Efficient prediction and uncertainty propagation of correlated loads

Aircraft structural design is influenced by the static and dynamic loads resulting from flight manoeuvres, gust/turbulence encounters and ground manoeuvres; thus the identification of such loads is crucial for the development and structural analysis of aircraft, requiring the solution of the aeroelastic dynamic responses. Numerical aeroelastic models are used to predict a large number (1000s) of “Interesting Quantities” (IQs), and for aircraft design the identification of the worst cases for each IQ is very important, but involves a significant computational effort. Of particular interest are the so-called correlated loads, where coincident values of pairs of IQs are plotted against each other. This paper demonstrates how to reduce the computational burden to determine the behaviour of the correlated loads envelopes with little reduction in the accuracy, and also to quantify the effects of uncertainty, for a range of different parameters. The methodology is demonstrated on a numerical aeroelastic wing model of a civil jet airliner.