A new method for predicting wind-driven rain catch ratios on building facades in urban residential areas using machine learning models DOI
Hui Yu, Huibo Zhang

Building and Environment, Год журнала: 2024, Номер unknown, С. 112467 - 112467

Опубликована: Дек. 1, 2024

Язык: Английский

Thermal comfort and urban microclimate response: A new thermal environment assessment model for waterfront spaces in historic ancient towns DOI
Yan Wang, Xinrui Liu,

Rong Xie

и другие.

Energy and Buildings, Год журнала: 2025, Номер 331, С. 115393 - 115393

Опубликована: Янв. 30, 2025

Язык: Английский

Процитировано

1

Cooling effects and energy-saving potential of urban vegetation in cold-climate cities: A comparative study using regression and coupled simulation models DOI
Dongliang Han, Mingqi Wang, Jun Li

и другие.

Urban Climate, Год журнала: 2025, Номер 59, С. 102268 - 102268

Опубликована: Янв. 11, 2025

Язык: Английский

Процитировано

0

Assessing tree canopy cooling efficiency in different local climate zones: A cost-benefit analysis DOI

Aowei Liu,

Chengsheng Wang,

Guanning Shang

и другие.

Urban forestry & urban greening, Год журнала: 2025, Номер 105, С. 128694 - 128694

Опубликована: Янв. 31, 2025

Язык: Английский

Процитировано

0

Improving the accuracy of microclimate coupled urban building energy modeling using convolutional neural networks DOI

J. Ye,

Chenyu Huang, Zhaoyang Zhong

и другие.

Building and Environment, Год журнала: 2025, Номер unknown, С. 112923 - 112923

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Evaluating urban heat mitigation strategies: Microclimate effects and energy consumption in residential areas across diverse climates DOI
Yan Wang, Zhonghua Gou

Energy and Buildings, Год журнала: 2025, Номер unknown, С. 115950 - 115950

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Developing a co-benefits evaluation model to optimize greening coverage designs on university campuses in hot and humid areas DOI

Xiaoqing Zhou,

Shiyuan Deng,

Yongbo Cui

и другие.

Energy and Buildings, Год журнала: 2024, Номер unknown, С. 115214 - 115214

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

2

Cooling Effects and Energy-Saving Potential of Urban Vegetation in a Cold Climate City: Insights from Regression and Coupled Simulation Models DOI
Dongliang Han, Tiantian Zhang, Xuedan Zhang

и другие.

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

1

Cooling Effects and Energy-Saving Potential of Urban Vegetation in a Cold Climate City: Insights from Regression and Coupled Simulation Models DOI
Dongliang Han, Tiantian Zhang, Xuedan Zhang

и другие.

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

0

Impact of Social Capital on Residents' Willingness in the Old Residential Renewal in China: Mediating Effect of Perceived Value DOI

Yuanyuan You,

Xiaodong Yang

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

0

Optimizing Energy Renovation in Building Portfolios: Approach and Decision-Making Platform DOI Creative Commons
Marco Castagna,

Olga Somova,

Cristian Pozza

и другие.

Energies, Год журнала: 2024, Номер 17(22), С. 5537 - 5537

Опубликована: Ноя. 6, 2024

The building sector contributes significantly to energy consumption and greenhouse gas emissions, with many buildings being inefficient. In response, the European Green Deal promotes improving efficiency support decarbonization goals. However, managing integrating data from multiple sources presents challenges, especially for large portfolios. This study introduces a novel methodology designed optimize renovation strategies, balancing technical, financial, maintenance considerations. is implemented in CERPlan 1.0, web-based decision-support platform that combines on performance, costs, needs. Through simulations, 1.0 helps decision-makers prioritize retrofit interventions based economic criteria while leveraging synergies between improvements regular maintenance. Application of this real estate portfolios reveals opportunities enhance cost-effectiveness savings. results show into planning reduces payback times allows more comprehensive strategies. conclusions highlight 1.0’s potential improve decision-making, making renovations efficient sustainable.

Язык: Английский

Процитировано

0