 | 5/21/2026 11:00 | Building Technology and Performance | GFS 116 | 461 | Darwish Darwazeh, Narges Zaeri and Farzeen Rizvi | National Research Council Canada | Operational Control and Air Mixing Fault Detection and Diagnostics in Rooftop Units | Fault Detection and Diagnostics Building Energy Performance Inverse modelling Rule-based methods Rooftop Units | Soft faults in rooftop units serving commercial buildings often go unnoticed during regular operation, masking underlying control and scheduling issues that lead to operational inefficiencies, energy waste, and compromised occupant comfort. Unlike hard faults, soft faults, such as scheduling errors, setpoint conflicts, and damper control issues, do not cause immediate system failure, making early detection critical to prevent escalating equipment wear. Conventional fault detection and diagnostics applications often employ simple rule-based algorithms with limited detection and diagnostic capabilities, leaving soft faults affecting rooftop units undetected. This study presents hybrid fault detection and diagnostic algorithms that utilize rule-based thresholds, statistical analysis, and inverse modelling to identify operational mode anomalies, operational mismatch faults, and mixing box faults using building automation system data. The hybrid approach incorporates diagnostic capabilities to isolate fault patterns and pinpoint their root causes, enabling targeted maintenance such as recalibrating schedules and making damper adjustments. The hybrid algorithms are tested using operational data from a rooftop unit serving a commercial building in Quebec, Canada. The methodology is demonstrated through practical examples, illustrating its effectiveness in detecting soft faults and isolating their root causes. For example, an operational mismatch fault was detected in two out of five thermal zones, with simultaneous heating and cooling detected in 8.77% and 8.16% of valid data points, respectively, during the cooling season, suggesting control misconfigurations or setpoint conflicts in the flagged zones. The proposed hybrid approach, which leverages existing BAS data, offers a cost-effective solution that supports building operational decisions, reduces energy consumption and greenhouse gas emissions, and enhances occupant comfort. |
| 7-4 | 5/21/2026 11:00 | Building Technology and Performance | GFS 116 | 490 | Haruka Kitagawa, Takuji Nakamura, Ko Shigemori, Sei Ito and Daisuke Sumiyoshi | Kyushu University; Shimizu Corporation | Optimum Operation of a Heat Source System considering Bidirectional Heat Interchange among Multiple Buildings | Heat interchange Heat source system Mixed-integer linear programming Operation planning Energy management | As the energy consumption of heat source systems for heating and cooling constitutes approximately 30-40% of the total energy consumption of buildings, the operation strategy of heat source systems is essential for reducing energy consumption. Previous studies showed that district heating and cooling, which centralizes the heat source system in a single plant and connects multiple buildings via a heat supply network, can supply heat more efficiently than localized systems in individual buildings owing to capacity optimization. Few studies focused on optimizing distributed heat source systems considering bidirectional heat interchange. This study aims to develop an operational planning system based on a mixed-integer linear program (MILP) to optimize the energy consumption of a heat source system considering the bidirectional heat interchange among multiple buildings. We implemented the system in a facility consisting of four buildings and the heat source units were distributed across all buildings. Each building was connected by bidirectional heat interchange pipes. The operational planning system formulates a 24-operation plan that regulates the number of operating units, including heat source equipment and pumps, and their outputs, every 30 minutes. In a demonstration experiment, the MILP-based operation was compared with the rule-based operation to evaluate its energy efficiency under actual operating conditions in buildings during summer. In the rule-based operation, each building managed its heat source units based on its respective cooling demands. Similarly, in the MILP-based operation, the heat source units were operated in each building when the cooling load was large. Regarding the system coefficient of performance (COP), a slight difference was observed during the corresponding period. However, when the cooling demand was small to medium, such as at night, the operation of the heat source units was consolidated, and they supplied heat to other buildings to maintain high-efficiency operating points. The system COP of the MILP-based operation was higher than that of the rule-based operation when the outdoor temperature was below 30 ℃. The MILP-based operation that considers bidirectional heat interchange was particularly effective in the intermediate season. |
| 7-5 | 5/21/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 101 | 20 | Wooyoung Jung, Prosper Babon-Ayeng, Kevin Keene, Sophia Witt and Jessica Baweja | Pacific Northwest National Laboratory; The University of Arizona | Do Common Performance Metrics in Indoor Environmental Quality Research Represent Actual Office Work? A Survey-Based Assessment | Office Worker Performance Indoor Environmental Quality Performance Evaluation Metrics Applicability Assessment | Existing studies in the field of indoor environmental quality (IEQ) have relied on a limited set of objective performance metrics, including call handling time, keystrokes, and cognitive performance tests, to represent office worker performance. However, these metrics may capture narrow and task-specific aspects of performance and may not represent the broader, multi-faceted nature of office work. This study assessed the applicability of such objective metrics by surveying office workers on whether and to what extend these metrics are relevant to their work and how much of their office work can be quantitatively measured. A total of 387 survey responses from a variety of occupations were analyzed and we found significant variability in the relevance of some performance metrics across occupations (e.g., call handling time, attention and concentration, executive functioning, language skills, and processing speed) through analysis of variance (ANOVA). The results indicate the heterogeneity of office work and the difficulty in developing a universal office worker performance prediction model applicable to all types of office workers. This study sheds light on the needs of adaptability in office worker performance data analyses and interpretations and paves the way for customized performance prediction models with respect to IEQ, specific to occupation types or individuals. |
| 7-5 | 5/21/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 101 | 102 | Fariza Sabit, Christian Rodriguez, Eric Ravussin and Dolaana Khovalyg | Laboratory of Integrated Comfort Engineering (ICE), École polytechnique fédérale de Lausanne (EPFL); Pennington Biomedical Research Center, Louisiana State University | Modeling the circadian dynamics of resting energy expenditure for the built environment | Resting energy expenditure metabolic rate circadian rhythms | Human Resting Energy Expenditure (REE) exhibits a robust circadian oscillation, yet current thermal comfort standards and building simulations typically rely on static metabolic assumptions. This work aims to integrate chronobiological principles into building engineering by developing a dynamic REE model based on accessible parameters. We analyzed continuous 24-hour energy expenditure data from six adults in a metabolic chamber under unstructured, "free-living" conditions. By employing a signal processing pipeline combining Asymmetric Least Squares smoothing with Linear Mixed Models, we isolated the endogenous circadian rhythm from behavioral noise, such as physical activity and the thermic effect of food. Results confirm a consistent metabolic peak in the biological afternoon (13:00–17:30) and indicate that Body Surface Area (BSA) significantly modulates both the metabolic baseline and the amplitude of the circadian swing. While this model targets REE during minimal activity (i.e., seated or reclining) and does not directly generalize to high-intensity tasks, it refines the physiological baseline upon which all other energy costs are superimposed. Accordingly, this time-dependent model provides a method to predict occupant heat generation based on clock time and body composition, supporting more accurate thermal comfort controls and building energy performance. |
| 7-5 | 5/21/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 101 | 162 | Shaymaa Hussain Al Marzouqi, Dongwoo Jason Yeom, Kamil Kaloush and Elham Fini | Arizona State University; Clemson University | Daylight Timing and Natural Scent on Cognitive Performance in Office Settings without Outdoor View | Indoor Environmental Quality (IEQ) Daylight Scent Cognitive Performance Well-being | The role of multisensory environments in supporting human performance has become a growing focus in indoor environmental quality (IEQ) research. This study examines the combined effects of daylight timing and natural scents on cognitive performance in office settings that lack outdoor views. A controlled experiment exposed participants to morning and afternoon daylight conditions combined with rosemary or frankincense scent, while environmental variables such as illuminance, color temperature, indoor air quality, and thermal conditions were continuously monitored to ensure stable indoor conditions. Physiological responses were tracked using wearable sensors measuring heart rate, heart rate variability, skin conductance, skin temperature, and brain activity (EEG). Cognitive performance was assessed through validated digital tasks targeting attention, memory, and executive function, alongside surveys on comfort and well-being. The study explores whether rosemary in the morning and frankincense in the afternoon provide cognitive benefits compared to using scents without regard to timing. Preliminary trends suggest that the timing of scent use may influence cognitive outcomes, with certain scent–time combinations being more effective in supporting cognitive performance than using scents at random times of day. These results point to the importance of considering when scents are used in relation to daylight exposure, even in windowless environments. By showing how sensory factors interact to influence cognitive performance, this study provides new insight into multisensory IEQ strategies. The findings may inform workplace design practices aimed at improving productivity and well-being where access to outdoor views is limited. |
| 7-5 | 5/21/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 101 | 412 | Hernan Rosas, Ming Hu and Edward Bernat | University of Maryland; University of Notre Dame | Advancing Pathways To Occupant Mental Wellbeing: Mapping Attention Restoration and Stress Reduction in Biophilic Design to a Validated Mental Health Framework | Neuroarchitecture Attention Restoration Theory Stress Reduction Theory Biophilic Design Mental Health | Foundational to biophilic design—natural features applied to architectural design—Attention Restoration Theory (ART) and Stress Reduction Theory (SRT) posit key cognitive and affective mechanisms underlying improved occupant wellbeing from exposure to nature and biophilic architecture. However, ART and SRT are limited by underspecified core concepts, and underlying mechanisms that are not well tied to cognitive neuroscience models, limiting neuroarchitecture research. We propose a mapping between ART and SRT and the National Institute of Mental Health’s Research Domain Criteria (RDoC)—a system of transdiagnostic factors underlying normative and psychopathological behavior. The RDoC factors have clear referents in both genetics and cognitive neuroscience and represent an integration of highly established empirical models. We propose mapping ART and SRT to the 3 domains (from 6 total) most central to cognitive-affective processing, i.e.: positive valence (PV), negative valence (NV), and cognition (COG). ART’s concept of directed attention fatigue aligns with the COG domain, which RDoC specifies in terms of attention, perception, working memory, and cognitive control. SRT emphasizes decreased stress and increased positive affective responding, which aligns with the PV and NV domains. Our group’s recent work has demonstrated that functional impairment in psychopathology is associated with increased NV and decreased PV and COG, and that exposure to nature increases PV and COG and decreases NV. Mapping ART and SRT to RDoC’s empirically defined domains of mental health, can provide an empirically supported path for work on neuroarchitecture and built environment research to more precisely understand of how biophilic architecture influences occupant wellbeing. |
| 7-5 | 5/21/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 101 | 413 | Andrew Cook and Yumna Kurdi | University of Idaho | Applying Technology to Learning: Visualizing Environmental Data Through Augmented Reality | visualization Augmented Reality Digital Twin STEM LiDAR | Creating digital twins of physical environments provides an effective way to visualize data collected by environmental sensors. This research introduces the development of an Augmented Reality (AR) application that uses iOS devices equipped with LiDAR technology, along with Unreal Engine 5, a gaming engine, to generate interactive digital twins. The combination of digital twins and AR will help with data collection and analysis, allowing for the visualization of environmental data in educational settings, ultimately helping to teach students and improve their surroundings. The iPhone's LiDAR sensor captures point clouds that record depth, geometry, and surface characteristics of the physical environment. Meanwhile, integrated cameras can collect various sets of color information, including visible light and thermal imagery. This data will directly mapped onto the reconstructed environment in the digital space, resulting in a digital twin that is rich in both structural details and contextual surface data. Unreal Engine's networking and visualization capabilities enable the seamless transfer of captured information from mobile devices and various environmental sensors to the digital twin. This allows users to view, analyze, store, and share environmental data easily. This work presents an AR application that serves as both a research tool and an educational platform. The system collects Indoor Environmental Quality (IEQ) data, which includes temperature, relative humidity, carbon dioxide concentration, and other factors, and projects these datasets onto the digital twin of the scanned space. Teachers and students can interact directly with the visualized data within AR, thereby supporting STEM learning, especially learning about building science and technology and generating actionable insights for their schools. Additionally, these visualizations can aid in decision-making regarding building performance and occupant well-being. Beyond its analytical capabilities, the application engages students and educators with STEM concepts through hands-on interaction with environmental data and immersive AR technology. By merging LiDAR-based spatial scanning with real-time environmental monitoring, this research showcases the potential of digital twin technologies not only to enhance indoor environmental awareness but also to expand access to data-driven learning experiences. |
| 7-5 | 5/21/2026 11:00 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 101 | 526 | Jinmog Han and Yunjeong Mo | Iowa State University | A design-oriented framework for smart home energy management system interfaces to support energy-saving occupant behavior | home energy management system human-building interaction human-building interface energy-saving behavior | As smart home energy management systems (SHEMS) become increasingly common in residential buildings, there is a growing need for interfaces that move beyond passive energy reporting to actively support energy-saving occupant behavior. However, many existing SHEMS interfaces remain technology-driven and often overlook the cognitive processes and interaction mechanisms that shape user understanding, engagement, and decision-making. As a result, energy feedback and control features frequently fail to translate into sustained behavioral change. This study proposes a design-oriented framework for SHEMS interfaces that explicitly connects functional requirements with usability considerations. The framework is grounded in five core interface functions: Information Delivery, Real-Time Feedback, Personal Motivation, Control Flexibility, and Social Comparison. These functions were systematically derived using Abstraction Hierarchy (AH) from cognitive systems engineering, which enables structured reasoning from high-level system purposes and user intentions to generalized functions and concrete interface elements. To guide how these functions should be realized in interaction design, Norman’s Design Principles were adopted as a usability-focused foundation and reformulated as explicit usability goals. The integration of AH-based functional modeling and usability goals results in a function–usability matrix that yields 30 actionable design guidelines. This matrix supports both forward interface design and diagnostic evaluation by maintaining traceability between user goals, system functions, and interaction design decisions. To demonstrate practical applicability, a five-function SHEMS interface prototype was developed. The prototype illustrates how the proposed framework can be instantiated in concrete interface layouts that support awareness, interpretation, motivation, and user control within a unified system, serving as a design-oriented demonstration rather than an empirical evaluation. Overall, this study contributes to human-building interaction research by offering a replicable, design-oriented methodology for developing SHEMS interfaces that are cognitively aligned, usable, and supportive of energy-saving behavior in residential contexts. |
| 7-6 | 5/21/2026 11:00 | Smart Cities and Green Infrastructure | GFS 207 | 209 | Dahyun Oh and Soowon Chang | Purdue university, School of Construction Management Technology | Transportation Infrastructure Innovation through Optimal Solar PV Deployment Planning in DOT Facilities and Right-of-Way using a Geographic Information System-based Multi-Criteria Decision Making | Solar Development Multi-Criteria Decision Making (MCDM) Geographic information system (GIS) Transportation infrastructure Right-of-Way (ROW) | State departments of transportation (DOTs) have sought opportunities to promote renewable energy development on public lands while enhancing the value of these assets. Among these efforts, solar photovoltaic (PV) systems have emerged as a promising solution, with several DOTs across the United States demonstrating feasibility by installing solar projects within their Right-of-Way (ROW) areas. However, the applicability of PV deployment remains highly context-dependent and influenced by geographical, environmental, regulatory and permitting requirements. This variability creates uncertainty and poses major challenges for DOT agencies, particularly in states such as Indiana that are at an early stage of solar adoption and lack prior experience. To address this gap, this study aims to guide pilot site selection under conditions of limited data and uncertainty by developing a geographic information system (GIS) based multi-criteria decision making (MCDM) framework. Evaluation criteria are derived through literature review and expert interviews across four categories: technical, economic, environmental, and social factors. Eight key factors including solar radiation, land slope, flood risk, land cover, electricity demand, distance to the transmission lines, land availability, and public support are identified. Two weighting methods, Interval-AHP and Fuzzy-AHP, and two scoring methods, VIKOR and TOPSIS, are applied, and the results from different method combinations are compared to explore robustness and consistency of site selection outcomes. This study focused on the Indiana DOT (INDOT) facilities and ROW sites statewide. Out of 165 active candidate sites, 111 sites are identified as suitable for solar development and the highest ranked site is identified as Winchester unit with a 0.92 score considering all four criteria. This study offers practical guidance for INDOT and other late adopting DOTs by demonstrating a decision-making process for advancing solar development under conditions of data scarcity and uncertainty. |
| 7-6 | 5/21/2026 11:00 | Smart Cities and Green Infrastructure | GFS 207 | 388 | Vimal Preet, Dr. P.S. Chani and Dr. Sandeep Agarwal | Indian Institute of Technology, Roorkee; University of Alberta | The Role of Urban Form and Green Cover in Residential Energy Consumption: A Pilot Study of Sector 22, Chandigarh | Urban Morphology energy consumption residential cluster Analysis Chandigarh | Global urbanization and economic growth are projected to significantly intensify energy demand, with estimates suggesting a 70% increase in urban energy consumption by 2050 compared to 2013. Among the multiple drivers of this trend, urban morphology plays a critical role in shaping both energy demand and its spatial distribution. Urban morphology encompasses the structure of cities—such as street patterns, open spaces, and canopies—the built form defined by density, layout, and building height, and the broader functional characteristics of urban systems. Understanding the nexus between urban form and energy consumption is essential for advancing sustainable urban development. This study investigates the influence of urban form and green cover on residential energy consumption through a pilot analysis of Sector 22, Chandigarh. Sector 22 was selected due to its diverse building typologies, which reflect broader patterns across the city. The research focuses exclusively on residential buildings, encompassing a total of 2,548 units. Key morphological parameters examined include building orientation, height, plot size, surrounding open areas, and proximity to tree cover and green spaces. Methodologically, a multivariate cluster analysis was employed to identify variations in energy consumption per square meter of built-up area. The results reveal distinct differences between government and private residential clusters. In government housing, orientation of plots and adjacency to green spaces emerged as primary differentiators of energy use, whereas in private residences, building height, orientation, and plot size were the dominant determinants. The findings underscore the critical role of urban form in shaping energy demand at the neighborhood scale. By highlighting the interplay of morphology and vegetation cover, this research contributes evidence to support energy-efficient urban planning and the integration of green infrastructure into residential layouts. Such insights are particularly relevant for policy frameworks seeking to mitigate rising urban energy consumption in rapidly expanding cities. |
| 7-6 | 5/21/2026 11:00 | Smart Cities and Green Infrastructure | GFS 207 | 460 | Cosimo Damiano Carpentiere, Riccardo Carnevale and Umberto Berardi | Politecnico di Bari; Polytechnic University of Bari | Enhancing Transparency and Sustainability in Urban Ventilation Systems through Blockchain, IoT, and AI: Case Studies from Seoul, Tokyo, Beijing, Dubai, São Paulo, and Sydney | Blockchain HVAC optimization IAQ management Smart cities Energy efficiency IoT AI | Abstract. [250 – 350 words] Rapid urbanization and climate change are intensifying the need for efficient and transparent energy management systems in metropolitan areas, where indoor air quality (IAQ) and energy efficiency are key concerns for both public health and sustainability. This paper investigates how blockchain-integrated HVAC optimization can address these challenges, focusing on six global cities: Seoul, Tokyo, Beijing, Dubai, São Paulo, and Sydney. Using a comparative multiple case study method, the research examines the deployment of digital infrastructures such as IoT sensors, AI-driven predictive analytics, and distributed ledger technologies in managing IAQ and building energy performance. The analysis reveals that Seoul applies blockchain-enabled monitoring in government offices to ensure transparent energy transactions, Tokyo integrates AI-enhanced digital twins to simulate IAQ and optimize ventilation in dense urban areas, and Beijing leverages blockchain-secured open data for managing large-scale smart city initiatives. Dubai introduces smart contracts in public facilities to incentivize sustainable HVAC practices, São Paulo highlights the challenges of integrating blockchain into diverse building stocks with emerging improvements in demand-response mechanisms, and Sydney demonstrates the coupling of blockchain-based microgrids with HVAC systems to support carbon neutrality objectives. Across these cases, results show that blockchain adoption enhances transparency, stakeholder trust, and accountability, while facilitating knowledge sharing, integration, and application as core processes in smart building management. The findings underscore that although technical and governance pathways differ, blockchain consistently strengthens the verifiability of IAQ and energy performance data, providing a scalable solution for diverse urban contexts. The study concludes that distributed ledger technologies, when combined with IoT and AI, represent a viable enabler for the next generation of ventilation and energy management systems, with direct implications for global energy policy, engineering practice, and sustainable urban development. |
