Multidisciplinary Analysis of the Impact of Blade Geometric Deviations on Compressor Performance Based on Fluid-Solid Grid Coordinated Deformation

Abstract

Abstract Machining errors are widely presented in the blade manufacturing process, and their influence on compressor performance cannot be overlooked. Accurate assessment of this influence is of great significance. In this study, an analytical framework is proposed to quantify the impact of radial machining errors on the aerodynamic and structural performance of blades. This framework integrates fluid-solid grid coordinated deformation methods with Backpropagation Neural Network surrogate model technology. NASA Rotor 67 is utilized as a case study to quantify the uncertainty associated with radial machining errors. The results indicate that, compared to the prototype, the relative standard deviation of isentropic efficiency, pressure ratio, and mass flow rate for the compressor are 0.278%, 0.192%, and 0.138%, respectively, while the relative standard deviation of the maximum von Mises stress on the blade reaches 2.85%. Isentropic efficiency, pressure ratio, and mass flow rate exhibit approximate monotonic positive correlations with each other, whereas all three parameters demonstrate a monotonic negative correlation with the maximum von Mises stress. Precision control of leading edge thickness is advantageous for enhancing isentropic efficiency and reducing von Mises stress levels at the blade root region, and meticulous attention should be given to the machining accuracy of leading edge thickness.