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A crystal symmetry-invariant Kobayashi–Warren–Carter grain boundary model and its implementation using a thresholding algorithm.

Authors :
Kim, Jaekwang
Jacobs, Matt
Osher, Stanley
Admal, Nikhil Chandra
Source :
Computational Materials Science. Nov2021, Vol. 199, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

One of the most important aims of grain boundary modeling is to predict the evolution of a large collection of grains in phenomena such as abnormal grain growth, coupled grain boundary motion, and recrystallization that occur under extreme thermomechanical loads. A unified framework to study the coevolution of grain boundaries with bulk plasticity has recently been developed by [1] , which is based on modeling grain boundaries as continuum dislocations governed by an energy based on the Kobayashi–Warren–Carter (KWC) model [2,3]. While the resulting unified model demonstrates coupled grain boundary motion and polygonization (seen in recrystallization), it is restricted to grain boundary energies of the Read–Shockley type, which applies only to small misorientation angles. In addition, the implementation of the unified model using finite elements inherits the computational challenges of the KWC model that originate from the singular diffusive nature of its governing equations. The main goal of this study is to generalize the KWC functional to grain boundary energies beyond the Read–Shockley-type that respect the bicrystallography of grain boundaries. The computational challenges of the KWC model are addressed by developing a thresholding method that relies on a primal dual algorithm and the fast marching method, resulting in an O (N log N) algorithm, where N is the number of grid points. We validate the model by demonstrating the Herring angle and the von Neumann–Mullins relations, followed by a study of the grain microstructure evolution in a two-dimensional face-centered cubic copper polycrystal with crystal symmetry-invariant grain boundary energy data obtained from the covariance grain boundary model of [4,5]. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09270256
Volume :
199
Database :
Academic Search Index
Journal :
Computational Materials Science
Publication Type :
Academic Journal
Accession number :
152231409
Full Text :
https://doi.org/10.1016/j.commatsci.2021.110575