NN-EVP: A physics informed neural network-based elasto-viscoplastic framework for predictions of grain size-aware flow response-Reference-Cited by-同舟云学术

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NN-EVP: A physics informed neural network-based elasto-viscoplastic framework for predictions of grain size-aware flow response

Published:2024-10 Issue: Volume:181 Page:104072
ISSN:0749-6419
Container-title:International Journal of Plasticity
language:en
Short-container-title:International Journal of Plasticity

Author:

Eghtesad Adnan^ORCID,Tan Jingye^ORCID,Fuhg Jan Niklas,Bouklas Nikolaos^ORCID

Publisher

Elsevier BV

Reference68 articles.

1. A crystal plasticity model that accounts for grain size effects and slip system interactions on the deformation of austenitic stainless steels;Agius;Int. J. Plast.,2022

2. As’ ad, F., Farhat, C., 2023. A Mechanics-Informed Neural Network Framework for Data-Driven Nonlinear Viscoelasticity. In: AIAA SCITECH 2023 Forum. p. 0949.

3. Implementation of a neural network into a user-material subroutine for finite element simulation of material viscoplasticity;Benabou;J. Eng. Mater. Technol.,2021

4. From CP-FFT to CP-RNN: Recurrent neural network surrogate model of crystal plasticity;Bonatti;Int. J. Plast.,2022

5. Perspective: Machine learning in experimental solid mechanics;Brodnik;J. Mech. Phys. Solids,2023

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