In spite of its shortcomings, faster turnaround time and cost-effectiveness make the Reynolds-averaged Navier-Stokes modeling approach still a popular and widely used methodology in many industrial applications, including the automotive industries in general, but the motorsports sector in particular. Existing literature suggests that all Reynolds-averaged Navier-Stokes models generally fail to predict pressure and velocity flow fields with a reasonable accuracy, especially in the vehicle wake region. Recent numerical works suggest that, when using two-equation eddy viscosity turbulence models, improved correlation between the experiment and computational fluid dynamics is not achievable through only mesh refinements or adding additional corrective terms in the turbulence transport equations, and additional efforts are necessary for better predictions. In this backdrop, the prediction improvement strategy adopted in this paper is based on the realization that the turbulence model closure coefficients are normally specified as constants and their values are determined from either a single observation or a simple functional form is assumed and that these coefficients are constructed and/or constrained to behave correctly in extremely limiting circumstances. Subsequently, this study investigated the influence of a few selected turbulence model closure coefficients on the veracity of computational fluid dynamics predictions by analyzing simulations run with turbulence model closure coefficient values that were different from the commonly used default ones. This was done by first investigating the individual effect of each model parameters on the prediction veracity, and then a combination of model closure coefficient values was formulated in order to obtain a prediction with the best experimental correlation. This procedure was applied to four different test objects which include NACA 4412 airfoil at 12 degrees angle of attack, the 25 and 35 degrees slant angle Ahmed body, and a full-scale sedan type passenger vehicle. The shear-stress transport k - omega was chosen as the turbulence model because of its popularity in automotive applications. It was observed that, irrespective of the test model, the computational fluid dynamics predictions are somewhat independent of some closure coefficients, while the prediction showed strong dependencies on certain model constant values, especially those in the dissipation equation. The present study demonstrated that, by using a modified set of closure coefficient values, very well correlated computational fluid dynamics predictions were possible. The findings from this study simply reiterate a 20-year-old conclusion by Stephen Pope that the closure coefficients for a model are not static and universal but instead are dynamic and must be calibrated for specific flow situations.
