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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Published on 26/05/23
Submitted on 26/05/23

Volume Adaptive Methods for Surrogate and Reduced Order Modeling, 2023
DOI: 10.23967/admos.2023.009
Licence: CC BY-NC-SA license

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