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Maestro: An adaptive low Mach number hydrodynamics algorithm for stellar flows

  • A. Nonaka
  • , A. S. Almgren
  • , J. B. Bell
  • , M. J. Lijewski
  • , C. M. Malone
  • , M. Zingale
  • Lawrence Berkeley National Laboratory
  • Stony Brook University

Research output: Contribution to journalArticlepeer-review

69 Scopus citations

Abstract

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 TypeIa supernovae.

Original languageEnglish
Pages (from-to)358-383
Number of pages26
JournalAstrophysical Journal, Supplement Series
Volume188
Issue number2
DOIs
StatePublished - 2010

Keywords

  • Convection
  • Hydrodynamics
  • Methods: numerical
  • Nuclear reactions, nucleosynthesis, abundances
  • Supernovae: general
  • White dwarfs

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