Well-balanced treatment of gravity in astrophysical fluid dynamics simulations at low Mach numbers
P. V. F. Edelmann, L. Horst, J. P. Berberich, R. Andrassy, J. Higl, G., Leidi, C. Klingenberg, F. K. Roepke

TL;DR
This paper demonstrates that well-balanced numerical schemes combined with low Mach number flux functions are essential for accurately simulating slow stellar flows, effectively handling gravity and pressure balance in astrophysical fluid dynamics.
Contribution
The study compares three well-balanced schemes within the SLH code, showing their effectiveness in maintaining hydrostatic equilibrium and accurately modeling stellar slow flows.
Findings
The $eta$-$eta$ and deviation methods preserve hydrostatic solutions accurately.
They reproduce the expected scaling of convective flow speed with heating.
The deviation method improves long-term orbital motion accuracy in Keplerian disks.
Abstract
Accurate simulations of flows in stellar interiors are crucial to improving our understanding of stellar structure and evolution. Because the typically slow flows are merely tiny perturbations on top of a close balance between gravity and the pressure gradient, such simulations place heavy demands on numerical hydrodynamics schemes. We demonstrate how discretization errors on grids of reasonable size can lead to spurious flows orders of magnitude faster than the physical flow. Well-balanced numerical schemes can deal with this problem. Three such schemes were applied in the implicit, finite-volume Seven-League Hydro (SLH) code in combination with a low-Mach-number numerical flux function. We compare how the schemes perform in four numerical experiments addressing some of the challenges imposed by typical problems in stellar hydrodynamics. We find that the - and deviation…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
