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Carnegie Mellon Center for Nonlinear Analysis
Extending DFDGM to Motion by Weighted Mean Curvature


Matt Elsey
University of Michigan
Department of Mathematics

Abstract: The distance function-based diffusion-generated motion (DFDGM) algorithm for multiphase motion by curvature has been demonstrated to be a powerful tool for very large-scale simulations of isotropic grain growth and recrystallization. Here, we discuss an extension of this algorithm for generating weighted motion by curvature while enforcing the natural Herring angle conditions. This extension allows for simulations under a simplified model for anisotropic grain growth. Some numerical convergence results and preliminary simulation results will be presented.