Learning macroscopic internal variables and history dependence from microscopic models-Reference-Cited by-同舟云学术

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Learning macroscopic internal variables and history dependence from microscopic models

Published:2023-09 Issue: Volume:178 Page:105329
ISSN:0022-5096
Container-title:Journal of the Mechanics and Physics of Solids
language:en
Short-container-title:Journal of the Mechanics and Physics of Solids

Author:

Liu Burigede,Ocegueda Eric^ORCID,Trautner Margaret^ORCID,Stuart Andrew M.,Bhattacharya Kaushik^ORCID

Publisher

Elsevier BV

Subject

Mechanical Engineering,Mechanics of Materials,Condensed Matter Physics

Reference38 articles.

1. ABAQUS user manual: ABAQUS theory guide, vol. 6.14;Anon,2014

2. A mechanics?informed artificial neural network approach in data?driven constitutive modeling;As’Ad;Internat. J. Numer. Methods Engrg.,2022

3. Asymptotic Analysis for Periodic Structures, Vol. 374;Bensoussan,2011

4. Learning markovian homogenized models in viscoelasticity;Bhattacharya;Multiscale Model. Simul.,2023

5. On the importance of self-consistency in recurrent neural network models representing elasto-plastic solids;Bonatti;J. Mech. Phys. Solids,2022

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