Birds dynamically adapt to disparate flight behaviours and unpredictable environments by actively manipulating their skeletal joints to change their wing shape. This in-flight adaptability has inspired many unmanned aerial vehicle (UAV) wings, which predominately morph within a single geometric plane. By contrast, avian joint-driven wing morphing produces a diverse set of non-planar wing shapes. Here, we investigated if joint-driven wing morphing is desirable for UAVs by quantifying the longitudinal aerodynamic characteristics of gull-inspired wing-body configurations. We used a numerical lifting-line algorithm (MachUpX) to determine the aerodynamic loads across the range of motion of the elbow and wrist, which was validated with wind tunnel tests using three-dimensional printed wing-body models. We found that joint-driven wing morphing effectively controls lift, pitching moment and static margin, but other mechanisms are required to trim. Within the range of wing extension capability, specific paths of joint motion (trajectories) permit distinct longitudinal flight control strategies. We identified two unique trajectories that decoupled stability from lift and pitching moment generation. Further, extension along the trajectory inherent to the musculoskeletal linkage system produced the largest changes to the investigated aerodynamic properties. Collectively, our results show that gull-inspired joint-driven wing morphing allows adaptive longitudinal flight control and could promote multifunctional UAV designs.

A numerical lifting-line method (implemented in an open-source software package) is presented that can accurately estimate the aerodynamics of wings with arbitrary sweep, dihedral, and twist. Previous numerical lifting-line methods have suffered from grid convergence challenges and limitations in accurately modeling the effects of sweep, or have relied on empirical relations for swept-wing parameters and have been limited in their application to typical wing geometries. This work presents novel improvements in accuracy, flexibility, and speed for complex geometries over previous methods. In the current work, thin-airfoil theory is used to correct section lift coefficients for sweep, providing a more general closure to the lifting-line problem. A linearized solution is presented, which can be used as a rapid approximation for the full solution, or as an initial guess for the nonlinear system of equations to speed convergence. Sensitivities to model parameters are investigated, and appropriate recommendations for these parameters are given. Agreement with Prandtl’s classical lifting-line method is excellent in the case of straight wings. Comparison with experimental data shows that this method can reasonably predict lift, drag, and lift distribution for a range of wing configurations. The speed and accuracy of this method make it well-suited for preliminary design and optimization.

Because the wing-structure weight required to support the critical wing section bending moments is a function of wingspan, net weight, weight distribution, and lift distribution, there exists an optimum wingspan and wing-structure weight for any fixed net weight, weight distribution, and lift distribution, which minimises the induced drag in steady level flight. Analytic solutions for the optimum wingspan and wing-structure weight are presented for rectangular wings with four different sets of design constraints. These design constraints are fixed lift distribution and net weight combined with 1) fixed maximum stress and wing loading, 2) fixed maximum deflection and wing loading, 3) fixed maximum stress and stall speed, and 4) fixed maximum deflection and stall speed. For each of these analytic solutions, the optimum wing-structure weight is found to depend only on the net weight, independent of the arbitrary fixed lift distribution. Analytic solutions for optimum weight and lift distributions are also presented for the same four sets of design constraints. Depending on the design constraints, the optimum lift distribution can differ significantly from the elliptic lift distribution. Solutions for two example wing designs are presented, which demonstrate how the induced drag varies with lift distribution, wingspan, and wing-structure weight in the design space near the optimum solution. Although the analytic solutions presented here are restricted to rectangular wings, these solutions provide excellent test cases for verifying numerical algorithms used for more general multidisciplinary analysis and optimisation.

To meet the growing need for fast supersonic flow solutions, the theory and implementation of a modern subsonic/supersonic, unstructured panel method are here presented. This work presents several improvements over legacy supersonic panel codes and available modern codes. Among these improvements are automatic methods for generating unstructured wakes, enforcing the Kutta condition at trailing edges, and placing interior control points. An efficient method for calculating domains of dependence on an unstructured mesh is also presented. For the first time in the literature regarding supersonic panel methods, a complete method for calculating influence coefficients is also described. The numerical sensitivities of the method are examined. Compared to analytic and experimental data, the method is accurate for small-perturbation flows. For example, the relative error in the root pressure coefficient on a straight wing in supersonic flow ([ ]) was calculated to be within approximately 7% of the analytic solution for a range of angles of attack. For a delta wing in supersonic flow ([ ]), the method is found to calculate lift slope and zero-lift drag to within 5% of experimental data. The method is also fast, having run times on the order of 1 minute for meshes with around 26,000 panels.