Improved Prediction of Pump Performance Through the Rotation–Curvature Correction—An Experimental and Numerical Study of a Low-Specific-Speed Helico-Axial Compression Cell in Series

Abstract

Within turbomachines, turbulence production and redistribution are affected by system rotation and streamline curvature. However, the most frequently used turbulence models do not account for these effects. In the present paper, we calibrate a rotation–curvature correction to the shear stress transport (SST) turbulence model to improve the accuracy of pump performance predictions through computational fluid dynamics (CFD) for a wide range of relative flow rates. The new formulation was achieved through comparison of experimental and numerical results obtained for a low-specific-speed (nondimensional specific speed ≈ 0.7) helico-axial compression cell in series. CFD results revealed secondary flows and strong rotor–stator interactions. Steady-state simulations with the standard SST turbulence model were unable to accurately predict pump performance because of such inherently unsteady features. Unsteady simulations improved the predicted performance, but the head coefficient was up to 10% higher than test results at part-load operation. Through calibration of a rotation–curvature correction, the error in the predicted head coefficient was essentially eliminated for relative flow rates above 50% relative flow. Below 47% relative flow, a rotating stall-phenomenon was identified. The stall cell propagated at a rate of 0.4 times the impeller angular frequency, and we identified a propagation mechanism related to a circumferential variation in impeller tip leakage flow (TLF) rate. The presented turbulence model formulation can improve performance predictions in turbomachinery applications where leakage flows are significant, and forms a basis for future work on extended modeling of increasingly complex operating conditions.