Data driven modeling of interfacial traction-separation relations using a thermodynamically consistent neural network

DOI10.1016/j.cma.2022.115826OpenAlexW4313201783MaRDI QIDQ2678537

Jiaxin Zhang, Congjie Wei, Kenneth M. Liechti, Cheng-Lin Wu

Publication date: 23 January 2023

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

Full work available at URL: https://arxiv.org/abs/2011.09946

zbMATH Keywords

machine learningcohesive zone modelingBayesian optimizationinterface mechanicsphysics constrained neural networkstraction-separation relations

Mathematics Subject Classification ID

Mechanics of deformable solids (74-XX) Geophysics (86-XX)

Uses Software

• Spearmint
• Adam

Cites Work

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• A Continuum Model for Void Nucleation by Inclusion Debonding
• Machine Learning for Fluid Mechanics
• Comparison between cohesive zone models
• Deep learning in fluid dynamics
• Brownian motion in a field of force and the diffusion model of chemical reactions

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