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Embedded polycrystal plasticity and adaptive sampling

delete2008-02-01
delete72
PRE
AI
N
Nathan R. Barton *
J
Jaroslaw Knap
A
A. Arsenlis
R
Richard Becker
R
Richard D. Hornung
D
David Jefferson
DOI:10.1016/j.ijplas.2007.03.004delete
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Abstract

Abstract

En 中文
A simulation capability for multi-scale embedded polycrystal plasticity is demonstrated with over two orders of magnitude wall-clock speedup compared to direct embedding. In the coarse-scale material model, the visco-plastic part of the material response is based on parameters determined from polycrystal level fine-scale calculations. Polycrystal plasticity parameters are approximated from fine-scale calculations using adaptive sampling to substantially reduce the total number of expensive fine-scale calculations which must be performed. The adaptive sampling method uses Kriging models for local interpolation of the fine-scale plasticity parameters and a metric-tree database for storage and retrieval of the fine-scale response models. Efficacy of the method is demonstrated through a variety of example problems involving both quasi-static and dynamic loading scenarios. (C) 2007 Elsevier Ltd. All rights reserved.
Keywords:
C. numerical algorithms
B. polycrystalline material
C. finite elements
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Journal

International Journal of Plasticity cover
International Journal of Plasticity
IF:
12.8
Papers:
4.0K
Citations:
2.5W

Organization

U
united states department of energy (doe)
Scholars:
11.3W
Papers: 9.6W
Citations: 246