TC-SRNet: Reconstruction and prediction of typhoon high-resolution turbulent fields based on meteorological numerical forecast scale wind fields and deep learning method-Reference-Cited by-同舟云学术

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TC-SRNet: Reconstruction and prediction of typhoon high-resolution turbulent fields based on meteorological numerical forecast scale wind fields and deep learning method

Published:2024-11 Issue: Volume:254 Page:105885
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:

Ren Hehe,Liu Haoyue,Zhang Chunwei,Sun Xingyu,Yang Jie,Ke Shitang

Funder

China Postdoctoral Science Foundation

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Jiangsu Province Natural Science Foundation

Publisher

Elsevier BV

Reference50 articles.

1. Machine learning for fluid mechanics;Brunton;Annu. Rev. Fluid Mech.,2020

2. Wind characteristics of a strong typhoon;Cao;J. Wind Eng. Ind. Aerod.,2009

3. Global warming and western North Pacific typhoon activity from an observational perspective;Chan;J. Clim.,2004

4. Stratocumulus-capped mixed layers derived from a three-dimensional model;Deardorff;Boundary-Layer Meteorol.,1980

5. Reconstruction of flow around a high-rise building from wake measurements using Machine Learning techniques;Diop;J. Wind Eng. Ind. Aerod.,2022

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