H. Sreekumar, L. Outzen, U. Römer, S. Langer
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 26/05/23Submitted on 26/05/23
Volume Adaptive Methods for Surrogate and Reduced Order Modeling, 2023DOI: 10.23967/admos.2023.009Licence: CC BY-NC-SA license
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