A deep learning-based crystal plasticity finite element model-Reference-Cited by-同舟云学术

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A deep learning-based crystal plasticity finite element model

Published:2025-01 Issue: Volume:254 Page:116315
ISSN:1359-6462
Container-title:Scripta Materialia
language:en
Short-container-title:Scripta Materialia

Author:

Mao Yuwei,Keshavarz Shahriyar,Kilic Muhammed Nur Talha,Wang Kewei^ORCID,Li Youjia,Reid Andrew C.E.^ORCID,Liao Wei-keng,Choudhary Alok,Agrawal Ankit^ORCID

Publisher

Elsevier BV

Reference30 articles.

1. Implementation and experimental validation of nonlocal damage in a large-strain elasto-viscoplastic fft-based framework for predicting ductile fracture in 3d polycrystalline materials;Cocke;Int. J. Plast.,2023

2. An artificial neural network for surrogate modeling of stress fields in viscoplastic polycrystalline materials;Khorrami;Comput. Mater.,2023

3. Friction behavior of polycrystalline diamond compact and the evolution of the friction film under different matching materials;Chen;Int. J. Refract. Met. Hard Mater.,2023

4. Multi-scale crystal plasticity model of creep responses in nickel-based superalloys;Keshavarz;Materials,2022

5. A non-Schmid crystal plasticity finite element approach to multi-scale modeling of nickel-based superalloys;Keshavarz;Acta Mater.,2016

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