A temporal graph neural network for cross-scale modelling of polycrystals considering microstructure interaction

Machine learning (ML) based methods have achieved preliminary success in the constitutive modeling for single crystals or homogenized polycrystals with remarkable computational efficiency. However, existing ML-based constitutive models neglect grain-level anisotropy, which limits the accurate analysis of local effects. In the current work, a temporal graph neural network (TGNN) model is proposed to simulate cross-scale deformation behaviors of …