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Multi-objective Optimization for the Design of an Unconventional Sun-Powered High-Altitude-Long-Endurance Unmanned Vehicle

机译:非常规太阳动力高空长寿无人飞行器设计的多目标优化

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摘要

The use of High Altitude and Long Endurance (HALE) Unmanned Aerial Vehicles (UAVs) is becoming increasingly significant in both military and civil missions as High-Altitude Pseudo-Satellite (HAPS). Since this class of aircraft is usually powered by solar cells, it typically features unconventional configurations to maximize sun exposed surfaces. In the present paper, a Multidisciplinary Design Optimization (MDO) and a Multi-Objective Optimization (MOO) environment have been developed to provide a computational design tool for modeling and designing these unconventional aircraft in order to achieve as independent objectives the maximization of solar power flux, the maximization of the lift-to-drag ratio, and the minimization of mass. To this purpose, a FEM models generator, capable of managing unconventional geometries, and a solar power estimator, are suitably developed to be integrated within a multi objective optimization loop. The simultaneous use of MDO/MOO approaches, and Design Of Experiment (DOE) creation and updating principles, enables to efficiently take into account the multiple and contrasting objectives/constraints arising from the different disciplines involved in the design problem. The study is carried out by using two different commercial codes for multi-objective optimization and for structural and aeroelastic analyses respectively. The use of advanced MDO/MOO approaches revealed to be effective for designing unconventional vehicles.
机译:作为高空伪卫星(HAPS),在军事和民用飞行任务中,高海拔和长寿命(HALE)无人机的使用正变得越来越重要。由于此类飞机通常由太阳能电池提供动力,因此通常具有非常规配置以最大化暴露于阳光下的表面。在本文中,已经开发了多学科设计优化(MDO)和多目标优化(MOO)环境,以提供用于对这些非常规飞机进行建模和设计的计算设计工具,以实现太阳能的最大化作为独立目标。通量,升阻比的最大值和质量的最小值。为此,适当地开发了能够管理非常规几何形状的FEM模型生成器和太阳能估计器,以将其集成到多目标优化循环中。 MDO / MOO方法的同时使用以及实验设计(DOE)的创建和更新原理,可以有效地考虑到涉及设计问题的不同学科所产生的多重且相互对照的目标/约束。这项研究是通过使用两个不同的商业代码进行多目标优化以及分别进行结构和气动弹性分析的。结果表明,使用先进的MDO / MOO方法可以有效地设计非常规车辆。

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