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论文:2012,Vol:30,Issue(3):395-401 |
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引用本文： |
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李沛峰, 张彬乾, 陈迎春. 基于响应面和遗传算法的翼型优化设计方法研究[J]. 西北工业大学 |
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Li Peifeng, Zhang Binqian, Chen Yinchun. An Effective Transonic Airfoil Optimization Method Using Response Surface Model (RSM)[J]. Northwestern polytechnical university |
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| 基于响应面和遗传算法的翼型优化设计方法研究 |
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| 李沛峰1, 张彬乾1, 陈迎春2 |
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1. 西北工业大学 航空学院,陕西 西安 710072;
2. 上海飞机设计研究所, 上海 200232 |
| 摘要: |
| 文章针对气动优化设计中高效率和高精度的矛盾,综合响应面方法和遗传算法的优点和不足,采用多项式响应面模型代替原始遗传算法中计算量庞大的目标特性分析模型,建立了多项式响应面模型和遗传算法相结合的翼型优化设计方法,在采用N-S方程进行气动求解达到较高的精度情况下,求解次数显著减少,优化效率大大提高。研究了设计变量对优化设计效率的影响,文中方法在较少设计变量、较少N-S方程求解次数情况下,即可得到满意的优化设计结果。设计区间对响应面模型精度的影响显著,合适的设计区间既可保证模型精度,减少响应面预测结果和CFD计算结果的偏差,又可获得最佳优化结果。文中方法适用于翼型的单设计点和多设计点优化设计问题,具有原理简单、适应面宽、快速易行,且精度高等特点,可广泛应用于工程设计问题中。 |
| 关键词:
响应面
遗传算法
翼型设计
优化设计方法
计算流体力学
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| An Effective Transonic Airfoil Optimization Method Using Response Surface Model (RSM) |
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| Li Peifeng1, Zhang Binqian1, Chen Yinchun2 |
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1. College of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China;
2. Shanghai Aircraft Design and Research Institute, Shanghai 200232, China |
| Abstract: |
| We try to find a highly efficient and highly accurate method for optimizing transonic airfoil with fewer de-sign variables and proper design space. Therefore we use the RSM and the genetic algorithm(GA) to do the optimi-zation. Sections 1 through 4 of the full paper explain the airfoil optimization method mentioned in the title,whichwe believe is effective. Their core consists of: (1) we use the high-fidelity N-S equation solutions to construct thequadratic polynomial response surfaces with only eight design variables and reduced computational complexity; (2)with the help of response surface approximations,we use the GA to find the optimal design of an airfoil; (3) westudy the design space with design variables given in Tables 2 and 3 and conclude that the smaller design space islikely to obtain the locally optimal solutions with high accuracy and that the larger design space may reduce the ac-curacy of RSM,thus leading to big differences from the N-S equation solutions; (4) we use the eight design varia-bles and the design space between-0. 004 and 0. 004 for each of the design variables; the single-point and two-pointoptimal design results, presented in Tables 6 and 8 and Figs. 2, 4 and 5, and their analysis show preliminarily thatour transonic airfoil optimization method is indeed accurate and efficient and has less computational complexity. Ac-cording to sections 1 through 4,our method has the following strong points: (1) our method is both efficient andaccurate in optimizing a transonic airfoil; (2) it can be widely applied in engineering practice. |
| Key words:
airfoils
approximation algorithms
computational complexity
computational fluid dynamics
design
drag
efficiency
genetic algorithms
mathematical models
Navier Stokes equations
optimization
polynomials
pressure distributions
transonic aerodynamics
two dimensional;response surface mod-el (RSM)
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| 收稿日期: 2011-06-12
修回日期:
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| DOI: |
| 通讯作者:
Email： |
| 作者简介: 李沛峰(1982-),西北工业大学博士研究生,主要从事飞行器设计及空气动力学研究。
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参考文献: |
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