Uncertainty quantification for worst case gust loads prediction

A system identification based approach is introduced to enable rapid prediction of worst case 1D and 2D gust loads. Using a simple 5 DOF flexible aircraft model, it is shown how the system identification method can be simply incorporated with a surrogate modeling approach, Kriging in this case, to determine worst case loads with a 97% reduction in computation compared to a brute force approach. The methodology is then used for preliminary studies into the prediction of the effects of uncertainty in stiffness and aerodynamics on the worst case gust responses.