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Geometrical Based Method for the Uncertainty Quantification of Correlated Aircraft Loads

机译:基于几何的相关飞机载荷不确定度量化方法

摘要

The identification of the critical load cases, aircraft configuration and flight conditions is a vital step in the aircraft design process; in particular the loads correlated at individual measurement stations, and between different stations, are of great interest. Typically, the correlation of various `Interesting Quantities', such as bending moment and torque, is described using the so called `potato plot', which are obtained by plotting Interesting Quantities time histories against each others. It is of interest to predict the effects of uncertainty in the structural and aerodynamic parameters on the correlated quantities in an efficient way. A geometrically based method is described enabling identification of probabilistic bounds for the correlated loads whilst still capturing all the information related to the critical cases. The method is demonstrated using gust loads acting on a representative civil jet aeroelastic numerical model, and very accurate yet efficient results are found in comparison to a Monte Carlo Simulation.
机译:在飞机设计过程中,关键载荷情况,飞机配置和飞行条件的识别是至关重要的一步;特别是在各个测量站以及在不同的站之间相关的负载引起了极大的兴趣。通常,使用所谓的“土豆图”来描述各种“有趣的量”(例如弯矩和扭矩)之间的相关性,这些“土豆图”是通过将“有趣的量”的时间历史相互绘制而成的。有趣的是,以有效的方式预测结构和空气动力学参数的不确定性对相关数量的影响。描述了一种基于几何的方法,该方法使得能够识别相关负载的概率边界,同时仍捕获与关键情况有关的所有信息。使用作用在代表性民用航空气动弹性数值模型上的阵风载荷证明了该方法,与蒙特卡洛模拟相比,发现了非常准确而有效的结果。

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