基于遗传算法的翼型性能优化-流体机械及工程专业论文.docxVIP

II II Abstract Aerofoil is widely used in fluid machines, and it has a decisive impact on the aerodynamic characteristics of fluid machines. Similarly, acoustic noise has been a important index of the product’s performance. So this paper sets both of them as the researching target. Surrogate model which is created with experiment design methods and approximation approaches is appeared along with the rising of Multidiscipline Design Optimization (MDO). Optimization methods is also developed fast with the optimization algorithm and computer’s development, especially the development of Genetic Algorithm is greatly improved the efficiency of the optimization methods. We integrate the surrogate model and genetic algorithm to create the optimize system of aerofoil. Taking CW-1 as an example, we get a well result. The particular works contain three aspects: First, use analytic function to describe the geometry of aerofoil and set the parameters which control the geometry of aerofoil. Develop a parameterized modeling program to reduce the workload. And then select the appropriate Experiment Design and the worksheet. Second, according to the Experiment Design Worksheet, the aerodynamic performance and acoustic noise of the aerofoil are simulated by the commercial CFD software Fluent, and get the swatches. The coefficients of polynomial are gained by the Partial Least Square Method (PLS). And then create the Response Surface Model (RSM) with the Weight Coefficient Method. Finally, taking the Response Surface Model as Estimate Function, the optimized aerofoil and the target value are gotten by the Genetic Algorithm. The optimized aerodynamic performance and acoustic noise are simulated by FLUENT. Contrasting the optimized performance to the origin ones, we can show the effect of optimization, and compared with the result of optimization, can appraise the effect of surrogate model and optimization algorithm. Key words: Aerofoil Design, Performance Optimization, Genetic Algorit