Towards Accurate Vortex Separation Simulations with RANS Using Improved k-kL Turbulence Model

Abstract

In this study, we present our improved RANS results of the missile aerodynamic flow computation involving leading edge vortex separation. We have used our in-house tailored version of the open source finite volume solver FlowPsi. An ongoing study in the NATO STO Applied Vehicle Technologies Panel (AVT-316) has revealed that a highly maneuverable missile configuration (LK6E2) shows unusual rolling moment characteristics due to the vortex–surface interactions occurring during wing leading edge separation of vortices. We show the performance of the recently developed k-kL turbulence model for this test problem. This turbulence model is shown to have superior capabilities compared to other widely used turbulence models, such as Spalart–Allmaras and shear stress transport. With the k-kL turbulence model, it is possible to achieve more realistic computational results that agree better with the physical data. In addition, we propose improvements to this turbulence model to achieve even better predictions of rolling moment behavior. Modifications based on turbulence production terms in the k-kL turbulence model significantly improved the predicted rolling moment coefficient, in terms of accuracy and uncertainty.