Aerodynamic optimization of a transonic axial compressor with a casing groove combined with tip injection

A multiobjective optimization to enhance the stall margin and peak adiabatic efficiency of an axial compressor with a casing groove combined with injection was performed in this work. The geometry of the casing groove was optimized using a hybrid multiobjective evolutionary algorithm coupled with a surrogate model. Reynolds-averaged Navier-Stokes equations with a k-epsilon turbulence model were discretized by finite volume approximations and solved on hexahedral grids to analyze the flow in the compressor. The stall margin and peak adiabatic efficiency were selected as objective functions with three design variables related to the geometry of the casing groove. Latin hypercube sampling was applied as a design-of-experiment technique to generate 25 design points within the design space. Response surface approximation models as the surrogate models for the objectives were constructed based on the objective function values at the design points. A fast nondominated sorting genetic algorithm for the local search coupled with the surrogate models was applied to determine the global Pareto-optimal solutions. The tradeoff between the two objectives was determined and is described with respect to the Pareto-optimal solutions. The multiobjective optimization results showed that the stall margin and peak adiabatic efficiency of the axial compressor with an optimized casing groove combined with injection were simultaneously improved compared to the compressor with a smooth casing.