Proposes two positivity-preserving correction schemes for dynamical low-rank approximations of the Vlasov equation using quadratic programming constraints, with one also preserving mass and momentum.
Efficient Admissible Set Projection in Optimization-based Invariant-Domain-Preserving Limiters for Ideal MHD
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abstract
Preserving the admissible set of the ideal magnetohydrodynamics (MHD) equations is important not only for producing physically meaningful numerical solutions, but more importantly for achieving robust computations. In this paper, we develop an optimization-based limiter to enforce admissibility while preserving global conservation and accuracy. For an easy and efficient projection, we decompose the admissible set into slices parameterized by the magnetic energy, so that the MHD projection reduces to a one-dimensional minimization, which can be solved efficiently by the Brent method. The splitting method can be used to efficiently solve the global minimization problem of the optimization-based limiter, which can be used to enforce cell average admissibility in discontinuous Galerkin (DG) schemes, and pointwise admissibility can be further enforced by the Zhang-Shu positivity-preserving limiter. We apply the limiter to high-order DG schemes and present numerical results for a few representative MHD problems.
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math.NA 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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Positivity-preserving dynamical low-rank methods for the Vlasov equation
Proposes two positivity-preserving correction schemes for dynamical low-rank approximations of the Vlasov equation using quadratic programming constraints, with one also preserving mass and momentum.