Pub Date : 2026-02-09DOI: 10.1016/j.enbuild.2026.117131
Lei Li, Long Jiang, Xiaoyi She, Jianhang He, Meng Wu, Meng Zhen, Kai Nan, Ming Zhang
With population aging, improving the winter outdoor thermal comfort of older adults in historic urban districts is important for health and for sustainable urban renewal. Focusing on two representative sites—Jinli in Chengdu (southern group, hot summer–cold winter) and Buzili in Zhangjiakou (northern group, cold zone), we combined micrometeorological measurements with questionnaires, obtaining 1,512 valid older adult samples. Physiologically Equivalent Temperature (PET) was used to assess winter thermal perception, and machine learning models were applied to identify key influencing factors. Results indicate that the northern group has a Neutral Physiologically Equivalent Temperature (NPET) of 7.4℃ and a thermally acceptable range (TAR) of 1.90–14.66℃, whereas the southern group has an NPET of 12.3℃ and a TAR of 8.93–18.51℃. Random Forest performed best for predicting Thermal Sensation Vote (TSV) (north R2 = 0.804, south R2 = 0.867). SHapley Additive exPlanations (SHAP) translated qualitative directions into indicative intervals: Va exceeds about 2.0 m/s it markedly shifts TSV toward “colder”, whereas keeping near ground Va within 1–1.5 m/s lowers risk; in the south, when RH reaches about 80% or higher and Ta is above about 12℃, the marginal warming effect of temperature increase alone attenuates, suggesting a priority for dehumidification plus moderate warming. PM2.5 and PM10 showed a negative association with Thermal Comfort Vote (TCV) in the north. This study provides winter thermal benchmarks and quantifies the context sensitivity of temperature–wind/humidity couplings into practice oriented indicative intervals, offering evidence for microclimate optimization and age friendly design in historic districts
{"title":"Winter thermal comfort of older adults in historic districts: A comparative study across two Chinese climate zones","authors":"Lei Li, Long Jiang, Xiaoyi She, Jianhang He, Meng Wu, Meng Zhen, Kai Nan, Ming Zhang","doi":"10.1016/j.enbuild.2026.117131","DOIUrl":"https://doi.org/10.1016/j.enbuild.2026.117131","url":null,"abstract":"With population aging, improving the winter outdoor thermal comfort of older adults in historic urban districts is important for health and for sustainable urban renewal. Focusing on two representative sites—Jinli in Chengdu (southern group, hot summer–cold winter) and Buzili in Zhangjiakou (northern group, cold zone), we combined micrometeorological measurements with questionnaires, obtaining 1,512 valid older adult samples. Physiologically Equivalent Temperature (PET) was used to assess winter thermal perception, and machine learning models were applied to identify key influencing factors. Results indicate that the northern group has a Neutral Physiologically Equivalent Temperature (NPET) of 7.4℃ and a thermally acceptable range (TAR) of 1.90–14.66℃, whereas the southern group has an NPET of 12.3℃ and a TAR of 8.93–18.51℃. Random Forest performed best for predicting Thermal Sensation Vote (TSV) (north R<ce:sup loc=\"post\">2</ce:sup> = 0.804, south R<ce:sup loc=\"post\">2</ce:sup> = 0.867). SHapley Additive exPlanations (SHAP) translated qualitative directions into indicative intervals: V<ce:inf loc=\"post\">a</ce:inf> exceeds about 2.0 m/s it markedly shifts TSV toward “colder”, whereas keeping near ground V<ce:inf loc=\"post\">a</ce:inf> within 1–1.5 m/s lowers risk; in the south, when RH reaches about 80% or higher and T<ce:inf loc=\"post\">a</ce:inf> is above about 12℃, the marginal warming effect of temperature increase alone attenuates, suggesting a priority for dehumidification plus moderate warming. PM2.5 and PM10 showed a negative association with Thermal Comfort Vote (TCV) in the north. This study provides winter thermal benchmarks and quantifies the context sensitivity of temperature–wind/humidity couplings into practice oriented indicative intervals, offering evidence for microclimate optimization and age friendly design in historic districts","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"89 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-09DOI: 10.1016/j.enbuild.2026.117127
Muhammad Aarish Shah, Syed Hassaan Ali Shah, Omama Zeb, Aman Alam
The building sector is one of the major energy consumer and carbon producers, primarily due to the conventional construction and operation methods. Conventional buildings alone account for more than 40% of the total global greenhouse gas emissions during their construction and operation phase. These massive emissions further exacerbate climate change and its adverse impacts like urban flooding, urban heat island, effect overall increase in temperatures, melting of glaciers etc. To counter these challenges and mitigate the ill impacts of climate change, a step towards sustainable construction technique needs to be considered. This study evaluates the combined impact of green roofs and vertical gardening on a typical 10-Marla residential building under regional climatic conditions using EnergyPlus simulations, informed by actual utility energy consumption and assessed using prevailing average residential electricity rates. A 10-Marla residential building was modeled