Model-free data-driven viscoelasticity in the frequency domain

DOI10.1016/J.CMA.2022.115657OpenAlexW4307154607MaRDI QIDQ2679436

Hossein Salahshoor, Michael Ortiz

Publication date: 20 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/2205.06674

zbMATH Keywords

frequency domainviscoelasticitymachine learningdata-driven computingmodel-free computing

Mathematics Subject Classification ID

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

Related Items (1)

Viscoelastic constitutive artificial neural networks (vCANNs) -- a framework for data-driven anisotropic nonlinear finite viscoelasticity

Cites Work

• Data-driven problems in elasticity
• On the \(\Gamma\)-convergence of discrete dynamics and variational integrators
• Model-free data-driven inelasticity
• Learning viscoelasticity models from indirect data using deep neural networks
• Data-driven computational mechanics
• Optimal Transport

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