On physics-informed data-driven isotropic and anisotropic constitutive models through probabilistic machine learning and space-filling sampling
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Publication:2136745
DOI10.1016/j.cma.2022.114915OpenAlexW3199814420MaRDI QIDQ2136745
Publication date: 12 May 2022
Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2109.11028
finite strainhyperelasticitysolid mechanicsphysics-informed machine learningdata-driven constitutive models
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