Embedded polycrystal plasticity and adaptive sampling

• DOI: 10.1016/j.ijplas.2007.03.004
• Publication Date: 2007-03-14T11:06:02Z
• Authors: Nathan R. Barton; Jaroslaw Knap; Athanasios Arsenlis; Richard Becker; Richard D. Hornung; David R. Jefferson
• Keywords: Speedup; Adaptive sampling; Interpolation

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.