Validating simulated predictions of internal damage within armor ceramics is preferable to simply assessing a modelÕs ability to predict penetration depth, especially if one hopes to perform subsequent ''second strike'' analyses. We present the results of a study in which crack networks are seeded by using a statistically perturbed strength, the median of which is inherited from a deterministic ''smeared damage'' model, with adjustments to reflect experimentally established size effects. This minor alteration of an otherwise conventional damage model noticeably mitigates mesh dependencies and, at virtually no computational cost, produces far more realistic cracking patterns that are well suited for validation against X-ray computed tomography (XCT) images of internal damage patterns. For Brazilian, spall, and indentation tests, simulations share qualitative features with externally visible damage. However, the need for more stringent quantitative validation, software quality testing, and subsurface XCT validation, is emphasized.
The ability to quantify the material damage at different length scales is critical in the multiscale analysis of material behavior from nanoscale to macroscale. In this article, on the basis of the equivalence of complementary elastic energy we propose a multiresolution rule that transforms different levels of material defects to the equivalent degradation of material properties. It facilitates a sequential memory-efficient processing of massive material defects in a multiresolution framework, and also supports a functionality of partial damage conversion to serve different needs in subsequent numerical analyses. Numerical simulation was conducted with different settings of material defects. The analysis results indicate the efficacy of the proposed method, offering a potential (i) to interface between multiscale material defects and (ii) as an effective method of homogenization for the determination of the damage variable in continuum damage mechanics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.