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Optimizing multidisciplinary scaled tests in terrestrial atmosphere for extraterrestrial unmanned aerial vehicle missions

机译:针对地面外无人飞行器任务优化在地面大气中的多学科规模测试

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摘要

Unmanned aerial vehicles are a valid tool for exploring celestial objects that have atmosphere. The design process of these vehicles includes numerical analysis phase, which is then followed by an experimental flight test campaign in order to validate and refine the design. In terrestrial conditions, it is impossible to use the full size prototype and recreate all the conditions of extraterrestrial flight. The only option is to use a scaled model maintaining certain similarity parameters to the prototype. This would, however, not reproduce the global multidisciplinary behavior in terrestrial conditions. Alternatively, relaxing similarity constraints enables reproducing the global multidisciplinary behavior but introduces known and measurable similarity differences. The objective of this study is to provide a methodology for designing a relaxed similarity scaled model for terrestrial multidisciplinary tests for any extraterrestrial unmanned aerial vehicle. The methodology is then applied to a case scenario in order to verify its validity.
机译:无人机是探索具有大气层的天体的有效工具。这些飞行器的设计过程包括数值分析阶段,然后进行实验性飞行测试,以验证和完善设计。在地面条件下,不可能使用完整尺寸的原型并重新创建所有地外飞行条件。唯一的选择是使用缩放模型,该模型保持与原型的某些相似性参数。但是,这将不会重现地球条件下的全球多学科行为。或者,放宽相似性约束可以重现全局的多学科行为,但会引入已知的和可测量的相似性差异。这项研究的目的是提供一种方法,用于为任何地面外无人飞行器的地面多学科测试设计一个宽松的相似比例缩放模型。然后将该方法应用于案例方案,以验证其有效性。

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