in Autodesk Revit and then exported to DesignBuilder software for energy analysis. The simulations were performed using EnergyPlus simulation engine, initially for the conventional building and later for the optimized building integrated with vertical and rooftop gardening. A cost-recovery analysis was performed to calculate the payback period for the amount required for retrofitting of these measures into a standard building. The results showed that there were annual energy savings of about 25% and the carbon emissions were also reduced by the same figure. The cost recovery period for the upfront cost was determined to be 3.45 years. The operative temperatures dropped by up to 1.2°C for summer season and increased by up to 1.6°C for winter season. The results should be interpreted conservatively, as localized urban heat island effects not fully captured in gridded weather datasets may further increase cooling demand and enhance the relative benefits of the proposed retrofits.
{"title":"Performance assessment of nature-based solutions for sustainable urban housing","authors":"Muhammad Aarish Shah, Syed Hassaan Ali Shah, Omama Zeb, Aman Alam","doi":"10.1016/j.enbuild.2026.117127","DOIUrl":"https://doi.org/10.1016/j.enbuild.2026.117127","url":null,"abstract":"The building sector is one of the major energy consumer and carbon producers, primarily due to the conventional construction and operation methods. Conventional buildings alone account for more than 40% of the total global greenhouse gas emissions during their construction and operation phase. These massive emissions further exacerbate climate change and its adverse impacts like urban flooding, urban heat island, effect overall increase in temperatures, melting of glaciers etc. To counter these challenges and mitigate the ill impacts of climate change, a step towards sustainable construction technique needs to be considered. This study evaluates the combined impact of green roofs and vertical gardening on a typical 10-Marla residential building under regional climatic conditions using EnergyPlus simulations, informed by actual utility energy consumption and assessed using prevailing average residential electricity rates. A 10-Marla residential building was modeled in Autodesk Revit and then exported to DesignBuilder software for energy analysis. The simulations were performed using EnergyPlus simulation engine, initially for the conventional building and later for the optimized building integrated with vertical and rooftop gardening. A cost-recovery analysis was performed to calculate the payback period for the amount required for retrofitting of these measures into a standard building. The results showed that there were annual energy savings of about 25% and the carbon emissions were also reduced by the same figure. The cost recovery period for the upfront cost was determined to be 3.45 years. The operative temperatures dropped by up to 1.2°C for summer season and increased by up to 1.6°C for winter season. The results should be interpreted conservatively, as localized urban heat island effects not fully captured in gridded weather datasets may further increase cooling demand and enhance the relative benefits of the proposed retrofits.","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"89 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-09DOI: 10.1016/j.enbuild.2026.117128
Bo Li, Gangquan Si, Minglin Xu, Detao Fan, Qianyue Wang, Xin Wang
Model predictive control (MPC) is a powerful strategy for optimizing building energy management, but its high computational burden hinders its deployment on resource-constrained hardware. To address this challenge, this paper presents a novel hierarchical control framework that synergizes MPC with deep reinforcement learning (DRL) to navigate the trade-off between control performance and computational burden. Within this framework, a low-level MPC controller is responsible for precise building energy management with the objective of maximizing energy efficiency and ensuring user thermal comfort, while a high-level DRL agent adaptively tunes the MPC’s meta-parameters to reduce unnecessary computational burden without significantly degrading performance. To implement this framework, an adaptive meta-parameter MPC algorithm is developed based on expert-guided proximal policy optimization by using an expert demonstrator to enhance the DRL training efficiency. Simulation results show that the proposed algorithm significantly outperforms standalone MPC and DRL methods. Compared to a fixed-long-horizon MPC, the proposed method reduces the actual computation time by 75.8% with only a marginal 2.6% increase in operational cost. Furthermore, by coordinately adjusting both the recomputation frequency and prediction horizon of the MPC controller, the framework achieves a more favorable trade-off between control performance and computational efficiency than a standard event-triggered MPC. Finally, robustness analyses confirm that the DRL agent learns an intelligent policy that adaptively intensifies computational effort to mitigate the impact of prediction errors and strategically allocates resources in response to price volatility, thereby maintaining high performance and efficiency even under extreme conditions.
