This article presents the application of aeroelastic tailoring in the design of wings for a flying demonstrator, as well as the validation of the design methodology with flight test results. The investigations were performed in the FLEXOP project (Flutter Free Flight Envelope Expansion for Economical Performance Improvement), funded under the Horizon 2020 framework. This project aimed at the validation of methods and tools for active flutter control, as well as at the demonstration of the potential of passive load alleviation through composite tailoring. The technologies were to be demonstrated by the design, manufacturing and flight testing of an unmanned aerial vehicle of approximately 7 m wingspan. This article addresses the work towards the load alleviation goals. The design of the primary load-carrying wing-box in this task is performed using a joint DLR–TU Delft optimization strategy. Two sets of wings are designed in order to demonstrate the potential benefits of aeroelastic tailoring—first, a reference wing in which the laminates of the wing-box members are restricted to balanced and symmetric laminates; second, a tailored wing in which the laminates are allowed to be unbalanced, hence allowing for the shear–extension and bending–torsion couplings essential for aeroelastic tailoring. Both designs are numerically optimized, then manufactured and extensively tested to validate and improve the simulation models corresponding to the wing designs. Flight tests are performed, the results of which form the basis for the validation of the applied aeroelastic tailoring approach presented in the article.

This paper presents an aero load correction strategy applicable to the static aeroelastic optimization of composite wings. The optimization framework consists of a successive convex subproblem iteration procedure, in which a gradient-based optimizer consecutively solves a local approximation problem. Responses are approximated as a linear and/or reciprocal function of the laminate membrane and bending stiffness matrices. Together with the laminate thicknesses h, they constitute the design variables in the optimization process. Internally, the design space is transformed from stiffness matrices to lamination parameters, resulting in a continuous and convex optimization problem. Structural responses considered in the stiffness optimization are strength, local buckling and mass; aileron effectiveness, divergence, and twist constitute the aeroelastic responses. Steady aeroelastic loads are calculated with a doublet lattice method (DLM) embedded in the applied finite element solver, allowing for the generation of response sensitivities that incorporate the effects of displacement-dependent aeroelastic loads. To incorporate flow phenomena that cannot be reproduced with DLM, a higher order aerodynamic method is considered. The developed correction methods and their application are presented in this paper. The correction is twofold, first, aiming at a correction of DLM by means of camber and twist modifications applied directly to the doublet lattice mesh and second, by employing the capabilities of a higher order computational fluid dynamics (CFD) solver, like the DLR-based TAU code. To this end, DLM loads transferred to the structure are rectified by means of the supposedly superior CFD results. The aero load correction method is applied in the stiffness optimization of a forward swept wing. First, a trim application without structural optimization is discussed, to demonstrate the convergence behavior of the correction forces. The results of a wing skin mass minimization with balanced and unbalanced laminates are presented. In particular, the differences between optimizations with and without aero correction are highlighted. Eventually, a stacking sequence optimization based on the continuous optimization results is demonstrated.

This article presents an optimization tool for the stacking sequence design of blended composite structures. Enforcing blending ensures the manufacturability of the optimized laminate. A novel optimization strategy is proposed combining a genetic algorithm (GA) for stacking sequence tables with a multi-point structural approximation using a modified Shepard’s interpolation in stiffness-space. A successive approximation approach is used where the set of design points used to create the structural approximations is successively enriched using the elite of the previous step. Additional improvement in the generality and efficiency of the algorithm is obtained by using load approximations thus enabling the implementation of a wide range of stress-based design criteria. A multi-panel, blended composite problem is used as an application to demonstrate the performance of the developed tool. The optimization is performed with mass as the objective to be minimized, subjected to strength and buckling constraints. The results presented show that completely blended and feasible stacking sequence designs can be obtained, having their structural performance close to the theoretical continuous optimum itself. Additionally, the multi-point Shepard’s approximation shows a considerable saving in computational costs, while the limitations of inexpensive stiffness-matching optimizations are observed.