Geometrical Based Method for the Uncertainty Quantification of Correlated Aircraft Loads

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.

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