{"title":"Computationally Efficient Smart Building Energy Management via Deep Reinforcement Learning-Enhanced Model Predictive Control","authors":"Bo Li, Gangquan Si, Minglin Xu, Detao Fan, Qianyue Wang, Xin Wang","doi":"10.1016/j.enbuild.2026.117128","DOIUrl":"https://doi.org/10.1016/j.enbuild.2026.117128","url":null,"abstract":"Model predictive control (MPC) is a powerful strategy for optimizing building energy management, but its high computational burden hinders its deployment on resource-constrained hardware. To address this challenge, this paper presents a novel hierarchical control framework that synergizes MPC with deep reinforcement learning (DRL) to navigate the trade-off between control performance and computational burden. Within this framework, a low-level MPC controller is responsible for precise building energy management with the objective of maximizing energy efficiency and ensuring user thermal comfort, while a high-level DRL agent adaptively tunes the MPC’s meta-parameters to reduce unnecessary computational burden without significantly degrading performance. To implement this framework, an adaptive meta-parameter MPC algorithm is developed based on expert-guided proximal policy optimization by using an expert demonstrator to enhance the DRL training efficiency. Simulation results show that the proposed algorithm significantly outperforms standalone MPC and DRL methods. Compared to a fixed-long-horizon MPC, the proposed method reduces the actual computation time by 75.8% with only a marginal 2.6% increase in operational cost. Furthermore, by coordinately adjusting both the recomputation frequency and prediction horizon of the MPC controller, the framework achieves a more favorable trade-off between control performance and computational efficiency than a standard event-triggered MPC. Finally, robustness analyses confirm that the DRL agent learns an intelligent policy that adaptively intensifies computational effort to mitigate the impact of prediction errors and strategically allocates resources in response to price volatility, thereby maintaining high performance and efficiency even under extreme conditions.","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"89 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-09DOI: 10.1016/j.enbuild.2026.117123
Lucas Verleyen, Lieve Helsen
Battery Energy Storage (BES) is often seen as an attractive component in residential (district) energy systems. Typically, BES is considered the sole source of flexibility. However, thermal energy systems inherently offer significant flexibility through the thermal capacity of the buildings and hydronic systems. Therefore, this paper presents a fully integrated approach that combines all relevant energy services (space heating, domestic hot water and electricity for appliances), detailed building models representing a flexible demand side, and proper hydronic and electrical connections between all components into one non-linear physics-based energy system model. An optimal controller acts as the system integrator, fully exploiting the inherent system flexibility and leveraging synergies between heat and electricity. The proposed method is applied to a Micro Energy Community (MEC) under Belgian boundary conditions. A comparative analysis of 33 energy system layouts is conducted to investigate the role and quantify the CO2 emission reduction cost of BES in fully integrated MECs optimised for minimal CO2 emissions. The analysis demonstrates that neglecting thermal system flexibility leads to biased results. The most cost-effective system for emission reduction is a scenario with a collective heat pump, without BES, and where heat and electricity are shared. This system reduces annual emissions by 11.6 tonnes at the cost of 215 EUR/tonne. A collective BES further reduces emissions by 0.1 tonnes, but at a significantly higher cost of 5,430 EUR/tonne. Therefore, BES is not cost-effective for emission reduction in buildings. However, this conclusion may change when considering grid support or applying other policy frameworks.
