翼吊式飞机跨声速气动特性的不确定性分析  

Uncertainty Analysis of Transonic Aerodynamics for Wing-Mounted Aircraft

作　　者：莫邵昌 张鑫帅 谢芳芳 季廷炜[1] 郑耀[1] MO Shaochang;ZHANG Xinshuai;XIE Fangfang;JI Tingwei;ZHENG Yao(School of Aeronautics and Astronautics,Zhejiang University,Hangzhou 310027,China;Jiangnan Industries Group Go.,Ltd,Xiangtan 411207,China)

机构地区：[1]浙江大学航空航天学院,浙江杭州310027 [2]江南工业集团有限公司,湖南湘潭411207

出　　处：《气体物理》2024年第4期27-38,共12页Physics of Gases

基　　金：国家自然科学基金(92271107)。

摘　　要：针对随机不确定性可能带来翼吊式飞机严重气动性能波动的问题,提出了一种基于主动学习加点策略的Gauss过程回归(Gaussian process regression,GPR)代理模型方法用于不确定性分析,该主动学习加点策略能够有效地降低模型不确定性,提高不确定预测的精度。关注来流不确定性输入,分别使用Smolyak稀疏网格多项式混沌展开(polynomial chaos expansion,PCE)方法和基于主动学习加点策略的GPR代理模型方法,结合Sobol灵敏度分析对翼-身-短舱-挂架几何进行了不确定性分析。结果表明,在跨声速条件下,攻角和Mach数的不确定性会引起翼吊式飞机升力系数和阻力系数的剧烈波动,其中升力系数的波动同时受攻角和Mach数的影响,阻力系数的波动主要由Mach数决定。Since random uncertainty may cause severe aerodynamic performance fluctuations for the wing-mounted aircraft,the Gaussian process regression(GPR)surrogate model method based on was proposed.The strategy of adding sample points by active-learning method can effectively reduce model uncertainty and improve the accuracy of uncertainty prediction.Focusing on incoming flow with uncertainty,the polynomial chaos expansion(PCE)method based on Smolyak sparse grid and the GPR surrogate model method based on the strategy of adding sample points by active-learning method were used to analyze the uncertainty of the wing-body-nacelle-pylon geometry combined with the Sobol sensitivity analysis method.Results show that the uncertainty of angle of attack and Mach number will cause dramatic fluctuation in lift coefficient and drag coefficient of the wing-mounted aircraft under transonic condition.The fluctuation of lift coefficient is affected by angle of attack and Mach number,and the fluctuation of drag coefficient is mainly determined by Mach number.

关 键 词：不确定性分析 Gauss过程回归(GPR) 多项式混沌展开(PCE) 灵敏度分析 气动性能 

分 类 号：V211[航空宇航科学与技术—航空宇航推进理论与工程]