Abstract
Flows in compressors are extremely complex with various scales. Small-scale turbulence, middle-scale rotor–stator interaction (RSI), large-scale corner separation, and tip leakage flow should all be considered in the simulation of compressors. Recently, a new hybrid Reynolds-averaged Navier–Stokes-large eddy simulation (RANS-LES) strategy that modifies the turbulent viscosity equation based on the Kolmogorov energy spectrum, termed the grid-adaptive simulation (GAS) method, is proposed by our group to achieve high accuracy simulation using different grid resolutions. In this study, the GAS method with the shear stress transport (SST) turbulence model is employed to simulate the RSI just with RANS-like grid resolution in a single-stage transonic compressor TUDa-GLR open test case. Compared with experiments and other simulation methods (including RANS and delayed detached eddy simulation (DDES) methods), results show that the GAS method can significantly improve the prediction accuracy for stall margin and radial distribution of flow parameters. Then, the effect of RSI on the secondary flow structures is analyzed based on the unsteady flow field simulated by the GAS method. Results show that the incorrect prediction of rotor tip leakage vortex breakdown and the underestimation of mixing losses in the tip region of the rotor are blamed for the high prediction deviation of RANS. An intuitive total pressure fluctuation caused by wakes is observed in the stator inlet. The particle tracking shows that the wake from the suction surface of the rotor has a strong trend to transport into the tip region of the stator. Spectral proper orthogonal decomposition (SPOD) is also utilized. Unsteady temporal–spatial structures induced by local unsteadiness and RSI are distinguished by SPOD, which includes the reverse flow in the tip region of the rotor and the pressure wave generated from RSI. SPOD also found that the separation of the stator on the suction side exhibits an unsteady fluctuation with a frequency of 1.6 blade passing frequency (BPF).