| 7-6 | 5/21/2026 11:00 | Smart Cities and Green Infrastructure | GFS 207 | 470 | Hayoung Kim and Soowon Chang | Purdue University | Integrated Building-Grid Modeling: A Co-Simulation Framework for Dynamic Reliability Assessment | Building-to-Grid Dynamic load modeling Co-simulation Energy reliability | Ensuring the stability and resilience of modern power grids requires increasingly accurate load modeling. Conventional grid planning often relies on static, averaged energy profiles, which fail to capture the dynamic power demand of modern buildings. This approach can critically underestimate grid stress, especially during peak hours, increasing the risk of unforeseen blackouts. As a preliminary study to address this gap, this paper proposes a novel integrated co-simulation framework that dynamically couples building energy models with power grid simulations. To demonstrate the methodology, building-level time-series load profiles for a standard reference building are generated using EnergyPlus. These profiles are then integrated into distribution- and transmission-level test systems (e.g., IEEE 34-bus, 118-bus) modeled in OpenDSS and MATPOWER. The framework compares scenarios using average versus time-series loads to assess discrepancies in grid reliability metrics such as Loss of Load Probability (LOLP) and Expected Unserved Energy (EUE). The results are expected to demonstrate a significant increase in reliability risk; the time-series load scenario yields substantially higher LOLP and EUE values, proving that the actual probability of blackouts is far greater than previously calculated. This study therefore, concludes that reliance on static profiles is inadequate for modern grid planning. As future work, the framework’s application will be expanded to model specific building archetypes, including residential, office, and commercial buildings, eventually leading to analyses of energy-intensive facilities like data centers. Furthermore, this validated platform will serve as a powerful testbed for developing and evaluating adaptive demand response strategies, enabling buildings to become active partners in grid management |
| 7-6 | 5/21/2026 11:00 | Smart Cities and Green Infrastructure | GFS 207 | 505 | Chenshun Chen, Mohammad Elmi and Julian Wang | Department of Architectural Engineering, The Pennsylvania State University | Glazing Façade Design for Energy-Efficient Buildings, Improved Thermal Comfort and UHI Mitigation in Dense Urban Center | Glazing Façade Building Energy-Efficiency UHI Thermal Comfort | With continued urbanization and the increasing occurrence of extreme weather events, urban areas have become more vulnerable to environmental and infrastructural challenges than in the past. A key concern in this context is the Urban Heat Island (UHI) effect. It is primarily driven by two factors: solar irradiation—which includes both direct sunlight and indirect reflections or re-radiation from building facades and urban surfaces—and anthropogenic heat, such as emissions from vehicles and waste heat from HVAC systems. Among these, glazing façade play a pivotal role by interacting with solar radiation, emitting surface heat, and contributing anthropogenic heat through HVAC systems, collectively influencing the surrounding outdoor microclimate. The situation is further intensified by certain material choices and designs—such as low-emissivity (Low-E) windows—that are intended to enhance building energy efficiency and indoor thermal comfort but can inadvertently increase solar reflection and create “heat traps” in the surrounding area. To address the challenges posed by current glazing façade designs and to enhance energy efficiency, thermal comfort, and UHI mitigation in a coherent manner, we propose several innovative alternatives, including Low-E/ATO co-coated double-pane windows, retro-reflective coated windows, translucent windows, and window-integrated greenery or gardens. These glazing façade designs are then tested both experimentally and numerically and benchmarked against other commonly used glazing systems. By examining key performance indicators from multiple perspectives—such as Energy Use Intensity (EUI), Total Solar Irradiance (TSI), and the Universal Thermal Comfort Index (UTCI)—we identify the most suitable design and further derive the optimal design strategy. The results show that with newly proposed Low-E/ATO co-coated double-pane window, modelled urban area could achieve the similar energy performance as the highly-reflective Low-E window, but drastically reduce the adjacent ground’s TSI (up to 25%) and therefore improve the outdoor thermal comfort (some locations up to 3.2˚C UTCI decrease). |
| 7-6 | 5/21/2026 11:00 | Smart Cities and Green Infrastructure | GFS 207 | 653 | Xindan Kang, Karen M. Kensek, John Wilson, Joon-Ho Choi | DriSteem | Tree Shading, Solar Radiation, and GIS-Examining the effect of tree shading on sidewalk heat reduction | Humidity control Indoor environmental quality (IEQ) Occupant health Building resilience Infection risk and airborne transmission Energy efficiency in buildings Climate‑resilient building design Smart building systems HVAC design and operation Bridging research and practice | Humidity is often treated as a comfort variable, yet research and field experience show it plays a much broader role in indoor environmental quality, occupant health, and building resilience. This session examines how relative humidity influences pathogen viability, material durability, system reliability, and energy performance across diverse building types, including healthcare, laboratories, commercial buildings, and mission critical facilities. Drawing on current research, standards activity, and real world operating experience, the session connects humidity control decisions made during design and commissioning to long term outcomes such as infection risk, equipment uptime, and climate resilience. The discussion will also address how emerging tools, including smart building systems and data driven controls, are changing how humidity is monitored and managed in practice. Designed for researchers, engineers, facility leaders, and policymakers, this session bridges theory and application by highlighting where guidance is clear, where gaps remain, and how interdisciplinary collaboration can improve outcomes in healthier, more resilient buildings. |
| 7-7 | 5/21/2026 11:00 | Indoor Air Quality | GFS 118 | 190 | Loubna Ait Lahsen, Flavia Barone, Myriam Bahrar and Mohamed El Mankibi | ENTPE – University of Lyon, LTDS, 3 rue Maurice Audin, Vaulx-en-Velin 69120, France | In-situ assessment of a multifunctional compact system (MCS) in a low energy residential test facility: A comparative study | multifunctional compact systems indoor air quality thermal comfort KPIs Fuzzy controller | The assessment of thermal comfort (TC) and indoor air quality (IAQ) is closely linked to the systems integrated into buildings that ensure these conditions. These systems are major energy consumers and striking a balance between indoor air quality (IAQ), thermal comfort, and energy savings is one of the objectives of this study. This study presents an in-situ experimental evaluation of a compact multifunctional system (MCS) that integrates heating, ventilation, cooling, and domestic hot water (DHW) production into a single unit intended for use in residential buildings to address these conflicting requirements. These preliminary tests focused solely on the ventilation mode of MCS. The MCS incorporates a dual-flow ventilation architecture with static heat exchangers. This study aims to make a comparative analysis between the MCS prototype and a conventional single-flow ventilation system. A fuzzy logic controller is designed to maintain a set temperature of 22°C while responding to peaks in CO2 concentration. A 15-minute CO2 injection phase and a 120-minute ventilation period, both with and without room heating. The results showed that the MCS prototype outperformed the conventional system in terms of IAQ and thermal stability. The MCS prototype ensured a stable indoor environment with an RMSE of only 2.69 °C, on the other hand the single-flow fan struggled to compensate for the infiltration of cold outside air, resulting in significant temperature oscillations and an RMSE of 6.56 °C. Additionally, the tracer gas decay analysis revealed that the MCS achieved a more efficient air change rate (ACH), returning CO2 levels to background concentrations faster than the reference system. The first experimental tests on the ventilation function of the MCS showed good results compared to conventional systems. In conclusion, the incorporation of a static heat exchanger has improved control algorithms such as fuzzy logic, offering a reliable way to maintain high IAQ standards in low-energy residential buildings without sacrificing thermal comfort. In future studies, we will evaluate the system, but this time by performing ventilation and heating and comparing the results with those of this study in order to characterize the MCS under study and propose optimizations for the design of this type of system. |
| 7-7 | 5/21/2026 11:00 | Indoor Air Quality | GFS 118 | 309 | Jeong-Min Oh, Ju-Hyun Lee, Seheon Kim and Jae-Weon Jeong | Hanyang University | Application of Hollow Fiber Membrane Humidifier in Residential EHP Systems for Indoor Air Quality in Winter | Membrane humidifier Numerical simulation Indoor humidity control | Indoor humidity in winter drops due to air heating and infiltration. Dry air with an RH below 30% can cause health issues, such as respiratory, eye, and skin irritation. Given that the indoor environment with adequate humidity level minimizes acute symptoms and viral survivability, humidification systems are usually applied to maintain RH range of 40–60% in the winter season. However, conventional ultrasonic and steam humidifiers have limitations, such as bacterial growth in the water tank, condensation from excess moisture, and high energy consumption. In contrast, hollow fiber membrane (HFM) based system can be an alternative, providing hygienic and energy-efficient isothermal humidification without direct contact between water and air. Even though recent studies have proposed various system schematics to implement HFM into the building HVAC, their application is limited to centric HVAC system, not pointing individual HVAC components. Therefore, this study proposes and evaluates an HFM module designed for integration with the indoor units of individual electric heat pump (EHP) heating systems in residential environments. The HFM module is designed and optimized to meet the humidification load determined by the TRNSYS 18 program. To assess the HFM module, dynamic simulation process, coupling the heat and mass transfer model with the indoor moisture model is presented. With the presented simulation process, the performance of the module is assessed, and the result of the assessment is analyzed with the perspective of humidification capability and indoor humidity level. The result showed that the proposed system is able to increase the thermal comfort satisfaction ratio from below 10% to over 90% during the heating period (November to March), and PMV value is revealed to be improved as well. The findings of this paper show that EHP-integrated HFM modules are a technically feasible and practical option for retrofitting the individual heating systems prevalent residential spaces. |
| 7-7 | 5/21/2026 11:00 | Indoor Air Quality | GFS 118 | 398 | Sudharshan Anandan, Andres Barrio-Zhang, Akshay Deolia, Tyler Hughes, Sohum Sodhi, Jae Hong Park, Ryan Wagner, Arezoo Ardekani and David Warsinger | Purdue University | Acoustically assisted fibrous filtration for enhanced particle capture | Fibrous filters acoustic interaction force acoustic streaming particle capture filter loading | Fibrous filters in air conditioning systems separate particles from the air stream by capturing them on fibers. However, particles in the 0.1–1 µm range, known as the most penetrating particle sizes (MPPS), are difficult to capture because diffusion, interception, impaction, electrostatic, and gravitational forces are not effective at moving these particles toward the fibers. In this work, we demonstrate, through experiments and scaling analysis, that an acoustic standing wave generates two force fields within a fibrous filter. Acoustic interaction forces attract particles to the fibers. Acoustic streaming forms localized mini-vortices near fiber boundaries, increasing the likelihood of particle deposition through fluid drag. Our prior simulation results also showed that acoustic interactions and streaming forces increase particle capture more than particle agglomeration. Agglomeration occurs only at very high concentrations (> 105–106 particles/cm3) for submicron aerosols. To determine capture efficiency (η), we conducted experiments in a bench-scale setup. This setup included an aerosol generation subsystem, an acoustically assisted fibrous filtration module, and sampling devices with optical and scanning mobility particle sizers. The sound pressure level inside the acoustic cavity was measured at 1533 Pa. We tested different fibrous filter combinations, varying in filter materials, fiber diameters, porosities, and loading. Here, we present the increase in η of a sintered metallic fiber with a mean fiber diameter of 6.92±2.22 µm as the filter loading increased. For a monodisperse 0.3 µm particle at a filter face velocity of 0.3 m/s,under acoustic excitation, the capture efficiency remained about 40%. Without acoustic assistance, η decreased from about 40% to 27%. These results show that adding acoustic fields to fibrous filtration can greatly enhance particle capture, particularly for the MPPS. This suggests a promising strategy to improve indoor air quality and reduce exposure to airborne contaminants. |
| 7-7 | 5/21/2026 11:00 | Indoor Air Quality | GFS 118 | 404 | Semi Park and Insung Kang | University of Texas at Arlington | Low- and no-cost ventilation strategies to reduce indoor cooking emissions: a case study of natural ventilation, window fans and kitchen hoods | Indoor air quality window fan low-cost strategy kitchen environment kitchen hood | Indoor air quality (IAQ) is an important environmental determinant of human health, comfort, and well-being, particularly in homes where people spend most of their time indoors. Yet many U.S. households, especially low-income households, lack adequate ventilation systems, and some do not even have kitchen hoods. Cooking activities are known to be a major source of indoor pollutants such as particulate matter (PM), nitrogen dioxide (NO2), and carbon monoxide (CO), which pose a range of health risks. This gap highlights the urgent need for interventions that are both effective in reducing cooking emissions and affordable, specifically, low-cost ventilation solutions for households limited by financial or structural barriers. Therefore, this study aims to assess the effectiveness of low-cost window fans and natural ventilation compared with kitchen hoods in reducing indoor cooking emissions. We conducted experiments under four conditions: (1) no ventilation (baseline), (2) natural ventilation (3) kitchen hood, (4) window fan. Various air pollutants including cooking emissions such as PM, NO2, CO, TVOC, as well as temperature and humidity, were continuously monitored during the experiments. Our findings indicate that window fans reduced indoor cooking emissions to levels comparable to kitchen hoods, but their total cost, including equipment and installation, ranges from $20-$50, which is significantly lower than the $650-$2,500 for conventional kitchen hoods. Natural ventilation was more effective than no ventilation, but both were far less effective than fan-operated mechanical ventilation, including window fans and kitchen hoods. These findings are expected to inform practical, affordable IAQ intervention strategies to mitigate health risks associated with indoor cooking emissions, particularly in low-income households. |
| 7-7 | 5/21/2026 11:00 | Indoor Air Quality | GFS 118 | 555 | Wanyu Rengie Chan, Marion Russell, Jiayu Li and Pradeep Prathibha | California Air Resources Board; Lawrence Berkeley National Laboratory; University of California Berkeley | Measurements of Volatile Organic Compounds and Polycyclic Aromatic Hydrocarbons in 10 Commercial Kitchens | Kitchen ventilation Exhaust hood VOCs PAHs Workplace exposure | Commercial kitchens are often characterized by harsh working environments, which are linked to high staff turnover as evidenced by limited measurement data and anecdotal reports. These kitchens are energy-intensive, and equipment upgrades that improve indoor environmental conditions and lower energy costs may be possible. In 2024, we recruited 10 independently operated restaurants in California to participate in a week-long sampling study. Our goal was to assess indoor environmental quality, including thermal conditions and indoor air pollutant concentrations, and identify opportunities for energy-saving measures, such as improved kitchen ventilation and efficient cooking appliances. Here, we present a subset of the indoor air pollutant measurements, namely volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs), that were measured on one day during the week-long sampling period in each kitchen. In addition to VOCs and PAHs, our study also monitored other indoor air pollutants, such as ultrafine particles and nitrogen oxides, to capture the full range of indoor air pollutants present. VOCs and PAHs were measured at each kitchen near where most cooking activities occurred. Our results show sum of VOCs to range between 142 to 519 g/m3, with a mean concentration of 277 g/m3. Aldehyde, alcohol, terpenes, and ketone are the key groups of VOCs measured, accounting for 46 to 88% (mean = 72%) of the total VOC concentrations measured. Aside from cooking related emissions, other sources of VOCs are evident from the presence specific groups of VOCs found in some of our samples, such as siloxane from personal care products and glycol ether likely associated with cleaning. The sum of 23 PAHs range between 19 to 1103 ng/m3, with a mean concentration of 378 ng/m3. Our results suggested higher PAHs in kitchens of larger restaurants with more cooking activities compared to the small establishments. While we are unable to draw conclusions about the levels of VOCs and PAHs with the design and performance of exhaust hoods, we noticed that in one of the kitchens with relatively higher PAHs, using an unlisted exhaust hood with low airflow rate is likely a contributing factor. |
| 8-1 | 5/21/2026 13:30 | Indoor Air Quality | SGM 123 | 206 | Rosemary Castorina, Karla Vargas, Flavia Wong, Zhong-Min Wang, Aditya Simha, Elizabeth Noth, Asa Bradman and Kazukiyo Kumagai | Center for Environmental Research and Community Health, School of Public Health, University of California, Berkeley; Department of Public Health, School of Social Sciences, Humanities and Arts, University of California, Merced; Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley; Environmental Health Laboratory Branch, Center for Laboratory Sciences, California Department of Public Health | Residential Volatile Organic Compounds (VOC) Measurements in the San Joaquin Valley: Findings from the SPHERE Study | San Joaquin Valley homes indoor air quality volatile organic compounds (VOCs) active air sampling TVOCs | California’s San Joaquin Valley, a major agricultural region surrounded by mountain ranges, experiences severe air pollution due to its basin-like topography which traps emissions, particularly during winter and summer inversion seasons. The San Joaquin Valley Pollution and Health Environmental Research (SPHERE) Study is a collaborative, community-based project led by UC Berkeley, UC Merced, the California Department of Public Health (CDPH) and local partners to assess air pollution exposures in and around Fresno, CA. To evaluate exposures to volatile organic compounds (VOCs), 4-hour active air sampling was conducted in 16 homes between September and November 2023. A total of 23 indoor and 8 outdoor samples were collected and analyzed to quantify VOC concentrations. Twenty-four individual VOCs were detected out of 76 target analytes. The nine most frequently detected indoor VOCs (detection frequency >50%) included toluene, para-xylene, - 4-Isopropyltoluene, styrene, ethylbenzene, 1,2,4-trimethylbenzene, ortho-xylene, meta-xylene, and benzene—six of which are BTEX compounds. Median (95th percentile) indoor concentrations of benzene, toluene, ethylbenzene, and xylenes were 0.26 (0.84) μg/m³, 2.06 (5.06) μg/m³, 0.56 (1.30) μg/m³, and 2.10 (4.91) μg/m³, respectively. Average indoor-to-outdoor (I/O) ratios exceeded 1 for all compounds except benzene, indicating substantial indoor sources (mean I/O ratios ranged from 0.70 to 20.4). Outdoor BTEX concentrations were inversely associated with residential distance from State Route 99 (ρ = -0.75; p < 0.05) and showed a significant and positive correlation with ambient NO₂, consistent with traffic-related emissions (ρ = 0.88; p < 0.05). Outdoor BTEX levels were also negatively correlated with ozone, reflecting expected patterns of photochemical degradation. In addition, continuous total VOC (TVOC) concentrations were measured using Atmotube Pro monitors, capturing real-time variations in indoor air quality over the course of the sampling period. Findings indicate that indoor environments are a predominate source of VOC exposure, frequently exceeding outdoor concentrations. Although measured levels were below federal and state health-based reference values, the results highlight meaningful patterns of localized exposure in disadvantaged communities. Continued air quality monitoring, source attribution, and targeted interventions are warranted to reduce exposures among vulnerable populations. |
| 8-1 | 5/21/2026 13:30 | Indoor Air Quality | SGM 123 | 207 | Hemakshat Sharma, Rosemary Castorina, Charles Perrino, Tanmayi Amanchi, Kazukiyo Kumagai, Asa Bradman and Elizabeth Noth | Department of Public Health, School of Social Sciences, Humanities and Arts, University of California, Merced; Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley; Environmental Health Laboratory Branch, Center for Laboratory Sciences, California Department of Public Healthth; Environmental Health Laboratory Branch, Center for Laboratory Sciences, California Department of Public Health | Stockton school-aged children’s exposures to polycyclic aromatic hydrocarbons (PAHs) | indoor air quality PAH concentration school San Joaquin Valley PM2.5 | Human exposure to polycyclic aromatic hydrocarbons (PAH) is associated with significant adverse health outcomes, yet the magnitude of and temporal trends in environmental concentrations are not well understood. Stockton, California, in the San Joaquin Valley, experiences some of the highest air pollution levels in the United States due to its valley topography that traps emissions and the influence of regional industry and transportation. The Stockton Air Pollution Exposure Project (SAPEP), a pilot study performed in December 2021, aimed to characterize exposures to PAH, fine particulate matter (PM₂.₅), and black carbon exposures among schoolchildren and to evaluate in-classroom air filtration effectiveness. We conducted a two-week monitoring campaign at a small K–8 parochial school, deploying PAH sampling equipment in four classrooms and at two outdoor locations. Indoor and outdoor PAH levels were measured over 24-hour periods on two consecutive days each week. Portable air cleaners were installed in half of the classrooms. Integrated 24-hour samples for PAHs were collected using Harvard-type impactors (two 37 mm filters) and XAD-2 filled sorbent tubes for very highly volatile compounds (e.g., naphthalene). Co-located real-time PM₂.₅ and black carbon monitors were also deployed indoors and outdoors to capture concentration patterns and assess filtration impacts. Week 1 measurements were higher than Week 2, reflecting heavy rainfall during the second week. In Week, indoor naphthalene levels were significantly lower in classrooms with air cleaners compared to those without and compared to outdoor levels (Kruskal–Wallis, n = 16, H = 7.07, p = 0.03). Of the 36 PAHs measured, 12 were detected in 100% of samples, including acenaphthene, acenaphthylene, acenaphthenequinone, anthracene, 1,4-anthraquinone, benzo(a)anthracene-7,12-dione, benzo[a]pyrene, 1,3-indanedione, fluorene, 9H-fluoren-9-one, 1,4-naphthoquinone, and phenanthrene. Naphthalene concentrations were highest (indoor median: 257.9 ng/m³; 95th percentile: 344.8 ng/m³; outdoor median: 285.84 ng/m³; 95th percentile: 329.6 ng/m³). The indoor-to-outdoor ratio for naphthalene was 1.30, indicating indoor sources predominated. We will present results integrating PAH, PM₂.₅ and black carbon concentration data, highlighting spatial and temporal patterns and the role of filtration in reducing exposures. These findings contribute to understanding pollutant sources and mitigation strategies in school environments located in overburdened communities. |
