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Proceedings Paper

Anomaly detection of microstructural defects in continuous fiber reinforced composites
Author(s): Stephen Bricker; J. P. Simmons; Craig Przybyla; Russell C. Hardie
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Paper Abstract

Ceramic matrix composites (CMC) with continuous fiber reinforcements have the potential to enable the next generation of high speed hypersonic vehicles and/or significant improvements in gas turbine engine performance due to their exhibited toughness when subjected to high mechanical loads at extreme temperatures (2200F+). Reinforced fiber composites (RFC) provide increased fracture toughness, crack growth resistance, and strength, though little is known about how stochastic variation and imperfections in the material effect material properties. In this work, tools are developed for quantifying anomalies within the microstructure at several scales. The detection and characterization of anomalous microstructure is a critical step in linking production techniques to properties, as well as in accurate material simulation and property prediction for the integrated computation materials engineering (ICME) of RFC based components. It is desired to find statistical outliers for any number of material characteristics such as fibers, fiber coatings, and pores. Here, fiber orientation, or ‘velocity’, and ‘velocity’ gradient are developed and examined for anomalous behavior. Categorizing anomalous behavior in the CMC is approached by multivariate Gaussian mixture modeling. A Gaussian mixture is employed to estimate the probability density function (PDF) of the features in question, and anomalies are classified by their likelihood of belonging to the statistical normal behavior for that feature.

Paper Details

Date Published: 12 March 2015
PDF: 10 pages
Proc. SPIE 9401, Computational Imaging XIII, 94010A (12 March 2015); doi: 10.1117/12.2079679
Show Author Affiliations
Stephen Bricker, Univ. of Dayton (United States)
J. P. Simmons, Air Force Research Lab. (United States)
Craig Przybyla, Air Force Research Lab. (United States)
Russell C. Hardie, Univ. of Dayton (United States)


Published in SPIE Proceedings Vol. 9401:
Computational Imaging XIII
Charles A. Bouman; Ken D. Sauer, Editor(s)

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