Actions for Order parameter re-mapping algorithm for 3D phase field model of grain growth using FEM [electronic resource].
Order parameter re-mapping algorithm for 3D phase field model of grain growth using FEM [electronic resource].
- Published
- Washington, D.C. : United States. Dept. of Energy, 2016.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy - Physical Description
- pages 18-25 : digital, PDF file
- Additional Creators
- Idaho National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
Access Online
- Restrictions on Access
- Free-to-read Unrestricted online access
- Summary
- Phase field modeling (PFM) is a well-known technique for simulating microstructural evolution. To model grain growth using PFM, typically each grain is assigned a unique non-conserved order parameter and each order parameter field is evolved in time. Traditional approaches using a one-to-one mapping of grains to order parameters present a challenge when modeling large numbers of grains due to the computational expense of using many order parameters. This problem is exacerbated when using an implicit finite element method (FEM), as the global matrix size is proportional to the number of order parameters. While previous work has developed methods to reduce the number of required variables and thus computational complexity and run time, none of the existing approaches can be applied for an implicit FEM implementation of PFM. Here, we present a modular, dynamic, scalable reassignment algorithm suitable for use in such a system. Polycrystal modeling with grain growth and stress require careful tracking of each grain’s position and orientation which is lost when using a reduced order parameter set. In conclusion, the method presented in this paper maintains a unique ID for each grain even after reassignment, to allow the PFM to be tightly coupled to calculations of the stress throughout the polycrystal. Implementation details and comparative results of our approach are presented.
- Report Numbers
- E 1.99:inl/jou--16-37562
inl/jou--16-37562 - Subject(s)
- Other Subject(s)
- Note
- Published through SciTech Connect.
01/14/2016.
"inl/jou--16-37562"
": S0927025615008186"
Computational Materials Science 115 C ISSN 0927-0256 AM
Cody J. Permann; Michael R. Tonks; Bradley Fromm; Derek R. Gaston. - Funding Information
- AC07-05ID14517
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