This study presents a coupled aerostructural optimization framework for the preliminary design of a low-Reynolds-number composite UAV wing, aiming to simultaneously enhance aerodynamic efficiency and structural performance. While previous work has primarily addressed aerodynamic optimization in isolation, the present approach integrates high-fidelity Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) analyses within a Surrogate-Based Optimization (SBO) framework. The design space includes both aerodynamic parameters—aspect ratio, taper ratio, sweep angle, and twist—and structural variables related to the internal wing layout and component thicknesses. To reduce the computational cost associated with high-fidelity simulations, Kriging surrogate models are employed in conjunction with an Expected Improvement (EI) infill strategy, enabling efficient exploration of the coupled design space. The framework is evaluated through multiple independent optimization runs using different initial sampling strategies, demonstrating consistent convergence toward feasible high-performance designs. The surrogate models exhibit strong predictive capability, as confirmed by Root Mean Square Error (RMSE) and Leave-One-Out (LOO) cross-validation metrics. The results indicate that aerodynamic variables, particularly aspect ratio and twist, are the primary drivers of range performance. However, structural variables—most notably skin thickness—strongly influence constraint satisfaction, especially with respect to buckling and strength requirements, and therefore play a key role in defining the feasible design space. The optimal configuration achieves a maximum range of approximately 203 km while satisfying all strength, stiffness, and aerodynamic constraints. Overall, the proposed methodology provides an efficient and robust tool for early-stage aerostructural design of low-Reynolds-number UAV wings.

This paper presents the end-to-end multidisciplinary development and flight-test assessment of a Class I fixed-wing mini unmanned aerial vehicle (UAV) designed for surveillance and reconnaissance missions. The development process progresses from mission and system-level requirements through conceptual, preliminary, and detailed design, followed by prototype fabrication and experimental flight testing. Conceptual design establishes aircraft mass, wing and power loading, aerodynamic configuration, wing geometry, airfoil selection, mass distribution, and initial stability characteristics. The preliminary and detailed stages progressively increase analysis fidelity through assessments of aerodynamics, structures, aeroelasticity, propulsion, stability and control, performance, and thermal management. High-fidelity Computational Fluid Dynamics (CFD) is employed for aerodynamic char-acterization and load prediction, while Finite-Element (FE) and aeroelastic models are used to assess strength, stiffness, static and dynamic aeroelastic behavior. The aircraft configuration incorporates a V-tail, electric pusher propulsion, composite structural components, integrated control surfaces, wingtip devices, and dedicated cooling arrangements. A representative 3D-printed flight-test article retaining the principal aerodynamic architecture was subsequently evaluated in climb, straight-and-level flight, sustained turns, and low-speed operation. The vehicle exhibited stable and predictable handling throughout the tested envelope. Flight-derived aerodynamic characteristics showed close agreement with the detailed-design CFD database, with drag-coefficient deviations remaining below approximately 3% in straight-and-level flight and within approximately 1.5% during climb. Larger discrepancies, reaching approximately 16%, were observed during sustained turns, highlighting the increased uncertainty associated with maneuvering flight and with drag values inferred using the propulsion model. Overall, the study demonstrates a traceable progressive-fidelity methodology for advancing a mini-UAV from requirements and conceptual sizing to multidisciplinary verification and prototype-level flight assessment.

This study presents an aerostructural optimization framework for the preliminary design of a low-Reynolds-number composite UAV wing, aiming to simultaneously enhance aerodynamic efficiency and structural performance. While previous work has primarily addressed aerodynamic optimization in isolation, the present approach integrates Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) analyses within a surrogate-based optimization (SBO) framework. The design space includes both aerodynamic parameters—aspect ratio, taper ratio, sweep angle, and twist—and structural variables related to the internal wing layout and component thicknesses. To reduce the computational cost associated with high-fidelity simulations, Kriging surrogate models are employed in conjunction with an Expected Improvement (EI) infill strategy, enabling efficient exploration of the coupled design space. The framework is evaluated through multiple independent optimization runs using different initial sampling strategies, demonstrating consistent convergence toward feasible high-performance designs. The surrogate models exhibit strong predictive capability, as confirmed by Root Mean Square Error (RMSE) and Leave-One-Out (LOO) cross-validation metrics. The results indicate that aerodynamic variables, particularly aspect ratio and twist, are the primary drivers of range performance. However, structural variables—most notably skin thickness—strongly influence constraint satisfaction, especially with respect to buckling and strength requirements, and therefore play a key role in defining the feasible design space. The optimal configuration achieves a maximum range of approximately 203 km while satisfying all strength, stiffness, and aerodynamic constraints. Overall, the proposed methodology provides an efficient and robust tool for the early-stage aerostructural design of low-Reynolds-number UAV wings.