Assessment of advanced RANS turbulence models for prediction of complex flows in compressors

Abstract

Reynolds-Averaged Navier-Stokes (RANS) Computational Fluid Dynamics (CFD) has been widely used in compressor design and analysis. However, reasonable prediction of compressor flow and its impact on compressor performance remains challenging. In this study, Menter’s Shear Stress Transport (SST) model and its variants, as well as the ω-based Reynolds stress model (Stress-BSL) are assessed. For a single rotor (Rotor 67), under the peak efficiency operating condition, all studied turbulence models predict its performance with reasonable accuracy; under the off-design conditions, SST with Helicity correction (SST-Helicity) shows superiority in predicting the effect of flow on the spanwise distribution of aerodynamic parameters. For Darmstadt’s 1.5-stage transonic axial compressor, SST-Helicity outperforms SST, SST with the Quadratic Constitutive Relation (SST-QCR) and Stress-BSL in predicting the performance as well as the spanwise distribution of aerodynamic parameters. At the design rotating speed, the stall margin given by SST-Helicity (20.90%) is the closest to the experimental measurement (24.81%), which is more than twice that by SST (8.71%) and 1.5 times that by SST-QCR (14.14%). This paper demonstrates that SST-Helicity model, together with a good quality and sufficiently refined grid, can capture the compressor flow features with reasonable accuracy, which results in a credible prediction of compressor performance and stage matching.