In this research, two inflatable-winged Unmanned Aerial Vehicles (UAVs) in distinct configurations, a single-fuselage layout with external trailing-edge control surfaces and a twin-fuselage layout with fully movable control surfaces were designed, developed, and flight tested to investigate the flight characteristics of inflatable-winged aircraft. Initially, inflatable wings were designed and fabricated from various materials, followed by rigorous ground testing, including structural characteristics tests, pressure retention and resistance tests, and low-speed wind-tunnel evaluations. Following this, two methods for controlling the inflatable wings were proposed, and their roll control effectiveness was thoroughly investigated. Subsequently, two inflatable-winged UAV prototypes, each employing a different configuration and manipulation method, were designed, assembled, and subjected to basic low-altitude flight tests to assess the feasibility of their aerodynamic layouts and control characteristics. The results demonstrated that a segmented wing design with a multi-boom configuration is particularly well-suited for inflatable wings. Additionally, both proposed control methods were tested and shown to be effective in flight. The findings provide valuable insights into the properties of inflatable wings and offer substantial guidance for the development of inflatable-winged aircraft.

The lightweight design of modern aircraft necessitates efficient optimization of complex thin-walled structures to improve performance and minimize mass. This paper proposes an Elastic Boundary Sub-model Optimization (EBSO) algorithm for accurately predicting and optimizing local buckling behavior in aerospace thin-walled structures. The method partitions the global structure into substructures and incorporates elastic boundary conditions to realistically simulate interaction effects between adjacent components. By establishing a direct mapping between substructural design parameters and critical buckling loads, an iterative optimization framework is developed to enable concurrent design of multiple thin-walled segments. A numerical case study involving an aircraft fuselage panel demonstrates that the EBSO algorithm significantly improves the accuracy of local buckling predictions. The results confirm that the method achieves a substantial weight reduction while maintaining structural stability, greatly enhancing the efficiency of lightweight design optimization.