NH-PINN: Neural homogenization-based physics-informed neural network for multiscale problems-Reference-Cited by-同舟云学术

NH-PINN: Neural homogenization-based physics-informed neural network for multiscale problems

Published:2022-12 Issue: Volume:470 Page:111539
ISSN:0021-9991
Container-title:Journal of Computational Physics
language:en
Short-container-title:Journal of Computational Physics

Author:

Leung Wing Tat,Lin Guang^ORCID,Zhang Zecheng

Funder

National Science Foundation

U.S. Department of Energy

NSF DMS

Advanced Scientific Computing Research

Brookhaven National Laboratory

Publisher

Elsevier BV

Subject

Computer Science Applications,Physics and Astronomy (miscellaneous),Applied Mathematics,Computational Mathematics,Modeling and Simulation,Numerical Analysis

Reference26 articles.

1. Asymptotic Analysis for Periodic Structures, vol. 374;Bensoussan,2011

2. Computational multiscale methods for quasi-gas dynamic equations;Chetverushkin;J. Comput. Phys.,2021

3. Adaptive multiscale model reduction with generalized multiscale finite element methods;Chung;J. Comput. Phys.,2016

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