| 8-1 | 5/21/2026 13:30 | Indoor Air Quality | SGM 123 | 367 | Dong Kyu Lee, Ji Hyeok Son, Sukumar Natarajan and Woong June Chung | Gachon University; University of Bath | Analysis of the correlation between particulate matter and microplastics according to particle size | Microplastics Particulate matters Indoor air quality μ-Raman spectrograpy | Indoor air quality (IAQ) is a critical determinant of occupants’ health and comfort, as has become a fundamental factor influencing health and comfort. While particulate matter (PM) is a well-established IAQ metric, often monitored in real-time, airborne microplastics (MP) are an emerging pollutant of concern. The quantification of MPs is significantly more complex, requiring time-intensive, filter-based sampling followed by offline spectroscopic analysis for particle identification. This procedural complexity prevents real-time exposure assessment. Therefore, this study investigates the correlation between PM and MP concentrations to establish a basis for estimating real-time MP exposure using readily available PM data. MPs were collected and analyzed in residential building, which are characterized by the longest occupancy among various building usage. Concentrations of PM and MPs will be measured in different residential areas (bedroom, kitchen, living room) for localized analysis. Sampling was conducted during the four hours of highest occupancy activity using a MiniVol-Tas device. And analysis was performed with a μ-Raman spectroscopy capable of small particles identification. Analysis revealed the presence of MPs of various sizes, however, comparison with PM concentrations was made by classifying them into particles smaller than 10 μm and 2.5 μm. Among the residential spaces, the bedroom exhibited the highest concentration of MPs, likely attributable to diverse sources such as bed sheet and clothing, as well as occupant activity. Furthermore, a correlation was identified between PM and MPs concentrations, suggesting that their similar distribution patterns in indoor air are primarily governed by internal sources such as clothing and occupant activity rather than outdoor infiltration. Future research will analyze the correlation between PM and MPs across various building usage beyond residential buildings, with a particular focus on detailed time-series analysis of this relationship, subsequently leading to the development of a predictive model. |
| 8-1 | 5/21/2026 13:30 | Indoor Air Quality | SGM 123 | 495 | Shuo-Hsuan Chang, Yuto Morishita, Ji Yoon Bae, Dorit Aviv, William Braham and Jihun Kim | University of Pennsylvania Stuart Weitzman School of Design | CALM (Clay-based Air-treating Living wall Module): Passive Cooling and VOC Removal | Living Wall System 3D Clay Printing Pollutant Removal | The Clay-based Air-treating Living-wall Module (CALM) combines a 3-D clay-printed Triply Periodic Minimal Surface (TPMS) shell with a hydrogel/zeolite/perlite/vermiculite substrate to create a wind-driven, flow-through brick that cleans incoming outdoor air. Full-scale tests in a 35°C closed-loop wind tunnel show that, even without vegetation, the substrate dampened the formaldehyde spike by 17.8%, accelerated the 1-hour decay rate by 17.6%, and cut the 90-min residual to around 202.3 µg/m³, which is comfortably below the 500 µg/m³ tVOC ceiling set by LEED and WELL. A preliminary test identified the same substrate (25% hydrogel, 15% zeolite, 30% perlite, 30% vermiculite) as the best trade-off between air permeability, water retention, and Plantago major viability. These results establish a non-biological baseline and confirm CALM’s promise as a low-energy façade element; planned work will integrate vegetation, assess long-term performance in diverse climates, and include a real-life-scale installation. |
| 8-2 | 5/21/2026 13:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 39 | Kiho Tanaka, Makiko Ukai and Sihwan Lee | Department of Urban Environmental Studies, Graduate School of Environmental Studies, Nagoya University, Nagoya; Graduate School of Engineering, Tokyo University of Science, Tokyo; Graduate School of Environmental Studies, Nagoya University, Nagoya | Performance evaluation of an office-integrated cultivation room utilizing human-emitted CO2 for sustainable building-integrated agriculture | Building-integrated agriculture (BIA) Carbon capture and utilization (CCU) CO2 recycling HVAC integration Energy performance | Integrating plant racks into office buildings enhances indoor environmental quality (IEQ) and supports sustainable building-integrated agriculture (BIA), yet balancing crop energy demands with building conditioning remains a critical challenge. This study explores a novel carbon capture and utilization (CCU) strategy by recycling human-emitted CO2 from office zones for crop photosynthesis. We propose a ‘cultivation room’ located in the southern perimeter zone of an office model in Nagoya, Japan, utilizing plant racks for hydroponic lettuce production. High-intensity artificial lighting (193 W/m2) was modeled to supplement natural daylight to ensure sufficient photosynthetic photon flux density (PPFD). To evaluate the environmental and energy impacts of this integration, a simulation model was developed using Rhinoceros and the Grasshopper plug-ins, Ladybug and Honeybee. Two operational scenarios were compared: (1) a combined system in which the cultivation room is ventilated with CO2-rich exhaust air from the office zone to utilize indoor thermal and gaseous resources, and (2) an independent system in which the cultivation room is ventilated exclusively with outdoor air. Ventilation rates were dynamically controlled to prioritize latent heat removal from plant transpiration. Simulation results revealed a distinct seasonal trade-off between energy efficiency and carbon reuse. In summer, the combined system significantly outperformed the baseline, reducing the total thermal load by 32% by utilizing cool office exhaust air. Conversely, in winter, the independent system proved thermally advantageous, functioning as an economizer to offset significant internal heat gains from artificial lighting. Notably, regarding CCU performance, the combined system reduced the external CO2 supply requirement to just 8% in summer and 17–20% in winter compared to the independent system. Consequently, this study proposes a seasonal hybrid operation strategy—switching between combined operation in summer and independent operation in winter—to maximize overall building sustainability. |
| 8-2 | 5/21/2026 13:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 92 | Arianna Peduzzi, Roberta Jacoby Cureau, Claudia Fabiani, Adriana Ciardiello, Maria Francesca Talamo, Veronica Lucia Castaldo and Anna Laura Pisello | EAPLAB at CIRIAF, Interuniversity Research Center, University of Perugia; Ricerca sul Sistema Energetico - RSE S.p.A. | Passive energy retrofit strategies for historic buildings: A systematic review of innovative and non-invasive solutions | Heritage building envelope Passive strategies Conservation Thermal performance PCMs | The energy retrofit of historic buildings is a crucial strategy for achieving the European decarbonization targets. The revised Energy Efficiency Directive mandates an annual renovation rate of 3% of buildings owned by public bodies, aiming to upgrade them into at least nearly zero-energy or zero-emission buildings. Enhancing the energy performance of heritage buildings reduces environmental impact, diminishes operational costs, and increases indoor comfort, while ensuring buildings’ functionality and adaptation to contemporary needs. However, this process presents unique challenges, particularly in preserving architectural integrity and addressing technical and regulatory constraints. In this context, retrofit strategies must harmonize energy efficiency goals with the safeguarding of cultural and architectural heritage, thus requiring tailored approaches and innovative proposals. Within this framework, this study aims to gain a comprehensive overview of the current retrofit options for historic buildings, with a focus on passive solutions. It explores innovative and non-invasive strategies and materials designed to improve the performance of historic buildings’ envelopes and outdoor paving. A systematic literature review is conducted using the Scopus database, yielding 275 scientific articles. Preliminary analysis of these publications reveals a growing interest in the topic, highlights emerging research trends, and identifies the most promising non-invasive solutions and possible future developments. Among the most recent studies, this review identified three macro-groups of solutions, focusing on: i) the transparent envelope, leveraging solar gain or adaptive technologies - such as thermochromic or photoluminescent coatings - to reduce energy consumption; ii) the opaque envelope, using materials capable of enhancing both thermal and moisture regulation; iii) horizontal surfaces (both building roofs and urban pavement) with cool materials capable to enhance building thermal performance while mitigating Urban Heat Island (UHI) effects. The findings underscore the complexity of implementing energy-efficient passive solutions in heritage contexts, where technical, regulatory, and cultural challenges are often deeply connected. Achieving this delicate balance requires careful planning, close interdisciplinary collaboration, and context-sensitive design approaches that respect and enhance architectural heritage. |
| 8-2 | 5/21/2026 13:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 189 | Zahra Salehi | University of Connecticut | Agrivoltaics as a Renewable Energy and Green Infrastructure Strategy for Enhancing Thermal Comfort, Energy Efficiency, and Climate Resilience | agrivoltaics renewable energy- thermal comfort green infrastructure climate resilience | Abstract: Agrivoltaics (AV), the dual use of land for agricultural production and photovoltaic energy generation, represents an emerging opportunity to bridge renewable energy innovation with sustainable building and environmental design. This study develops a GIS- and AHP-based framework to identify suitable locations for agrivoltaic deployment in Connecticut, with emphasis on urban–agricultural interfaces and controlled environments such as greenhouses. By integrating land cover, canopy, soil, and zoning data, the framework identifies high-potential parcels that can simultaneously support food production and renewable energy generation. Beyond energy benefits, AV systems introduce shading and microclimate regulation that improve thermal comfort, reduce cooling loads, and mitigate heat stress for both crops and human occupants in agricultural buildings. Preliminary findings demonstrate that agrivoltaic installations can significantly decrease greenhouse cooling demand during peak summer months while maintaining adequate daylight for crop growth. The results also highlight the role of AV as a form of green infrastructure that enhances ecosystem services, including urban heat mitigation, stormwater management, and carbon reduction. Importantly, agrivoltaics offers a climate-adaptive strategy, aligning with resilience planning and environmental policy objectives by reducing energy-related emissions and increasing local food-energy security. This research contributes a transferable framework that situates agrivoltaics not only as a renewable energy technology but also as a design strategy for sustainable buildings, improved indoor environmental quality, and long-term climate resilience. |
| 8-2 | 5/21/2026 13:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 508 | Xu Liu and Julian Wang | Pennsylvania State University | Spectral-Selective Glazing Strategies for Energy-Efficient and Adaptive Building Envelopes | Climate-adaptive Envelopes Spectrally selective Smart window Building Energy Efficiency | Windows account for approximately 30–40% of heat gain and loss through the building envelope, contributing up to 25–30% of total HVAC energy consumption in typical buildings. As such, glazing systems are a critical target for improving energy efficiency. Conventional solutions—such as low-emissivity and solar-control coatings—primarily address shortwave solar radiation by transmitting visible light while blocking near-infrared gains. While effective in reducing cooling demand, these approaches are static and cannot adapt to seasonal changes or regulate longwave thermal losses. This study investigates dynamic spectral-selective glazing strategies, including coatings and film-based solutions for transparent windows, that operate across both shortwave and longwave ranges. The proposed methodology integrates laboratory characterization of optical and thermal properties with building energy simulations using EnergyPlus, in order to quantify the combined impacts of shortwave solar control and longwave emissivity tuning. Preliminary findings highlight two complementary strategies: (1) maintaining high visible transmittance with reduced near-infrared transmission to minimize cooling load without compromising daylighting, and (2) enabling dynamic emissivity regulation in the mid-infrared (8–13 µm) to switch between thermal insulation in heating-dominated conditions and radiative cooling in hot, arid climates. Simulation results across representative climate zones indicate that dynamic emissivity regulation can significantly improve the heating–cooling balance compared to static low-emissivity glazing. The conclusions drawn from this work suggest that integrating spectral selectivity with climate-responsive emissivity control can advance the next generation of energy-efficient and adaptive building envelopes. Beyond energy performance, the study emphasizes the retrofit potential of coating- and film-based solutions, supporting both sustainable building practices and broader carbon reduction goals. |
| 8-2 | 5/21/2026 13:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 517 | Takao Katsura, Erkki Hirvonen, Kanato Kimura, Takaharu Matsui, Kentaro Sekine, Kazuyoshi Harimoto, Miyuki Watanabe and Katsunori Nagano | Hokkaido University; National Institute of Techinology Tomakomai Collage; Taisei Corporation | Improvement of thermal insulation performance of transparent vacuum insulation panels and in-situ performance test | Transparent vacuum insulation panel Window insulation retrofit In-situ performance test | Reducing the energy consumption of buildings, factories, and other facilities is essential to achieving decarbonization. In order to reduce the energy consumption in the residential houses and commercial buildings, Zero Energy Buildings (ZEB) and Houses (ZEH) have been defined in Japan. Then efforts are underway to make buildings ZEB or ZEH. However, energy-saving technologies have not been introduced in existing buildings, especially insulation performance is insufficient. In order to retrofit the insulation of existing buildings, transparent vacuum insulation panels (TVIPs) using structured cores for window insulation retrofit of existing buildings are proposed. The TVIP is produced by inserting the structured core, the low-emissivity film, and the adsorbent into the transparent gas barrier envelopes and vacuum-sealing them. Although the TVIP has the advantage of being inexpensive, lightweight, and easy to install for insulation retrofit, it had a major challenge of outgassing from the core material after vacuum sealing. However, the thermal conductivity of the vacuum layer after vacuum sealing in TVIP was successfully reduced to less than 0.008 W/(m・K) by reducing outgassing from the core material. In this paper, the authors introduce the fabrication process of the prototype TVIP and the results of the thermal conductivity measurement. In addition, the authors carried out the In-situ performance test of TVIP, in which TVIP was installed on the double layer window glass and the surface temperature and the heat flux were measured. The result shows that U-value of double layer window glass with TVIP was reduced from 3.4 W/(m2K) to 1.0~1.5 W/(m2K). |
| 8-2 | 5/21/2026 13:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 544 | Mohammad Elmi, Siddharth Jayakrishnan Jayakrishnan, Adam Muhammad and Julian Wang | Pennsylvania State University | An Experimental Analysis of Photothermal Nanocoatings for Greenhouse Energy Efficiency | Greenhouse photothermal materials experimental validation energy efficiency sustainable agriculture | Greenhouses require intensive energy input to maintain stable growing conditions, particularly in extreme climates. In prior research, we proposed a greenhouse covering coated with antimony tin oxide (ATO) nanoparticles and demonstrated through simulation that such coatings could significantly reduce energy demand without reducing photosynthetically active radiation (PAR). The present study experimentally validates those predictions using a controlled lab-scale greenhouse prototype. Polyethylene sheets were coated with ATO nanoparticles to form a spectrally selective photothermal nanocoating and integrated into the greenhouse prototype. The prototype was tested inside a thermal chamber equipped with a full-spectrum solar simulator, enabling replication of seasonal extremes. Two representative dates, December 19th (cold conditions) and July 21st (hot conditions), were selected to represent worst-case seasonal performance. The thermal and energy responses of the greenhouse with ATO-coated sheets were compared with those of an identical greenhouse without coatings with a standard uncoated double-layer polyethylene covering. The experimental findings confirm strong alignment with earlier simulation studies, demonstrating both the accuracy of the simulation models and the practical feasibility of the coating. Energy testing revealed that ATO nanocoating improved total annual energy savings over 10% compared to uncoated double-layer polyethylene films. Notably, these efficiency gains were achieved without reducing PAR transmittance, ensuring no negative impacts on crop growth. This study provides the first experimental validation of nanocoated greenhouse films for energy management, confirming their dual role in reducing operational energy use while sustaining plant productivity. This study advances sustainable agricultural practices by demonstrating the potential of photothermal nanocoatings as scalable, high-impact solutions for greenhouse energy efficiency. |
| 8-3 | 5/21/2026 13:30 | Building Technology and Performance | SGM 101 | 122 | Xue Cui, Minhyun Lee, Xuange Zhang, Mohammad Nyme Uddin and Junjiang Luo | The Hong Kong Polytechnic University; Yonsei University | Time-series forecasting of indoor temperature: Toward sensor-free occupant-centric HVAC control | Indoor temperature Time-series forecasting Occupant-centric control Gradient boosting regression Feature interpretability | Indoor temperature is a critical variable for occupant-centric HVAC control in buildings, directly influencing thermal comfort and control performance. Many existing OCC deployments heavily rely on dense sensor networks, which face practical challenges related to cost, maintenance, and reliability in real buildings. To address this limitation, this study proposes a sensor-free time-series forecasting framework for indoor temperature prediction. The proposed approach relies only on limited and readily available information in buildings, including air conditioner (AC) operational settings, outdoor environmental conditions, temporal information, and leave- and arrival-related variables. An eXtreme Gradient Boosting (XGBoost) regression model is developed to predict indoor temperature in a time-series manner under realistic sensing constraints. The model is trained and evaluated using a time-series cross-validation scheme that strictly preserves chronological order and effectively prevents temporal leakage. The developed model achieves an R^2 of 0.61, RMSE of 0.29 ℃, MAE of 0.24 ℃, MSE of 0.09, MAPE of 0.90%, and SR_0.5 of 90.88%, demonstrating that indoor thermal dynamics can be reliably predicted without relying on indoor environmental sensors. In addition, SHapley Additive exPlanations (SHAP) are employed to analyze feature contributions and enhance model interpretability. The novelty of this study lies in demonstrating that reliable indoor temperature forecasting can be achieved under realistic sensing constraints by systematically leveraging only readily available information in buildings. |
| 8-3 | 5/21/2026 13:30 | Building Technology and Performance | SGM 101 | 179 | Jincheng Dai, Ryozo Ooka, Chao Lin, Ken Takahashi and Shintaro Ikeda | Dept. of Architecture, Faculty of Eng., The University of Tokyo; Institute of Industrial Science, The University of Tokyo | Developing a surrogate RC Model for Optimal HVAC Control Applications in Modelica-Based Building Digital Twin | Digital twin RC model Building energy simulation Optimal Control Modelica | In the development of building digital twin (DT) frameworks for HVAC systems, EnergyPlus simulations via the Spawn interface have been used for building load calculation. However, although such systems can technically be exported as Functional Mock-up Units (FMUs), their runtime dependence on the EnergyPlus engine limits portability and flexibility in diverse deployment environments and makes control optimization difficult to implement efficiently. To address this issue, we develop a surrogate modeling approach based on a resistance–capacitance (RC) thermal model. The RC model was first fitted using data from a building simulation model based on architectural drawings design parameters, and then RC model was calibrated using nighttime natural cooling data. This calibration ensured that the adjusted RC model primarily reflects the building’s inherent thermal properties, with little influence from HVAC operation. In this study, the target system is a two-story office building located in the cold region of Sapporo, Japan. It features energy efficient building systems, including a groundwater-source heat pump, a thermal storage tank, and ceiling radiant air conditioning. To accurately represent HVAC dynamics, we developed a detailed HVAC system model using Modelica. Furthermore, the RC model was calibrated using data from a Modelica–Spawn co-simulation model. This co-simulation model had been validated against measured data. This calibration process enabled the surrogate RC model to approximate the load calculation results of Spawn when coupled with the Modelica HVAC system. In addition, after replacing Spawn with the RC model to form the DT framework, we evaluated its integration into an optimal HVAC control setting, with particular attention to computational efficiency, response fidelity, and compatibility with control algorithms. Overall, the developed surrogate approach provided a physically grounded, computationally efficient, and FMU-compatible solution that successfully constructed a building digital twin and used it to examine the application of optimal HVAC control algorithms. |
| 8-3 | 5/21/2026 13:30 | Building Technology and Performance | SGM 101 | 205 | Eunwan Kim, Jeonghoon Choi and Dongjun Suh | Kyungpook National University | Camera-Only Unsupervised Visual Anomaly Detection for IEQ-Oriented Building Operations | Indoor Environmental Quality (IEQ) Building Management System (BMS) integration Building envelope defects Operations and maintenance (O&M) Unsupervised visual anomaly detection | Indoor environmental quality (IEQ) can be undermined by visual conditions that conventional sensing and rule-based diagnostics capture poorly, including early mold spots, damp or leakage stains, condensation marks, peeling paint, and fine cracks. This study presents a camera-only unsupervised anomaly detection approach designed for building operations. The system produces pixel-level masks of surface anomalies on walls and ceilings so that maintenance staff can act on precise locations rather than coarse image-level alarms. The contribution is an end-to-end workflow aligned with facility practice. It supports periodic scans or continuous monitoring with existing cameras; generates heatmaps and binary masks that quantify affected area; aggregates findings by room, floor, and asset zone; and exports actionable priorities to building management or maintenance platforms for inspections, ventilation checks, moisture mitigation, cleaning, and minor envelope repair. Practical constraints are addressed, including variable illumination, mixed finishes, and cluttered scenes, as well as privacy through on-premise processing and runtimes suitable for edge devices. Utility is evaluated on public datasets that provide pixel annotations for two representative defect families relevant to IEQ and envelope performance: moisture-related surface stains and cracks or peeling on walls and ceilings. We report standard segmentation and detection metrics to characterize localization and alarm quality. Across mask-annotated datasets and lighting changes, the approach delivers stable localization of low-contrast and early-stage defects while remaining computationally practical for real-world deployment. The results indicate that vision-based unsupervised anomaly detection can complement existing sensing and inspection routines and provide a reproducible pathway for IEQ-relevant anomaly detection in buildings. |
