Sparse Jacobian construction for mapped grid visco-resistive magnetohydrodynamics.

*(English)*Zbl 1426.76417
Forth, Shaun (ed.) et al., Recent advances in algorithmic differentiation. Selected papers based on the presentations at the 6th international conference on automatic differentiation (AD2012), Fort Collins, CO, USA, July 23–27, 2012. Berlin: Springer. Lect. Notes Comput. Sci. Eng. 87, 11-21 (2012).

Summary: 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.

For the entire collection see [Zbl 1247.65002].

For the entire collection see [Zbl 1247.65002].