Aerodynamic Shape Optimization of a Stator

In this paper, a numerical study conducted on a compressor stator is presented. The results are compared with existing literature and experimental data. For this purpose, a grid refinement study for the baseline geometry at the design condition with an unstructured mesh family is performed. The total pressure loss coefficient and the exit flow angle are compared against the experimental data. Moreover, the corner separation on the suction side is compared against the experimental data. Subsequently, a multi-objective optimization is performed on the baseline geometry to improve two objectives: flow deviation angle and total pressure loss coefficient at the stator exit. For the CAD-based optimization, a parametric model with 55 design variables is built in the parametric design platform CAESES. This parametric model is fitted to the baseline geometry to start the optimization process. The Flow360 compressible flow solver is employed for the steady RANS analysis, utilizing the Spalart-Allmaras turbulence model. The surrogate-assisted multi-objective genetic algorithm (MOGA) is employed for the optimization. Non-uniform profile boundary conditions, obtained from experimental tests, are applied at the inlet. The results for the baseline simulation at the design condition demonstrate strong agreement with both experimental and numerical findings. In the optimal Pareto front solutions, both objectives exhibit improvement. The optimal solution is compared with previously published results in literature.