| 8-3 | 5/21/2026 13:30 | Building Technology and Performance | SGM 101 | 278 | Mahdi Bonyani, Maryam Soleymani and Chao Wang | Louisiana State University | A Physics-Informed Modeling of Data Center Cooling and Self-Supervised Learning-Based Autoencoder for Fault Detection and Diagnosis | Data Center Cooling Fault Detection Physics-Informed Modeling Deep Learning Self-Supervised Learning | Effective Fault Detection and Diagnosis (FDD) is crucial for data center energy efficiency but often struggles with labeled data scarcity. We propose the Physics-Informed Spatio-Temporal Graph (PI-STG) framework, a two-stage self-supervised approach. Utilizing the AlphaDataCenterCooling virtual testbed, we generate high-fidelity data via signal-level fault injection. Stage 1 employs an auto-encoder for robust unsupervised anomaly detection. Stage 2 utilizes a graph neural network, explicitly modeled on the hydraulic cooling topology, to diagnose root causes by tracing fault propagation. Experiments demonstrate that PI-STG achieves an F1-score of 0.931, outperforming purely data-driven baselines like LSTM-AE and GAT, particularly in diagnosing complex actuator failures. Furthermore, the framework reduces energy waste from undetected faults by over 15%, bridging the gap between theoretical deep learning and practical facility management. |
| 8-3 | 5/21/2026 13:30 | Building Technology and Performance | SGM 101 | 518 | Yihui Li, Zhexuan Yu, Jun Xiao, Hao Zhou and Borong Lin | Center of Tsinghua Think Tanks, Tsinghua University; School of Architecture, Tsinghua University; Weiyang College, Tsinghua University | Physics-Embedded Transfer Learning Graph Neural Network for Building Energy Prediction | Graph neural network Transfer learning Physics-informed modeling Building energy prediction Heat transfer equations | Accurate and scalable building energy prediction in the early design stage remains a critical challenge due to heterogeneous spatial configurations, climate variability, and limited simulation data. This study proposes a hybrid framework that integrates transfer learning with physics-embedded graph neural networks (GNNs) to enhance the generalization and interpretability of building energy prediction. Buildings are represented as heterogeneous graphs, where spatial units (e.g., rooms, façades) are modeled as nodes with geometric and material attributes, while thermal interactions are encoded as edges. To address cross-building and cross-climate transferability, we introduce a transfer learning scheme that adapts knowledge from source domains with abundant simulation data to target cases with scarce data. Moreover, fundamental heat transfer equations—including conductive, convective, and radiative mechanisms—are embedded as physics-informed constraints within the GNN message-passing process, ensuring thermodynamic consistency and reducing overfitting to data-driven correlations. Experiments are conducted on multi-climate datasets with diverse building typologies. Results show that the proposed method achieves higher prediction accuracy and robustness compared with purely data-driven GNNs and conventional machine learning baselines, while requiring significantly fewer target-domain samples. In addition, the physics-guided transfer learning framework improves interpretability by explicitly linking learned graph representations with established thermal dynamics. This research contributes to the development of generalizable, physically consistent, and data-efficient prediction methods, offering an integrated approach to support green building design and performance optimization in complex architectural contexts. |
| 8-4 | 5/21/2026 13:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 207 | 316 | Jongwon Lee | Keimyung Univeristy | Does Building Retrofit Program for Low-Income Households Really Create Healthy Homes? | Building Retrofit Program Low-income housing Indoor environmental quality Energy welfare Post-occupancy evaluation Ventilation behavior | Background: Building Retrofit Programs for low-income households have been globally implemented as dual strategies for carbon neutrality and energy welfare. These programs typically include insulation upgrades, window replacements, HVAC system improvements, and boiler replacements. While existing literature demonstrates the long-term energy and economic benefits of building energy efficiency improvements, limited research has examined their comprehensive impact on indoor environmental quality (IEQ) and occupant wellbeing. Objective: This study investigates whether building retrofit program genuinely creates healthy living environments for low-income households by conducting a comprehensive before-and-after assessment of IEQ parameters in retrofitted dwellings. Methods: A field study was conducted during winter 2024 in deteriorated residential buildings occupied by vulnerable populations in Daejeon Metropolitan City, South Korea. Low-cost sensors were deployed to quantitatively measure thermal comfort parameters (temperature, humidity), indoor air quality indicators (CO₂, TVOC, formaldehyde), and acoustic conditions before and after retrofit interventions. Parallel occupant satisfaction surveys were administered to validate physical measurements and capture subjective wellbeing outcomes. Results: Post-retrofit measurements revealed improved thermal comfort with stabilized temperature and humidity levels. However, CO₂ concentrations showed a slight increasing trend, and certain air quality parameters deteriorated. While objective noise measurements indicated improvements, subjective assessments revealed mixed responses. The improved airtightness following retrofits, combined with inadequate ventilation practices due to lack of occupant education, appears to have created unintended consequences for indoor air quality. Previously, the low airtightness of deteriorated buildings provided passive ventilation; post-retrofit, the enhanced building envelope without proper ventilation strategies led to pollutant accumulation. Conclusion: While building retrofit program successfully addresses energy efficiency and thermal comfort objectives, it may inadvertently compromise other IEQ dimensions without holistic implementation strategies. This study emphasizes the need for comprehensive IEQ assessment frameworks in energy retrofit policies, moving beyond singular energy-focused metrics. Critical policy implications include: (1) mandatory pre- and post-retrofit IEQ monitoring protocols, (2) integrated ventilation system upgrades in retrofit packages, and (3) systematic occupant education programs on ventilation practices and IEQ management. These findings underscore that true wellness homes require balanced consideration of energy efficiency, environmental quality, and occupant behavior. |
| 8-4 | 5/21/2026 13:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 207 | 450 | Xianzhun Zhong, Yongxin Xie and Jianlei Niu | Hong Kong Polytechnic University | Calibration of the sweating function in a multi-node thermoregulation model based on chamber experiment | Thermal health Thermoragulation model JOS-3 Model Thermal response Sweating | Climate change brings about more frequent and more extreme heatwaves, which put people’s health in jeopardy. Thermoregulation model serve as a potentially effective method to predict human thermal responses under extreme weather conditions, based on the prediction results of which a warning sign could be determined. With an open source, joint system thermoregulation model (JOS-3 model) boosts the development of thermoregulation model. However, there are still some deficiencies existing in JOS-3 Model. As one of the major deficiencies, the sweating function of JOS-3 Model is not triggered accurately and promptly, making it difficult to predict human thermal response accurately, especially in hot environment. Moreover, the total weight loss simulated by JOS-3 Model is generally underestimated, which is also the consequence of an insufficient sweating function. The main purpose of this paper is to calibrate the sweating function of JOS-3 model based on the data collected from chamber experiment. During the chamber experiment, the skin temperature, core temperature and sweat rate of the subject were constantly measured. The correlation of sweat rate with skin temperature and core temperature was later explored. Participants’ body weight were also recorded before and after each experiment to gather their body weight loss, which will also be used as a indicator when calibrating the sweating function. The optimized model could make more precise predictions of human sweating under a hot environment, making the prediction of the heat exchange between human and environment more accurate. Therefore, the optimized model is more conducive to evaluating the health risks that the extreme weather poses to people. |
| 8-4 | 5/21/2026 13:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 207 | 474 | Shaofang Xu, Giovanni Calzolari, Jilong Wang, Jianlin Ren, Fei Liu, Bin Lu, Qiang Li, Wei Liu, Junjie Liu and Tengfei Zhang | China Academy of Building Research; Dalian University of Technology; Hebei University of Technology; KTH Royal Institute of Technology; Qingdao University of Technology; Tianjin University | Efficient reconstruction of the atmospheric boundary layer in spatially constrained wind tunnels | Computational fluid dynamics Wind profile Machine learning Genetic algorithm Adjoint method Urban climate | Atmospheric boundary layer (ABL) wind tunnels are essential experimental platforms for studying building wind loads, natural ventilation, and urban wind, etc. The reproduction of ABL profiles often require long development sections and heavily depend on empirical formulas and repeated trial-and-error adjustments, resulting in long commissioning time and high costs. To overcome these limitations, this study proposes a multi-stage optimization framework to efficiently reconstruct ABL profiles by designing the shape of spires and roughness elements in wind tunnels with short test section. The framework begins with the preliminary design of spires and roughness elements based on Irwin’s formula. The target is a power-law wind velocity and turbulence intensity profile. A support vector regression (SVR) surrogate model is then developed to relate spires’ geometric parameters to the wind velocity and turbulence intensity profiles based on numerical simulations with computational fluid dynamics (CFD). The surrogate model is further integrated with a genetic algorithm (GA) that identifies Pareto-optimal solutions for creating the target wind profiles. Finally, adjoint shape optimization is applied for local geometric refinement. The designed spires and roughness elements are 3D printed and the corresponding wind tunnel experiments are conducted for validation. The results demonstrates that the target wind velocity and turbulence intensity profiles are successfully created in a short test section. Compared with conventional empirical designs, the integrated SVR–GA–adjoint approach reduces mean absolute errors in velocity and turbulence intensity by approximately 50%. Overall, the proposed framework offers a systematic and reproducible strategy for generating desired ABL in short test sections, improving wind tunnel design practices and providing a reliable experimental foundation for wind related studies in the urban environment, thereby advancing applications in environmental wind engineering. |
| 8-4 | 5/21/2026 13:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 207 | 524 | Sreelakshmi Kavuthimadathil and Satish Bk | Welsh School of Architecture,Cardiff university; Welsh School of Architecture,Cardiff University | Towards Adaptive, human-centric lighting: Limitations of Subjective Measures and a multimodal framework | Indoor lighting human behavioural response Nonvisual effects of lighting Non-invasive measurement adaptive lighting systems user centric lighting control | Indoor lighting plays a crucial role in shaping occupant comfort, health, and productivity, as they spend 90% of their time indoors. While intensive research on adaptive lighting technologies is ongoing, most current strategies are still primarily based on static standards and subjective questionnaires, which may not reliably capture dynamic human responses to real-time changes in lighting conditions. Also, current strategies often address only a few parameters, such as illuminance and colour temperature, and overlook how variations in lighting influence actual human behaviour. This paper presents a comprehensive review of the literature spanning the non-visual effects of light. It highlights persistent methodological shortcomings, ⅰ) particularly the narrow parameter focus, ⅱ) methodological constraints like reliance on invasive sensing, static comfort models, and laboratory-based studies with limited ecological validity and ⅲ) difficulty with integration with control systems. The paper further examines the limitations of relying solely on subjective lighting evaluations for occupant-responsive lighting control. A living lab study was conducted in a university environment (n = 81), where illuminance levels were measured across nine spatial zones and compared with occupants’ self-reported satisfaction, perceived control, and productivity using Likert-scale surveys. Results showed weak and inconsistent relationships between measured illuminance and subjective responses. The zone with the highest illuminance also reported the highest dissatisfaction, indicating a mismatch between objective lighting levels and perceived comfort. Response clustering, adaptation effects, and contextual confounding factors further limited the sensitivity and reliability of subjective assessments. The findings highlight the importance of integrating non-invasive behavioural and physiological sensing modalities with qualitative assessments when evaluating indoor lighting environments. Therefore, the paper proposes a structured methodological framework that employs non-invasive behavioural and physiological drivers, such as eye-tracking metrics, heart rate and heart-rate variability, facial expression analysis, and posture and movement patterns to capture real-time occupant responses under static and dynamic lighting conditions. The framework is designed to support transparent, closed-loop lighting adaptation while maintaining user override and practical deployability. |
| 8-4 | 5/21/2026 13:30 | Health, Wellbeing, and Human Behaviors in the Built Environment | GFS 207 | 652 | Zhilong Liu, Yifan Zhang, Tsz Him Ian Chiu, Ghazal Chizarian, Joon-Ho Choi | #N/A | Modern Workplace Environment Pre- and Post-Occupant Satisfaction in Modern Office Hot-Desking Systems: A Comparative Study of Workplace Environments | ||
| 8-5 | 5/21/2026 13:30 | Generative AI in Sustainable Built Environment | GFS 101 | 114 | Mojtaba Parsaee, Tarlan Abazari and Soroush Samareh Abolhassani | Arizona State University; Mississippi State University | Towards AI-driven Digital Twins and Cyber-Physical-Social Systems for Circular Disaster Management: Developing A Multi-Agent Debris Life Cycle Simulation Framework | Circular Recovery Environmental Sustainability Climate Resilience Regenerative Design Agentic Simulation | This paper presents a novel debris life cycle simulation framework driven by generative artificial intelligence (AI) agents, designed to support the development of digital twins (DTs) and cyber-physical-social systems (CPSS) for circular disaster management. Escalating climate-induced disasters produce vast quantities of construction and demolition (C&D) debris that pose significant challenges to urban resilience and sustainability by straining local capacities, disrupting essential services, and causing substantial environmental impacts. Conventional linear debris management approaches, i.e., dominated by rapid clearance and mass landfilling, exacerbate resource depletion, pollution, and greenhouse gas (GHG) emissions while foreclosing opportunities for material recovery. Circular economy strategies, emphasizing reuse, repair, and recycling, offer a more sustainable recovery pathway but remain underutilized for post-disaster contexts. To address this challenge, this study develops a multi-agent framework that connects cyber (virtual building stock models and simulations), physical (material stocks, debris flows, and environmental impacts), and social (a stakeholder engagement interface) dimensions, embodying CPSS-aligned DTs for community-scale circular recovery planning. The proposed framework integrates large language models (LLMs), building information modeling, geographic information systems, life cycle assessment, interactive visualization, and AI-generated audio narration to simulate and compare linear and circular debris management scenarios at the community scale. Using a bottom-up archetype-based approach, the framework profiles building stocks by typology and vintage, enabling detailed debris quantification and cradle-to-grave environmental impact assessment across three scenarios: linear landfilling, moderate circularity via recycling, and enhanced circularity combining reuse and recycling. Validated through a case study of the 2023 tornado in Sullivan, Indiana, the framework demonstrates that circular strategies can divert nearly 46% of debris from landfills and reduce embodied GHG emissions by approximately 28% compared to conventional methods. The LLMs, coupled with an interactive user interface, translate complex life cycle metrics into stakeholder-friendly insights, enabling transparent, participatory decision-making among emergency managers, planners, and policymakers. Overall, this research establishes a conceptual and technical foundation for advancing AI-driven DTs and CPSS that enable circular disaster management. Future work should focus on real-time data integration, expanded impact metrics, and enhanced multi-agent coordination to enable adaptive, scalable, and resilient urban recovery systems. |
| 8-5 | 5/21/2026 13:30 | Generative AI in Sustainable Built Environment | GFS 101 | 184 | Carlos Faubel, Derian Mowen, Marjan Miri, Ursula Demarquet Alban, Antonio Martinez-Molina and Miltiadis Alamaniotis | Department of Architecture, Design & Urbanism, Antoinette Westphal College of Media Arts and Design, Drexel University; Department of Civil, Architectural and Environmental Engineering, College of Engineering, Drexel University; Department of Electrical and Computer Engineering, The University of Texas at San Antonio UTSA | Fusing visual and sensor data with multimodal transformers for indoor environmental quality assessment in educational settings | indoor environmental quality CNN-ViT model educational buildings artificial intelligence in built environments | Indoor environmental quality (IEQ) plays a central role in the health, comfort, and cognitive performance of building occupants, particularly in educational environments where students spend extended periods of time. Prior work has shown that elevated carbon dioxide (CO2) concentrations, increased total volatile organic compounds (TVOCs), particulate matter (PM), and suboptimal hygrothermal conditions negatively affect attention, memory, and decision-making among students. As educational buildings move toward more occupant-centric and energy-efficient operation, artificial intelligence (AI) tools offer new opportunities for real-time IEQ assessment. However, existing approaches often rely solely on sensor data and lack the contextual awareness needed to interpret environmental shifts that are influenced by occupancy, activity patterns, or space configuration. This study presents a multimodal transformer (MulT) model that fuses synchronized environmental sensor data with time-lapse RGB images to assess seven IEQ indicators: dry-bulb temperature (T), relative humidity (RH), CO2 concentrations, TVOCs, and PM (PM1, PM2.5, PM10). Data were collected at 5-minute intervals from four representative educational spaces, namely, a conference room, a hybrid laboratory, and two classrooms, over 7 days each from March to May 2025. The model combines a convolutional neural network (CNN) for local visual features, a Vision Transformer (ViT) for global spatial reasoning, and a cross-modal fusion transformer to jointly estimate all IEQ variables. Results show significantly strong convergence and robust generalization. On a dedicated test set containing unseen paired samples from all environments, the model achieved a test mean squared error (MSE) of 85.05 and a mean absolute error (MAE) of 3.64, which demonstrates that the learned multimodal embeddings transfer well to new images and sensor combinations, preserving accuracy outside the training distribution. The MAE of ~3.6 across seven heterogeneous IEQ variables further highlights the model’s strength, given that the targets span different physical scales. The approach effectively captures both environmental dynamics and visual cues such as occupancy level, equipment use, and lighting conditions, improving assessment stability in diverse indoor scenarios. The findings highlight the potential of MulT-based architectures for real-time IEQ monitoring in educational settings and point toward broader applications in automated building diagnostics, early-warning systems, and adaptive HVAC control strategies. |
| 8-5 | 5/21/2026 13:30 | Generative AI in Sustainable Built Environment | GFS 101 | 485 | Xinyue Zhang and Weirong Zhang | Beijing University of Technology | Augmentation Framework for HVAC Fault Diagnosis Based on Denoising Diffusion Models | HVAC Deep learning Fault detection and diagnosis Diffusion model | Fault detection and diagnosis in Heating, Ventilation, and Air Conditioning (HVAC) systems are essential for maintaining energy efficiency and indoor comfort. However, a persistent challenge is the scarcity of fault samples, particularly for rare faults, which leads to severe data imbalance. This imbalance degrades the performance of diagnostic models, increases false alarms, and compromises system reliability. While deep learning methods have improved diagnostic accuracy, they often struggle to capture the complex spotiotemporal interactions inherent in HVAC fault data when using traditional one-dimensional time-series inputs. To address these limitations, we propose a novel data augmentation framework, GRA-Diff, based on Denoising Diffusion Probabilistic Models (DDPMs). This framework uniquely integrates a Gramian Angular Field (GAF) transformation, converting one-dimensional time-series data into two-dimensional images to better preserve temporal dependencies and inter-parameter relationships. At the core of our model is an innovative generative module, ResCUA-Net, which enhances a U-Net architecture with residual connections, class-conditional embeddings, and self-attention mechanisms to generate high-quality, diverse, and realistic synthetic fault samples. Experimental results on the ASHRAE-1043-RP dataset demonstrate that GRA-Diff significantly outperforms existing approaches in sample quality and diagnostic accuracy, achieving a 3.78% improvement over the state-of-the-art CVAE-GAN model. Under an extreme 30:1 data imbalance ratio, our method improved the average fault recognition rate from 40% to over 85%. Furthermore, we introduce a comprehensive, multi-dimensional evaluation framework to ensure generated samples meet high application standards. By providing a more robust and generalizable solution, this study contributes to the advancement of intelligent building management and energy-efficient operations. |
