Learning Invariant Representation of Multiscale Hyperelastic Constitutive Law from Sparse Experimental Data
DOI10.4208/cicp.oa-2023-0098zbMath1529.74079OpenAlexW4386428579MaRDI QIDQ6049615
Jun-Zhi Cui, Rui He, Zihao Yang, Jieqiong Zhang, Xiao-Fei Guan
Publication date: 15 September 2023
Published in: Communications in Computational Physics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.4208/cicp.oa-2023-0098
artificial neural networkheterogeneous hyperelastic materialmicroscopic finite element solverphysics-constrained data-driven method
Artificial neural networks and deep learning (68T07) Learning and adaptive systems in artificial intelligence (68T05) Nonlinear elasticity (74B20) Inhomogeneity in solid mechanics (74E05) Finite element methods applied to problems in solid mechanics (74S05) Theory of constitutive functions in solid mechanics (74A20) Numerical and other methods in solid mechanics (74S99)
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