Leading-edge flow prediction in Wells turbine under the influence of tip leakage flows

Abstract

Monitoring of aerodynamic parameters of the blade helps to enhance the operating capabilities of the Wells turbine. In this study, a few discrete pressure points were used to estimate the pressure patterns by fitting the exact potential-flow solution for flow over a parabola. The sectional aerodynamics was assessed by the leading-edge flow sensing (LEFS) algorithm. A characteristic parameter was employed to deduce leading-edge flow status. Moreover, the influence of rotor speeds and tip gaps on the vortex boundary was discussed in terms of the Lagrangian frame. For the rotor speed larger than 1000 rpm at the incipient stall point, there is no boundary layer separation at the suction side of the blade tip leading edge. At the same rotor speed, a large tip gap reduces the axial shear of the suction flows and the axial stretching of the tip leakage vortex, which helps to enhance the interaction time and strength of the leakage vortex and the suction flows. For the Wells turbine with attached flows, the LEFS algorithm can accurately evaluate the pressure distribution and suction parameters near the leading edge. The LEFS-derived dimensionless parameter can act as an equivalent angle of attack under different tip gaps, providing the possibility for stall warning of Wells turbines.