建筑模拟(英文版)2026,Vol.19Issue(1):271-285,15.DOI:10.1007/s12273-025-1392-x
Urban wind field prediction using Fourier Neural Operators across different wind directions and cities
Urban wind field prediction using Fourier Neural Operators across different wind directions and cities
摘要
关键词
computational fluid dynamics/FNO/microclimate/urban wind field prediction/AI/machine learning/signed distance function(SDF)Key words
computational fluid dynamics/FNO/microclimate/urban wind field prediction/AI/machine learning/signed distance function(SDF)引用本文复制引用
Cheng Chen,Geng Tian,Shaoxiang Qin,Senwen Yang,Dingyang Geng,Dongxue Zhan,Jinqiu Yang,David Vidal,Liangzhu(Leon)Wang..Urban wind field prediction using Fourier Neural Operators across different wind directions and cities[J].建筑模拟(英文版),2026,19(1):271-285,15.基金项目
The research is made possible by the general support from the Consortium for Research and Innovation in Aerospace in Québec(CRIAQ)through the project"Multi-scale Aerodynamic Modeling of Helicopters/UAV in Urban Environments"[#051811],the Natural Sciences and Engineering Research Council(NSERC)of Canada through the Discovery Grants Program[#RGPIN-2024-06297],and the SEED project Creating Electrified and Decarbonized Healthy Urban Microclimate around Building Clusters through Climate-Resilient Solutions under the Canada First Research Excellence Fund(Volt-Age). (CRIAQ)