Improved Methodology for RANS Modeling of High-Speed Turbulent Scalar Mixing

Abstract

Reynolds averaged Navier-Stokes (RANS) turbulence modeling upgrades are discussed which improve predictions of scalar mixing in high-speed flows relevant to aero-propulsive fuel injection. The turbulent scalar fluctuation model (SFM) utilized (that solves partial differential equations for energy/species variance and corresponding dissipation rates) is reviewed and upgrades which improve model predictions are discussed along with model validation studies. The SFM is cast in a k- turbulence model framework with unified compressibility extensions specialized for high speed aero-propulsive flows and low Reynolds number extensions for wall-bounded flows. The SFM predicts the spatial variation of turbulent Prandtl and Schmidt numbers using time-scale relations, providing more consistent and reliable solutions than those based on user-specified average values. The SFM has been systematically upgraded to treat flows of increasing complexity using a “buildingblock” approach to ensure that modifications made to improve the analysis of more complex cases will not degrade model performance in analyzing fundamental cases. A GUI-driven validation tool, CRAVE, has been developed to facilitate an automated validation/calibration process using various experimental and LES data sets. This paper will focus on upgrades implemented to the k- turbulence model and SFM that improve model predictions over a wide range of aeropropulsive flows, with recent validation studies discussed comparing predicted mean and fluctuating scalar quantities to experimental and LES-based data sets, including those obtained from a newly developed DDES model.