Transonic Axial-Flow Blade Shape Optimization Using Evolutionary Algorithm and Three-Dimensional Navier-Stoke Solver

Abstract

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 Generic Framework for the Design Optimisation of Multidisciplinary UAV Intelligent Systems Using Evolutionary Computing

“…An attractive feature of EAs is that they evaluate multiple populations of points and are capable of finding a number of solutions in a Pareto set. EAs have been successfully applied to different aircraft, wing, aerofoil and rotor blade design and optimization problems [9][10][11][12] . One major drawback of EAs is that they are slow in converging, as they require a large number of function evaluations to find optimal solutions and have poor performance with increasing number of variables.…”

Surrogate Based Optimization Techniques for Aerodynamic Design of Turbomachinery

“…Oyama et al [63] reported blade profile modification with the help of B-spline curve of NASA rotor 67 to increase adiabatic efficiency by 2%. Chen et al [69] optimized camber line, thickness distribution and stacking line by polynomial curve to define compressor blade and gained 1.73% improvement of adiabatic efficiency.…”

Aerodynamic optimization of turbomachinery blades using evolutionary methods and ANN-based surrogate models

“…For this reason, heuristic/evolutionary global algorithms such as Genetic Algorithm (GA) and Simulated Annealing (SA), although more computation intensive compared with gradient-based methods, are used to ensure reaching close to the global minimum. These algorithms have been recently applied in turbomachinery design problems; examples of such algorithms are given in (Dennis et al 1999;Wang and Damodaran 2000;Oyama et al 2002).…”

“…The optimization scheme required from 220 to 675 calls to the flow analysis code. Oyama et al (2002) worked on 3D blade shape optimization and included the mass flow rate and pressure ratio as constraints in the objective function.…”