Spatial strain correlations, machine learning, and deformation history in crystal plasticity.

ABSTRACT: Systems far from equilibrium respond to probes in a history-dependent manner. The prediction of the system response depends on either knowing the details of that history or being able to characterize all the current system properties. In crystal plasticity, various processing routes contribute to a history dependence that may manifest itself through complex microstructural deformation features with large strain gradients. However, the complete spatial strain correlations may provide further predictive information. In this paper, we demonstrate an explicit example where spatial strain correlations can be used in a statistical manner to infer and classify prior deformation history at various strain levels. The statistical inference is provided by machine-learning techniques. As source data,

SUBMITTER: Papanikolaou S 

PROVIDER: S-EPMC7722264 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature