Modification of Shear Stress Transport Turbulence Model Using Helicity for Predicting Corner Separation Flow in a Linear Compressor Cascade

Abstract

Abstract Three-dimensional corner separation significantly affects compressor performance, but turbulence models struggle to predict it accurately. This paper assesses the capability of the original shear stress transport (SST) turbulence model to predict the corner separation in a linear highly loaded prescribed velocity distribution (PVD) compressor cascade. Modifications for streamline curvature, Menter’s production limiter, and the Kato-Launder production term are examined. Comparisons with experimental data show that the original SST model and the SST model with different modifications can predict the corner flow well at an incidence angle of −7 deg, where the corner separation is small. However, all the models overpredict the extent of the flow separation when the corner separation is larger, at an incidence angle of 0 deg. The SST model is then modified using the helicity to take account of the energy backscatter, which previous studies have shown to be important in the corner separation regions of compressors. A Reynolds stress model (RSM) is also used for comparison. By comparing the numerical results with experiments and RSM results, it can be concluded that sensitizing the SST model to helicity can greatly improve the predictive accuracy for simulating the corner separation flow. The accuracy is quite competitive with the RSM, whereas in terms of computational cost and robustness it is superior to the RSM.