This paper presents a new non-linear formulation of the classical Vortex Lattice Method (VLM) approach for calculating the aerodynamic properties of lifting surfaces. The method accounts for the effects of viscosity, and due to its low computational cost, it represents a very good tool to perform rapid and accurate wing design and optimization procedures. The mathematical model is constructed by using two-dimensional viscous analyses of the wing span-wise sections, according to strip theory, and then coupling the strip viscous forces with the forces generated by the vortex rings distributed on the wing camber surface, calculated with a fully three-dimensional vortex lifting law. The numerical results obtained with the proposed method are validated with experimental data and show good agreement in predicting both the lift and pitching moment, as well as in predicting the wing drag. The method is applied to modifying the wing of an Unmanned Aerial System to increase its aerodynamic efficiency and to calculate the drag reductions obtained by an upper surface morphing technique for an adaptable regional aircraft wing

In the present paper, an \u2018in-house\u2019 genetic algorithm was numerically and experimentally validated. The genetic algorithm was applied to an optimization problem for improving the aerodynamic performances of an aircraft wing tip through upper surface morphing. The optimization was performed for 16 flight cases expressed in terms of various combinations of speeds, angles of attack and aileron deflections. The displacements resulted from the optimization were used during the wind tunnel tests of the wing tip demonstrator for the actuators control to change the upper surface shape of the wing. The results of the optimization of the flow behavior for the airfoil morphing upper-surface problem were validated with wind tunnel experimental transition results obtained with infra-red Thermography on the wing-tip demonstrator. The validation proved that the 2D numerical optimization using the \u2018in-house\u2019 genetic algorithm was an appropriate tool in improving various aspects of a wing\u2019s aerodynamic performances.Peer reviewed: YesNRC publication: Ye

In this paper, an \u2018in-house\u2019 genetic algorithm is described and applied to an optimization problem for improving the aerodynamic performances of an aircraft wing tip through upper surface morphing. The algorithm\u2019s performances were studied from the convergence point of view, in accordance with design conditions. The algorithm was compared to two other optimization methods, namely the artificial bee colony and a gradient method, for two optimization objectives, and the results of the optimizations with each of the three methods were plotted on response surfaces obtained with the Monte Carlo method, to show that they were situated in the global optimum region. The optimization results for 16 wind tunnel test cases and 2 objective functions were presented. The 16 cases used for the optimizations were included in the experimental test plan for the morphing wing-tip demonstrator, and the results obtained using the displacements given by the optimizations were evaluated.Peer reviewed: YesNRC publication: Ye

A new wing-tip concept with morphing upper surface and interchangeable conventional and morphing ailerons was designed, manufactured, bench and wind-tunnel tested. The development of this wing-tip model was performed in the frame of an international CRIAQ project, and the purpose was to demonstrate the wing upper surface and aileron morphing capabilities in improving the wing-tip aerodynamic performances. During numerical optimisation with ‘in-house’ genetic algorithm software, and during wind-tunnel experimental tests, it was demonstrated that the air-flow laminarity over the wing skin was promoted, and the laminar flow was extended with up to 9% of the chord. Drag coefficient reduction of up to 9% was obtained when the morphing aileron was introduced.

The drag coefficient and the laminar-to-turbulent transition for the aerofoil component of a wing model are optimised using an adaptive upper surface with two actuation points. The effects of the new shaped aerofoils on the global drag coefficient of the wing model are also studied. The aerofoil was optimised with an ‘in-house’ genetic algorithm program coupled with a cubic spline aerofoil shape reconstruction and XFoil 6.96 open-source aerodynamic solver. The wing model analysis was performed with the open-source solver XFLR5 and the 3D Panel Method was used for the aerodynamic calculation. The results of the aerofoil optimisation indicate improvements of both the drag coefficient and transition delay of 2% to 4%. These improvements in the aerofoil characteristics affect the global drag of the wing model, reducing it by up to 2%. The analyses were conducted for a single Reynolds number and speed over a range of angles of attack. The same cases will also be used in the experimental testing of the manufactured morphing wing model.