The Flying V is an innovative new aircraft concept currently being developed by the faculty of Aerospace Engineering at Delft University of Technology. This aircraft is a flying wing having a large sweep on the inner section, and a small sweep angle at the outer, giving the aircr
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The Flying V is an innovative new aircraft concept currently being developed by the faculty of Aerospace Engineering at Delft University of Technology. This aircraft is a flying wing having a large sweep on the inner section, and a small sweep angle at the outer, giving the aircraft its characteristic V shape. The objective of this research is to create a parameterisation of the cockpit and aft center fairing for the Flying V that includes an integration of pilot anthropometry, satisfies visibility certification constraints, ensures positioning of nose landing gear and radar, while providing a high probability of good aerodynamic performance and being able to be used in an aerodynamic design optimisation. To accomplish this, a geometric parameterisation of the cockpit model is made by means of defining a rail on which cross-sectional profiles are placed. A loft through the profiles creates the outer mold line of the cockpit. Constraints were imposed on the cockpit model by pilot anthropometry, the required view angles at the pilot design eye point and by the presence of the radar and nose landing gear. Additionally, a center fairing is defined to reduce the root effect caused by the high sweep angle of the aircraft. Finally, the geometrical model is coupled to an aerodynamic solver to assess its performance and to make future aerodynamic optimisation possible. Demonstration of the model has shown that a cockpit design for the Flying V is possible at a 0.8% reduction of the aircraft lift to drag ratio while satisfying all constraints. Furthermore, the center fairing has shown to increase lift at the root by 13.5%, resulting in an increase of 0.94% in the aircraft lift to drag ratio. Lastly, the robustness of the cockpit and center fairing geometric models was found to be up to 20.3% and 39.9% respectively, where the former can be increased to 50.4% if a lower tolerance on the geometric model is chosen.