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Proceedings Paper

Microstructure representation and material characterization for multiscale finite element simulations of local mechanical behavior in damaged metallic structures
Author(s): M. Parra Garcia; C. Luo; A. Noshadravan; A. Keck; R. Teale; A. Chattopadhyay; P. Peralta
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Paper Abstract

Prediction of scatter on the mechanical behavior of metallic materials due to microstructural heterogeneity is important, particularly for damaged metallic structures, where degradation mechanisms such as fatigue can be very sensitive to microstructure variability, which is also a contributing factor to the scatter observed in the fatigue response of metallic materials. Two-dimensional (2D) and Three-dimensional (3D) representations of microstructures of 2xxx Al alloys are created via a combination of dual-scale serial sectioning techniques, with a smaller scale for particles and a larger scale for grains, Electron Backscattering Diffraction (EBSD) and available meshing and volume reconstruction software. In addition, "artificial" representations of the grains are also built from measurements of the crystallography and the geometry of the grains in representative cross sections of the samples. These measurements are then used to define a Representative Volume Element (RVE) with mechanical properties that are comparable to those in larger length scales, via simulations performed using finite element models of the RVE. In this work, the characteristics of the RVE are varied by introducing changes on either geometry, material properties or both and by "seeding" defects that represent damage (microcraks) or damage precursors (precipitates). Results indicate that models obtained predict the variability on stress fields expected at the local level, due to crystallographic and geometric variability of the microstructure.

Paper Details

Date Published: 3 April 2008
PDF: 8 pages
Proc. SPIE 6926, Modeling, Signal Processing, and Control for Smart Structures 2008, 69260K (3 April 2008); doi: 10.1117/12.776580
Show Author Affiliations
M. Parra Garcia, Arizona State Univ. (United States)
C. Luo, Arizona State Univ. (United States)
A. Noshadravan, Univ. of Southern California (United States)
A. Keck, Arizona State Univ. (United States)
R. Teale, Arizona State Univ. (United States)
A. Chattopadhyay, Arizona State Univ. (United States)
P. Peralta, Arizona State Univ. (United States)


Published in SPIE Proceedings Vol. 6926:
Modeling, Signal Processing, and Control for Smart Structures 2008
Douglas K. Lindner, Editor(s)

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