Maestro: an adaptive low mach number hydrodynamics algorithm for stellar flows. 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.

References in zbMATH (referenced in 14 articles , 1 standard article )

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  1. Yilmaz, Ilyas: Parallel direct numerical simulation and analysis of turbulent Rayleigh-Bénard convection at moderate Rayleigh numbers using an efficient algorithm (2020)
  2. Avgerinos, Stavros; Bernard, Florian; Iollo, Angelo; Russo, Giovanni: Linearly implicit all Mach number shock capturing schemes for the Euler equations (2019)
  3. Boscarino, S.; Russo, G.; Scandurra, L.: All Mach number second order semi-implicit scheme for the Euler equations of gas dynamics (2018)
  4. Minion, M. L.; Saye, R. I.: Higher-order temporal integration for the incompressible Navier-Stokes equations in bounded domains (2018)
  5. Motheau, Emmanuel; Duarte, Max; Almgren, Ann; Bell, John B.: A hybrid adaptive low-Mach number/compressible method: Euler equations (2018)
  6. Nonaka, Andrew; Day, Marcus S.; Bell, John B.: A conservative, thermodynamically consistent numerical approach for low Mach number combustion. I: Single-level integration (2018)
  7. Anshu Dubey, Ann Almgren, John Bell, Martin Berzins, Steve Brandt, Greg Bryan, Phillip Colella, Daniel Graves, Michael Lijewski, Frank Loffler, Brian O’Shea, Erik Schnetter, Brian Van Straalen, Klaus Weide: A Survey of High Level Frameworks in Block-Structured Adaptive Mesh Refinement Packages (2016) arXiv
  8. Berzins, Martin; Beckvermit, Jacqueline; Harman, Todd; Bezdjian, Andrew; Humphrey, Alan; Meng, Qingyu; Schmidt, John; Wight, Charles: Extending the Uintah framework through the petascale modeling of detonation in arrays of high explosive devices (2016)
  9. Pazner, Will E.; Nonaka, Andrew; Bell, John B.; Day, Marcus S.; Minion, Michael L.: A high-order spectral deferred correction strategy for low Mach number flow with complex chemistry (2016)
  10. Zhang, Weiqun; Almgren, Ann; Day, Marcus; Nguyen, Tan; Shalf, John; Unat, Didem: BoxLib with tiling: an adaptive mesh refinement software framework (2016) ioport
  11. Almgren, Ann; Bell, John; Nonaka, Andrew; Zingale, Michael: Low Mach number modeling of stratified flows (2014)
  12. Almgren, A. S.; Aspden, A. J.; Bell, J. B.; Minion, M. L.: On the use of higher-order projection methods for incompressible turbulent flow (2013)
  13. May, Sandra; Nonaka, Andrew; Almgren, Ann; Bell, John: An unsplit, higher-order Godunov method using quadratic reconstruction for advection in two dimensions (2011)
  14. Nonaka, A.; May, S.; Almgren, A. S.; Bell, J. B.: A three-dimensional, unsplit Godunov method for scalar conservation laws (2011)