Parameterization of Large Variability Using the Hyper-Dual Meta-Model

One major problem in the design of aerospace components is the nonlinear changes in the response due to a change in the geometry and material properties. Many of these components have small nominal values and any change can lead to a large variability. In order to characterize this large variability, traditional methods require either many simulation runs or the calculations of many higher order derivatives. Each of these paths requires a large amount of computational power to evaluate the response curve. In order to perform uncertainty quantification analysis, even more simulation runs are required. The hyper-dual meta-model is used to characterize the response curve with the use of basis functions. The information of the curve is generated with the utilization of the hyper-dual step to determine the sensitivities at a few number of simulation runs. This paper shows the accuracy of this method for two different systems with parameterization at different stages in the design.