Abstract
Recently, surrogate modeling methods have been explored for structural acoustics applications. These often involve evaluation of an “expensive” high-fidelity computational model to obtain training data. However, in many applications, models of varying fidelity and computational cost are available. In such situations, one can leverage multi-fidelity surrogate modeling, where the training data from models of varying fidelity are combined and simultaneously used to produce a surrogate model. A particularly popular class of multi-fidelity surrogate modeling techniques is known as co-Kriging, where simulation output from both “expensive” and “cheap” computational models are correlated and a correction process is obtained that maps between the results of these models of varying fidelity. This talk will review co-Kriging and demonstrate its utility on a canonical structural acoustics problem. [Work supported by the Office of Naval Research.]
Published Version
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