{"title":"The role and CO2 emission reduction cost of battery energy storage in fully integrated, optimally controlled micro energy communities","authors":"Lucas Verleyen, Lieve Helsen","doi":"10.1016/j.enbuild.2026.117123","DOIUrl":"https://doi.org/10.1016/j.enbuild.2026.117123","url":null,"abstract":"Battery Energy Storage (BES) is often seen as an attractive component in residential (district) energy systems. Typically, BES is considered the sole source of flexibility. However, thermal energy systems inherently offer significant flexibility through the thermal capacity of the buildings and hydronic systems. Therefore, this paper presents a fully integrated approach that combines all relevant energy services (space heating, domestic hot water and electricity for appliances), detailed building models representing a flexible demand side, and proper hydronic and electrical connections between all components into one non-linear physics-based energy system model. An optimal controller acts as the system integrator, fully exploiting the inherent system flexibility and leveraging synergies between heat and electricity. The proposed method is applied to a Micro Energy Community (MEC) under Belgian boundary conditions. A comparative analysis of 33 energy system layouts is conducted to investigate the role and quantify the CO<ce:inf loc=\"post\">2</ce:inf> emission reduction cost of BES in fully integrated MECs optimised for minimal CO<ce:inf loc=\"post\">2</ce:inf> emissions. The analysis demonstrates that neglecting thermal system flexibility leads to biased results. The most <ce:italic>cost-effective</ce:italic> system <ce:italic>for emission reduction</ce:italic> is a scenario with a collective heat pump, without BES, and where heat and electricity are shared. This system reduces annual emissions by 11.6 <ce:italic>tonnes</ce:italic> at the cost of 215 <ce:italic>EUR</ce:italic>/<ce:italic>tonne</ce:italic>. A collective BES further reduces emissions by 0.1 <ce:italic>tonnes</ce:italic>, but at a significantly higher cost of 5,430 <ce:italic>EUR</ce:italic>/<ce:italic>tonne</ce:italic>. Therefore, BES is not <ce:italic>cost-effective for emission reduction</ce:italic> in buildings. However, this conclusion may change when considering grid support or applying other policy frameworks.","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"1 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-09DOI: 10.1016/j.enbuild.2026.117136
Yingying Lyu, Xuelian Bai, Ligang Wang, Yating Wang, Chaoqiang Jin
The short airflow paths of row-based cooling systems can enhance cooling efficiency for data centers (DCs). However, the placement of row-based air conditioning units (ACUs) close to the racks significantly increases the airflow velocity in the aisles. Meanwhile, different power modules share one hot aisle, which is easy to occur the hot exhaust air mixing problem. Existing researches neglect the airflow interaction, which leads to the return air temperatures inaccurately reflecting the cooling demand of each module. To address this issue, this study investigates the interaction phenomena within the row-based cooling system, through the combination of experimental observations and numerical simulations. To evaluate the interaction, a new index ΔT, defined as the return air temperature difference of in-row ACUs between different power modules, was presented. Then the effect of varying the shared hot aisle width on the interaction under different power ratios are analyzed. The results indicate that the airflow interaction intensifies with power ratios, and there exists a proper hot aisle width at different power ratios. To further relieve the interaction, improvement strategies involving airflow deflectors, vertical isolation, and horizontal isolation were proposed. With these strategies implemented, the airflow becomes more organized in the hot aisle, and ΔT increases from 0.75 °C to 1.06 °C, 1.64 °C, and 1.66 °C, respectively. Finally, installing a vertical curtain in the shared hot aisle central and sealing the top effectively alleviated the hot exhaust air interaction in higher power modules scenarios, with ΔT increased from 0.86 °C to 1.578 °C.
