Imperial College London

ProfessorChristopherPain

Faculty of EngineeringDepartment of Earth Science & Engineering

Professorial Research Fellow
 
 
 
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Contact

 

+44 (0)20 7594 9322c.pain

 
 
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Location

 

4.96Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Wu:2022:10.1007/s00521-022-07042-6,
author = {Wu, P and Pan, K and Ji, L and Gong, S and Feng, W and Yuan, W and Pain, C},
doi = {10.1007/s00521-022-07042-6},
journal = {NEURAL COMPUTING & APPLICATIONS},
pages = {11539--11552},
title = {Navier-stokes Generative Adversarial Network: a physics-informed deep learning model for fluid flow generation},
url = {http://dx.doi.org/10.1007/s00521-022-07042-6},
volume = {34},
year = {2022}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AU - Wu,P
AU - Pan,K
AU - Ji,L
AU - Gong,S
AU - Feng,W
AU - Yuan,W
AU - Pain,C
DO - 10.1007/s00521-022-07042-6
EP - 11552
PY - 2022///
SN - 0941-0643
SP - 11539
TI - Navier-stokes Generative Adversarial Network: a physics-informed deep learning model for fluid flow generation
T2 - NEURAL COMPUTING & APPLICATIONS
UR - http://dx.doi.org/10.1007/s00521-022-07042-6
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000765675100003&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
VL - 34
ER -