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- Mission-Based Multidisciplinary design optimization methodologies for unmanned aerial vehicles with morphing technologiesPublication . Albuquerque, Pedro Filipe Godinho Lopes Fernandes de; Gamboa, Pedro Vieira; Silvestre, Miguel Ângelo RodriguesOne of the most challenging aspects of aircraft design is to synthesize the mutual interactions among disciplines in order to achieve enhanced design solutions from the earliest stages of the design process. The complexity of the aircraft physics and the multiple couplings between disciplines complicates this task. The advance of design tools and optimization methods alongside with the computer’s exponential increase in data handling capacity is paving the way for the development of comprehensive multidisciplinary design codes that gradually contribute to a paradigm change, leading to a revolution in the design methodologies. The research work presented in this thesis features two unmanned aerial vehicles preliminary design optimization methodologies - a Parametric Design Analysis and a Multilevel Design Optimization. A specific code has been developed for each methodology, with low-fidelity models being used for the main design disciplines, namely the aerodynamics, propulsion, weight, static stability and dynamic stability. To increase the usability of the codes a graphical user interface for both programs has also been developed. The first methodology is called Parametric AiRcRaft design OpTimization (PARROT) and relies on a parametric study that optimizes the wing layout for one of two different goals: surveillance mission or maximum payload. Whereas in the former the goal is to maximize the flight range or endurance, the latter’s objective is to maximize the useful payload lifted. Constraints include the take-off distance, climb rate, bank angle, cruise velocity, among others. The results have shown to be in line with some experimental benchmarking data and to allow the user to easily evaluate the impact of varying two key design variables (wing mean chord and wingspan) on multiple performance metrics, thus significantly contributing to help the designer’s decision-making process. The second methodology is called MulTidisciplinary design OPtimization (MTOP) and adopts the Enhanced Collaborative Optimization (ECO) architecture, together with a gradient-based optimization algorithm. As the goal is to minimize the energy consumption for the specified mission profile, it results in an unconstrained system problem which aims to assure compatibility between subspaces and dully constrained subspace level problems, which aims to minimize the energy consumption. Instead of each subspace representing the traditional design disciplines (e.g. aerodynamics, structures, stability, etc), the author has chosen to make a different subspace out of each flight stage (e.g. take-off, climb, cruise, etc). The main reason for this choice was the inclusion of morphing technologies as part of the optimization process, namely a variable span wing (VSW), a variable camber flap (VCF) and a variable propeller pitch (VPP). The software final output is the combination of design variables that better suits the objective function subjected to the design constraints. The results have shown how the selection of the optimum combination of morphing/adaptive technologies highly depends on the mission profile. Moreover, the morphing mechanisms weight has a strong impact on the overall performance, which is not easily grasped without an optimization methodology like the one presented. Globally, these two methodologies foster a more efficient and effective preliminary design stage by feeding the designer’s decision-making process with a large set of relevant data.