PDNNs: The parallel deep neural networks for the Navier–Stokes equations coupled with heat equation-Reference-Cited by-同舟云学术

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PDNNs: The parallel deep neural networks for the Navier–Stokes equations coupled with heat equation

Published:2022-11-28 Issue:4 Volume:95 Page:666-681
ISSN:0271-2091
Container-title:International Journal for Numerical Methods in Fluids
language:en
Short-container-title:Numerical Methods in Fluids

Author:

Zhang Wen¹²,Li Jian¹²^ORCID

Affiliation:

1. School of Electrical and Control Engineering Shaanxi University of Science and Technology Xi'an China

2. School of Mathematics and Data Science Shaanxi University of Science and Technology Xi'an China

Funder

Education Department of Shaanxi Province

National Natural Science Foundation of China

Publisher

Wiley

Subject

Applied Mathematics,Computer Science Applications,Mechanical Engineering,Mechanics of Materials,Computational Mechanics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/fld.5164

Reference47 articles.

1. A domain decomposition method for the time-dependent Navier-Stokes-Darcy model with Beavers-Joseph interface condition and defective boundary condition

2. Analysis of a stabilized finite volume method for the transient Stokes equations;Shen L;Int J Numer Anal Model,2009

3. A multi-level stabilized finite element method for the stationary Navier–Stokes equations

4. Numerical implementation of the Crank-Nicolson/Adams-Bashforth scheme for the time-dependent Navier-Stokes equations

5. Superconvergence by L 2‐projections for stabilized finite element methods for the Stokes equations;Li J;Int J Numer Anal Model,2009

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