Physics-aware recurrent convolutional neural networks for modeling multiphase compressible flows-Reference-Cited by-同舟云学术

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Physics-aware recurrent convolutional neural networks for modeling multiphase compressible flows

Published:2024-07 Issue: Volume:177 Page:104877
ISSN:0301-9322
Container-title:International Journal of Multiphase Flow
language:en
Short-container-title:International Journal of Multiphase Flow

Author:

Cheng Xinlun^ORCID,Nguyen Phong C.H.,Seshadri Pradeep K.^ORCID,Verma Mayank^ORCID,Gray Zoë J.^ORCID,Beerman Jack T.^ORCID,Udaykumar H.S.,Baek Stephen S.^ORCID

Publisher

Elsevier BV

Reference32 articles.

1. Modern compressible flow: With historical perspective;Anderson,2003

2. Ansys fluent - Fluid Simulation Software;Ansys Inc.,2023

3. Supersonic cylinder wake dynamics;Awasthi;J. Fluid Mech.,2022

4. Automatic differentiation in machine learning: a survey;Baydin;J. March. Learn. Res.,2018

5. Physics-informed neural networks (PINNs) for fluid mechanics: a review;Cai;Acta Mech. Sinica,2022

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