Modeling Variable-Density Turbulent Mixing with BHR2 in FLASH

Turbulent mixing in variable-density, compressible flows play a critical role in high-energy-density physics but remains a significant challenge for numerical modeling. To address this, Los Alamos National Laboratory has developed a class of Reynolds Average Navier Stokes (RANS) models, the BHR-RANS [Besnard-Harlow-Rauenzahn, LA-12303-MS, 1992] that enable to emulate turbulence driven by physical processes such as the Kelvin-Helmholtz, Rayleigh-Taylor, and Richtmyer-Meshkov instabilities. The BHR-2 model [LA-UR-12-24386, 2012] in particular, was recently implemented into FLASH’s hydrodynamics simulation framework. The model evolves equations for turbulent kinetic energy and turbulence length scale, enabling the representation of anisotropic, non-equilibrium mixing and scale-dependent transport. Incorporating BHR2 into FLASH required extending the hydrodynamic solver infrastructure to support additional evolution equations, source terms, and nonlinear diffusion terms. This implementation expands FLASH’s capabilities for modeling turbulent mixing with improved physical accuracy, supporting a range of applications in astrophysics and high-energy-density laboratory experiments.

This material is based on work supported by the U.S. Department of Energy (DOE) National Nuclear Security Administration (NNSA) under awards DE-NA0004144 and DE-NA0004147, and under subcontracts no. 630138 and C4574 with Los Alamos National Laboratory. We acknowledge support from the U.S. DOE Advanced Research Projects Agency-Energy (ARPA-E) under Award Number DE-AR0001272, and the U.S. DOE Office of Science (SC) under Award Number DE-SC0023246. The software used in this work was developed in part by the U.S. DOE NNSA- and U.S. DOE Office of Science-supported Flash Center for Computational Science at the University of Chicago and the University of Rochester. J.A. Saenz was supported by the Mix and Burn project within the Physics and Engineering Models program of the Advanced Simulation and Computing program at Los Alamos National Laboratory.