High-Fidelity Swept and Leaned Rotor Blade Design Optimization Using Evolutionary Algorithm

Abstract

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. * NRC Research Associate, Turbomachinery and Propulsion System Division, Member AIAA. Located at Ohio Aerospace Institute ICOMP, 22800 Cedar Point Rd., Cleveland, OH 44142, USA = Senior Scientist, Turbomachinery and Propulsion System Division, Associate Fellow AIAA # Professor, Institute of Fluid Science, Associate Fellow AIAA INTRODUCTION Compressor is a critical part in developing a new aeroengine because a small improvement in efficiency can result in huge savings in yearly fuel costs of an aircraft fleet. Although today’s aeroengine compressors have achieved very high performance, there is still an increasing demand for new compressor designs to achieve an even higher performance. One approach to improve further compressor performance is to develop a computer-based design system using a high-fidelity flow solver and a numerical design optimization method. Currently, the state-of-the-art blade design systems depend on the axisymmetric through-flow method in the initial stage of the blade shape design. High-fidelity Computational Fluid Dynamics (CFD) such as the three-dimensional Navier-Stokes (N-S) solver may be also used, but often just for validation purposes or for evaluating losses coefficient to be used for the next through-flow calculation. Then, a blade design is manually optimized by trial and error basis by design experts by relying on their experiences and intuition. Such conventional approach, however, has nearly reached its limits. The first reason is that the though-flow method cannot capture complicated flow structure inside a compressor such as secondary flow, shock/boundary layer interaction. Another reason is that a blade design for a compressor is very difficult to be solved by trial and error basis since it involves a large number of design parameters, multimodal and nonlinear objectives and constraints such as efficiency, total pressure ratio, and mass flow rate. Therefore, there is a demand for a revolutionary approach using three-dimensional N-S computations and an efficient and robust numerical design optimization method. In [1], the authors successfully developed a highfidelity numerical optimization tool for aerodynamic transonic axial-flow blade designs. In this tool, an evolutionary algorithm named real-coded adaptiverange genetic algorithm was adopted for efficient and robust design optimization. A three-dimensional N-S solver is used for aerodynamic analysis. To overcome expected difficulty in computational time, the computation was parallelized and performed on SGI ORIGIN 2000 clusters. Aerodynamic redesign of the NASA rotor 67 has demonstrated superiority of the method over the conventional design approach.