Akira Oyama

TRANSONIC AXIAL-FLOW BLADE SHAPE OPTIMIZATION USING EVOLUTIONARY ALGORITHM AND THREE-DIMENSIONAL NAVIER-STOKES SOLVER

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.

Real-Coded Adaptive Range Genetic Algorithm Applied to Transonic Wing Optimization

Real-coded Adaptive Range Genetic Algorithms (ARGAs) have been applied to a practical three-dimensional shape optimization for aerodynamic design of an aircraft wing. The real-coded ARGAs possess both advantages of the binary-coded ARGAs and the floating-point representation to overcome the problems of having a large search space that requires continuous sampling. The results confirm that the real-coded ARGAs consistently find better solutions than the conventional real-coded Genetic Algorithms do.

Transonic Wing Optimization Using Genetic Algorithm

A Genetic Algorithm (GA) has been applied to optimize a transonic wing shape for generic transport aircraft. A threedimensional compressible Navier-Stokes (N-S) solver is used to evaluate aerodynamic performance. The N-S evaluation is parallelized on Numerical Wind Tunnel (NWT) at National Aerospace Laboratory in Japan, a parallel vector machine with 166 processing elements. Designed wings show a tradeoff between an increase of the airfoil thickness driven by a structural constraint and a reduction of the wave drag produced by a shock wave. The present result indicates that GA has found a best feasible solution in the given design constraints.

Wing design using real-coded adaptive range genetic algorithm

Real-coded adaptive range genetic algorithms (ARGAs) have been developed. The real-coded ARGAs possess both advantages of the binary-coded ARGAs and the use of the floating point representation to overcome the problems of having a large search space that requires continuous sampling. First, the efficiency and the robustness of the proposed approach have been demonstrated by using a typical test function. Then the proposed approach has been applied to an aerodynamic airfoil shape optimization problem. The results confirm that the real-coded ARGAs consistently find better solutions than the conventional real-coded GAs do. The design result is considered to be the global optimal and thus ensures the feasibility of the real-coded ARGAs in aerodynamic designs.

Euler/Navier-Stokes Optimization of Supersonic Wing Design Based on Evolutionary Algorithm

This paper presents aerodynamic shape optimization of a supersonic wing for supersonic civil transportation (SST) using an Evolutionary Algorithm (EA) coupled with an Euler/Navier-Stokes code. To overcome enormous computational time necessary for the design, aerodynamic evaluations are parallelized on Numerical Wind Tunnel (NWT) at National Aerospace Laboratory, a parallel vector machine with 166 processing elements. Parallelization of function evaluations in EA is straightforward and its performance is extremely good since most of computational time is used by flow computations. The design result indicates that the present EA successfully minimizes both the induced drag and the volume wave drag in the given design space.

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

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.

Transonic Wing Shape Optimization Based on Evolutionary Algorithms

A practical three-dimensional shape optimization for aerodynamic design of a transonic wing has been performed using Evolutionary Algorithms (EAs). Because EAs coupled with aerodynamic function evaluations require enormous computational time, Numerical Wind Tunnel (NWT) located at National Aerospace Laboratory in Japan has been utilized based on the simple master-slave concept. Parallel processing makes EAs a very promising approach for practical aerodynamic design.