Uncertainty quantification of geometric and flow variables affecting the performance of a transonic axial compressor

Manufacturing and operational uncertainties always lead to significant variability in compressor performance. In this work, the uncertainties inherent in a transonic axial compressor are quantified to determine their effect on the performance. These uncertainties include the effects of inlet total pressure, inlet turbulence intensity, blade surface roughness, endwall surface roughness, blade thickness and tip clearance size. A validated roughness prediction model and a tip clearance loss model in conjunction with a 3D Reynolds-Averaged Navier-Stokes (RANS) solver are utilized to simulate these uncertainties and quantify their effect on the adiabatic efficiency, surge margin and choked mass flow of the compressor. The sensitivity analysis method is employed to determine which parameters play the most significant roles in influencing the overall performance of the compressor. To propagate these uncertainties, the non-instrusive polynomial chaos expansion (PCE) algorithm is used in this paper. The uncertainties considered are ranked in order of their effect on compressor performance and the probability distributions of compressor performance are predicted according to the built UQ platform.