Publications Details

Recent advancements in multilevel-multifidelity techniques for forward UQ in the DARPA sequoia project

Geraci, Gianluca G.; Eldred, Michael S.; Gorodetsky, Alex A.; Jakeman, John D.

In the context of the DARPA funded project SEQUOIA we are interested in the design under uncertainty of a jet engine nozzle subject to the performance requirements of a reconnaissance mission for a small unmanned military aircraft. This design task involves complex and expensive aero-thermo-structural computational analyses where it is of a paramount importance to also include the effect of the uncertain variables to obtain reliable predictions of the device’s performance. In this work we focus on the forward propagation analysis which is a key part of the design under uncertainty workflow. This task cannot be tackled directly by means of single fidelity approaches due to the prohibitive computational cost associated to each realization. We report here a summary of our latest advancement regarding several multilevel and multifidelity strategies designed to alleviate these challenges. The overall goal of these techniques is to reduce the computational cost of analyzing a high-fidelity model by resorting to less accurate, but less computationally demanding, lower fidelity models. The features of these multifidelity UQ approaches are initially illustrated and demonstrated on several model problems and afterward for the aero-thermo-structural analysis of the jet engine nozzle.