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Quantifying Particle Clustering in Discontinuously Reinforced Metal Matrix Composites

Published

Author(s)

J J. Williams, N Chawla, Richard J. Fields

Abstract

Reinforcement particle clustering significantly influences the mechanical behavior of metal matrix composites. We have employed clustering analysis techniques to quantify the degree of particle clustering by two techniques: (i) measuring the coefficient of variance in the average near neighbor spacing, and (ii) quantifying the cluster size distributions by image analysis technique. Verification of the applicability of the clustering analysis techniques was conducted on SiC particle reinforced Al matrix composites, where the degree of clustering was tailored by systematically varying the Al to SiC particle size. The degree of clustering increased with increasing Al:SiC particle size ratio, with a minimum in particle clustering taking place for particle size ratios of about one. The findings of this study indicate that the clustering analysis techniques employed are suitable for quantifying the degree of clustering in the composites.
Citation
NIST Interagency/Internal Report (NISTIR) - 6914
Report Number
6914

Keywords

aluminum, clustering, coeffient of variance, metal matrix composite, silicon carbide, size ratio

Citation

Williams, J. , Chawla, N. and Fields, R. (2021), Quantifying Particle Clustering in Discontinuously Reinforced Metal Matrix Composites, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD (Accessed December 5, 2024)

Issues

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Created October 12, 2021