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Deep generative framework for predicting non-Gaussian wind pressure on a high-rise building using data from sparse sensors

Zhixin Liu Haotian Dong Yu Zhang Xiaoqing Du

建筑模拟（英文版）2025，Vol.18Issue(10)：2807-2824,18.

建筑模拟（英文版）2025，Vol.18Issue(10)：2807-2824,18.DOI:10.1007/s12273-025-1340-9

Deep generative framework for predicting non-Gaussian wind pressure on a high-rise building using data from sparse sensors

Zhixin Liu ¹Haotian Dong ²Yu Zhang ¹Xiaoqing Du²

作者信息

1. Department of Civil Engineering,Shanghai University,99 Shangda Rd.,Shanghai 200444,China
2. Department of Civil Engineering,Shanghai University,99 Shangda Rd.,Shanghai 200444,China||Research Center for High-Performance Bridges,Shanghai University,99 Shangda Rd.,Shanghai 200444,China
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摘要

关键词

pressure time series prediction/WGAN/boundary layer wind tunnel test

Key words

pressure time series prediction/WGAN/boundary layer wind tunnel test

引用本文复制引用

Zhixin Liu,Haotian Dong,Yu Zhang,Xiaoqing Du..Deep generative framework for predicting non-Gaussian wind pressure on a high-rise building using data from sparse sensors[J].建筑模拟（英文版）,2025,18(10):2807-2824,18.

基金项目

The authors gratefully acknowledge grants from the open funding of the Key Laboratory of Transport Industry of Wind Resistant Technology for Bridge Structures(KLWRTBMC24-02),the National Natural Science Foundation of China(52008239,52478534,51978392),and Fujian Provincial Department of Science and Technology,China(2023Y0040). （KLWRTBMC24-02）

建筑模拟（英文版）

ISSN：1996-3599

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