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Continually reactivating iterative-projection method for instantiating microstructure from two-point statistics
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DOI：10.1016/j.actamat.2022.118230.png)
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Abstract
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Processing-structure (PS) linkages play a significant role in materials development. Nevertheless, currently there is a fascinating but of bottleneck task in terms of instantiating microstructure to understand and validate PS linkages. Its challenge lies on the lack of a robust method in computation efficiency and ac-curacy. Inspired from several advanced techniques such as hybrid input-output (HIO) algorithm, image processing operations and different-phase neighbors-based pixel swapping rule, we proposed a contin-ually reactivating iterative-projection process (CRIP) method to address the challenge above. The output at each iteration in CRIP is continuously improved by eliminating and moving isolated or noise pixels towards an error-reduction direction to activate the iterative-projection process of the next iteration. The performance of the method was examined on two microstructure examples. It shows at least 99.86% im-provement in convergence time compared with the classical simulated annealing algorithm and around 6.14 x 10 -4 reduction in error compared with the traditional HIO algorithm. More importantly, CRIP is suitable for the task of instantiating microstructure from periodic two-point statistics predicted by PS linkage, which has been demonstrated by applying it to two experimental datasets of Ni-based superal-loys and dual-phase steels. Our proposed method has the advantages of high efficiency, easy operation, reliable accuracy and remarkable generalization ability.(c) 2022 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Keywords:
Microstructure instantiation
Hybrid input-output
Simulated annealing
Two -point statistics
Processing -structure linkages
Journal
IF:
9.3
Papers:
2.0W
Citations:
12.9W
Organization
Cited Papers
Microstructure reconstructions from 2-point statistics using phase-recovery algorithms.png)
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