Speeding up of microstructure reconstruction: II. Application to patterns of poly-dispersed islands
W. Olchawa, R. Piasecki

TL;DR
This paper introduces a fast, multi-scale statistical method for reconstructing complex two-phase island patterns, significantly reducing computation time while accurately preserving morphological features like shape, size, and interface length.
Contribution
The authors develop a weighted doubly-hybrid approach combining entropic and correlation descriptors, using a synthetic initial configuration to accelerate microstructure reconstruction.
Findings
Significantly reduces Monte Carlo steps compared to standard methods
Accurately reproduces island shapes, sizes, and interfaces
Effective for patterns with jagged borders
Abstract
We report a fast, efficient and credible statistical reconstruction of any two-phase patterns of islands of miscellaneous shapes and poly-dispersed in sizes. In the proposed multi-scale approach called a weighted doubly-hybrid, two different pairs of hybrid descriptors are used. As the first pair, we employ entropic quantifiers, while correlation functions are the second pair. Their competition allows considering a wider spectrum of morphological features. Instead of a standard random initial configuration, a synthetic one with the same number of islands as that of the target is created by a cellular automaton. This is the key point for speeding-up of microstructure reconstruction, making use of the simulated annealing technique. The program procedure allows requiring the same values for the reconstructed and target interface. The reconstruction terminates when three conditions related…
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