Multi-condition Robust Optimization Design of High Subsonic Cascades Considering the Uncertain Changes of Inlet Flow Condition

To achieve the design of high-performance and highly robust subsonic compressor cascades across various Reynolds numbers, this study investigates the impact of inlet flow fluctuations on cascade performance at different Reynolds numbers, followed by a rigorous data-driven optimization algorithm for robust optimization. The impact of fluctuation in inlet Mach number and incidence angle on the aerodynamic performance of the cascade is investigated using the two-dimensional normal distribution variable generation method within a non-intrusive polynomial chaos framework. The total pressure loss of the cascade increases with the decrease in Reynolds number, and the influence of inlet flow condition fluctuation becomes more pronounced. The sensitivity of the static pressure ratio to inlet flow fluctuation remains essentially unchanged with variations in Reynolds number. After robust optimization, compared with the prototype, the mean value of total pressure loss is reduced by 10.40% and the standard variance by 28.82%. The region with high entropy fluctuation decreases obviously.