Finite Element-Based Material Learning via Automatic Differentiation: Learning constitutive neural network models from full-field deformation data 事件

Finite Element-Based Material Learning via Automatic Differentiation: Learning constitutive neural network models from full-field deformation data arXiv:2606.05199v1 Announce Type: cross Abstract: The identification of constitutive neural network models from heterogeneous full-field deformation data provides a robust alternative to traditional calibration methods based on homogeneous stress-strain experiments, particularly given the high dimensionality of trainable parameters. Existing approach