Prediction of local elasto-plastic stress and strain fields in a two-phase composite microstructure using a deep convolutional neural network

DOI10.1016/j.cma.2024.116816arXiv2310.19128OpenAlexW4391467000MaRDI QIDQ6121794

L. L. Graham-Brady, Indrashish Saha, Ashwini Gupta

Publication date: 26 March 2024

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2310.19128

zbMATH Keywords

plasticitycomposite materialmachine learningdeep learningstress predictionstrain prediction

Mathematics Subject Classification ID

Mechanics of deformable solids (74-XX) Biology and other natural sciences (92-XX)

Cites Work

• Effects of fiber distribution on elastic--viscoplastic behavior of long fiber-reinforced laminates
• Elastoplastic modeling of circular fiber-reinforced ductile matrix composites considering a finite RVE
• Computational inelasticity
• A data-driven approach to full-field nonlinear stress distribution and failure pattern prediction in composites using deep learning
• A random field-based method to estimate convergence of apparent properties in computational homogenization
• A stochastic computational method for evaluation of global and local behavior of random elastic media
• Random heterogeneous materials. Microstructure and macroscopic properties

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