This paper investigates the influence of the spanwise-distributed trailing-edge camber morphing on the dynamic stall characteristics of a finite-span wing at Re = 2 × 10⁵. The mathematical model of the spanwise-distributed trailing-edge camber morphing is established based on Chebyshev polynomials, and the deformed wing surface is modeled by a spline surface according to the rib’s morphing in the chordwise direction. The Computational Fluid Dynamics (CFD) method is adopted to obtain flow-field results and aerodynamic forces. The SST-γ model is introduced and the overset mesh technique is adopted. The numerical results show that the spanwise-distributed trailing-edge morphing obviously changes the aerodynamic and energy transfer characteristics of the dynamic stall. Especially when the phase difference between the trailing-edge motion and the wing pitch is −π/2, the interaction between the three-dimensional (3-D) Leading-Edge Vortex (LEV) and Trailing-Edge Vortex (TEV) is strengthened, and the work done by the aerodynamic force turns negative. This indicates that the trailing-edge deformation has the potential to suppress the oscillation amplitude of stall flutter. We also found that as the trailing-edge camber morphing varies more complexly along the spanwise direction, the suppression effect decreases accordingly.

An integrated optimization design methodology is developed for variable camber wing using active aeroelastic wing (AAW) technology, based on a genetic optimization algorithm. The optimization design for low aspect ratio aircraft’s scale model’s trim using multiple variable camber wings is conducted in a steady rolling maneuver. The goal is to reduce the structural mass while taking into account the limitations of the wing root’s moment, flutter speed, and the equivalent deflection angle of the morphing leading and trailing edges. A comparison between the new method and the conventional design method with single variable camber is also presented. The results showed that morphing the leading and trailing edges could increase control efficiency by 34.71% when compared to the traditional control surface. By coordinating the morphing of multiple leading and trailing edges, the AAW technology could fully utilize the flexibility of the wing structure to effectively reduce maneuver load and the wing’s structural mass by 12.9%.

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.

Limit cycle oscillation happens in airfoil systems with freeplay nonlinearity within a specific velocity range. Because the traditional linear control law’s limit cycle suppression effect is typically insignificant and its robustness is insufficient, a corresponding nonlinear control law must be designed in order to improve the system’s control effect and robustness. According to this article, the limit cycle speed range is optimized between 11.4−16.9 m/s and 12.9−19.2 m/s. The linear quadratic regulartor (LQR) control law is created for the 2D airfoil aeroelastic system with freeplay nonlinearity. At the same time, the sliding mode control law (SMC) is designed for the 2D airfoil aeroelastic system with freeplay nonlinearity above, it shows that the speed range of the limit cycle is optimized from 11.4−16.9 m/s to 29.4−39.3 m/s. The result of the calculating example shows that the SMC law is better than that of LQR for nonlinear systems in this paper.