Building and Environment, Год журнала: 2024, Номер 270, С. 112493 - 112493
Опубликована: Дек. 28, 2024
Язык: Английский
Journal of Wind Engineering and Industrial Aerodynamics, Год журнала: 2024, Номер 254, С. 105910 - 105910
Опубликована: Окт. 17, 2024
Язык: Английский
Процитировано
0
Journal of Physics Conference Series, Год журнала: 2024, Номер 2893(1), С. 012024 - 012024
Опубликована: Ноя. 1, 2024
Abstract Outdoor environment modelling is crucial for multiple facets of a sustainable urban development, such as mitigating the detrimental environmental impacts (i.e. greenhouse gas emissions), proposing energy-efficient building designs, optimizing usage green resources, and improving overall comfort level residents. This paper presents comprehensive review techniques models related to various aspects an outdoor modelling, including microclimate dynamics solar radiation wind-flow air-temperature assessment simulations, urban-canyons heat island effects green-infrastructure planning. Each section covers compares traditionally used methods in field with newer artificial intelligence (AI) based models, aiming explore their relevant efficiencies areas improvement. For instance, microclimate’s traditional like radiative transfer are evolving machine-learning high-resolution remote sensing methodologies community-based participatory models. Similarly, encompasses CFD, wind-tunnel modified by machine learning (ML) data-driven methodologies. Moreover, also discusses (UHI) phenomenon Overall, aims provide state art on cutting-edge all necessary help informed decision-making environments.
Язык: Английский
Процитировано
0
Building and Environment, Год журнала: 2024, Номер unknown, С. 112495 - 112495
Опубликована: Дек. 1, 2024
Язык: Английский
Процитировано
0
Building and Environment, Год журнала: 2024, Номер 270, С. 112493 - 112493
Опубликована: Дек. 28, 2024
Язык: Английский
Процитировано
0