Automated identification of slip system activity fields from digital image correlation data

Crystallographic slip system identification methods are widely employed to characterize the fine scale deformation of metals. While powerful, they usually rely on occurrence discrete bands with clear traces and can struggle when complex mechanisms such as cross-slip, curved slip, diffuse and/or intersecting occur. This paper proposes a novel framework, termed SSLIP (for Slip Systems based Local Identification Plasticity), in which measured displacement gradient fields (from Digital Image Correlation) locally matched kinematics one or multiple combined theoretical systems, crystal orientations. To identify amounts that conforms kinematics, an optimization problem is solved for every datapoint individually, resulting activity field considered system. The framework demonstrated validated HCP virtual experiment, incorporating 24 systems. Experimental case studies FCC BCC metals show how full-field cross-slip becomes feasible, even considering 48 systems BCC. Moreover, methodology extended into dedicated method, directly yields orientation local plane trace orientation, purely two chosen directions. For more challenging cases revealing persistent uncertainty identification, two-step approach be employed, highly experiment.