Title

Anomaly detection and microstructure characterization in fiber reinforced ceramic matrix composites

Date of Award

2015

Degree Name

M.S. in Electrical Engineering

Department

Department of Electrical and Computer Engineering

Advisor/Chair

Advisor: Russell C. Hardie

Abstract

Ceramic matrix composites (CMCs) have the potential to replace current superalloys being used in hot components of jet engines. CMCs with continuous fiber reinforcement exhibit significant strength retention beyond temperatures at which Nickel based superalloys approach their melting temperature (900 C). While ceramics typically exhibit brittle failure modes making them unsuitable for use in dynamic systems, fiber reinforcement increases fracture toughness, crack growth resistance and strength. Differences in weave type, processing technique, and chemical makeup, however, result in a broad range of material microstructures each with a high degree of variability. Little is known about how the variation and imperfections within the microstructure affect the material properties. It is theorized that stress concentrations exist at certain abnormal microstructural configurations, resulting in either crack nucleation or propagation. Due to the amount of data available and the amount of variation in the microstructure, it is impractical to hope to discover the relationship between microstructural organization and cracking simply by observation. Instead, it is thought that the areas of greatest importance are those that do not adhere to the typical behavior of the material. These areas can be highlighted for analysis via anomaly detection methods for any measurable feature. In this thesis, two features are developed to describe the microstructure: fiber orientation and orientation gradient. Because fiber reinforcments are the primary method for strength enhancement, the features defined in this work both describe fibers, though the anomaly detection algorithm can be applied to other material constituents. Various image pre-processing techniques are implemented to prepare the feature field for anomaly detection. Novel techniques for segmentation of individual material phases are described. An ellipse detection algorithm for identification of fibers is described, as well as a subsequent fiber tracking algorithm. The orientation and orientation gradient fields are described in detail. Fiber orientation refers to the geometric interpretation of individual fibers embedded in ceramic matrix. The orientation gradient of fibers describes the relative changes in orientation in a neighborhood of fibers. Eigen-analysis of the orientation gradient reveals the geometric distortion of fiber orientations with position. This affect is similar to an affine transformation with shear and scaling. It is shown that by modeling the normal behavior of a microstructure, anomalies can be identified and described. Here, it is shown that anomalies of the orientation gradient can be identified and are commonly linked to expansion/contraction at fiber tow edges. This is a large step in correlating microstructure organization with damage, and ultimately optimizing material design.

Keywords

Ceramic-matrix composites Microstructure Simulation methods, Ceramic-matrix composites Defects, Failure analysis (Engineering) Data processing, Jet engines Materials Testing, Electrical Engineering, Materials Science, anomaly detection, fiber tracking, ceramic matrix composites, microstructure charaterization, gaussian mixture modeling

Rights Statement

Copyright 2015, author

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