{"title":"Improvement strategies based on airflow characteristic in a row-based cooling data center","authors":"Yingying Lyu, Xuelian Bai, Ligang Wang, Yating Wang, Chaoqiang Jin","doi":"10.1016/j.enbuild.2026.117136","DOIUrl":"https://doi.org/10.1016/j.enbuild.2026.117136","url":null,"abstract":"The short airflow paths of row-based cooling systems can enhance cooling efficiency for data centers (DCs). However, the placement of row-based air conditioning units (ACUs) close to the racks significantly increases the airflow velocity in the aisles. Meanwhile, different power modules share one hot aisle, which is easy to occur the hot exhaust air mixing problem. Existing researches neglect the airflow interaction, which leads to the return air temperatures inaccurately reflecting the cooling demand of each module. To address this issue, this study investigates the interaction phenomena within the row-based cooling system, through the combination of experimental observations and numerical simulations. To evaluate the interaction, a new index Δ<ce:italic>T</ce:italic>, defined as the return air temperature difference of in-row ACUs between different power modules, was presented. Then the effect of varying the shared hot aisle width on the interaction under different power ratios are analyzed. The results indicate that the airflow interaction intensifies with power ratios, and there exists a proper hot aisle width at different power ratios. To further relieve the interaction, improvement strategies involving airflow deflectors, vertical isolation, and horizontal isolation were proposed. With these strategies implemented, the airflow becomes more organized in the hot aisle, and Δ<ce:italic>T</ce:italic> increases from 0.75 °C to 1.06 °C, 1.64 °C, and 1.66 °C, respectively. Finally, installing a vertical curtain in the shared hot aisle central and sealing the top effectively alleviated the hot exhaust air interaction in higher power modules scenarios, with Δ<ce:italic>T</ce:italic> increased from 0.86 °C to 1.578 °C.","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"160 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-08DOI: 10.1016/j.enbuild.2026.117122
Wojciech Matys, Beata Sadowska, Ana Tejero González, Marta Baum, Dorota Anna Krawczyk
{"title":"Atrium residential buildings versus compact shape houses − comparative analysis of energy demand in Spain and Poland","authors":"Wojciech Matys, Beata Sadowska, Ana Tejero González, Marta Baum, Dorota Anna Krawczyk","doi":"10.1016/j.enbuild.2026.117122","DOIUrl":"https://doi.org/10.1016/j.enbuild.2026.117122","url":null,"abstract":"","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"45 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146138293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-08DOI: 10.1016/j.enbuild.2026.117077
Dana B. Khalaf, Anas Kh. Mahmoud
{"title":"Evaluating envelope retrofitting strategies to enhance thermal comfort and energy efficiency in Jordanian affordable housing","authors":"Dana B. Khalaf, Anas Kh. Mahmoud","doi":"10.1016/j.enbuild.2026.117077","DOIUrl":"https://doi.org/10.1016/j.enbuild.2026.117077","url":null,"abstract":"","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"6 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146138296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-07DOI: 10.1016/j.enbuild.2026.117120
Youngmin Ji, Dongwoo Kwon, Geonwoo Ji, Daehee Kim, Sangheon Pack
{"title":"Unsupervised Spatiotemporal Adaptive Model Transfer Framework for Nonintrusive Occupancy Detection using Environmental Data","authors":"Youngmin Ji, Dongwoo Kwon, Geonwoo Ji, Daehee Kim, Sangheon Pack","doi":"10.1016/j.enbuild.2026.117120","DOIUrl":"https://doi.org/10.1016/j.enbuild.2026.117120","url":null,"abstract":"","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"89 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-07DOI: 10.1016/j.enbuild.2026.117118
Amel Bounnah, Pr. Fatiha Bourbia
{"title":"Optimizing urban morphology for thermal comfort: real-time wind-solar synchronization via ansys discovery and grasshopper","authors":"Amel Bounnah, Pr. Fatiha Bourbia","doi":"10.1016/j.enbuild.2026.117118","DOIUrl":"https://doi.org/10.1016/j.enbuild.2026.117118","url":null,"abstract":"","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"9 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146138305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：