Aerodynamic Optimisation of Non-Planar Lifting Surfaces

A novel population structured genetic algorithm (sGA) with embedded potential flow vortex ring panel method (VRM) has been developed to minimise induced and parasitic drag subject to constraints on lift, root bending moment, and longitudinal static stability. The optimisation architecture can activate up to four independent wing segments allowing up to 28 design variables. Minimum drag of wing tip extensions and winglet configurations are compared using the non-linear stochastic optimisation method. The optimiser identified joined box wings as offering the greatest induced efficiency followed by C-wings. With span and root bending moment constraints winglets offered best total drag reduction. C-wings are further investigated for potential to enhance longitudinal static stability performance by staggering the horizontal extension of the winglet to balance moments around the wing’s centre of gravity. Preliminary results suggest that while longitudinal static stability can be reached it would be very poor. Inclusion of more design constraints and additional analysis of the structural dynamics of C-wings, especially effecting the torsional mode, is necessary