Extraction of reduced-order process-structure linkages from phase-field simulations

Phase-field simulations have achieved notable success in capturing characteristic details of microstructure evolution in directional solidification of ternary eutectic alloys. In spite of the impressive advances in high performance computations, phase-field simulations for most practical problems in materials design are resource intensive because of the need to incorporate multiple physical fields over large-scale three-dimensional domains. There is, therefore, a need to learn and capture the underlying materials knowledge embedded in the results produced by such expensive simulations, and facilitating an easy transferability to new problems of interest. This paper demonstrates the viability of extracting the salient process-structure linkages from phase-field simulations, while casting them in forms amenable for a rapid and efficient exploration of a relatively large process space. The presented framework is based on low dimensional representation of material structure obtained through principal component analysis (PCA) of 2-point spatial correlations.

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