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目的:1.比较并改善翼型参数化方法,获得设计变量少、拟合精度高的参数化方法;2.在参数化的基础上利用数值模拟的方法获取翼型流场参数,优化并获得特定条件下升阻比最大的翼型。创新点:1.通过与多项式拟合方法的对比证明了类别/形状函数转换(CST)法在翼型拟合方面的优越性,并通过调整控制点分布,在不增加设计变量的基础上改善了CST方法;2.通过建立响应面模型,利用多岛遗传算法与非线性序列二次规划法相结合的方式获得了更好的翼型优化效果。方法:1.利用修饰后的CST法对翼型进行参数化拟合与设计,并通过与二项式拟合法比较来验证其优越性;2.通过数值方法对翼型周围流场进行计算并与实验结果对比,获得精确计算气动参数的仿真条件;3.通过拉丁超立方采样获得设计变量,建立设计变量与翼型升阻比之间的响应面模型,通过多岛遗传算法与非线性序列二次规划法的结合和优化,得到一定条件下升阻比最大的翼型。结论:1.CST法是一种优秀的参数化方法,本文的优化改善了形状函数控制点选取法则,使其对翼型头部和尾部的描述更加精确;与多项式相比,CST法可以通过更少的设计变量得到更高的拟合精度。2.基于多岛遗传算法的非线性序列二次规划法在本文中用以优化翼型使其具有更高升阻比。优化前后翼型的比较显示,两种优化方法的结合可以得到比单独使用各优化方法更好的结果。
To compare and improve the airfoil parameterization method to obtain a parameterized method with less design variables and high fitting accuracy; 2. To obtain and obtain the airfoil flow field parameters by numerical simulation based on the parameterization Under the specific conditions, the ratio of lift to drag ratio of the largest airfoil. Innovative points: 1. By comparing with the polynomial fitting method, the superiority of the CST method in airfoil fitting is proved, and the control point distribution can be adjusted to improve without increasing the design variables The CST method is established.2. The optimization of airfoil optimization is achieved through the establishment of response surface model and the combination of multi-island genetic algorithm and nonlinear quadratic programming. Methods: 1. The modified CST method was used to parameterize and design the airfoil, and its superiority was verified by comparison with the binomial fitting method.2. The numerical simulation of the flow field around the airfoil Compared with the experimental results, the simulation conditions for accurate calculation of aerodynamic parameters were obtained.3. Design variables were obtained by Latin hypercube sampling, and the response surface model between design variables and lift-drag ratio of airfoil was established. By using multi-island genetic algorithm and nonlinear sequence The combination of quadratic programming and optimization, under certain conditions, get the most resistance than the airfoil. Conclusion: 1.CST method is an excellent parameterization method, the optimization of this paper improves the selection rules of shape function control points, which makes the description of airfoil head and tail more accurate. Compared with the polynomial, CST method can pass Fewer design variables get better fitting accuracy. 2. Nonlinear sequence quadratic programming method based on multi-island genetic algorithm is used in this paper to optimize the airfoil to have a higher lift-drag ratio. The comparison of airfoil before and after optimization shows that the combination of the two optimization methods can get better results than using each optimization method alone.