Provably Positive Central DG Schemes via Geometric Quasilinearization for Ideal MHD Equations
Kailiang Wu, Haili Jiang, Chi-Wang Shu

TL;DR
This paper develops high-order positivity-preserving central discontinuous Galerkin schemes for ideal MHD, addressing the divergence-free constraint through geometric quasilinearization and source term discretization, ensuring physical and numerical stability.
Contribution
It introduces the first rigorous PP analysis of central DG methods for ideal MHD and constructs new schemes that maintain positivity in multidimensional cases.
Findings
Standard CDG methods are PP in 1D with a limiter.
In multidimensions, standard CDG methods are not PP without modifications.
New locally divergence-free CDG schemes are proven to be PP for ideal MHD.
Abstract
In the numerical simulation of ideal MHD, keeping the pressure and density positive is essential for both physical considerations and numerical stability. This is a challenge, due to the underlying relation between such positivity-preserving (PP) property and the magnetic divergence-free (DF) constraint as well as the strong nonlinearity of the MHD equations. This paper presents the first rigorous PP analysis of the central discontinuous Galerkin (CDG) methods and constructs arbitrarily high-order PP CDG schemes for ideal MHD. By the recently developed geometric quasilinearization (GQL) approach, our analysis reveals that the PP property of standard CDG methods is closely related to a discrete DF condition, whose form was unknown and differs from the non-central DG and finite volume cases in [K. Wu, SIAM J. Numer. Anal. 2018]. This result lays the foundation for the design of our PP CDG…
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Taxonomy
TopicsComputational Fluid Dynamics and Aerodynamics · Fluid Dynamics and Turbulent Flows · Model Reduction and Neural Networks
