Intrusive and data-driven reduced order modelling of the rotating thermal shallow water equation

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dc.authoridUzunca, Murat/0000-0001-5262-063X
dc.contributor.authorKarasozen, Bulent
dc.contributor.authorYildiz, Suleyman
dc.contributor.authorUzunca, Murat
dc.date.accessioned2025-03-23T19:42:10Z
dc.date.available2025-03-23T19:42:10Z
dc.date.issued2022
dc.departmentSinop Üniversitesi
dc.description.abstractIn this paper, we investigate projection-based intrusive and data-driven model order reduction in numerical simulation of rotating thermal shallow water equation (RTSWE) in parametric and non-parametric form. Discretization of the RTSWE in space with centered finite differences leads to Hamiltonian system of ordinary differential equations with linear and quadratic terms. The full-order model (FOM) is obtained by applying linearly implicit Kahan's method in time. Applying proper orthogonal decomposition with Galerkin projection (POD-G), we construct the intrusive reduced-order model (ROM). We apply operator inference (OpInf) with re-projection as data-driven ROM. In the parametric case, we make use of the parameter dependency at the level of the PDE without interpolating between the reduced operators. The least-squares problem of the OpInf is regularized with the minimum norm solution. Both ROMs behave similarly and are able to accurately predict the in the test and training data and capture system behaviour in the prediction phase with several orders of magnitude in computational speed-up over the FOM. The preservation of system physics such as the conserved quantities of the RTSWE by both ROMs enable that the models fit better to data and stable solutions are obtained in long-term predictions which are robust to parameter changes. (C) 2022 Elsevier Inc. All rights reserved.
dc.identifier.doi10.1016/j.amc.2022.126924
dc.identifier.issn0096-3003
dc.identifier.issn1873-5649
dc.identifier.scopus2-s2.0-85122597527
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.amc.2022.126924
dc.identifier.urihttps://hdl.handle.net/11486/6716
dc.identifier.volume421
dc.identifier.wosWOS:000782653800005
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Science Inc
dc.relation.ispartofApplied Mathematics and Computation
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250323
dc.subjectModel order reduction
dc.subjectFinite differences
dc.subjectHamiltonian systems
dc.subjectFluids
dc.subjectLeast-squares
dc.titleIntrusive and data-driven reduced order modelling of the rotating thermal shallow water equation
dc.typeArticle

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