PRISMS-PF: A general framework for phase-field modeling with a matrix-free finite element method

Stephen DeWitt, Shiva Rudraraju, David Montiel, W. Beck Andrews, Katsuyo Thornton

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

A new phase-field modeling framework with an emphasis on performance, flexibility, and ease of use is presented. Foremost among the strategies employed to fulfill these objectives are the use of a matrix-free finite element method and a modular, application-centric code structure. This approach is implemented in the new open-source PRISMS-PF framework. Its performance is enabled by the combination of a matrix-free variant of the finite element method with adaptive mesh refinement, explicit time integration, and multilevel parallelism. Benchmark testing with a particle growth problem shows PRISMS-PF with adaptive mesh refinement and higher-order elements to be up to 12 times faster than a finite difference code employing a second-order-accurate spatial discretization and first-order-accurate explicit time integration. Furthermore, for a two-dimensional solidification benchmark problem, the performance of PRISMS-PF meets or exceeds that of phase-field frameworks that focus on implicit/semi-implicit time stepping, even though the benchmark problem’s small computational size reduces the scalability advantage of explicit time-integration schemes. PRISMS-PF supports an arbitrary number of coupled governing equations. The code structure simplifies the modification of these governing equations by separating their definition from the implementation of the numerical methods used to solve them. As part of its modular design, the framework includes functionality for nucleation and polycrystalline systems available in any application to further broaden the phenomena that can be used to study. The versatility of this approach is demonstrated with examples from several common types of phase-field simulations, including coarsening subsequent to spinodal decomposition, solidification, precipitation, grain growth, and corrosion.

Original languageEnglish
Article number29
Journalnpj Computational Materials
Volume6
Issue number1
DOIs
StatePublished - Dec 1 2020
Externally publishedYes

Funding

This work was supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering under Award #DESC0008637 as part of the Center for PRedictive Integrated Structural Materials Science (PRISMS Center) at University of Michigan. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. This research was also supported through computational resources and services provided by Advanced Research Computing at the University of Michigan, Ann Arbor. The authors thank other contributors to the PRISMS-PF codebase, including Dr. Larry Aagesen, Mr. Jason Luce, and Mr. Xin Bo Qi.

FundersFunder number
Office of Basic Energy Sciences
U.S. Department of Energy Office of Science
U.S. Department of Energy
Office of ScienceDE-SC0008637
University of Michigan
Division of Materials Sciences and Engineering0008637

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