4.7 Article

An adaptive scalable fully implicit algorithm based on stabilized finite element for reduced visco-resistive MHD

期刊

JOURNAL OF COMPUTATIONAL PHYSICS
卷 454, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcp.2022.110967

关键词

Visco-resistive implicit MHD; Continuous finite element; Streamline upwind Petrov-Galerkin; Physics-based preconditioning; Adaptive mesh refinement; Plasmoid instability

资金

  1. U.S. Department of Energy National Nuclear Security Administration [89233218CNA000001]
  2. National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility at Lawrence Berkeley National Laboratory [DE-AC02-05CH11231, FES-ERCAP0016552, FES-ERCAP0016553]

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This paper presents a high-order stabilized finite-element algorithm based on the MFEM finite element library for solving the reduced visco-resistive MHD equations. The use of physics-based preconditioning strategy and adaptive mesh refinement scheme is also discussed. Experimental results demonstrate the accuracy, efficiency, and scalability of the implicit scheme in the presence of large scale disparity.
The magnetohydrodynamics (MHD) equations are continuum models used in the study of a wide range of plasma physics systems, including the evolution of complex plasma dynamics in tokamak disruptions. However, efficient numerical solution methods for MHD are extremely challenging due to disparate time and length scales, strong hyperbolic phenomena, and nonlinearity. Therefore the development of scalable, implicit MHD algorithms and high-resolution adaptive mesh refinement strategies is of considerable importance. In this work, we develop a high-order stabilized finite-element algorithm for the reduced visco-resistive MHD equations based on the MFEM finite element library (mfem .org). The scheme is fully implicit, solved with the Jacobian-free Newton-Krylov (JFNK) method with a physics-based preconditioning strategy. Our preconditioning strategy is a generalization of the physics-based preconditioning methods in Chacon et al. (2002) [3] to adaptive, stabilized finite elements. Algebraic multigrid methods are used to invert sub-block operators to achieve scalability. A parallel adaptive mesh refinement scheme with dynamic load-balancing is implemented to efficiently resolve the multi-scale spatial features of the system. Our implementation uses the MFEM framework, which provides arbitrary-order polynomials and flexible adaptive conforming and non-conforming meshes capabilities. Results demonstrate the accuracy, efficiency, and scalability of the implicit scheme in the presence of large scale disparity. The potential of the AMR approach is demonstrated on an island coalescence problem in the high Lundquist-number regime (>= 107) with the successful resolution of plasmoid instabilities and thin current sheets. Published by Elsevier Inc.

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