A physics-informed neural network-based approach to reconstruct the tornado vortices from limited observed data-Reference-Cited by-全球学者库

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A physics-informed neural network-based approach to reconstruct the tornado vortices from limited observed data

Published:2023-10 Issue: Volume:241 Page:105534
ISSN:0167-6105
Container-title:Journal of Wind Engineering and Industrial Aerodynamics
language:en
Short-container-title:Journal of Wind Engineering and Industrial Aerodynamics

Author:

Zhang Han,Wang Hao^ORCID,Xu Zidong,Liu Zhenqing,Khoo Boo Cheong^ORCID

Publisher

Elsevier BV

Subject

Mechanical Engineering,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering

Reference48 articles.

1. Tensorflow: a System for Large-Scale Machine Learning;Abadi,2016

2. Fluent19.2 Theory Guide,2018

3. Experimental investigation of large-scale tornado-like vortices;Ashrafi;J. Wind Eng. Ind. Aerod.,2021

4. Modelling wind fields and debris flight in tornadoes;Baker;J. Wind Eng. Ind. Aerod.,2017

5. The calculation of train stability in tornado winds;Baker;J. Wind Eng. Ind. Aerod.,2018

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Numerical study of wind loads on the streamlined bridge deck in the translating tornado-like vortex;Physics of Fluids;2023-10-01

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