Wing aerostructural optimization using the Individual Discipline Feasible architecture

At present, on the aviation market a need exists for lighter and more efficient aircraft than the ones dominating the airspace today. Beside the reduction in operating costs and air pollutants of these new generation aircraft, this reduction in fuel use can result in several advantages with respect to the performance of the aircraft like increased range, increased payload capacity, decreased of take-off field length and decreased take-off noise. The present thesis is an effort to contribute to this reduction of fuel use by performing a gradient-based aerostructural wing optimization of a modern high-speed transport aircraft, the Airbus A320, for minimal necessary fuel weight while maintaining its range specification. The novelty of this work is the use of the Individual Discipline Feasible (IDF) architecture instead of the traditional Multidisciplinary Feasible architecture. Using the IDF approach the disciplines within the aerostructural optimization are completely decoupled. The consistency of the system as a whole is maintained by the use of equality constraints to equate the output of one discipline to the input of another. No coupled sensitivity information is required because of this decoupled system. This makes the system not only simpler, but also provides more freedom in software choice for the disciplinary analyses. Furthermore, the time to perform optimization is reduced as the work of making the system consistent is removed from the computationally expensive individual disciplines and put it in the hands of the cheap optimization algorithm. The CFD solver SU2 is used within the aerodynamic discipline to deform the grid, calculate the flow properties and gain sensitivities of lift and drag with respect to surface perturbations of the wing. The Euler model is used and the viscous drag component is calculated using a separate estimation. For the structural discipline the FEMWET software is used, providing the structural data including the static aeroelastic deformation of the wing. The optimization design variables are selected to be the angle of attack, the exterior shape of the wing, being the airfoil and planform shapes, and the thicknesses of the equivalent panels representing the internal wing box. The problem is constraint by compression, tension, shear, buckling and fatigue failure modes. Moreover it is constraint by a minimum aileron effectiveness and a maximum wing loading. The aerodynamic analysis is performed under cruise conditions while the wing structure is analyzed under the critical load cases of the reference aircraft. The optimization algorithm chosen is the Sparse Nonlinear Optimizer, based on the Sequential Quadratic Programming optimization algorithm. The optimization resulted in a reduction of the aircraft fuel weight of 11%. This has been achieved by reducing induced drag through an increase in span and an improved lift distribution, by reducing wave drag by improved airfoil shapes and by reducing wing structural weight by a reduction in wing sweep.Flight Performance and PropulsionFlight Performance and PropulsionAerospace Engineerin