A partially input convex neural network learns anisotropic hyperelastic response from homogenized stress-strain data, and an evolution strategy inverts it to recover microstructure design parameters and preferred directions.
Mechanical analysis of heterogeneous materials with higher-order parameters
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Inverse design of anisotropic microstructures using physics-augmented neural networks
A partially input convex neural network learns anisotropic hyperelastic response from homogenized stress-strain data, and an evolution strategy inverts it to recover microstructure design parameters and preferred directions.