A study was conducted to demonstrate the application of a hybrid multiobjective evolutionary algorithm coupled with the Kriging (KRG) model to obtain a global Pareto-optimal front for the design of circumferential casing grooves in an axial compressor with NASA Rotor 37. The existing multiobjective optimization was motivated to provide an efficient tool for the design of an axial compressor with circumferential casing groove treatment. It was expected for designers to meet their design requirements with regard to the stall margin (SM) and adiabatic efficiency from the Pareto-optimal designs (PODs) obtained in the study. Numerical solutions at the selected design points were obtained by three-dimensional RANS analysis. The shape of the grooves was optimized by considering width and depth as design variables to improve the SM and the peak adiabatic efficiency.
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