Turbine Cascade Profile Loss Sensitivity to Incoming Wake Parameters: Effects of Reduced Frequency, Wake Momentum Defect and Axial Gap

Abstract

Abstract In the present work the profile losses of a highly loaded low pressure turbine cascade, operating under realistic unsteady conditions, have been measured for different incoming wake parameters. A moving bar system has been used for wake generation, allowing the variation of bar diameter, bar count and axial gap between the bars and the cascade leading edge. The overall test matrix spans three different bar diameters, three different reduced frequencies and two axial gaps, for a total of 18 different conditions tested. For each of them, the time-dependent cascade inflow has been characterized by means of phase-locked hot-wire measurements in order to determine the effects of the wake parameter modification on the turbulence intensity peak and on the incoming wake momentum deficit, that are well known to affect the generation of losses in the downstream cascade. The procedure recently developed by the authors based on the simultaneous acquisition of the signals of two kiel probes, located upstream and downstream of the cascade, has been used to accurately quantify the profile losses for each condition, identifying the contribution due to the wake bowing, tilting and dilation process into the cascade channel and that due to the wake-boundary layer interaction. Additionally, Proper Orthogonal Decomposition (POD) has been applied to the ensemble data matrix constructed from the loss coefficient distributions in the pitchwise direction, measured for the different conditions, with the aim of highlighting the loss trend vs the design space parameter variation. The POD modes obtained from the cross-correlation matrix provide a direct information on the flow region where losses are prevalently produced, while the corresponding POD coefficients give the weight of each parameter in the loss generation. The paper shows the potentiality of this procedure in providing a rapid identification of the main causes of losses, and the dominant parameter affecting the process of loss generation.