Intrusive and data-driven reduced order modelling of the rotating thermal shallow water equation
Yazarlar (3)
Bülent Karasözen
Middle East Technical University (Metu), Türkiye
Middle East Technical University (Metu), Türkiye
Doç. Dr. Süleyman Yıldız Middle East Technical University (Metu), Türkiye
Prof. Dr. Murat UZUNCA Sinop Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Applied Mathematics and Computation (Q1) | ||
| Dergi ISSN | 0096-3003 Dergi Bilgileri (2022) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2022 |
| Cilt / Sayı / Sayfa | 421 / 1 / 126924–0 | DOI | 10.1016/j.amc.2022.126924 |
| Makale Linki | http://dx.doi.org/10.1016/j.amc.2022.126924 | ||
| UAK Araştırma Alanları |
Uygulamalı Matematik
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| Özet |
| In 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 … |
| Anahtar Kelimeler |
| Finite differences | Fluids | Hamiltonian systems | Least-squares | Model order reduction |
Science Direct
Intrusive and data-driven reduced order modelling of the rotating thermal shallow water equation
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 6 |
| Scopus | 6 |
| Google Scholar | 8 |