Low Mach Number Modeling of Stratified Flows

  • Ann AlmgrenEmail author
  • John Bell
  • Andrew Nonaka
  • Michael Zingale
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 77)


Low Mach number equation sets approximate the equations of motion of a compressible fluid by filtering out the sound waves, which allows the system to evolve on the advective rather than the acoustic time scale. Depending on the degree of approximation, low Mach number models retain some subset of possible compressible effects. In this paper we give an overview of low Mach number methods for modeling stratified flows arising in astrophysics and atmospheric science as well as low Mach number reacting flows. We discuss how elements from the different fields are combined to form MAESTRO, a code for modeling low Mach number stratified flows with general equations of state, reactions and time-varying stratification.


White Dwarf Stratify Flow Adaptive Mesh Refinement Buoyancy Term Background Stratification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The work at LBNL was supported by the Applied Mathematics Program of the DOE Office of Advance Scientific Computing Research under U.S. Department of Energy under contract No. DE-AC02-05CH11231. The work at Stony Brook was supported by a DOE/Office of Nuclear Physics grant Nos. DE-FG02-06ER41448 and DE-FG02-87ER40317 to Stony Brook. An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. This research used resources of the Oak Ridge Leadership Computing Facility located in the Oak Ridge National Laboratory, which is supported by the Office of Science of the Department of Energy under Contract DE-AC05-00OR22725. The MAESTRO code is freely available from


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ann Almgren
    • 1
    Email author
  • John Bell
    • 1
  • Andrew Nonaka
    • 1
  • Michael Zingale
    • 2
  1. 1.Lawrence Berkeley National LaboratoryBerkeleyUSA
  2. 2.Stony Brook UniversityStony BrookUSA

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