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In this paper the development of statistical metamodels and statistical fast running models is presented first. They are utilized for propagating uncertainties in a multi-discipline design optimization process. Two main types of uncertainty can be considered in this manner: uncertainty due to variability in design variables or in random parameters; uncertainty due to the utilization of metamodels instead of the actual simulation models during the optimization process. The value of the new developments and their engagement in multi-discipline design optimization is demonstrated through a case study. An underwater vehicle is designed under four different disciplines, namely, noise radiation, self-noise due to TBL excitation, dynamic response due to propulsion impact loads, and response to an underwater detonation.

An indirect variational boundary element formulation and two typical applications are presented in this paper. The significance of this method is that it can include openings in the model, and it considers the acoustic medium on both sides. Computationally it is superior to the direct method because the assembled fully populated boundary element matrices are symmetric. The theoretical background is presented. A typical generic interior cab noise analysis is performed. The excitation is comprised by an exterior impinging acoustic field and loads applied at the mounts. The coupled option was selected to solve this problem. A typical acoustic uncoupled radiation analysis is also performed. The noise radiated from a T-drive is computed and the solution time is compared to the direct method.