==Abstract==

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This contribution presents a combined framework to perform parametric

surrogate modeling of vibroacoustic problems that enables efficient training of large-scale

problems. The proposed framework combines the active subspace method to perform

dimensionality reduction of high-dimensional problems and thereafter a clustering-based

approach within the identified active subspace region to yield smaller training clusters.

Finally, a trained neural network assists the cluster classification task for any desired

parameter point so as to query the parametric system response during the online phase.

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