Modeling Variable-Density Flows With New Hybrid RANS/LES Framework

ORAL

Abstract

Hybrid RANS/LES methods have been widely used to predict flows featuring single-fluid and constant density over the last decades. Their success stems from the ability to accurately predict complex flows at a significantly lower cost than LES and DNS formulations. However, limited research has been performed extending such formulations to variable-density flow, characterized by turbulence generated by shear and buoyancy mechanisms. This class of flows is often simulated with hybrid methods based on incompressible and single-fluid closures. Hence, the authors have been developing a framework to extend the Partially-Averaged Navier-Stokes equations (PANS) to variable density flows, which can be applied to other hybrid models. This presentation provides an overview of the current state of PANS modeling for variable density flows. The performance of a proposed PANS variable density closure [1] is assessed by predicting i) a low-speed oceanic turbulent mixing flow and ii) a low-/high-speed Richtmyer–Meshkov materials mixing problem. The results are compared against available numerical and experimental results.

[1] F.S. Pereira, F.F. Grinstein, D.M. Israel, R. Rauenzahn, and S.S. Girimaji - Partially averaged Navier-Stokes closure modeling for variable-density turbulent flow. Phys. Rev. Fluids, Vol. 6(8), 084602, 2021.

*Los Alamos National Laboratory

Publication: F.S. Pereira, F.F. Grinstein, D.M. Israel, R. Rauenzahn, and S.S. Girimaji - Partially averaged Navier-Stokes closure modeling for variable-density turbulent flow. Phys. Rev. Fluids, Vol. 6(8), 084602, 2021.

Presenters

  • Filipe Pereira

    • Los Alamos National Laboratory

Authors

  • Filipe Pereira

    • Los Alamos National Laboratory
  • Luke van Roekel

    • Los Alamos National Laboratory
  • Tiffany R Desjardins

    • Los Alamos National Laboratory
  • John J Charonko

    • Los Alamos
    • Los Alamos National Laboratory
  • Forrest W Doss

    • Los Alamos National Laboratory