AI-enabled damage estimation of hurricane-impacted residential communities through CFD simulations and stratified sampling

This study introduces a novel framework for estimating hurricane-induced damage to individual buildings by integrating AI-based 3D building modeling, Computational Fluid Dynamics (CFD), and stratified sampling. By leveraging the precise geometric characteristics of individual buildings extracted fro...

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Vydané v:	Journal of wind engineering and industrial aerodynamics Ročník 251; s. 105806
Hlavní autori:	Kim, Sejin, Ding, Fei, Spence, Seymour M.J.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.08.2024
Predmet:	AI-Based 3D modeling Computational fluid dynamics Enhanced stratified sampling Hurricane damage estimation Vulnerability modeling Enhanced stratified sampling Computational fluid dynamics Hurricane damage estimation AI-Based 3D modeling Vulnerability modeling
ISSN:	0167-6105, 1872-8197
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