Quantification of 3D spatial correlations between state variables and distances to the grain boundary network in full-field crystal plasticity spectral method simulations

Deformation microstructure heterogeneities play a pivotal role during dislocation patterning and interface network restructuring. Thereby, they affect indirectly how the microstructure recrystallizes. Given this relevance, it has become common practice to study the evolution of deformation microstructure heterogeneities with 3D experiments and full-field crystal plasticity computer simulations including tools such as the spectral method. Quantifying material point to grain or phase boundary distances, though, is a practical challenge with spectral method crystal plasticity models because these discretize the material volume rather than mesh explicitly the grain and phase boundary interface network. This limitation calls for specific data post-processing methods to quantify the spatial correlations between state variable values at each material point and the points' corresponding distance to the closest grain or phase boundary. This work contributes to the development of advanced such post-processing routines. Specifically, two grain reconstruction and three distancing methods are developed for solving above challenge. The individual strengths and limitations of these methods surplus the efficiency of their parallel implementation is assessed with an exemplary Düsseldorf Advanced Material Simulation Kit large scale crystal plasticity study. We apply the new tool to assess the evolution of subtle stress and disorientation gradients towards grain boundaries. (paper)