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- Title
Quantitative Analysis and Feature Recognition in 3-D Microstructural Data Sets.
- Authors
Lewis, A. C.; Suh, C.; Stukowski, M.; Geltmacher, A. B.; Spanos, G.; Rajan, K.
- Abstract
A three-dimensional (3-D) reconstruction of an austenitic stainless-steel microstructure was used as input for an image-based finite-element model to simulate the anisotropic elastic mechanical response of the microstructure. The quantitative data-mining and data-warehousing techniques used to correlate regions of high stress with critical microstructural features are discussed. Initial analysis of elastic stresses near grain boundaries due to mechanical loading revealed low overall correlation with their location in the microstructure. However, the use of data-mining and feature-tracking techniques to identify high-stress outliers revealed that many of these high-stress points are generated near grain boundaries and grain edges (triple junctions). These techniques also allowed for the differentiation between high stresses due to boundary conditions of the finite volume reconstructed, and those due to 3-D microstructural features.
- Subjects
THREE-dimensional imaging; STAINLESS steel; MICROSTRUCTURE; SIMULATION methods &; models; ANISOTROPY; STEEL alloys
- Publication
JOM: The Journal of The Minerals, Metals & Materials Society (TMS), 2006, Vol 58, Issue 12, p52
- ISSN
1047-4838
- Publication type
Article
- DOI
10.1007/BF02748496