Space‐Time Block Preconditioning for Incompressible Resistive Magnetohydrodynamics

Le résumé fourni par la source

ABSTRACT This work develops an all‐at‐once space‐time preconditioning approach for resistive magnetohydrodynamics (MHD). We consider parallel‐in‐time due to the long time domains required to capture the physics of interest, as well as the complexity of the underlying system, and thereby the computational cost of long‐time integration. To ameliorate this cost by using many processors, we thus develop a novel approach to solving the whole space‐time system that is parallelizable in both space and time. We develop a space‐time block preconditioning for resistive MHD, following the space‐time block preconditioning concept first introduced by Danieli et al. in 2022 for incompressible flow, where an effective preconditioner for classic sequential time‐stepping is extended to the space‐time setting. The starting point for our derivation is the continuous Schur complement preconditioner, A New Approximate Block Factorization Preconditioner for Two‐Dimensional Incompressible (Reduced) Resistive MHD , by Cyr et al. in the SIAM Journal on Scientific Computing, 2013. We proceed to generalize this work, to produce, to our knowledge, the first space‐time block preconditioning approach for the challenging equations governing incompressible resistive MHD. The numerical results are promising for the model problems of island coalescence and tearing mode, which we investigate numerically in a mixed regime, where advective and diffusive forces are both present. The overhead computational cost associated with space‐time preconditioning vs. sequential time‐stepping is modest and primarily in the range of 2×–5×, which is low for parallel‐in‐time schemes in general. Additionally, the scaling results for inner (linear) and outer (nonlinear) iterations are flat in the case of fixed time‐step size and only grow very slowly in the case of time‐step refinement.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.