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机翼减阻设计是民用客机气动设计的关键,本文提出了一种基于非均匀B样条曲线曲面造型技术和改进的粒子群算法的新型优化方法。前者用来描述机翼的外形,具有计算量小的优点,在优化过程中不仅具有良好的局部操控性,又能保证整体外形的光顺性;后者作为一种新兴的智能化优化方法,具有简单易行、收敛速度快、全局搜索能力强等优点,同时又适用于多目标优化问题。研究结果表明:三次非均匀B样条曲线曲面能够方便地使用较少的控制顶点较为精确地描述翼型及机翼的外形,在此基础上利用改进的粒子群算法进行的多目标气动优化设计,优化效率得到了提升。在效率因子本身较高的初始外形基础上,最终外形的气动性能也取得了较大幅度的提高。
The drag reduction design of the airfoil is the key to the aerodynamic design of civil passenger aircraft. In this paper, a new optimization method based on non-uniform B-spline curve and surface modeling technology and an improved Particle Swarm Optimization (PSO) algorithm is proposed. The former is used to describe the shape of the wing, with the advantages of small amount of computation, not only has good local controllability in the optimization process, but also ensures the smooth appearance of the overall shape; the latter, as a new intelligent optimization method, Has the advantages of simple and easy to operate, fast convergence, strong global search capability and the like, and is also suitable for multi-objective optimization problems. The results show that the cubic non-uniform B-spline curves and surfaces can conveniently describe the shape of airfoils and wings conveniently with fewer control vertices. Based on this, the multi-objective aerodynamic optimization design using improved Particle Swarm Optimization , Optimization efficiency has been improved. Based on the initial shape of the efficiency factor itself, the aerodynamic performance of the final shape has also been greatly improved.