Published June 2010 | Version v1
Journal article

MAESTRO: AN ADAPTIVE LOW MACH NUMBER HYDRODYNAMICS ALGORITHM FOR STELLAR FLOWS

  • 1. Center for Computational Science and Engineering, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States)
  • 2. Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY 11794-3800 (United States)

Description

Many astrophysical phenomena are highly subsonic, requiring specialized numerical methods suitable for long-time integration. In a series of earlier papers we described the development of MAESTRO, a low Mach number stellar hydrodynamics code that can be used to simulate long-time, low-speed flows that would be prohibitively expensive to model using traditional compressible codes. MAESTRO is based on an equation set derived using low Mach number asymptotics; this equation set does not explicitly track acoustic waves and thus allows a significant increase in the time step. MAESTRO is suitable for two- and three-dimensional local atmospheric flows as well as three-dimensional full-star flows. Here, we continue the development of MAESTRO by incorporating adaptive mesh refinement (AMR). The primary difference between MAESTRO and other structured grid AMR approaches for incompressible and low Mach number flows is the presence of the time-dependent base state, whose evolution is coupled to the evolution of the full solution. We also describe how to incorporate the expansion of the base state for full-star flows, which involves a novel mapping technique between the one-dimensional base state and the Cartesian grid, as well as a number of overall improvements to the algorithm. We examine the efficiency and accuracy of our adaptive code, and demonstrate that it is suitable for further study of our initial scientific application, the convective phase of Type Ia supernovae.

Availability note (English)

Available from http://dx.doi.org/10.1088/0067-0049/188/2/358

Additional details

Identifiers

Publishing Information

Journal Title
Astrophysical Journal, Supplement Series
Journal Volume
188
Journal Issue
2
Journal Page Range
p. 358-383
ISSN
0067-0049
CODEN
APJSA2