Experimental characterization and multidisciplinary conceptual design optimization of a bendable load stiffened unmanned air vehicle wing

Demand for deployable MAVs and UAVs with wings designed to reduce aircraft storage volume led to the development of a bendable wing concept at the University of Florida (UF). The wing shows an ability to load stiffen in the flight load direction, still remaining compliant in the opposite direction, enabling UAV storage inside smaller packing volumes. From the design prospective, when the wing shape parameters are treated as design variables, the performance requirements: high aerodynamic efficiency, structural stability under aggressive flight loads and desired compliant nature to prevent breaking while stored, in general conflict with each other. Creep deformation induced by long term storage and its effect on the wing flight characteristics are additional considerations. Experimental characterization of candidate bendable UAV wings is performed in order to demonstrate and understand aerodynamic and structural behavior of the bendable load stiffened wing under flight loads and while the wings are stored inside a canister for long duration, in the process identifying some important wing shape parameters. A multidisciplinary, multiobjective design optimization approach is utilized for conceptual design of a 24 inch span and 7 inch root chord bendable wing. Aerodynamic performance of the wing is studied using an extended vortex lattice method based Athena Vortex Lattice (AVL) program. An arc length method based nonlinear FEA routine in ABAQUS is used to evaluate the structural performance of the wing and to determine maximum flying velocity that the wing can withstand without buckling or failing under aggressive flight loads. An analytical approach is used to study the stresses developed in the composite wing during storage and Tsai-Wu criterion is used to check failure of the composite wing due to the rolling stresses to determine minimum safe storage diameter. Multidisciplinary wing shape and layup optimization is performed using an elitist non-dominated sorting genetic algorithm: NSGA-II. Simultaneous maximization of aerodynamic efficiency and aggressive flight load carrying capacity are chosen as two design objectives. The design points on the Pareto optimal front thus achieved are compared with a baseline design to observe some designs with improved performance both aerodynamically and structurally. Reliability based optimization concludes the work where uncertainties in design variables, design parameters and modeling are considered to achieve designs satisfying specified reliability constraint.