Title | Random composites characterization using a classifier model |
Publication Type | Journal Article |
Year of Publication | 2007 |
Authors | Liu H., Arwade SR, Igusa T. |
Journal | Journal of Engineering Mechanics |
Volume | 133 |
Issue | 2 |
Start Page | 129 |
Pagination | 129-140 |
Date Published | 02/2007 |
ISSN | 0733-9399 |
Keywords | Bayesian analysis, Composite materials, Damage, Decision making, fracture, Microstructures, Statistics, Uncertainty principles |
Abstract | A new method is introduced for characterizing and analyzing materials with random heterogeneous microstructure. The method begins with classifiers which process information from high-fidelity analyses of small-sized simulated microstructures. These classifiers are subsequently used in a multipass moving window to identify subregions of potentially critical microscale behavior such as strain concentrations. In the derivation of the method, it is shown how information theory-based concepts can be formulated in a Bayesian decision theory framework that addresses microstructural issues. Furthermore, it is shown how a sequence of classifiers can be constructed to refine the analysis of microstructure. While the method presented herein is general, a relatively simple example of a two-dimensional, two-phase composite is used to illustrate the analysis steps. |
DOI | 10.1061/(ASCE)0733-9399(2007)133:2(129) |