Two-Stage Design of Experiment Optimization Framework for Morphing Wing of Acrobatic Aircraft

This study presents an integrated two-stage optimization framework designed to enhance the aerodynamic performance of acrobatic aircraft through the coupled design of morphing airfoils and wing planforms. In the first stage, design of experiments is employed to identify key geometric parameters of a morphing airfoil. These parameters are then used to construct surrogate models using Response Surface Methodology and optimized with the Nelder–Mead algorithm to simultaneously maximize the stall angle and lift coefficient under realistic flight conditions. The optimized airfoil configurations serve as inputs for the second stage, where wing-level parameters are optimized using a Multi-Objective Genetic Algorithm. This process is validated through high-fidelity computational fluid dynamics simulations. Compared to a baseline NACA0012 configuration, the proposed methodology yields substantial performance improvements: a 33% increase in maximum lift-to-drag ratio, a 17% enhancement in lift coefficient, improved roll rate, and delayed flow separation. By bridging the conventional gap between airfoil and wing design, this framework offers a robust and efficient computational approach for developing next-generation morphing aircraft, delivering both methodological innovation and practical insights for performance-driven aerospace applications.