Chenglong Duan

Predicting stress–strain behaviors of additively manufactured materials via loss-based and activation-based physics-informed machine learning architectures

Predicting the stress–strain behaviors of additively manufactured materials is crucial for part qualification in additive manufacturing (AM). Conventional physics-based constitutive models of materials have limitations, such as oversimplification of material properties and narrow...