Prediction of acoustic resonance in a multistage high-speed axial compressor

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Economic and regulatory requirements for high operational flexibility of jet engines and power plants lead to more frequent off-design operation of turbomachinery components. Regarding operating stability, the compressor constitutes the most critical and challenging component in these turbomachines. Besides the well-known and intensely investigated aerodynamic instabilities of surge, rotating stall, and rotating instability, high pressure fluctuations have been identified as acoustic resonance in high-speed and high-pressure axial compressors at specific off-design operating points. Recent research shows that acoustic resonance can excite mechanical vibrations, which might result in severe blade damage or immediately fatal structural failure. In addition, research shows that acoustic resonances can shift the stability limit to higher mass flow rates by triggering rotating stall and surge. As several industrial producers of turbomachinery have experienced acoustic resonances there is considerable need for the understanding and characterization on the physical mechanism of this phenomenon for future design processes. First approaches by the applicant and his coworkers have led to two models to predict and characterize acoustic resonance, but data of these phenomena have rarely been reported in open literature. Therefore, validation of these models is necessary. To this end, improved physical understanding of the formation mechanism of the standing waves and of the excitation mechanisms is essential. The objective of the proposed project is to give further insights into the excitation mechanism and the resonance conditions in multi-stage axial compressors. Extensive simultaneous measurements of the tip leakage flow and the resonant acoustic field are carried out for the first time in a high-speed multistage axial compressor, which approximates realistic machine conditions. Based on the highly accurate measurements and numerical simulations, validation and calibration of the prediction models will be performed, which will lead to an approach to predict the occurrence of acoustic resonance.