| 8-5 | 5/21/2026 13:30 | Generative AI in Sustainable Built Environment | GFS 101 | 503 | Wooyoung Jung and Namgyun Kim | Texas A&M University; The University of Arizona | Multi-Agent AI Learning Assistant for Human Building Interaction: System Architecture and Preliminary Performance | Human Building Interaction Artificial Intelligence Learning Assistant Large Language Model Multi-Agent Framework STEM Education Personalized Learning | Human-Building Interaction (HBI) has emerged as a key domain within building science – typically encompassing civil/architectural engineering and architecture – in the past decade, as its potential to improve building performance by integrating human dynamics into the control of buildings. Educating students in HBI presents unique challenges due to its interdisciplinary nature. It requires multiple skills, including programming (e.g., Arduino and Python), wiring circuits with sensors, and understanding diverse domains, including thermal comfort, lighting, indoor air quality and more. We aim to address this challenge by developing an artificial intelligence (AI) learning assistant, incorporating web-based multi-agent frameworks for HBI education. In this study, we highlight this assistant’s expandability, accessibility, and enhanced usefulness compared to general-purpose large language models (LLMs). Specifically, this assistant is supported through both LangChain and LangGraph, to combine the flexible integration of diverse LLM capabilities with the structured orchestration of complex workflows, thereby enabling adaptive and educational interactions for HBI education. We showed its usefulness in supporting Arduino programming by comparing its response with those generated by a general-purpose LLM model using systematic evaluation criteria. This research and development effort will contribute to advancing educational innovation in HBI as well as interdisciplinary subjects in architecture, engineering, and construction by lowering technical barriers for students, fostering interdisciplinary skill development, and creating a scalable framework where AI supports experiential learning and empowers learners to transition from passive knowledge absorption to active problem-solving and innovation. |
| 8-6 | 5/21/2026 13:30 | Indoor Air Quality | GFS 118 | 116 | Emmanuel I. Aghimien, Ajla Aksamija and Timothy O. Adekunle | School of Architecture, University of Utah | Indoor Environmental Quality in a Mid-Century Research Laboratory Building | Research laboratory building Indoor environmental quality Building performance analysis Energy Efficiency Occupant comfort | Research laboratory buildings are among the most energy-intensive building types due to their high energy demand, ventilation requirements, and the need to maintain controlled indoor environmental conditions. Previous indoor environmental quality (IEQ) investigations exist, however, IEQ research on purpose-built research laboratory buildings, particularly those constructed during the middle of 20th century, remains underexplored. This study investigates the IEQ conditions of a mid-century research laboratory building constructed in 1960 and located on the University of Utah campus. Indoor environmental data were collected in two representative chemical engineering laboratories located within the basement and third floors of the building. This paper presents results from a seven month analysis period, spanning April to October 2025. The monitored IEQ parameters included indoor air temperature, relative humidity (RH), carbon dioxide (CO₂) concentration, and fine indoor particulate matter (PM2.5). Measurements were recorded at hourly intervals and analyzed to assess temporal variations at both hourly and monthly scales. The results showed distinct thermal and indoor air quality patterns between the two laboratories. The basement laboratory (Basement Lab) had extended periods of underheating during the fall months, while the third-floor laboratory (Lab 3) exhibited more stable thermal conditions with occasional short-term temperature increases during summer. Relative humidity levels in both spaces showed pronounced seasonal variability, including extended periods below recommended comfort ranges. For both laboratories, CO₂ concentrations generally remained below the commonly adopted indoor air quality threshold of 1000ppm, although intermittent spikes were observed in the third-floor laboratory during occupied periods. Lastly, PM2.5 concentrations were consistently low in both spaces throughout the monitoring period. Overall, the findings from this study illustrate how IEQ conditions are influenced by floor level, facade exposure, room volume, and occupancy patterns within a mid-century research laboratory building. The study provides empirical evidence that can support future performance assessments aimed at improving occupant comfort and environmental performance in existing laboratory facilities. |
| 8-6 | 5/21/2026 13:30 | Indoor Air Quality | GFS 118 | 147 | Youngbo Won, Wenhao Chen, Zhong-Min Wang, Jeff Wagner and Kazukiyo Kumagai | California Department of Public Health | How Ventilation and Air Cleaning Strategies Affect Classroom PM₂.₅ and CO₂ under Normal and Wildfire Conditions? – A CONTAM Simulation Study | Multizone model IAQ Mechanical ventilation Natural ventilation Portable air cleaner | Particulate matter (particularly PM₂.₅) and carbon dioxide (CO₂) are critical indicators of indoor air quality (IAQ). This study employs a multizone model (CONTAM) to simulate PM₂.₅ and CO₂ concentrations under various ventilation scenarios, with and without portable air cleaners (PACs), during normal and wildfire conditions in a school setting. The building includes one hallway and eight classrooms, each accommodating around 20 students, with an air change rate of 12 h⁻¹ (including air recirculation) and 18% outdoor air intake. After validating the model by comparing simulation results with the previous measurements, 50 additional scenarios with different ventilation conditions (mechanical vs. natural ventilation) and PAC operations were analyzed for normal conditions (31 days in October) and wildfire conditions (a three-day event in September with an average outdoor PM₂.₅ concentration of 30 µg/m³ from 8 AM to 4 PM). The simulations showed that under normal conditions (average outdoor PM₂.₅ concentration of 10 µg/m³), introducing 20% outdoor air through an HVAC system with a MERV 8 filter kept PM₂.₅ and CO₂ levels below 5 µg/m³ and 1,000 ppm, respectively. Using a MERV 13 filter further reduced PM₂.₅ concentrations to 3 µg/m³. During wildfires, with outdoor PM₂.₅ at 30 µg/m³, introducing 20% outdoor air through an HVAC system with a MERV 8 filter raised indoor PM₂.₅ levels above 10 µg/m³. Opening windows significantly affected indoor PM₂.₅ levels, with indoor PM levels matching outdoor levels within 2 hours without PACs. When a window and a door facing outdoors were opened during recess, indoor PM₂.₅ and CO₂ concentrations quickly aligned with outdoor levels. These simulation results highlight the importance of reducing outdoor air intake and utilizing effective filtration strategies to mitigate wildfire-related impacts on IAQ in schools. |
| 8-6 | 5/21/2026 13:30 | Indoor Air Quality | GFS 118 | 158 | Shikang Wen and Qingyan Chen | The Hong Kong Polytechnic University | Field investigation of the impact of different terminal devices on thermal comfort and ventilation uniformity | Vertical temperature stratification Air change rate Radiant surface system Gravity cabinet unit Fan coil unit | Indoor thermal comfort and air quality in buildings significantly depend on heating, ventilation, and air conditioning (HVAC) system performance, particularly at the final stage through terminal units. Current studies have not comprehensively evaluated advanced terminal unit performance regarding indoor thermal comfort and air quality under both heating and cooling modes. To address this gap, this study presents a field investigation of three terminal systems in an office building located in Suzhou’s hot summer and cold winter climate: radiant surface systems (RSS), gravity cabinet units (GCU), and fan coil units (FCU). Thermal performance is evaluated through vertical air temperature stratification, while ventilation uniformity was assessed using local air change rates (ACH) determined by the CO₂ decay method. The results indicated that all three terminal systems provided satisfactory thermal comfort, maintaining vertical temperature differences between ankle and head levels below 2 °C in both cooling and heating seasons. However, pronounced seasonal performance asymmetry was observed. The FCU exhibited the most consistent performance across seasons. The GCU achieved superior thermal uniformity during cooling but experienced the largest vertical stratification during heating. In contrast, the RSS demonstrated outstanding heating performance with minimal stratification, while slightly increased stratification occurred during cooling. Ventilation measurements revealed that ACH uniformity was higher at lower heights during cooling and higher at upper heights during heating, reflecting buoyancy-driven airflow behavior. Remarkably, the RSS delivered the most uniform air distribution during heating, whereas its ventilation uniformity was reduced during cooling relative to the GCU and FCU. These findings highlight the importance of accounting for seasonal performance differences when selecting terminal devices and provide practical guidance for HVAC system design in hot summer and cold winter climate regions. |
| 8-6 | 5/21/2026 13:30 | Indoor Air Quality | GFS 118 | 353 | Trond Thorgeir Harsem, Bente Hellum, Haakon Flaaronning, Marie Heistad and Mina Andrea Torvanger | Norconsult - Digtital AS; Norconsult - Norge AS; Norconsult-Norway, affiliate, Royal Institute of Technology, Stockholm; Oslo Metropolitan University | Influence of Surgical Staff Movement on Airborne Particle Concentrations in Operating Rooms with Laminar and Mixing Ventilation | Operating room Particle concentration Ventilation solution Laminar Airflow Mixed ventilation Steady State operating persons Movement of operating persons | Operating rooms (ORs) are critical environments where airborne contamination control is essential for reducing the risk of surgical site infections. Ventilation strategies typically rely on either laminar air flow (LAF) systems or mixed ventilation (MV). For several decades, the effectiveness of these approaches, particularly the ability of LAF to minimize particle concentrations near the surgical wound has been widely debated. Numerous experimental studies with stationary mannequins have concluded that LAF provides superior protection by establishing a clean air zone around the operating field. However, recent findings suggest that the situation becomes more complex once healthcare personnel are moving within the room, disturbing the airflow patterns and potentially transporting contaminants into the critical zone. This study presents detailed measurement results from a newly established full-scale operating room laboratory, specifically designed to evaluate airflow performance under realistic surgical conditions. The laboratory setup allows for controlled experiments with both LAF and MV configurations, including scenarios with surgical staff activity. Particle concentrations and flow structures were measured in critical zones close to the operating site. The experimental results provide new insights into the limitations of steady-state mannequin-based studies, highlighting the importance of movement in assessing OR air quality. The findings contribute to the ongoing discussion of optimal OR ventilation design and operation and suggest that strategies for controlling and mitigating airborne pollutants must account not only for the ventilation principle itself, but also for realistic workflow conditions. This research is supported by the Norwegian Research Council. |
| 8-6 | 5/21/2026 13:30 | Indoor Air Quality | GFS 118 | 417 | Hassan Kotb Ali, Yunus Emre Cetin and Martin Kriegel | Hermann-Riestchel-Institut, Technische Universität Berlin, Berlin, Germany | Air Curtain Intervention to Reduce Air Exchange Between Operating Rooms and Anterooms | Operating room Air curtain Numerical simulation | Surgical Site Infections (SSIs) remain a major concern in hospitals, as they significantly increase patient morbidity and mortality, prolong recovery times, and contribute to higher healthcare costs. A key contributor to the occurrence of SSIs is the infiltration of airborne contaminants into operating rooms (ORs), a process that is often exacerbated by the frequent opening and closing of doors by surgical staff during ongoing procedures. These disturbances can allow contaminated air to flow into the sterile environment of the OR, undermining infection control strategies that are otherwise carefully maintained. Air curtains, which can be strategically positioned in the buffer space between the OR and the anteroom, represent a promising dynamic intervention. By establishing a protective barrier against particle intrusion, they offer an additional layer of defense beyond conventional ventilation systems. Nevertheless, the development of optimal designs for such systems—requiring the proposal, testing, and rigorous evaluation of multiple airflow configurations—remains insufficiently investigated, leaving important gaps in current knowledge. This study addresses these gaps by investigating airflow dynamics during door-opening events between an operating room and its anteroom using advanced computational fluid dynamics (CFD) simulations. Two distinct scenarios were analyzed: a reference case without any intervention and a modified configuration equipped with a ceiling-mounted air curtain and floor-level exhaust. The simulations reveal that the air curtain generates a temporary containment zone, stabilizing the flow field and reducing unwanted air exchange across the doorway. Contaminant entrainment caused by staff-induced wake flows was also significantly suppressed. Compared with the baseline, the system consistently lowered the volume of air transferred into the operating room, highlighting its potential as an effective dynamic strategy to strengthen protective airflow. |
| 8-7 | 5/21/2026 13:30 | Panel Discussion | GFS 116 | 596 | Dolaana Khovalyg, Minyoung Kwon, Matteo Bilardo, Cristina Piselli, Wooyoung Jung | École Polytechnique Fédérale de Lausanne (EPFL); Politecnico di Torino; SCOPE; University of Florence | Personalized Environmental Control Systems (PECS): Multi-Dimensional Trade-Offs in New and Existing Buildings | Personalized Environmental Control Systems Human-Centric Environments Multi-Dimensional Trade-Offs | Personalized Environmental Control Systems (PECS) offer promising pathways to improve occupant comfort, satisfaction, and productivity while potentially reducing energy use. However, their implementation is rarely straightforward: upfront investment, operational strategies, user interaction, and control modes all influence PECS performance in buildings. This interactive workshop examines the multi-dimensional trade-offs of deploying PECS — economic, energetic, human-centric, and operational — to help practitioners make informed decisions across different building contexts. The session will begin with a set of concise, expert-led presentations introducing 4 key perspectives: (1) direct and indirect costs of PECS technologies, (2) potential energy savings and impacts on operational energy expenditures, (3) benefits for human comfort, well-being, and productivity, and (4) the role of control strategies (manual, automated, or hybrid) in determining performance outcomes across the previous three dimensions. After grounding the audience in these fundamentals, participants will engage in a guided, hands-on group activity. Each group will analyze a case study scenario featuring different building types (existing buildings without renovation, existing buildings undergoing renovation, and new construction) along with climate context, client constraints, and budget conditions. Participants will work collaboratively to identify trade-offs, propose optimized PECS configurations, and justify their decisions. This workshop will equip attendees with actionable insights and evaluation strategies for selecting PECS solutions that balance comfort delivery with energy efficiency and cost constraints, preparing them to navigate real-world implementation challenges. |
| 9-1 | 5/21/2026 15:30 | Indoor Air Quality | SGM 123 | 12 | Abdollah Baghaei Daemei, Zhenan Feng and Daniel Paes | School of Built Environment, Massey University | Assessing the Effectiveness of Game-Based Learning Versus Video-Based Learning for Mold Prevention Education | Serious games gamification mold prevention indoor air quality education | Indoor mold growth remains a persistent indoor air quality challenge with well-documented links to respiratory illness, damp housing, and reduced occupant well-being. While educational tools and interventions have been increasingly applied in the built environment to address issues such as energy use, safety, and general indoor air quality, comparable educational tools specifically targeting mold prevention remain largely absent. Also, evidence comparing interactive learning approaches with conventional formats remains limited. This study compares game-based learning with video-based learning for mold prevention education, using a pre- and post-test experimental design with 120 participants. Participants from the general public in New Zealand were randomly assigned to either a game-based or a video-based intervention, both of which delivered equivalent educational content. Outcomes included knowledge acquisition, self-efficacy, intrinsic motivation, perceived task load, and system usability. The game was compared with a video-based training condition serving as a control. Statistical analyses showed that knowledge significantly improved from pretest to post-test in both conditions, with no significant difference in immediate knowledge gain (post) between groups. However, participants in the game-based condition reported significantly higher intrinsic motivation and system usability, as well as lower perceived task load, than those in the video condition. These findings indicate that while both approaches support short-term learning, the serious game provides motivational and experiential advantages. |
| 9-1 | 5/21/2026 15:30 | Indoor Air Quality | SGM 123 | 32 | Zohreh Kiani, Kátia Cordeiro Mendonça, Ali Alexandre Nour Eddine and Marc Abadie | Eurovent Certita Certification, Paris, France; Eurovent Certita Certification, Paris, France - LaSIE UMR CNRS 7356, University of La Rochelle, La Rochelle, France; LaSIE UMR CNRS 7356, University of La Rochelle, La Rochelle, France; Tipee Plateforme Technologique du Bâtiment Durable, Lagord, France | Does numerical simulation reproduce reality? A comparative assessment of indoor environmental quality in multifamily buildings | Indoor Environmental Quality Building Simulation Performance-Based approach | Accurately simulating indoor environmental quality is essential for designing energy-efficient and health-promoting residential buildings. As numerical simulation tools become increasingly central to evaluating ventilation performance, it is crucial to assess how well these tools reproduce actual indoor conditions. A performance-based methodology was developed, using TRNSYS and CONTAM coupling to simulate conditions in multifamily buildings equipped with mechanical extraction ventilation. The methodology relies on dynamic heat and mass transfer calculations in multizone approach, considering airflow, moisture and pollutant transport (CO2, PM2.5, and formaldehyde (HCHO)). Sorption effects and particle size distribution are not included for HCHO and PM2.5 but moisture buffering and particle deposition are accounted. This study compares simulated outputs with real-world data from two complementary sources. The first one is the international IEA EBC ANNEX 86 database, containing indoor air quality measurements from 21 studies across 11 countries, covering 1173 homes and 3268 locations. It provides summary statistics by room type and time period (e.g., bedroom: 23:00–07:00, living room and kitchen: 07:00–23:00). The second source includes two national French indoor air quality campaigns. The first campaign (2003 – 2005) and second one (2020 - 2023) involved data collection during one week in 567 homes from 74 locations and 571 homes from 321 locations, respectively. The first dataset provides weekly time series for CO2, temperature, and RH, and summary statistics (medians, percentiles, and maximum concentrations) for PM2.5 and HCHO by main room (bedroom and living-room). For the second one, only statistical data are currently available and mainly focused on bedrooms. Simulated outputs (CO2, HCHO, PM2.5 concentration and RH levels) are compared against these real-world measurements to explore the reliability of the model, particularly regarding simulation parameters such as moisture and pollutant source strengths and schedules. The comparison also considers varying boundary conditions, including airtightness, climate, and external pollution, reflecting the diversity of real-world variability. |
| 9-1 | 5/21/2026 15:30 | Indoor Air Quality | SGM 123 | 240 | Soo-Min Jeong, Bon Seo and Su-Gwang Jeong | Soongsil University | Controlled sustained release of natural volatile organic compounds from phytoncide emulsion-zeolite composites via surfactant hydrophilic-lipophilic balance adjustment | Controlled release Phytoncide oil-in-water emulsion Hydrophilic-lipophilic balance (HLB) Zeolite Desorption kinetics | Natural volatile organic compounds (nVOCs) provide environmental and physiological benefits for indoor air quality, yet high volatility and concentration instability constrain long-term application. Phytoncide oil exists in high concentration but volatilizes rapidly, whereas phytoncide water has a low concentration and releases gradually. To harness these contrasting traits, an oil-in-water emulsion was formulated and combined with natural zeolite to develop a stable and sustained nVOCs controlled-release system. The influence of the emulsion mixing ratio on characteristics of emission control systems and release behavior was analyzed to identify optimal conditions. The phytoncide emulsion was prepared by adjusting the hydrophilic–lipophilic balance (HLB) using nonionic surfactant, Tween 80 and Span 80. Dynamic light scattering indicated that the emulsion with HLB 14 yielded a mean droplet size of 160 nm and a polydispersity index of 0.11, representing the highest stability. After loading onto pretreated zeolite, SEM and FT-IR confirmed preservation of zeolite particle morphology and framework and the presence of phytoncide constituents. Quantitative TGA and DTG showed that the HLB-14 specimen achieved a loading capacity approximately 1.6 times greater than prior studies, with greater emulsion stability accompanied by increased loading efficiency. In desorption-kinetics-based analysis, the release rate constant decreased relative to neat oil (0.8601 day⁻¹) to 0.1414 day⁻¹ for PTZE-W5-HLB12 and 0.1201 day⁻¹ for PTZE-W5-HLB14, indicating that the zeolite significantly retarded release. Conditions with higher emulsion stability produced more gradual and sustained release across both short- and long-term periods, whereas variation in the oil fraction within the emulsion did not significantly affect loading efficiency or release behavior. Release profiles for all specimens were best fitted to the Weibull model (R² ≥0.99), with shape parameters ranging from 0.65 to 0.72, consistent with diffusion-dominated transport. These findings demonstrate sustained, controlled release of phytoncide nVOCs through HLB-guided emulsion stabilization combined with porous carriers and indicate applicability to antimicrobial/anti-inflammatory functional filters and HVAC systems. |
| 9-1 | 5/21/2026 15:30 | Indoor Air Quality | SGM 123 | 370 | Divine Agbobli, Yunjeong Mo and Cristina Poleacovschi | Iowa State University | A Review of the Factors Influencing Adoption and Abandonment of Indoor Air Quality Improvement Strategies | Indoor air quality monitoring Indoor air quality prevention Indoor air quality improvement | Building occupants spend over 80% of their time in buildings, which often lack natural air circulation to maintain a natural balance compared to an open outdoor space. Exposure to poor indoor air quality (IAQ) can cause headaches, dizziness, and irritation of the eyes, nose, and throat, and in the long term, cause respiratory diseases. Technologies for IAQ monitoring and prevention offer potential to improve IAQ, but factors including cost, privacy, and portability hinder long-term adoption. While prior reviews have detailed IAQ monitors and their health impacts in specific settings (e.g., healthcare units) and isolated studies have applied behavioral models like the technology acceptance models (TAM), knowledge-attitude-behavior (KAB), and compatibility, opportunity and motivation behavior (COM-B) to explain short-term usage, no literature comprehensively examines the drivers and barriers to the adoption, long-term use and abandonment of IAQ technologies across settings and over time. This study aims to conduct a systematic review (2015–2025), following PRISMA protocols, to identify, categorize, and synthesize technological, behavioral, organizational, and contextual factors influencing the adoption, long-term use and abandonment of IAQ monitoring and prevention technologies. The study will search multidisciplinary databases (e.g., Google Scholar, Scopus, PubMed) to build a novel, integrative framework that informs the design and deployment of IAQ interventions and technologies, helping designers, policymakers, and practitioners enhance sustained IAQ improvement through technology-centered behavioral strategies. By bridging technical and behavioral domains, this framework can guide the development of cost-effective, trustworthy, and engaging IAQ technologies suited for schools, healthcare facilities, workplaces, and homes. |
