Analysis and Optimization of a Novel Seamless Morphing Trailing Edge for Lambda Wing Unmanned Aerial Vehicles

The Lambda wing UAV inevitably needs to adjust the lift coefficient and pitch moment by controlling the flap when encountering multiple flight states. Inspired by the natural morphing mechanisms of bird wings, this study draws upon bionic principles to explore a seamless morphing trailing edge (SMTE) design that mimics the smooth and continuous deformation observed in avian flight. A comparative analysis between SMTE flaps and traditional hinge flaps highlights the superior rearward stealth performance of SMTE flaps in the direction angles of 120° to 140°, along with a reduction in aerodynamic drag. During the optimization, a model based on flexible wing ribs and elastic skin was established, and statistical analysis revealed a strong linear correlation between the maximum lift coefficient provided by the flaps and the overall lift-to-drag ratio. Consequently, the optimization process omitted the enhancement of the comprehensive lift-to-drag ratio during the flap deflection. Additionally, a deep Neural Network Surrogate Model was introduced to streamline the computationally intensive aerodynamic calculations. Ultimately, an MOGA-2 optimization model incorporating local deep Neural Network Surrogate Models was utilized to achieve the comprehensive optimization of aerodynamic and stealth characteristics, through an adjustment of the wing rib and skin proportions. The UAV rearward RCS and the maximum lift coefficient provided by the flaps have decreased by 2.8% and increased by 6.6%, respectively.