翼型不确定性对气动特性影响分析与外形监测方法

It is crucial to assess how airfoil form uncertainty affects aerodynamic properties in order to suggest shape inspection indicators throughout the aircraft's whole life cycle. The traditional shape parameterization method has many variables and the calculation of aerodynamic characteristics is complex, making it difficult to directly analyze the uncertainty propagation between shape and aerodynamic characteristics. Class shape transform (CST) is applied to reduce the necessary variables for airfoils parameterization. Uncertain shape is described with random shape parameters. Aerodynamic coefficients are calculated through computational fluid dynamics (CFD) to generate samples. To create surrogate models for aerodynamics calculations, the sparse polynomial chaos expansion approach with least angle regression (LAR) is utilized. The coefficients of the polynomial chaos are used to directly determine the global sensitivity of the shape parameters, and the sensitivity results are used to pick crucial points for shape inspection. Examples show that controlling the deviation intervals of only two key points can reduce the variance of the lift coefficient by 25% and increase the average value by 3.8%, providing a reasonable inspection method for actual processing and maintenance.