Design optimization of transonic compressor rotor using CFD and genetic algorithm

The paper describes a new optimization strategy for computationally expensive design optimization problems of turbomachinery, combined with design of experiment (DOE), response surface models (RSM), genetic algorithm (GA) and a 3-D Navier-Stokes solver. Data points for response evaluations were selected by Latin hypercube design (LHD) and 3-dimensional Navier-Stokes analysis was carried out at these sample points. The quadratic response surface model was used to approximate the relationships between the design variables and flow parameters. The genetic algorithm was applied to the response surface model to perform global optimization to obtain the optimum design. The above method was applied to the optimization design of NASA rotor37. The object was to maximize the adiabatic efficiency. An optimum leading edge line was found which produced a new 3-dimensional blade combined with sweep and composite bowing. As a result of this optimization, the adiabatic efficiency was successfully increased by 1.58%. It was found that the strategy of this paper provides a reliable design optimization method for turbomachinery blades at reasonable computing cost.