| 9-1 | 5/21/2026 15:30 | Indoor Air Quality | SGM 123 | 425 | Mina Lesan, Avijit Sarker, Saeid Chahardoli, Yi Xiao and Arup Bhattacharya | Louisiana State University; LSU | Adaptive Placement of Portable Air Cleaners under Changing Contaminant Sources | Indoor air quality Portable air cleaners PM₂.₅ CFD modelling Discrete Phase Model | Indoor air quality is increasingly compromised by various and different sources of contamination, one of which is particulate matter (PM10, PM2.5) and micro-contaminants that disperse within various sources and locations. In a large office room with various contaminant sources, placement of portable air cleaners is important to achieve the required IAQ by diluting contamination at the breathing level. However, contaminant source number and location are not fixed and may change over space and time. This spatiotemporal uncertainty complicates air cleaner placement. Therefore, in this study, an elaborate experimental investigation was conducted with six randomized source scenarios and six corresponding air purifier placements. These random source locations and the air purifier locations were modeled using Computational Fluid Dynamics (CFD), with the RNG turbulence model to simulate contaminant transport. Particle trajectories for PM₂.₅ were tracked with a Lagrangian Discrete Phase Model (DPM). In comparing models with seven sources, airflow-aligned placement maintained higher breathing-zone performance and degraded with randomized and increased numbers of source locations. A corner placement of the portable air cleaners (PACs) in the uniform occupancy scenario achieved a 72% reduction in particle concentration in the defined zone relative to a central placement in the grouped occupancy scenario. |
| 9-1 | 5/21/2026 15:30 | Indoor Air Quality | SGM 123 | 453 | Kumar Naddunuri and Shankha Pratim Bhattacharya | Indian Institute of Technology, Kharagpur, India | Assessing the energy saving potential of personalized ventilation system | Personal environmental control systems (PECS) Air terminal device (ATD) Comfort Dynamic conditions Performance. | Personalized environmental control systems (PECS) devices are used to provide occupant’s preferred heating, cooling and ventilation requirements. Personalized ventilation (PV) systems emphasizes on providing cooling and ventilation and is considered to be an alternative air distribution principle that aim to condition the occupant immediate surroundings rather than conditioning the entire space, thereby creating a micro thermal environment, the system effectively delivers the fresh air near to the breathing zone and caters to individual comfort requirements in a workstation space. The main elements of personalized ventilation system are air terminal device (ATD), controllers, duct unit. PV has the flexibility to adjust the airflow direction and controllers play a major role in its performance. However, if the system is not designed properly, it can consume excess energy. Numerous studies have explored the effect of personalized ventilation systems in conjunction with mixing and displacement ventilation systems, these studies extensively focused on comfort and energy saving aspects in terms of regulating supply temperature, and airflow rate though experimental and simulation studies, while a significant number of studies investigated different strategies and their impact. Most of these studies tried to create a balance between the comfort, ventilation rate and energy savings, but very few studies examined the dynamic factors that influence the personalized ventilation system performance as a whole. This study will analytically evaluate the contributing factors including background ventilation, personalized ventilation supply conditions, space characteristics, workstation layout, occupant related parameters, airflow dynamics, design characteristics, working conditions, performance strategies, additional devices aiding with PV to eventually improve the comfort, perceived air quality and energy performance in a workspace. The results of the study indicate that dynamic conditions related to occupant movement, disturbances, PV operation according to occupancy schedules in the space can influence the PV performance and cause a fluctuation in energy consumption pattern. Therefore, quantifying the impact of these factors in addition to supply conditions is necessary to achieve desired comfort and energy savings. |
| 9-2 | 5/21/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 231 | Francesca Vecchi, Simona Semeraro, Roberto Stasi and Umberto Berardi | Polytechnic University of Bari | Modelling the Adoption of Renewable Energy Communities in Urban Districts: An Agent-Based Approach | Renewable Energy Communities Agent-Based Modeling Urban energy transition Prosumers Peer influence | The transition to decentralized energy systems has introduced new configurations as Renewable Energy Communities (RECs), where individual prosumers collaborate to maximize collective energy and access to collective market energy mechanisms. Yet, adoption dynamics within urban environments and customers’ response remain poorly investigated, especially in terms of how technical, economic and social factors influence decision-making. This study presents an agent-based model (ABM) to simulate the spatial and temporal enrolment by agents (considered as buildings) in a REC. The case study is a mixed-use urban district in Bari, in a 20-year lifetime, assuming as renewable technology rooftop photovoltaic panels. A utility function is built on social, technical, environmental and economic aspects, which reflect the key REC dimensions. The model includes household-level heterogeneity, energy flows and costs, and impacts of energy compensation mechanisms. If the payback time for PV installation is within 20 years, a probabilistic adoption mechanism evaluates when the relative utility of installing PV individually is lower than becoming a member of a REC and adjusts its decision based on behavioral patterns, perceived innovation and peer influence. Preliminary results highlight the convenience of enrolling in a REC rather than individual prosumers. The higher utility is related to the amount of energy shared, the applied collective incentives and the improved social patterns. Most of the members enroll in the REC already in the first year of simulation, mainly in summer months, while the adoption curve tends to stabilize afterwards. Despite model assumptions, this framework can support policymakers in identifying targeted incentives, enhancing the effectiveness and inclusivity of energy transition policies. |
| 9-2 | 5/21/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 238 | Bon Seo, Soo-Min Jeong and Su-Gwang Jeong | Soongsil University | Analysis of determinants of building energy use in Seoul through clustering and regression, and proposal of tailored energy policies | Building energy use Energy use intensity(EUI) K-means clustering Multiple linear regression Policy implication | Buildings account for a major share of greenhouse gas emissions, particularly in high-density cities such as Seoul, where over two-thirds of energy-related emissions come from the building sector. Globally, city-level mitigation strategies are emphasized to achieve carbon neutrality (Net Zero), with improvements in building energy efficiency recognized as one of the most effective measures. This study analyzes electricity and city gas data of Seoul’s buildings to identify the determinants of energy use intensity (EUI) and propose reduction strategies tailored to district characteristics. Electricity and gas data from 2022, including monthly consumption, building type, floor area, and district information, were preprocessed, yielding 115,960 electricity and 78,723 gas records. Based on the annual mean electricity and gas EUI of 25 districts, K-means clustering classified the districts into four groups. Multiple linear regression was then conducted for electricity and gas EUI in each group using numerical variables (SVF, summer peak, winter peak, summer minimum, log(area)) and categorical variables (building types with more than 1,000 records). Results demonstrated that electricity EUI was most strongly influenced by summer peak (standardized β=+0.57, p<0.01), while gas EUI was dominated by winter peak (β=+0.76, p<0.01), underscoring the significance of seasonal loads. Among categorical variables, multi-family residential buildings in Group D showed the largest positive coefficient for gas EUI (B=+30.96), indicating a strong dependency on heating and hot water, whereas elderly and childcare facilities in Group C exhibited notable gas-reducing effects (B=−9.86). Accommodation facilities consistently displayed significant positive coefficients across all groups for both electricity (B=+1.90) and gas (B=+9.90), with Group B recording the highest coefficients (electricity: B=+2.55, gas: B=+17.01). These findings highlight the limitations of uniform policy approaches and suggest that tailored strategies—such as high-efficiency retrofits for accommodation facilities, heating upgrades in multi-family residential buildings, and dissemination of best practices from efficient facilities—are essential for improving building energy performance and reducing emissions. |
| 9-2 | 5/21/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 289 | Hisato Osawa and Taro Mori | Faculty of Engineering, Hokkaido University, Hokkaido | Development of a WebGIS for Visualizing Building Energy Consumption and Renewable Energy Potential: Automated Generation of 3D Building Models Using GIS Data | Carbon Neutrality Geographic Information System (GIS) Building Modeling Energy Consumption Web GIS | Achieving carbon neutrality by 2050 has become a common global goal, and countries around the world are formulating and implementing policies to reduce greenhouse gas emissions. In Japan, one of the key strategies to achieve this goal is to encourage the development and implementation of plans that promote decarbonization at the municipal level. However, many small municipalities face significant barriers in advancing these initiatives. Examples include a shortage of specialized personnel, limited financial resources, and a lack of technical expertise necessary to design and implement effective decarbonization measures. To address these challenges, there is an urgent need for analytical tools and systems that can help small municipalities assess local energy consumption patterns and evaluate the potential for introducing renewable energy sources. On the other hand, the availability and use of Geographic Information Systems (GIS) and open data have rapidly expanded in Japan. Notably, the Japanese government’s “Plateau” project currently provides GIS-based building information for 200 locations across the country. This study aims to develop a web-based GIS (WebGIS) that leverages existing GIS datasets and open data to estimate building-level energy consumption and renewable energy potential within municipalities. This report focuses on developing a method to automatically generate three-dimensional (3D) building models using attribute and geometric data obtained from GIS. These models are used to predict heating and cooling loads, which are key factors in building energy consumption. By automating the model generation process, the system can efficiently process large volumes of building data, ensuring scalability and applicability to diverse urban environments. Furthermore, the study validates the simulation results generated by these models, evaluates their accuracy, and identifies areas for improvement. |
| 9-2 | 5/21/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 486 | Zhiyan Jin and Weirong Zhang | Beijing University of Technology | System Performances Comparative Analysis of PV-Battery Systems for Rural Buildings Between Electrochemical and Mathematical Aging Battery Models | Photovoltaic-battery system Aging of battery Electrochemical model Economic analysis | Technology cost reductions and improved performance of photovoltaic-battery (PVB) systems in renewable energy utilization have driven an increasing number of residential users to adopt PV-battery systems. Economic viability and pay back serve as primary concerns for many users when making investment decisions, making accurate assessment of system economic benefits a critical factor for broader PVB system deployment. As a crucial component of PVB systems, previous studies have predominantly employed simplified battery models and paid less attention to the impact of battery aging on the system operation performances, resulting in relatively crude battery degradation calculations and lifetime predictions, which further compromise the accuracy of whole-system lifecycle economic assessments. This study uses a system control strategy based on time-of-use (TOU) pricing and multiple operational scenarios were designed with battery State of Charge (SOC) windows as primary control parameters. The performance of electrochemical and mathematical battery models was analyzed and compared. The results indicate that the electrochemical model (EM) achieves 4-15% lower battery capacity degradation compared to the mathematical model (MM) due to real-time scheduling and feedback during operation, which avoids unnecessary charge-discharge behaviors. The difference between the two models diminishes when the SOC window is larger, as higher capacity utilization increases overall battery operating time , reducing the gap in capacity degradation. Regarding economic indicators, the EM demonstrates superior performance due to its longer predicted lifespan compared to MM, thereby reducing battery replacement investments caused by aging within the system’s designated lifecycle. Under optimal scenarios, the EM achieves a net present value of 38,700, while the MM reaches only 22,600. Consequently, the EM corresponds to a shorter overall discounted payback period for the system, typically 9-10 years, which is faster than the MM 's approximately 12 years for investment recovery, playing an important guiding role in users' investment decisions. |
| 9-2 | 5/21/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 512 | Nida Batool Sheikh, Muhammad Mashhood Arif, Jelle Laverge and Marc Delghust | Department of Architecture & Urban Planning, Ghent University Belgium; Department of Planning, Geography and Environmental Studies, University of Fraser Valley, Abbotsford Canada | Residential Energy and Transport Coupling for Neighbourhood Decarbonization in Transit-Oriented Development | Building Energy Use Intensity Transport Energy Use Intensity Transit-Oriented Development Carbon Efficiency Bus Rapid Transit | Urban energy transitions are most meaningful when the operational energy use of buildings and the energy use from mobility patterns are assessed together. This study couples Building Energy Use Intensity (BUI) with Transport Energy Use Intensity (TUI) for 700 households situated within 500m buffer radius of Bus Rapid Transit (BRT) stations in a rapidly growing metropolitan setting of the Global South. Monthly electricity and natural gas bills inform BUI, while household travel diaries (modes, distances, and trip frequencies) addresses TUI; both are converted to operational carbon intensities using standardized energy-to-carbon factors. Station-level heterogeneity is analyzed to test how transit proximity and urban form shape neighborhood energy demand. Findings indicate a statistically significant relationship between BUI and TUI with variations alongside different stations. Central, well-serviced station areas display lower combined (building and transport) energy intensities than peripheral locations, suggesting that compact, transit-adjacent residential environments reduce mobility energy use while varying building operational energy use. This paper, hence, addresses the question that can integrating residential efficiency with mobility needs deliver greater carbon saving benefits than treating them separately, by easing operational, supply-chain, and infrastructure burdens? Policy and design implications are thereby proposed pertinent to building retrofits and high-performance systems with transit-oriented development and prioritizing compact, mixed-use housing stock near high-quality transit. Coordinated building and transport measures in this research provides a scalable pathway to lower energy demand and carbon footprints in fast-urbanizing contexts. |
| 9-2 | 5/21/2026 15:30 | Energy Efficiency, Conservation, Renewable Energy, and Embodied Carbon | SGM 124 | 582 | Dongwoo Kim, Tae Kon Kim, Seung Hoon Choi, Dagyeong Jeong, Kwangho Lee, Min Hwi Kim and Deuk Won Kim | Korea Institute of Energy Research; Korea University | Development and Performance Evaluation of a Thermal Energy Prosumer System Using EnergyPlus-Based Simulation During the Cooling | Thermal energy prosumer EnergyPlus-based simulation District-scale cooling Performance assessment Carbon emissions | This study aims to develop and evaluate a thermal energy prosumer system during the cooling season using EnergyPlus-based simulation. The research focuses on J-Town, located in Chungcheongbuk-do, Korea, where multiple buildings share cooling energy via heat pumps and chilled-water storage systems. A district-level thermal energy prosumer model is implemented in a single EnergyPlus simulation environment to represent buildings that can both consume and supply cooling energy through heat exchangers. The implemented model captures the dynamic interactions among cooling load demand, thermal storage behavior, and system operation under different prosumer configurations. Real BEMS data from the demonstration site are utilized to reflect realistic system capacities and operating schedules. Based on the developed model, several scenario-based operation strategies are evaluated to assess their impacts on energy consumption, operating cost, and carbon emissions. The results demonstrate that the performance of thermal energy prosumer systems strongly depends on the location of the main prosumer and the resulting operational characteristics of heat pump systems. The findings of this study provide insights into the design and operation of district-scale thermal energy prosumer systems and establish a simulation-based framework for future development of advanced control strategies. |
| 9-3 | 5/21/2026 15:30 | Building Technology and Performance | SGM 101 | 80 | Xianzhe Yang, Akihito Ozaki, Seonghwan Yoon, Sung-Jun Yoo, Younhee Choi and Yusuke Arima | Kyushu University; Pusan National University | Thermal environment prediction in a large open office space with complex air-conditioning system using dynamic coupled BES–CFD | Thermal environment building energy simulation CFD co-simulation air conditioning system | The building sector accounts for approximately 40% of primary energy consumption, with over half attributed to heating, ventilation, and air conditioning (HVAC) systems. Therefore, improving the energy efficiency of HVAC systems is critical for reducing energy consumption and greenhouse gas emissions. In parallel, environmental standards such as Net-Zero-Energy Building (ZEB) and WELL require HVAC systems that are multifunctional, responsive to dynamic conditions, and capable of delivering high thermal comfort. Hybrid HVAC systems that integrate different conditioning principles, such as hydronic radiant heating and cooling (HRHC) systems, all-air systems, and dedicated outdoor air systems (DOASs), have gained attention because of their potential to achieve both energy efficiency and localized comfort control. However, the thermal behavior of such systems, particularly in open or large spaces, remains insufficiently understood owing to the complex interactions among convective, radiative, and latent processes. Conventional steady-state or simplified models are often inadequate for capturing these dynamics. To address this issue, this study developed a comprehensive numerical analysis method for evaluating the hygrothermal environment of hybrid HVAC systems, based on a coupling framework that integrates a Building Energy Simulation (BES) tool with Computational Fluid Dynamics (CFD). The proposed framework incorporates detailed mathematical models for DOAS and HRHC systems, allowing for the accurate prediction of thermal inertia, time-varying surface temperatures, and coupled moisture transfer. The BES and CFD models were dynamically linked through boundary-condition exchange, including time-dependent convective heat transfer coefficients and airflow between zones. Moreover, the framework was validated using a reference house equipped with a hybrid HVAC system, and a case study was conducted for cooling season conditions. The results showed that the system maintained stable hygrothermal conditions throughout the day, largely facilitated by the thermal storage effect of the HRHC-equipped slab. CFD analysis confirmed that thermal comfort was achieved within the occupied zone. This integrated approach provides a robust tool for the design and operation of hybrid HVAC systems. Future work will extend the analysis to long-term and seasonal performance evaluations, including heating operations, to support the development of optimized control strategies. |
| 9-3 | 5/21/2026 15:30 | Building Technology and Performance | SGM 101 | 167 | Ayane Fujiwara, Hideki Tanaka, Shusaku Mizuta, Terutake Furuta and Fumiharu Oba | Campus Planning & Environment Management Office, Nagoya University; Dairei Kogyo Co.,Ltd.; Graduate School of Environmental Studies, Nagoya University | Operational Performance of a Small-Scale NZEB Office and Effective Utilization of Photovoltaic Surplus Power on Non-Business Days using Base Air-Conditioning | ZEB Base Air-Conditioning PV Surplus Power air conditioning system groundwater | Net-Zero Energy Buildings (NZEBs) play a key role in achieving carbon neutrality in the commercial sector, and they are being promoted actively across many countries through development of comprehensive roadmaps, guidelines, and supportive policies. In some regions of Japan, there are many cases in which the reverse power flow of surplus electricity generated by photovoltaics (PV) is not permitted under contracts, which present significant challenges for effective utilization of photovoltaic power in NZEBs. This paper investigated the effectiveness of NZEB technologies in a small-scale office building located in a warm climate, where NZEB status was achieved at the design stage. In addition, a specific measure for the effective utilization of surplus PV power generated on non-business days was examined, and the effectiveness of the measure was analyzed. Furthermore, for surplus PV power generated on non-business days, a trial operation of base air conditioning was conducted on non-business days with the aim of reducing thermal storage loads on weekdays, and the effectiveness of the approach was verified. This study reports the results of the efforts. The NZEB office building has introduced an air-conditioning system that utilizes renewable energy from groundwater and radiant cooling. The purpose of this study was to understand the actual operating conditions of the systems during summer and to evaluate their energy consumption and indoor thermal environment. Holiday Air Conditioning Mode reduced electricity consumption of the packaged air conditioner serving the main second-floor office the following Monday and improved indoor thermal comfort, which can be attributed to a reduction in the thermal load stored within the building at the beginning of the workweek. In addition, changing the weekday radiant cooling operation from radiant cooling panels to radiant floor cooling resulted in approximately 20% reduction in electricity consumption and improvement COP about 0.5. |
