Application of chord length distributions and principal component analysis for 
quantification and representation of diverse polycrystalline microstructures

Latypov, Marat I.; Kühbach, Markus; Beyerlein, Irene J.; Stinville, Jean Charles; Tóth, L. S.; Pollock, Tresa M.; Kalidindi, Surya R.

doi:10.1016/j.matchar.2018.09.020

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Application of chord length distributions and principal component analysis for quantification and representation of diverse polycrystalline microstructures

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Kühbach, Markus
Theory and Simulation, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Citation

Latypov, M. I., Kühbach, M., Beyerlein, I. J., Stinville, J. C., Tóth, L. S., Pollock, T. M., et al. (2018). Application of chord length distributions and principal component analysis for quantification and representation of diverse polycrystalline microstructures. Materials Characterization, 145, 671-685. doi:10.1016/j.matchar.2018.09.020.

Cite as: https://hdl.handle.net/21.11116/0000-0003-A363-5

Abstract

Quantification of mesoscale microstructures of polycrystalline materials is important for a range of practical tasks of materials design and development. The current protocols of quantifying grain size and morphology often rely on microstructure metrics (e.g., mean grain diameter) that overlook important details of the mesostructure. In this work, we present a quantification framework based on directionally resolved chord length distribution and principal component analysis as a means of extracting additional information from 2-D microstructural maps. Towards this end, we first present in detail a method for calculating chord length distribution based on boundary segments available in modern digital datasets (e.g., from microscopy post-processing) and their low-rank representations by principal component analysis. The utility of the proposed framework for capturing grain size, morphology, and their anisotropy for efficient visualization, representation, and specification of polycrystalline microstructures is then demonstrated in case studies on datasets from synthetic generation, experiments (on Ni-base superalloys), and simulations (on steel during recrystallization). © 2018 Elsevier Inc.