A review on data-driven constitutive laws for solids

arXiv:2405.03658v1 Announce Type: cross
Abstract: This review article highlights state-of-the-art data-driven techniques to discover, encode, surrogate, or emulate constitutive laws that describe the path-independent and path-dependent response of solids. Our objective is to provide an organized taxonomy to a large spectrum of methodologies developed in the past decades and to discuss the benefits and drawbacks of the various techniques for interpreting and forecasting mechanics behavior across different scales. Distinguishing between machine-learning-based and model-free methods, we further categorize approaches based on …

abstract art article arxiv cs.ce cs.lg data data-driven discuss encode highlights independent laws path physics.app-ph review spectrum state taxonomy type