首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于高斯过程回归和遗传算法的翼型优化设计
引用本文:常林森,张倩莹,郭雪岩.基于高斯过程回归和遗传算法的翼型优化设计[J].航空动力学报,2021,36(11):2306-2316.
作者姓名:常林森  张倩莹  郭雪岩
作者单位:上海理工大学能源与动力工程学院,上海200093;上海理工大学上海市动力工程多相流动与传热重点实验室,上海200093
摘    要:针对高升阻比风力机翼型前缘曲率半径较大的问题,传统的翼型参数化方法前缘控制能力不足,且基于面元法XFOIL预测精度差的问题,利用增强类函数/形函数转换(CST)参数化方法控制翼型的形状变化、拉丁超立方实验设计、计算流体力学(CFD)流场计算模块、高斯过程回归模型和遗传算法,提出了基于高可信度Reynolds average Navier-Stocks(RANS)和高斯回归模型辅助遗传算法的翼型优化设计方法。结果表明:基于高斯回归模型的翼型优化方法,可以将优化所用CFD计算次数降低一阶,从而大幅度提升优化设计效率。由标准算例超临界翼型RAE2822的降阻设计表明,在百次量级的CFD次数阻力降低43.16%,激波被削弱且升力、力矩和面积严格满足约束。由风力机翼型NACA64618的最大化升阻比优化设计表明,所设计翼型不仅在设计攻角和副设计攻角处升阻比大大增加,在整个小攻角范围内其气动性能都得到了提升,且两个主设计点,无不良阻力的产生。 

关 键 词:高斯过程回归(GPR)  CST参数化方法  遗传算法  贝叶斯优化  翼型设计
收稿时间:2020/9/21 0:00:00

Airfoil optimization design based on Gaussian process regression and genetic algorithm
CHANG Linsen,ZHANG Qianying,GUO Xueyan.Airfoil optimization design based on Gaussian process regression and genetic algorithm[J].Journal of Aerospace Power,2021,36(11):2306-2316.
Authors:CHANG Linsen  ZHANG Qianying  GUO Xueyan
Institution:1.School of Energy and Power Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China2.Shanghai Key Laboratory of Multiphase Flow and Heat Transfer in Power Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China
Abstract:In view of the problems that the leading edge curvature of the wind turbine airfoil with high lift-to-drag ratio has large radius,the traditional airfoil parameterization method has insufficient leading edge control ability,and there exists poor prediction accuracy based on the panel method XFOIL,an enhanced class function/shape function transformation (CST) parameterized method was used to control the shape change of airfoil,Latin hypercube experimental design,computational fluid dynamics (CFD) flow field calculation module,Gaussian process regression model and genetic algorithm,based on high-confidence Reynolds average Navier -Stocks (RANS) and Gaussian regression model-assisted genetic algorithm for airfoil optimization design method.The results showed that the airfoil optimization method based on the Gaussian regression model can reduce the number of CFD calculations for optimization by one order,thereby greatly improving the optimization design efficiency.The resistance reduction design of the supercritical airfoil RAE2822 of the standard calculation example showed that the resistance of the CFD frequency in the order of hundreds of times was reduced by 43.16%,the shock wave was weakened and the lift,moment and area could strictly meet the constraints.The maximum lift-to-drag ratio of the wind turbine airfoil NACA64618 showed that the designed airfoil not only greatly increased the lift-to-drag ratio at the design angle of attack and the secondary design angle of attack,but also improved its aerodynamic performance in the entire range of the small angle of attack.And there were two main design points,without bad resistance. 
Keywords:
本文献已被 万方数据 等数据库收录!
点击此处可从《航空动力学报》浏览原始摘要信息
点击此处可从《航空动力学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号