期刊
COMPUTATIONAL MATERIALS SCIENCE
卷 47, 期 2, 页码 342-352出版社
ELSEVIER
DOI: 10.1016/j.commatsci.2009.08.010
关键词
Polycrystal plasticity; Processing; Texture; Mechanical properties; Probability and statistics; Uncertainty quantification
资金
- Computational Mathematics Program of the AFOSR [F49620-00-1-0373]
- Materials and Surface Engineering Program of the NSF [DMS-0809062]
- Materials Science Division of the ARCI [W911NF-071-0519]
- Directorate For Engineering
- Div Of Civil, Mechanical, & Manufact Inn [0757824] Funding Source: National Science Foundation
Quantification and propagation of uncertainty in process conditions and initial microstructure on the final product properties in a deformation process are presented. The stochastic deformation problem is modeled using a sparse grid collocation approach that allows the utilization of a deterministic simulator to build interpolants of the main solution variables in the stochastic support space. The ability of the method in estimating the statistics of the macro-scale microstructure-sensitive properties and constructing the convex hull of these properties is shown through examples featuring randomness in initial texture and process parameters. A data-driven model reduction methodology together with a maximum entropy approach are used for representing randomness in initial texture in Rodrigues space. Comparisons are made with the results obtained from the Monte-Carlo method. (C) 2009 Elsevier B.V. All rights reserved.
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