• Media type: E-Article
  • Title: A Class of Well-Balanced Algorithms for Relativistic Fluids on a Schwarzschild Background
  • Contributor: LeFloch, Philippe G.; Parés, Carlos; Pimentel-García, Ernesto
  • imprint: Springer Science and Business Media LLC, 2021
  • Published in: Journal of Scientific Computing
  • Language: English
  • DOI: 10.1007/s10915-021-01611-y
  • ISSN: 0885-7474; 1573-7691
  • Keywords: Computational Theory and Mathematics ; General Engineering ; Theoretical Computer Science ; Software ; Applied Mathematics ; Computational Mathematics ; Numerical Analysis
  • Origination:
  • Footnote:
  • Description: <jats:title>Abstract</jats:title><jats:p>For the evolution of a compressible fluid in spherical symmetry on a Schwarzschild curved background, we design a class of well-balanced numerical algorithms up to third-order accuracy. We treat both the relativistic Burgers–Schwarzschild model and the relativistic Euler–Schwarzschild model and take advantage of the explicit or implicit forms available for the stationary solutions of these models. Our schemes follow the finite volume methodology and preserve the stationary solutions. Importantly, they allow us to investigate the global asymptotic behavior of such flows and determine the asymptotic behavior of the mass density and velocity field of the fluid.</jats:p>