A modified simulated annealing algorithm for hybrid statistical reconstruction of heterogeneous microstructures

Abstract Mathematical descriptors of complex microstructures easily obtained from limited microstructural information offer next-generation, inexpensive solutions for digital material reconstruction. In this work, we propose a versatile method for accurate digital reconstruction and design of material’s microstructure. The method uses a combination of the full set of two-point correlation function (TPCF) and two-point correlation cluster function (TPCCF) applicable to two-dimensional (2D) and three-dimensional (3D) reconstructions. We employ a modified Simulated annealing (SA) algorithm to accelerate the optimization procedure using a novel probability-based neighborhood generator consisting of three different neighborhood functions. We demonstrate the applications of the method in reconstruction of solid oxide fuel cells (SOFC) and similar complex-microstructure heterogeneous materials. In each case, we demonstrate the accuracy of the method using several distinctive statistical measures, namely TPCF, TPCCF, porosity, and specific surface in 2D and 3D spaces.