The design of composite structures based on _bre angle optimisation rapidly becomes intractable as the number of design variables increases. Lamination parameters can be used instead as intermediate design variables in order to overcome this issue. An extra step is then required in order to convert the optimal design expressed in lamination param- eter into feasible blended stacking sequences. However, disparities between the lamination parameter and stacking sequence designs performance are generally observed due to dis- crepancies between both design spaces. In this paper, the lamination parameter blending constraints recently proposed by the authors are applied to the aeroelastic optimisation of the common research wing model in order to diminish these discrepancies and achieve more realistic lamination parameter designs. A comparison between the optimised designs achieved with and without the proposed blending constraints is carried out to evaluate our approach. Results demonstrate that the application of blending constraints greatly in- creases the matching quality between lamination parameter and stacking sequence designs, consequently facilitating the retrieval of equivalent blended stacking sequences. @en

Optimizing the laminates of large composite structures is nowadays well-recognized as having significant benefits in the design of lightweight structural solutions. However, designs based on locally optimized laminates are prone to structural discontinuities and enforcing blending during the optimization is therefore crucial in order to achieve structurally continuous and ready-tomanufacture designs. Bi-step strategies, relying on a continuous gradient-based optimization of lamination parameters followed by a discrete stacking sequence optimization step during which blending is enforced, have been proposed in the literature. However, significant mismatch between continuous and discrete solutions were observed due to the discrepancies between both design spaces. The present paper highlights the capability of the continuous blending constraints, recently proposed by the authors, in reducing the discrepancies between discrete and continuous solutions. The paper also demonstrates that more realistic optimal continuous designs are achieved thanks to the application of the blending constraints during the aeroelastic optimization of a variable stiffness wing. Additionally, the proposed blending constraints have been applied to NASTRAN SOL 200 showing their ease of implementation in commercial software. @en

The present paper proposes a set of blending constraints expressed in lamination parameter space, applicable during the continuous optimisation of composite structures. Thicknesses and ply orientations of large composite structures are often locally optimised in response to unequal spatial load distribution. During this process, ensuring structural continuity is essential in order to achieve designs ready to be manufactured. Single step stacking sequence optimisations relying on evolutionary algorithms to enforce continuity, through the application of blending rules, are prone to the curse of dimensionality. By contrast, multi-step optimisation strategies including a continuous sub-step can optimise composite structures with reasonable computational effort. However, the discrepancies between continuous and discrete optimisation step result in performance loss during stacking sequence retrieval. By deriving and applying blending constraints during the continuous optimisation, this paper aim is to reduce the performance loss observed between optimisation levels. The first part of this paper is dedicated to the derivation of blending constraints. The proposed constraints are then successfully applied to a benchmark blending problem in the second part of this paper. Numerical results demonstrate the achievement of near-optimal easy-to-blend continuous designs in a matter of seconds. Keywords: Composite materials, Blending, Lamination parameters, Optimisation, Variable @en

Wind turbines are fatigue critical machines for which the problem of vibrations is becoming predominant as rotor sizes keep increasing. Whereas the load reduction potential of wind turbine smart blades with trailing-edge control devices is now well-recognised, the design of load alleviation control systems which are efficient, robust and yet simple remains an open problem. The present paper evaluates the efficiency of a new proposed decoupled loop-shaping control (DLSC) strategy for the load alleviation of wind turbine blades equipped with multiple control surfaces. The efficiency of the proposed decoupling control strategy is evaluated against the well-established model predictive controller (MPC). For that purpose, an in-house wind turbine aeroelastic control (WTAC) simulator is employed to simulate the aeroelastic dynamics of the NREL 5 MW wind turbine operating in a fully turbulent environment. WTAC incorporates a wind field generator, an aerodynamic model and a finite element structural blade model. Trailing edge flaps are used as active control surfaces and are dynamically coupled to the aeroelastic wind turbine blade models. First, a state-of-the-art MPC is designed to address the load alleviation control problem. MPC is specifically chosen on account of its multi-input multi-output (MIMO) nature and constraints handling capabilities. Although high load alleviation efficiency is achieved, the MPC remains a complex timebased state controllers. Next, the proposed frequency-based loop-shaping controller is applied to the same control problem. The DLSC takes advantages of the dynamic response of blades to reformulate the MIMO load alleviation control problem as decoupled single-input single-output (SISO) control loops. Classic loop-shaping control theory is then used to design SISO controllers. The DLSC performance is compared with that of the MPC based on 1P blade root load bending moment reduction. The results of this investigation demonstrate the efficiency of the proposed DLSC strategy with respect to the MPC controller. The advantageous simplicity and insightful features of the DLSC are also highlighted.@en