Sparse Jacobian construction for mapped grid visco-resistive magnetohydrodynamics

Daniel R. Reynolds, Ravi Samtaney

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


We apply the automatic differentiation tool OpenAD toward constructing a preconditioner for fully implicit simulations of mapped grid visco-resistive magnetohydrodynamics (MHD), used in modeling tokamak fusion devices. Our simulation framework employs a fully implicit formulation in time, and a mapped finite volume spatial discretization. We solve this model using inexact Newton-Krylov methods. Of critical importance in these iterative solvers is the development of an effective preconditioner, which typically requires knowledge of the Jacobian of the nonlinear residual function. However, due to significant nonlinearity within our PDE system, our mapped spatial discretization, and stencil adaptivity at physical boundaries, analytical derivation of these Jacobian entries is highly nontrivial. This paper therefore focuses on Jacobian construction using automatic differentiation. In particular, we discuss applying OpenAD to the case of a spatially-adaptive stencil patch that automatically handles differences between the domain interior and boundary, and configuring AD for reduced stencil approximations to the Jacobian. We investigate both scalar and vector tangent mode differentiation, along with simple finite difference approaches, to compare the resulting accuracy and efficiency of Jacobian construction in this application. © 2012 Springer-Verlag.
Original languageEnglish (US)
Title of host publicationLecture Notes in Computational Science and Engineering
PublisherSpringer Nature
Number of pages11
ISBN (Print)9783642300226
StatePublished - Jul 7 2012

ASJC Scopus subject areas

  • Engineering(all)
  • Modeling and Simulation
  • Computational Mathematics
  • Discrete Mathematics and Combinatorics
  • Control and Optimization


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