| 9-3 | 5/21/2026 15:30 | Building Technology and Performance | SGM 101 | 386 | Chengbo Du, Bess Krietemeyer, Bing Dong, Nina Wilson, Peng Gao, Tong Lin and Jianshun Zhang | Syracuse University | Green Design Studio: A Modular Interface for Multi-Scale Building Performance Simulation in Architectural Practice | Building performance simulation Parametric design Human-computer interaction Engineering abstraction Architectural practice | Building performance simulation tools remain underutilized in architectural practice despite their potential to inform resource-conscious design decisions. This gap persists because existing simulation software either demands specialized engineering expertise or oversimplifies the modeling process at the expense of accuracy and design flexibility. Compounding this challenge, design questions frequently span multiple simulation domains—envelope optimization affects both thermal loads and natural ventilation potential; occupancy patterns influence both energy consumption and indoor air quality—yet current workflows require parallel tool configurations with manual parameter synchronization. This paper presents Green Design Studio (GDS), a modular interface layer that bridges validated simulation engines with architect-friendly Rhino-Grasshopper parametric workflows. GDS interfaces with EnergyPlus for thermal simulation through Honeybee, CONTAM for multizone airflow analysis through the ANT plugin, and provides extensible architecture for future engine integration. A unified translation layer converts interface interactions into engine-specific formats, enabling modifications to propagate automatically across simulation domains without redundant specification. GDS introduces a "modular modification" approach enabling precise, element-level control over building component properties without requiring whole-model regeneration, addressing a fundamental usability barrier in performance-driven design exploration. The system architecture comprises six integrated modules—Space, Envelope, Schedule & Program, HVAC, Site & Weather, and Renewables—each encapsulating domain-specific parameters within a unified Rhino environment that eliminates context switching between graphical modeling and visual programming platforms. Validation confirms that GDS-generated models produce results identical to experimental measurement, ensuring the interface layer introduces no computational artifacts while reducing workflow complexity. GDS represents a contribution toward democratizing multi-domain building performance simulation for architectural practice while preserving the computational rigor essential for reliable design feedback. |
| 9-3 | 5/21/2026 15:30 | Building Technology and Performance | SGM 101 | 410 | Jun-Sub Kim, Seong Woo Park, Jeong Won Kim and Hyeun Jun Moon | Dankook University | Building Genome Analysis for Integrated Indoor Environmental Quality and Energy Performance in a Commercial Building | Building genome Indoor environmental quality (IEQ) Energy performance Commercial building Anomaly detection | Building performance assessment often considers energy use or indoor environmental quality (IEQ) separately, while the combined effects of occupancy and multi-domain operation are less systematically analyzed at the zone level. This can make it difficult for operators to decide where to investigate first and which domain is most relevant when performance differs across zones. This study presents a building genome analysis framework that represents each zone as an operational fingerprint constructed by sequencing multiple markers into a fixed-order genome vector. Six zone-level markers are used: energy load (M1), occupancy (M2), indoor temperature (M3), humidity (M4), CO₂ concentration (M5), and PM2.5 concentration (M6). Time-series data are divided into operating and non-operating periods based on the site schedule (10:00–23:00). For each marker and period, four statistical genes are extracted (mean, maximum, minimum, and standard deviation), and all marker gene blocks are concatenated to form a zone genome vector. The genome vectors are normalized across zones and screened using a PCA-based Hotelling’s T² statistic to identify abnormal zones. A contribution-based drill-down analysis then explains which marker domains and gene statistics drive the deviation. A case study using June–August 2025 operational data from a commercial retail building in Korea demonstrates the approach for four AHU-associated zones. The screening identifies two abnormal zones: Zone-4, primarily driven by PM2.5-related deviation during operating hours, and Zone-6, primarily driven by temperature-related deviation during non-operating hours, consistent with a showcase-dominated zone with limited HVAC operation and frequent sampling activities. The results suggest that building genome analysis can translate multi-domain sensor data into simple zone-level prioritization and interpretable diagnosis to support practical building operation. |
| 9-3 | 5/21/2026 15:30 | Building Technology and Performance | SGM 101 | 420 | Lindsay Li Chen Hu, Sicheng Zhan and Leslie Keith Norford | Massachusetts Institute of Technology | Towards cost-effective energy savings: Learnings from non-invasive occupant-centric control implementation in an office building | Occupant-centric control Rule-based control Building energy savings Occupant behavior | Occupant-centric control (OCC) has been a popular topic in building energy research and is a viable strategy for reducing operational energy use in buildings. Yet, the implementation of this control strategy often involves sophisticated technology that is expensive to acquire, install, and maintain, weakening the economic argument for implementing these controls. An approach that tailors OCC solutions to buildings with minimal or outdated occupant sensing technology could increase the likelihood that operators of existing buildings adopt OCC to reduce energy use and improve thermal comfort. This study implemented OCC in an 80-person office suite only through existing hardware to investigate how energy savings can be achieved in buildings by working with legacy control systems. Over the course of two summer months, energy use in the office suite was reduced by 53%. The bulk of the savings come from a reduction in occupied hours, achieved by shortening daily occupancy schedules in common spaces and determining occupancy through manual overrides in single-occupancy spaces. The results of the study confirm that, under a schedule where the office is only partially occupied during the working week, significant energy savings can be achieved in offices through non-invasive methods that make use of existing infrastructure and thoughtfully selected system parameters. However, the lack of flexibility in legacy systems means that energy consumption during occupied hours remains highly contingent on individual occupant behavior, limiting potential energy savings. Thus, occupant engagement and education should be considered crucial to OCC implementation in legacy building control systems and surveys should be emphasized as a necessary procedure for understanding occupant behavior and preference. The widespread implementation of non-invasive, computationally efficient OCCs in legacy systems could effectively reduce energy use in existing buildings where a substantial retrofit is not financially viable. |
| 9-3 | 5/21/2026 15:30 | Building Technology and Performance | SGM 101 | 654 | Xuewen Quan, Karen M. Kensek, Sathyanaraya Raghavachary, Haonan Wang | #N/A | Toward AI in AECO: Integrating BIM Facility Data with an LLM-RAG Framework | ||
| 9-4 | 5/21/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 118 | 208 | Quang Van Tran, Farzad Hashemi, Parisa Najafian and Esteban Ochoa Lopez | School of Architecture and Planning, University of Texas at San Antonio | Roof Retrofit Scenarios for Thermally Vulnerable Homes: A CFD-Based Evaluation of Indoor Comfort and Air Quality in San Antonio, Texas | Cool roofs Thermal comfort Indoor air quality CFD Heat vulnerable homes | In the hot and humid climate of San Antonio, Texas, residential buildings consume 43 percent of the city’s electricity. Yet older, heat-vulnerable homes, particularly in Westside neighborhoods, remain largely overlooked in energy efficiency efforts, as local government weatherization programs mainly provide one-size-fits-all solutions that require the building envelope to be in good condition. Roofs are the most exposed elements in the envelope and strongly influence heat gain and indoor conditions. This study evaluates thermal performance and indoor air quality across roof retrofit scenarios in an older detached single-family home representative of this underserved housing stock. We employed transient Computational Fluid Dynamics (CFD) simulations in ANSYS Fluent with the Stress-Blended Eddy Simulation to resolve unsteady indoor mixing, coupled with a surface-to-surface radiation model to capture the radiative exchange between interior surfaces. A housing condition survey in the study area identified asphalt shingles and metal roofs as the most common materials, with a wide range of surface reflectance. Guided by these data, we analyzed albedo values of 0.20, 0.40, 0.60, and 0.80 to span from typical dark shingles to high reflectance white coatings. Simulations represent typical spring conditions when passive ventilation is more viable and mechanical cooling demands are lower, making roof reflectivity more impactful. This study evaluates indoor thermal and air quality outcomes by examining how roof reflectivity alters the relationship between indoor and outdoor temperature, humidity, and pollutant levels, focusing on particulate matter from infiltration. We hypothesize that higher-albedo roofs will reduce indoor heat gain and pollutant levels, delay overheating, and lessen reliance on mechanical cooling in poorly insulated homes. We further hypothesize that benefits diminish during peak summer, underscoring the need for complementary retrofit strategies such as window sealing, shading, and ventilation. Roof-surface thermal imagery from a DJI Matrice 350 RTK drone will provide additional validation of reflectance-driven performance differences. The findings establish retrofit benchmarks for ASHRAE Climate Zone 2A and highlight cool roofs as a cost-effective strategy to improve thermal comfort, health, and resilience in underserved communities while supporting affordable housing goals. |
| 9-4 | 5/21/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 118 | 264 | Mana Nemati Aghdam and Manish Dixit | Department of Construction Science, Texas A&M University, 400 Bizzell St, College Station, Texas. | Integrated LCA and Energy Simulation for Envelope Decisions: Climate-Dependent Results | Life cycle assessment (LCA) Embodied impacts Operational energy Window-to-wall ratio Climate zone | This paper presents a whole-building life cycle assessment of Francis Hall, an academic building at Texas A&M University, to compare embodied and operational impacts under different climates and envelope design choices. The study combines Tally, linked to a Revit model, with EnergyPlus simulations generated through Revit Systems Analysis. A baseline case in College Station, Texas (climate zone 2A) is evaluated and then re-simulated in Chicago, Illinois (zone 5A) to study climate sensitivity. Design variations include three window-to-wall ratios (10%, 30%, 60%), two wall insulation levels, and two glazing types (single and double low-e). Tally reports 13 TRACI indicators; global warming potential, primary energy, and water use are compared alongside annual heating, cooling, lighting, and equipment loads. Results show that operational impacts change more than embodied impacts across scenarios, with cooling dominating in 2A and heating dominating in 5A. Larger window areas consistently increase both embodied and operational impacts, while improved glazing reduces energy use in both climates with only small material changes. Added insulation yields strong benefits in 5A but limited gains in 2A, indicating that its effectiveness is climate-dependent. The findings highlight the need to evaluate envelope decisions with both LCA and energy modeling and show that climate-responsive control of glazing area, glazing performance, and insulation level can reduce total life cycle impacts. |
| 9-4 | 5/21/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 118 | 266 | Mohamed Dardir, Jeffrey Wilson and Umberto Berardi | Polytechnic University of Bari; South Dakota State University; University of Waterloo | Natural Infrastructure for Health and Environmental Risk Mitigation | natural infrastructure climate adaptation climate hazards health risk mitigation urban sustainability | Urban microclimates are facing escalating environmental risks associated with climate change, e.g., extreme heat, flooding, and storm events. These risks result in increased healthcare demands and reduced quality of life, especially among vulnerable populations. Previous conduct of natural urban developments had limited perception of their multifaceted benefits, impacting their adoption in municipal planning. This paper introduces a comprehensive, evidence-based and data-driven decision-making framework to demonstrate how natural and green retrofitting features, including urban greenery and cool urban surfaces, can effectively mitigate extreme environmental risks while promoting significant co-benefits for public health and local economy. The presented method integrates evidence-based statistical models for community data and localized weather measurements, using log-linear Poisson regression and microclimate simulations, applying community-level urban modeling. This modeling approach investigates the impact of applying natural retrofitting features on environmental and community resilience. This integrated method aims to simulate environmental variables (pollutant dispersion, heat exposure intensity, urban flooding, and wind storms), anticipate community health outcomes (emergency department visits, hospitalizations, etc.) and quantify reductions in energy consumption. The proposed applications revealed that even modest increases in urban natural features substantially reduce microclimate ambient temperatures, manage wind speeds, control runoff potential, and decrease heat-related health impacts. Remarkably, this framework provides municipalities with evidence-based, actionable insights to prioritize investments in nature-based climate adaptation and resilient urban design. Key findings show that expanding natural infrastructure controlled ambient temperatures and reduced daily humidex during anticipated heatwaves by more than 11%. The proposed application also controlled flooding and storm peak conditions. Anticipated reductions in health risks were also reported as a result of enhanced urban environments. While limitations exist in terms of the availability of health data, this research offers an adaptable model for future studies on community resilience through natural infrastructure. This decision-making framework gives evidence-based insights into the strategic investment in nature-based solutions for healthier, more sustainable, and resilient cities in the face of increasing climate hazards. |
| 9-4 | 5/21/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 118 | 372 | Maryam Meshkinkiya and Farzad Hashemi | UT San Antonio | Beyond Numerical Features: Mixed-Type Clustering of Urban Building Archetypes Using Hierarchical and K-prototypes Methods | Building Archetype Open Data Categorical Hierarchical K-Prototype | Future-proofing the building stock against severe weather events requires a multidisciplinary research approach and the integration of multi-source data. Conducting studies that scale beyond individual buildings to the neighborhood and city levels demands the use of representative archetypes. Building archetypes are standardized representations of similar buildings, commonly used in urban analysis when detailed data for each individual building is unavailable. Archetype-based methods are widely used in urban microclimate studies, urban energy modeling, material stock estimation, and urban decarbonization scenarios. Various grouping techniques (e.g., rule-based and unsupervised) are employed to identify representative archetypes across the building stock. Most previous work has focused primarily on numerical and continuous building features, even though many important features are categorical attributes. Recently, k-prototypes clustering has been proposed in the building-archetype literature to handle mixed numerical–categorical data. This study extends that line of work by applying hierarchical clustering and then systematically comparing hierarchical and k-prototypes in terms of how each method handles mixed-type building features, with particular attention to categorical variables. Specifically, we apply hierarchical clustering with Gower distance to construct a tree-based structure that organizes buildings according to shared physical and functional characteristics. The framework is demonstrated for the residential building stock of San Antonio, Texas. We evaluate the proposed hierarchical approach against k-prototypes clustering using Silhouette and Within-Cluster Sum of Squares (WCSS) scores. The results show that hierarchical clustering with Gower distance yields better-separated and more categorically coherent clusters, whereas k-prototypes with the mixed distance produces more compact, prototype-centered clusters driven by numerical similarity. These contrasting behaviors reveal a trade-off between categorical coherence and numerical compactness in archetype generation and highlight that the choice of clustering method and distance metric should be aligned with the specific goals of urban building archetype analysis. |
| 9-4 | 5/21/2026 15:30 | Climate Change Adaptation, Resilience, and Environmental Policy | GFS 118 | 414 | Maryam Abbasi Kamazani and Manish K. Dixit | Texas A&M University; Texas A&M Universiy | AI-driven and simulation-based multi-objective building envelope optimization: strengths, limitations, and gaps | Building Performance Simulation Multi-Objective Optimization Surrogate Modeling Generalizability Climate Change | Multi-objective optimization (MOO) coupled with building performance simulation has become a standard approach for exploring trade-offs among energy use, comfort, cost, and environmental impacts. Yet the same characteristics that make simulation-based MOO reliable, high-fidelity physics, detailed schedules, and explicit systems modeling, also make it expensive, data-intensive, and difficult to generalize across buildings and climates. In parallel, AI-driven acceleration (surrogate modeling, meta-model-assisted search, and hybrid simulation-learning workflows) has enabled orders-of-magnitude speedups, opening the door to larger design spaces and richer objective sets. However, many reported surrogate-assisted MOO pipelines remain narrowly scoped: models are often trained for a single building geometry under a single climate file and then optimized within that same context, limiting transferability to other climates, morphologies, operations, and system configurations. This paper synthesizes the state of simulation-based and AI-driven MOO for envelope-centric building design. It highlights methodological strengths (transparent physics, explicit constraint handling, and multi-criteria decision support), diagnoses recurring limitations (computational burden, discrete design spaces, workflow fragility, and evaluation inconsistencies), and emphasizes the generalizability challenge as a central barrier to practical deployment. The review concludes with research directions on benchmark-driven validation, uncertainty-aware and robustness-based optimization, interoperable BIM-BEM-LCA data pipelines, and climate- and geometry-spanning surrogate models that can support credible, scalable decision-making. |
| 9-5 | 5/21/2026 15:30 | Visual (Lighting and Daylighting) Quality and Accustic Quality | GFS 207 | 152 | Haerin Yang, Minwoo Kim and Jeehwan Lee | Myongji University; Technical University of Munich | A Multi-Layered Daylighting Assessment of LEED Certified Buildings | LEED Daylighting Building Simulation Occupant-centered Assessment Daylight Performance Metrics | Meticulous daylighting design is not only a fundamental passive strategy for energy conservation but also a critical architectural element directly linked to human physical and emotional health. In school buildings—where growing students spend the majority of their daytime—daylighting must receive particular attention at the design stage, as it significantly influences creativity, physical development, and emotional well being. The recent update of the LEED v5 standard, incorporating both Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE), represents a notable shift toward more detailed, occupant centric environmental evaluations. However, a truly comprehensive understanding of indoor light environments requires a holistic approach that extends beyond these conventional metrics. This study conducts a multi layered daylighting analysis of five LEED certified school buildings to evaluate their performance against a broader set of indicators, including Average Glare (AG), Daylight Factor (DF), and Equivalent Melanopic Lux (EML). The case study buildings were selected based on their high daylighting credits and the availability of complete architectural documentation. Detailed digital models were developed in Rhino, and simulations were performed using CLIMATE STUDIO and ALFA to generate a comprehensive dataset of performance metrics. A key finding of this study is that, while the daylight performance metric of Spatial Daylight Autonomy (sDA) satisfied LEED requirements from a physical environment perspective, the occupant centered metric of Average Glare did not consistently yield corresponding results. This discrepancy highlights the necessity of employing a broader and more diversified set of evaluation metrics to achieve a truly comprehensive assessment of indoor daylighting performance. This expected discrepancy highlights the limitations of a limited set of criteria and underscores the necessity of a multi-metric framework for a more accurate and occupant-centered daylighting assessment. Ultimately, this study emphasizes the importance of designing an environment where various metrics are simultaneously considered and balanced, focusing not merely on numerical values but on creating a truly satisfying and comfortable environment for occupants. |
| 9-5 | 5/21/2026 15:30 | Visual (Lighting and Daylighting) Quality and Accustic Quality | GFS 207 | 172 | Bahereh Vojdani, Deok-Oh Woo and Andressa Martinez | assistant professor at the University of Maryland, College Park.; Urban and Regional Planning and Design, University of Maryland, College Park | Assessing Architect-Friendly Daylighting Feedback from LLaMA: A Zero- and Few-Shot Evaluation of an LLM Approach | Large Language Models Zero-Shot Daylighting Simulation Explainability | Large Language Models (LLMs)—such as GPT and LLaMA—have demonstrated strong potential in natural language understanding, yet their application in building performance simulations remains underexplored (Johnsen, 2024). In particular, the ability of LLMs to interpret quantitative outputs from daylighting simulations and communicate architect-friendly design feedback has not been systematically evaluated. This study examines how LLMs interpret and explain daylight performance metrics in early-stage architectural design. We curated a dataset of 108 simulated office spaces across diverse climates, orientations, and material properties, with daylighting results being reported using four key metrics: Spatial Daylight Autonomy (sDA), Annual Sunlight Exposure (ASE), Daylight Autonomy (DA), and Useful Daylight Illuminance (UDI). These metrics capture different aspects of daylight availability and glare risk. For instance, low sDA coupled with high ASE indicates poor daylight access but excessive direct sunlight, which may lead to visual discomfort. We prompted two LLMs—GPT-4 (via OpenAI) and LLaMA (via Ollama)—to generate performance explanations under both zero-shot (no examples given) and few-shot (five example prompts provided) conditions (Zeng et al., 2024). We define zero-shot learning as a setting in which the model is asked to perform a task without prior examples, while few-shot learning involves limited examples to guide the model’s output, mimicking real-world adaptation without model retraining. LLM outputs were evaluated using four interpretability dimensions adapted from natural language processing (NLP) research: clarity (readability for architects), correctness (technical accuracy of daylighting interpretation), specificity (connection to climate, orientation, or materials), and actionability (presence of design strategies). These criteria are based on frameworks from prior AI evaluation studies in explainable machine learning (Lan, 2025). Results show GPT-4 consistently generated more accurate and actionable feedback, particularly when interpreting low sDA/high ASE trade-offs. LLaMA responses improved in the few-shot condition, though common limitations included misuse of technical terms (e.g., UDI) and overly generic suggestions. This study highlights both the opportunities and limitations of current LLMs as simulation-to-feedback tools and establishes a foundation for developing domain-tuned models to support sustainable building design. |
