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A reliable and efficient aerodynamic design optimization tool using evolutionary algorithm has been developed for transonic compressor blades. A real-coded adaptive-range genetic algorithm is used to improve efficiency and robustness in design optimization. To represent flow fields accurately and produce reliable designs, three-dimensional Navier-Stokes computation is used for aerodynamic analysis. To ensure feasibility of the present method, aerodynamic redesign of NASA rotor67 is demonstrated. Entropy production is considered as the objective function to be minimized. The computation is parallelized on the SGI ORIGIN2000 cluster at Institute of Fluid Science, Tohoku University, by distributing flow analyses of design candidates to 64 processing elements. The present method successfully obtained a design that reduced entropy production by more than 19% compared with the rotor67 while satisfying constraints on the mass flow rate and the pressure ratio. The use of the present tool for turbomachinery blade design is demonstrated to allow designers to achieve higher aerodynamic efficiency, while shortening design cycle and reducing design costs significantly.

A new constraint-handling technique based on Pareto-optimality concept is proposed for evolutionary algorithms to efficiently deal with multiobjective multi-constraint design optimization problems. The essence of the proposed method is to apply non-dominance concept based on constraint function values to infeasible designs and to apply nondominance concept based on objective function values to feasible designs. The proposed technique does not need any constants to be tuned as the proposed technique does not use weighted-sum of constraints. First, the proposed approach is demonstrated to be remarkably more robust than traditional constraint-handling techniques through the optimal design of a welded beam and conceptual design optimization of a two-stage-to-orbit space plane. Next, high-fidelity aerodynamic design optimization of an axial compressor blade design is demonstrated.

In this paper, aerodynamic blade design optimization for a transonic axial compressor has demonstrated by using an evolutionary-algorithm-based high-fidelity design optimization tool. The present method uses a three-dimensional Navier-Stokes solver named TRAF3D for aerodynamic analysis to represent flow fields accurately and the realcoded ARGA for efficient and robust design optimization. The present method successfully obtained a design that reduced entropy production by more than 16% compared with the rotor67 while satisfying constraints on the mass flow rate and the pressure ratio. This study gave some insights into design optimization of a swept and leaned rotor blade for transonic axial compressors.

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