Data-Oriented Constitutive Modeling of Plasticity in Metals.

ABSTRACT: Constitutive models for plastic deformation of metals are typically based on flow rules determining the transition from elastic to plastic response of a material as function of the applied mechanical load. These flow rules are commonly formulated as a yield function, based on the equivalent stress and the yield strength of the material, and its derivatives. In this work, a novel mathematical formulation is developed that allows the efficient use of machine learning algorithms describing the elastic-plastic deformation of a solid under arbitrary mechanical loads and that can replace the standard yield functions with more flexible algorithms. By exploiting basic physical principles of elastic-plastic deformation, the dimensionality of the problem is reduced without loss of generality. The da

SUBMITTER: Hartmaier A 

PROVIDER: S-EPMC7178379 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature