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Bayesian estimation of defect patterns in composite materials using through-thickness dielectric measurements
Author(s): Mushuang Liu; Yan Wan; Vamsee Vadlamudi; Frank L. Lewis; Kenneth Reifsnider; H. Felix Wu
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Paper Abstract

Composite materials play important roles in multifunctional applications, and thus, the diagnosis of damage patterns in composite materials becomes crucial to avoid critical events" such as structural or functional failures. The impact of an individual damage in composite materials has been extensively studied, however, the interaction of defects/cracks, which leads to critical fracture paths, has not been understood well. In this paper, we develop a Bayesian estimation based statistical analysis technique that estimates the damage pattern of a composite material, in particular, the relative positions of defects in the material, by measuring its through-thickness dielectric properties. We first explain the fundamental dielectric principle that leads to the detection of defect patterns. A capacitance model is then built to measure the material permittivity, and the relationship between the dielectric permittivity and relative positions are found using COMSOL Multiphysics. The interaction effects between defects observed in the simulation are interpreted using the fundamental dielectric principle. A Bayesian estimation based statistical analysis model is then developed to estimate the relative positions of defects in composite materials from the measured global dielectric properties.

Paper Details

Date Published: 1 April 2019
PDF: 9 pages
Proc. SPIE 10971, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XIII, 109710Z (1 April 2019); doi: 10.1117/12.2514647
Show Author Affiliations
Mushuang Liu, The Univ. of Texas at Arlington (United States)
Yan Wan, The Univ. of Texas at Arlington (United States)
Vamsee Vadlamudi, The Univ. of Texas at Arlington (United States)
Frank L. Lewis, The Univ. of Texas at Arlington (United States)
Kenneth Reifsnider, The Univ. of Texas at Arlington (United States)
H. Felix Wu, U.S. Dept. of Energy (United States)


Published in SPIE Proceedings Vol. 10971:
Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XIII
Andrew L. Gyekenyesi, Editor(s)

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