Design of provably physical-constraint-preserving methods for general relativistic hydrodynamics

Kailiang Wu
Phys. Rev. D 95, 103001 – Published 1 May 2017

Abstract

The paper develops high-order physical-constraint-preserving (PCP) methods for general relativistic hydrodynamic (GRHD) equations, equipped with a general equation of state. Here the physical constraints, describing the admissible states of GRHD, are referred to the subluminal constraint on the fluid velocity and the positivity of the density, pressure and specific internal energy. Preserving these constraints is very important for robust computations, otherwise violating one of them will lead to the ill-posed problem and numerical instability. To overcome the difficulties arising from the inherent strong nonlinearity contained in the constraints, we derive an equivalent definition of the admissible states. Using this definition, we prove the convexity, scaling invariance and Lax-Friedrichs (LxF) splitting property of the admissible state set G, and discover the dependence of G on the spacetime metric. Unfortunately, such dependence yields the nonequivalence of G at different points in curved spacetime, and invalidates the convexity of G in analyzing PCP schemes. This obstacle is effectively overcame by introducing a new formulation of the GRHD equations. Based on this formulation and the above theories, a first-order LxF scheme is designed on general unstructured mesh and rigorously proved to be PCP under a Courant-Friedrichs-Lewy (CFL) condition. With two types of PCP limiting procedures, we design high-order, provably (not probably) PCP methods under discretization on the proposed new formulation. These high-order methods include the PCP finite difference, finite volume and discontinuous Galerkin methods.

  • Received 16 March 2017

DOI:https://doi.org/10.1103/PhysRevD.95.103001

© 2017 American Physical Society

Physics Subject Headings (PhySH)

Fluid DynamicsGravitation, Cosmology & Astrophysics

Authors & Affiliations

Kailiang Wu*

  • Department of Mathematics, The Ohio State University, Columbus, Ohio 43210, USA

  • *wu.3423@osu.edu

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Issue

Vol. 95, Iss. 10 — 15 May 2017

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