Robust design and tolerancing of compressor blades

Abstract

Variations in the geometry of compressor blades can be introduced by variability in the manufacturing process or by in-service erosion. Recent research efforts have focused on characterizing the impacts of this geometric variability on turbomachinery performance and designing blade geometries whose performance is robust to this variability. Relatively little work has been done to specify the appropriate level of variability by designing the manufacturing tolerances. This thesis presents new approaches for optimizing tolerances that can be applied to compliment existing geometry optimization techniques. Building upon previous research, a Gaussian random field model of manufacturing variability is developed and used to estimate the statistical performance impacts of geometric variability on compressor blade performance. Flow mechanisms that deteriorate the mean performance in the presence of geometric variability are analyzed for design and off-design conditions. A probabilistic, gradient-based optimization framework is presented and applied to optimize the tolerances of compressor blades, as well as to optimize the tolerances and blade geometry simultaneously. The effectiveness of simultaneous optimization of the geometry and manufacturing tolerances is compared to a sequential procedure where the nominal blade geometry is optimized first, followed by the tolerances. Single-point optimization, where the performance at a single flow incidence is optimized, is found to produce geometries that are not robust to manufacturing variations. Adopting a multi-point design strategy results in blades that are robust to both variations in the geometry and incidence, allowing a sequential design strategy to be used.