| 9-5 | 5/21/2026 15:30 | Visual (Lighting and Daylighting) Quality and Accustic Quality | GFS 207 | 255 | Dongwoo Lee, Manal Anis, Donghyeok Choi, Hyungsub Kim and Yun Kyu Yi | Inha University; University of Illinois at Urbana-Champaign | Developing an Outdoor View Evaluation Method for Complex Shading Systems | Outdoor View Evaluation Universal Visible Sky Factor (uVSF) Kinetic Shading System | Access to outdoor views provides notable benefits to building occupants, supporting health, well-being, orientation, and overall comfort. Despite extensive research on daylight, energy, ventilation, and visual comfort, outdoor view remains one of the least explored aspects of indoor environmental quality. The influence of kinetic shading devices on view quality, in particular, has received limited attention. Previous approaches have relied on two-dimensional representations, which do not capture the three-dimensional nature of human vision. Since human eyes perceive a wide field of view both vertically and horizontally, reducing this to flat 2D images introduces. This study introduces a method based on the Universal Visible Sky Factor (uVSF), developed to evaluate the impact of shading systems on outdoor views. The uVSF calculates the ratio of unobstructed sky area by projecting obstruction boundaries onto a continuous sky dome. It also allows assessment of visible sky ratios from multiple viewing points at different vertical heights, moving beyond conventional evaluations. The method was tested on a window equipped with a kinetic shading system composed of horizontal and vertical movable elements. Using uVSF, the study measured unobstructed sky areas from several viewing heights. Compared with traditional 2D evaluations, the uVSF revealed noticeable differences. Initial results indicate that 2D view measurement and uVSF differ by more than 10%. Adjusting the vertical measuring points alters uVSF values but shows no change in the 2D evaluation. These findings suggest that conventional methods may underestimate view access by overlooking spatial depth and vertical obstructions. This research demonstrates the potential of the uVSF method to provide a more accurate assessment of outdoor view quality. Future work will expand testing across a wider range of shading configurations and compare uVSF with existing metrics to examine its accuracy, applicability, and limitations. |
| 9-5 | 5/21/2026 15:30 | Visual (Lighting and Daylighting) Quality and Accustic Quality | GFS 207 | 409 | Won Hee Ko, Luis Santos, Michael Kent, Hanwook Kim and Nehal Nagarjun | Department of Architecture, Design and Media Technology, Aalborg University; Harley Ellis Devereaux; Hillier College of Architecture and Design, New Jersey Institute of Technology; School of Business, Singapore University of Social Sciences, Singapore | How View Content Determine Minimum Window Size and Energy Implications: Evidence from Virtual Reality Experiments | Window views View access Virtual reality Occupant satisfaction WWR | Windows play a critical role in connecting building occupants to the external environment, with view quality influencing health, well-being, and work performance. At the same time, windows affect energy efficiency and carbon emissions, making the provision of high-quality views a complex design challenge. Despite this importance, empirical evidence remains limited, and few accessible tools exist to support view-related design decisions. This study focuses on access, a key dimension of window view quality defined as the amount of view visible to occupants. Access is shaped by design decisions across multiple scales—including massing, floor layout, and facade design—and has implications for both occupant satisfaction and building energy use. Building on prior research, we examine a wider range of view contents, asking whether view content alters the minimum window size required for occupant satisfaction. Using immersive virtual reality, 60 participants evaluated 50 simulated office scenes varying in window size, viewing distance, direction, and content. Results show that view content, direction, and their interaction with distance significantly influence satisfaction. Three-layered views or those incorporating natural elements consistently received higher ratings, while views limited to buildings or building–sky combinations scored lower. By integrating this dataset with prior participant data (n = 100), we refined the View Access Index and validated key thresholds: a window-to-wall ratio (WWR) of 25% is sufficient for direct views with high-quality content, whereas approximately 38% WWR is required for less desirable content (e.g., buildings only). Side views—the most common condition in office layouts—require a wider WWR range (28%–60%), depending on viewing distance and view content. |
| 9-6 | 5/21/2026 15:30 | Indoor Air Quality | GFS 101 | 34 | Jing Wu, Dahai Qi and Lexuan Zhong | Université de Sherbrooke; University of Alberta | Wildfire Smoke Alters Particle Size Distributions Indoors and Outdoors in an Urban Office Building | Wildfire smoke Particle size distribution Nanoparticle infiltration Indoor air quality PM2.5 | Wildfire smoke is a growing contributor to urban particulate pollution, yet its size-resolved impacts on outdoor and indoor air quality remain inadequately characterized. This study examined particle size distributions (10 nm – 10 µm) outdoors and indoors in Edmonton, Canada, during the 2025 wildfire season. Here, we combined scanning mobility and optical particle sizers to capture hourly particle concentrations, revealing a shift from ultrafine particles (~21 nm) under background conditions to accumulation-mode particles (~209 nm) during wildfire events. The relationship between particle number concentrations in different size bands and PM2.5 (mass concentration) was examined, indicating strong linear relationships (R² > 0.85) between PM2.5 and particle number concentrations in the 100–300 nm and 300–1000 nm size ranges. As a result, ambient PM2.5 data obtained from the nearby weather stations are an effective predictor of size-resolved wildfire smoke concentrations for both size bands. Indoor particle measurements indicated that wildfire smoke entered the building, though indoor concentrations remained much lower than outdoors. Regression-based outdoor particle estimates enabled paired indoor–outdoor analysis, revealing positive correlations (r > 0.6) for both particle bands in the 100–300 nm and 300–1000 nm size ranges, with average indoor/outdoor ratios of 0.20 ± 0.07 and 0.18 ± 0.11, respectively. This result indicates substantial attenuation of wildfire smoke particles by the filtration system (MERV 8 + MERV 14), given the high pollutant levels during wildfire season. These findings provide novel insights into size-dependent wildfire smoke infiltration processes and highlight the need for particle-size–resolved models to improve indoor exposure assessments during wildfire episodes. |
| 9-6 | 5/21/2026 15:30 | Indoor Air Quality | GFS 101 | 319 | Ruoyu Lan, David Lorenzetti, Marion Russell and Michael Sohn | Lawrence Berkeley National Laboratory | Ventilation and Filtration Tradeoffs for Increasing Building Protection from Outdoor Aerosols | Indoor hazard assessment simulation ventilation | Outdoor pollutants, such as industrial chemicals, aerosols, and smoke, can pose acute threats to building occupants. The degree of protection provided by the building depends on many unknown or variable building characteristics, and decision-makers must develop planning actions in light of these broad unknowns. In this presentation, we present a graphical approach to mapping the tradeoffs between building design, building operation, and the protection offered to occupants from pollutants of outdoor origin. Specifically, we develop nomographs that show the interactions between building characteristics (e.g., filter efficiency), release conditions (e.g., the duration of the outdoor source, and distance from the building), agent properties (such as deposition rate and toxic load exponent), and ventilation strategies (including air change rates and response strategies). The graphic approach naturally demonstrates how uncertainty about any of these inputs affects the predicted protection factor. Key findings demonstrate that building protection factors can vary by several orders of magnitude. Counter-intuitively, certain ventilation strategies may increase indoor exposure during short-duration releases, while providing protection during extended events. The nomograms also reveal critical thresholds where small changes in building operation significantly affect occupant safety, particularly for agents with steep dose-response curves. The practical utility of this approach is demonstrated through case studies, ranging from industrial accidents to deliberate releases. |
| 9-6 | 5/21/2026 15:30 | Indoor Air Quality | GFS 101 | 514 | Yi Fang, Haoran Zhao, Tim Tyner, Stephanie M. Holm, Brett C. Singer, Anabelle Garza, Arlette Garcia-Ramirez, Briseida Vasquez, Debra Manzo Garcia, Jesus Rivera, John R. Balmes and Amy Dryden | AEA Clean Energy; Central California Asthma Collaborative; Fielding School of Public Health, University of California Los Angeles; Lawrence Berkeley National Laboratory; University of California San Francisco; University of California, San Francisco | Range Hood Use and Effectiveness in Reducing Indoor Air Pollution During Gas and Induction Cooking | Kitchen Ventilation Air Pollution Exposure PM₂.₅ NO₂ Home Intervention Study | The Cooking Energy and Ventilation Impacts on Children’s Asthma (CEVICA) study measured cooking frequency, range hood use, indoor air quality and respiratory health indicators of children with asthma living in homes with gas stoves in California’s San Joaquin Valley. The study installed electric induction stoves and repeated measurements over three 2-week intensive periods, at baseline and at the end of two consecutive 3-month study phases. Stove replacements occurred at the start of Phase 1 or Phase 2 by random assignment. There were 4184 cooking events identified by automated analysis of time-series data from temperature sensors mounted above the cooktops and 1038 related range hood usage events detected from data recorded by anemometers, smart plugs, or motor loggers. Analysis of 1-minute resolved PM₂.₅ and NO₂ data identified and quantified 2685 PM2.5 events and 2606 NO₂ events. Range hood use was characterized as a binary variable (≥3 min vs. <3 min use). For PM₂.₅, range hood use was more common during cooking events associated with higher particle emissions and longer cooking durations, and PM₂.₅ concentrations during events with range hood use were comparable to those without use, suggesting that ventilation use often occurred during higher-emission cooking scenarios. For NO₂, pollution concentrations were about 45 percent higher than events with range hood use. The lowest pollutant levels were observed when the range hood operated for more than half of the cooking duration. These findings show that consistent operation of kitchen exhaust devices during cooking can substantially reduce short-term indoor exposure to PM2.5 and NO₂ in homes. |
| 9-6 | 5/21/2026 15:30 | Indoor Air Quality | GFS 101 | 580 | Elham Hasani Alavy, Mahsa Khanpoor Siahdarka, Zahra Qavidelfardi and Faeghe Rahnama | School of Property, Construction and Project management, RMIT University, Melbourne, Australia; Shahid Behehshti University; Shahid Beheshti University; University of Arizona | Lessons from the Post Occupancy Evaluation of the Indoor Learning Environments: A Review | Thermal Comfort Indoor Air Quality Air Contaminants University Classrooms Healthy Environment | Indoor Environmental Quality (IEQ) is critical in university classrooms due to high occupancy density and prolonged exposure. This study presents a systematic review of peer-reviewed literature published since 2015, synthesizing evidence on thermal comfort and indoor air quality (IAQ) in higher-education classrooms. Results show strong methodological convergence, with the PMV–PPD model and subjective temperature indicators, particularly Thermal Sensation Vote (TSV),most frequently applied. Naturally ventilated classrooms consistently exhibited higher neutral temperatures (≈26–29 °C), exceeding standard comfort limits and reflecting adaptive behavior, while air-conditioned classrooms showed narrower comfort ranges (≈23–25 °C) but often reduced occupant satisfaction. Carbon dioxide emerged as the primary IAQ proxy, with most studies reporting concentrations above 1,000 ppm during occupancy. The findings reveal a persistent mismatch between standard-based criteria and field conditions, highlighting the need for integrated, occupant-centric IEQ assessment frameworks that jointly address thermal comfort and ventilation performance. |
| 9-8 | 5/21/2026 15:30 | Online Session | VHE 206 | 368 | Yasaman Norouzi and Manish Kumar Dixit | Texas A&M University | Forecasting the U.S. Residential Renewable Electricity Mix: A Time-Series Approach for 50-Year Building GWP Projections (1949–2080) | Renewable energy forecasting ARIMA residential electricity operational carbon grid decarbonization GWP projections. | Assessments of building operational Global Warming Potential (GWP) often rely on static representations of today’s electricity grid, overlooking the influence of long-term grid decarbonization on future emissions. This study presents a dynamic forecasting framework to project the evolution of the U.S. residential electricity mix and its implications for operational GWP through 2080. Using 75 years of historical electricity data from the U.S. Energy Information Administration (EIA), Autoregressive Integrated Moving Average (ARIMA) models are applied to estimate baseline trends in renewable electricity adoption. To account for long-term uncertainty, statistical forecasts are calibrated using scenario envelopes informed by EIA, IEA, and NREL energy outlooks. Results show that under a mid-ambition scenario, renewable electricity exceeds 50% of the residential mix by mid-century. Incorporating these dynamics reduces cumulative 50-year operational GWP by approximately 31% relative to static grid assumptions, indicating that static approaches substantially overestimate long-term operational impacts. The proposed framework provides a transparent and replicable method for integrating evolving electricity systems into prospective operational LCA of buildings. |
| 9-8 | 5/21/2026 15:30 | Online Session | VHE 206 | 527 | Kátia Fugazza, Pedro Braga and Sylvia Meimaridou Rola | UNESA; Universidade Federal do RIo de Janeiro (UFRJ) | Architectural Retrofit and HVAC Modernization in Existing Hospitals: A Case Study of the Municipal Hospital Carlos Tortelly | Hospital retrofit Hybrid ventilation HVAC Brazilian standards Healthcare architecture | The implementation of the Unified Decentralized Health System (Sistema Único Descentralizado de Saúde – SUDS), followed by the consolidation of the Brazilian Unified Health System (Sistema Único de Saúde – SUS), marked a decisive restructuring of healthcare delivery in Brazil. In Niterói, the Niterói Project became a state and national reference for the municipalization of federal and state units, with the Niterói Social Security Center (Centro Previdenciário de Niterói – CPN) playing a central role as the largest outpatient facility, also managing Hospitalization Authorizations (AIHs) for the contracted private network and the Emergency Home Medical Assistance Service (SAMDU). Within this context, the Carlos Tortelly Municipal Hospital was inaugurated in March 1982, designed according to the healthcare model of the time, and has since remained a regional reference in public healthcare. After 43 years of continuous operation, the Carlos Tortelly Municipal Hospital presents architectural and HVAC deficiencies in relation to the current Brazilian standards for healthcare ventilation and indoor air quality, such as ABNT NBR 7256:2022, NBR 16401, and NBR ISO 14644. Only circulation areas rely on natural ventilation, while wards, emergency departments, and critical units depend on outdated mechanical systems that no longer ensure adequate air exchange rates, thermal comfort, or environmental safety. This study presents a comparative assessment between the current system and the proposed HVAC project, aiming to determine the extent to which the new design can comply with national regulations, provide adequate thermal comfort under the hot and humid microclimate of Niterói, and integrate architectural recommendations for retrofit. The methodology includes technical inspections, documentation review of the existing infrastructure, and environmental measurements (temperature, relative humidity, and air exchange rates), combined with a comparative analysis of the current system and the proposed HVAC design. It is concluded that the modernization of the Carlos Tortelly Municipal Hospital requires an integrated approach, combining HVAC upgrades with architectural interventions that promote hybrid ventilation strategies. This approach is essential to ensure regulatory compliance, energy efficiency, sanitary safety, and improved environmental quality in medium-sized public hospitals in Brazil. |
| 9-8 | 5/21/2026 15:30 | Online Session | VHE 206 | 528 | Zhongqing Yang and Hikaru Kobayashi | Department of Architecture and Building Science, Graduate School of Engineering, Tohoku University | Occupant-Distribution-Based CO2 Measurement to Optimize Demand-Controlled Ventilation in Office Spaces | Indoor air quality Demand-controlled ventilation CO2 measurement Ventilation airflow rate Demand response flexibility | Demand-controlled ventilation (DCV) in office buildings relies on a single zone-level carbon dioxide (CO2) sensor to regulate outdoor air supply in response to zone occupancy inferred from CO2 levels. Although effective for reducing ventilation energy relative to constant-volume systems, this strategy assumes spatially uniform occupancy and CO2 distribution, which can limit both indoor air quality (IAQ) and operational flexibility. To address this gap, this study proposes a method that combines CO2 sensing with seat-level occupancy detection to allocate ventilation air more intelligently across the breathing zones of occupants. In the experimental setup, CO2 sensors were installed in the breathing zone of each row within a typical office layout and above the multi-user activity table to capture spatial variations in occupant-generated CO2 concentration. Occupancy data were collected at each seat in conjunction with CO2 measurements to dynamically model airflow rate adjustments to occupied areas by a demand-controlled ventilation system. System performance was evaluated by analyzing the modeled airflow response and IAQ maintenance, quantifying the potential demand response flexibility of the ventilation system under time-varying occupancy conditions. The results demonstrate that incorporating seat-level occupancy with targeted CO2 sensing can contribute to improving the responsiveness and efficiency of the building ventilation system. |
| 9-8 | 5/21/2026 15:30 | Online Session | VHE 206 | 531 | Niloofar Nikookar and Azadeh O. Sawyer | Carnegie Mellon University | An AI-Driven Affective Lighting System for Stress Reduction and Satisfaction in Office Environments. | Affective Lighting psychological wellbeing Reinforcement learning Adaptive lighting control | For years, dynamic lighting systems have been designed to supplement daylight and meet task-illumination requirements. However, the influence of light on humans extends beyond adequacy, as lighting attributes and their interactions have a profound impact on human psychology, including mood, and perception of space. This study presents a context-aware and user-centered lighting control framework for office environments that offers lighting modes focused on calmness, activation, and productivity designed to support office work through context-dependent presets and personalization. Unlike conventional dynamic systems that primarily respond to daylight levels, this framework links human affect to environmental conditions, such as blinds position and sky state, and adjusts correlated color temperature (CCT) and brightness accordingly. The system employs white light tones (2700K – 6500K) to both support task performance and influence users’ affective state, ensuring suitability for everyday office environments. The system couples derived lighting presets and modes grounded in a user study with a reinforcement learning (RL) framework using a contextual bandit approach (LinUCB), which is designed to fine-tune lighting conditions to individual preferences through ongoing interaction. The implementation integrates a sensing system and a lighting control architecture that enables continuous real-time adaptation. |
| 9-8 | 5/21/2026 15:30 | Online Session | VHE 206 | 535 | Kátia Fugazza, Marcos Marques and Sylvia Meimaridou Rola | PUC-Rio; Universidade Federal do RIo de Janeiro (UFRJ) | Architectural Retrofit and Multidisciplinary HVAC Modernization with BIM Methodology in Existing Hospitals: A Case Study of the Carlos Tortelly Municipal Hospital | BIM Hospital retrofit Facility Management Multidisciplinary engineering Sustainability Climate resilience | The modernization of existing hospitals requires a multidisciplinary approach that integrates architecture, engineering, and facility management throughout the entire building life cycle. In Brazil, many hospitals built in the 1980s present architectural and technical deficiencies in relation to current standards for ventilation, indoor air quality, energy efficiency, and operational safety. The Carlos Tortelly Municipal Hospital, inaugurated in 1982 in Niterói and operating for 43 years, exemplifies these challenges and demands a retrofit process that includes not only the updating of HVAC systems but also the integration of structural, electrical, hydraulic, and building automation disciplines. This study analyzes the modernization project of the Carlos Tortelly Municipal Hospital through the lens of Building Information Modeling (BIM), applied from early design to construction, operation, and maintenance. BIM is considered not only as a coordination tool for different disciplines but also as a collaborative platform for integration with Facility Management (FM) systems, enabling predictive maintenance and data-driven asset management. This approach allows for performance evaluation regarding air exchange rates, thermal comfort, and energy efficiency under the hot and humid microclimate of Niterói, while ensuring compliance with Brazilian standards for healthcare ventilation and environmental quality. The methodology combines technical inspections, document analysis, multidisciplinary BIM modeling, and environmental simulations, along with a comparative assessment between the current operating systems and the proposed retrofit design. Literature and case studies on BIM adoption in building maintenance and public facilities demonstrate its potential to reduce life-cycle costs, enhance sustainability, extend building lifespan, and support transparency in public healthcare management. It is concluded that the modernization of the Carlos Tortelly Municipal Hospital should be conducted through an integrated strategy that links architectural retrofit, engineering system upgrades, and BIM-based facility management. This multidisciplinary and data-driven approach fosters resilience, sustainability, and environmental quality in medium-sized public hospitals, aligning with national innovation policies such as the Brazilian BIM Strategy (Estratégia BIM BR) and with broader climate adaptation goals. |
| 9-8 | 5/21/2026 15:30 | Online Session | VHE 206 | 537 | Deok-Oh Woo, Rocky Alazazi, Karen Ternes, Rajul Patel and Sarah Beatty | Citra; Culturewell; Trinity Health Oakland Hospital; University of Maryland | High-Intensity UVC Irradiation of Air Handling Units for Enhanced Energy Efficiency Under Varying Biofouling Risks | Biofouling Cooling coil Air Handling Unit High-intensity UVC irradiation UVGI | Ultraviolet germicidal irradiation (UVGI) is widely used to inactivate microorganisms on air-handling unit (AHU) cooling coils; however, its impact on energy performance under real-world operating conditions remains insufficiently quantified, particularly with respect to initial coil biofouling severity. The thermal performance response of two operational AHUs with similar capacities but distinct levels of coil biofouling was evaluated under high-intensity UVC irradiation. Field measurements were conducted in a healthcare facility located in a cool–humid climate during the cooling season. Baseline operation was monitored for eight weeks, followed by seven weeks of continuous high-intensity UVC operation. The installed UVC systems delivered surface irradiation intensities exceeding 1000 μW/cm². Thermal performance was assessed using enthalpy-based heat-transfer conductance (UA) calculated at reference conditions, while fan power was continuously monitored. Results indicate that high-intensity UVC irradiation significantly improved coil thermal performance in both AHUs. Mean UA increased by 14.7% for the moderately fouled coil and by 18.4% for the heavily fouled coil, indicating greater absolute performance recovery at higher initial biofouling levels. In contrast, no measurable reduction in fan energy consumption was observed due to residual non-biological particulate accumulation caused by upstream filter bypass. Overall, the findings demonstrate that UVC irradiation is effective in restoring cooling coil heat-transfer performance across varying fouling conditions, while highlighting the importance of filtration integrity in realizing airflow-related energy savings. The results provide field-based evidence to support more accurate estimation of UVC-related energy benefits in building applications. |
