Analytics for microstructure datasets produced by phase-field simulations

Phase-field simulations have become valuable tools in explorations of the effects of the processing parameters on the internal structure evolution of materials in a broad range of advanced materials. Simulations conducted on high performance computers have enabled the resolution of relatively large material volumes and have generated big datasets. Although such computations have captured faithfully the many features observed in the corresponding experiments, there has not yet been a broadly adopted framework to quantitatively analyze the predicted material structures and compare them rigorously with experiments. This paper demonstrates that the recently developed framework for the quantification of the material structure, based on the concepts of 2-point spatial correlations and principal component analyses (PCA), can address this critical need. It is further demonstrated that the adoption of a rigorous framework for structure quantification can help to establish objectively many of the modeling parameters and choices made in the simulations.