Relative Importance of Uncertain Parameters in Aerospace Applications

Sophisticated numerical models play a crucial role in the design of aerospatial structures. While there is general agreement that many parameters of these complex finite element models are affected by uncertainty, it is typically not apparent which of the parameters are the most important ones, in terms of their impact on the response quantity of interest. The bruteforce approach, i.e. analysing the impact of each uncertain parameter individually, is unacceptable due to its exorbitant computational cost. A recently developed algorithm, which makes use of the cross-correlation between the uncertain parameters and the response, is capable of quickly filtering out the most important parameters and delivers a parsimonious estimate of the relative importance of the uncertain parameters. In the present contribution, the application to a satellite structure with 120,000 DOF’s and 1,300 uncertain parameters is demonstrated, along with the full verification using the brute-force approach. It is shown that with the proposed algorithm, the required computational efforts are reduced by one order of magnitude.