The wing aerodynamic shape optimization is a typical high-dimensional problem with numerous independent design variables. Researching methods to reduce the dimensionality of optimization from the perspective of aerodynamic characteristics is necessary. One traditional aerodynamic-based approach decouples the wing’s camber and thickness according to the thin airfoil theory, but it has limitations due to unclear application scope and effectiveness. This paper proposes an improved approach that determines the values of certain thickness variables based on a data-driven aerodynamic characteristics model before optimization, which considers longitudinal stability. By reducing the number of design variables, the dimensionality of optimization is decreased effectively. The derivation of the improved approach is accomplished through the design of experiments, parametric modeling, computational fluid dynamics, and sensitivity analysis. The effectiveness of the improved approach is validated by applying it to the aerodynamic optimization of an ONERA-M6 wing in subsonic flow based on the surrogate-based optimization algorithm. The results demonstrate that the improved approach significantly accelerates the optimization process while maintaining global effectiveness.

The flush airdata sensing system (FADS) is a measurement method that calculates aircrafts airdata by obtaining the pressure distribution from the ports. The traditional design method of port layout is to install the ports on the side of aircraft nose where the pressure is sensitive to angle of sideslip and angle of attack. Yet, for the aircraft whose surface pressure gradient with respect to angle of sideslip is rather slighter than that with respect to angle of attack, especially for blended wing body configuration, its measurement errors of angle of sideslip will increase significantly. In order to enhance the measurement accuracy, this paper proposes a resolution-based port layout design method for plane aircrafts while the traditional gradient-based design method deteriorates. Firstly, the pressure distribution of aircraft under various cases are obtained by computational fluid dynamics method, and then the feasible set of ports is introduced. Secondly, the layouts under different port counts are gained by resolution-based method and traditional method respectively. Finally, it establishes FADS to predict the angle of attack, angle of sideslip and airspeed by artificial neural network, and evaluates the performance of resolution-based method and traditional method. The result shows that, the resolution-based method obtains the optimal layout, and has a quite minor error and system uncertainty than traditional method, which effectively improves the system's accuracy.

Most existing studies on aerodynamic shape optimization have not considered longitudinal trim under control surface deflection, typically achieving self-trim through a constraint of zero pitching moment or adjusting the optimized configuration for longitudinal trim. However, adjustments to the optimized configuration might introduce additional drag, reducing overall optimization benefits. In this paper, a novel approach of incorporating control surface deflection for longitudinal trim in aerodynamic optimization is proposed. Firstly, an aerodynamic computation program based on the high-order panel method was developed, introducing velocity perturbations on specific mesh surfaces to simulate actual control surface deflections. Subsequently, a comprehensive optimization framework was established, encompassing parametric modeling, aerodynamic computation, and variable-fidelity control surface deflection analysis. Finally, aerodynamic optimization analysis was conducted under both subsonic and supersonic conditions. Thirty-one design variables were selected with the trimmed lift-to-drag ratio in cruising condition as the objective function and the control surface deflection angle as the constraint. The results indicated an 8.52% increase in the trimmed lift-to-drag ratio compared to the baseline model under subsonic conditions and an 8.1% increase under supersonic conditions.