Intelligent multiscale modeling of short fiber reinforced composites based on process-guided material database

Deep material network and transfer learning - An application for multiscale short fiber composites

Physics-based machine learning in materials modeling and multiscale simulation

The rise of Machine Learning (ML) has been continuously advancing the frontier of materials modeling and multiscale simulations. However, due to expense of physical or numerical experiments, material modelers & designers oftentimes cannot foresee all …

Advances in immersed particle method and deep material network for data-driven RVE analysis

Deep material networks for creating microstructural database of polycrystalline materials in additive manufacturing

Deep material network for data-driven structure-property predictions

Advances in RVE large deformation analysis of heterogeneous structures using an immersed particle modeling method and mechanistic machine learning technology

Multiscale microstructural database for concurrent modeling of nonlinear softening material with damage and failure

Multiscale simulations of material with heterogeneous structures based on representative volume element techniques

A consistent concurrent framework for multiscale material failure based on self-consistent clustering analysis