Print Email Facebook Twitter A fully adaptive nonintrusive reduced-order modelling approach for parametrized time-dependent problems Title A fully adaptive nonintrusive reduced-order modelling approach for parametrized time-dependent problems Author Alsayyari, F.S. (TU Delft RST/Reactor Physics and Nuclear Materials) Perko, Z. (TU Delft RST/Reactor Physics and Nuclear Materials) Tiberga, M. (TU Delft RST/Reactor Physics and Nuclear Materials) Kloosterman, J.L. (TU Delft RST/Radiation, Science and Technology) Lathouwers, D. (TU Delft RST/Reactor Physics and Nuclear Materials) Department RST/Radiation, Science and Technology Date 2021 Abstract We present an approach to build a reduced-order model for nonlinear, time-dependent, parametrized partial differential equations in a nonintrusive manner. The approach is based on combining proper orthogonal decomposition (POD) with a Smolyak hierarchical interpolation model for the POD coefficients. The sampling of the high-fidelity model to generate the snapshots is based on a locally adaptive sparse grid method. The novelty of the work is in the adaptive sampling of time, which is treated as an additional parameter. The goal is to have a robust and efficient sampling strategy that minimizes the risk of overlooking important dynamics of the system while disregarding snapshots at times when the dynamics are not contributing to the construction of the reduced model. The developed algorithm was tested on three numerical tests. The first was an advection problem parametrized with a five-dimensional space. The second was a lid-driven cavity test, and the last was a neutron diffusion problem in a subcritical nuclear reactor with 11 parameters. In all tests, the algorithm was able to detect and include more snapshots in important transient windows, which produced accurate and efficient representations of the high-fidelity models. Subject Data-drivenGreedyLocally adaptive sparse gridProper orthogonal decompositionTime-adaptive To reference this document use: http://resolver.tudelft.nl/uuid:a90b88f1-5c0c-4268-82e6-213f52a2f19e DOI https://doi.org/10.1016/j.cma.2020.113483 ISSN 0045-7825 Source Computer Methods in Applied Mechanics and Engineering, 373 Part of collection Institutional Repository Document type journal article Rights © 2021 F.S. Alsayyari, Z. Perko, M. Tiberga, J.L. Kloosterman, D. Lathouwers Files PDF 1_s2.0_S004578252030668X_main.pdf 3 MB Close viewer /islandora/object/uuid:a90b88f1-5c0c-4268-82e6-213f52a2f19e/datastream/OBJ/view