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

TitleApplication of chord length distributions and principal component analysis for quantification and representation of diverse polycrystalline microstructures
Publication TypeJournal Article
Year of Publication2018
AuthorsLatypov MI, Kühbach M, Beyerlein IJ, Stinville JCharles, Toth LS, Pollock TM, Kalidindi SR
JournalMaterials Characterization
Volume145
Pagination671–685
ISSN10445803
KeywordsChord length distribution, EBSD, Grain size, Microstructure, Principal component analysis
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).

URLhttps://doi.org/10.1016/j.matchar.2018.09.020
DOI10.1016/j.matchar.2018.09.020