Nonintrusive model order reduction for cross-diffusion systems
Yazarlar (3)
Bülent Karasözen
Middle East Technical University (Metu), Türkiye
Middle East Technical University (Metu), Türkiye
Gülden Mülayim Adıyaman Üniversitesi, Türkiye
Prof. Dr. Murat UZUNCA Sinop Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Communications in Nonlinear Science and Numerical Simulation (Q1) | ||
| Dergi ISSN | 1007-5704 Dergi Bilgileri (2022) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 12-2022 |
| Cilt / Sayı / Sayfa | 115 / 1 / 106734–0 | DOI | 10.1016/j.cnsns.2022.106734 |
| Makale Linki | http://dx.doi.org/10.1016/j.cnsns.2022.106734 | ||
| UAK Araştırma Alanları |
Uygulamalı Matematik
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| Özet |
| In this paper, we investigate tensor based nonintrusive reduced-order models (ROMs) for parametric cross-diffusion equations. The full-order model (FOM) consists of ordinary differential equations (ODEs) in matrix or tensor form resulting from finite difference discretization of the differential operators by taking the advantage of Kronecker structure. The matrix/tensor differential equations are integrated in time with the implicit–explicit (IMEX) Euler method. The reduced bases, relying on a finite sample set of parameter values, are constructed in form of a two-level approach by applying higher-order singular value decomposition (HOSVD) to the space–time snapshots in tensor form, which leads to a large amount of computational and memory savings. The nonintrusive reduced approximation for an arbitrary parameter value is obtained through tensor product of the reduced basis by the parameter dependent core tensor … |
| Anahtar Kelimeler |
| Implicit–explicit methods | Matrix differential equations | Reduced-order modeling | Tensor algebra |
Science Direct
Nonintrusive model order reduction for cross-diffusion systems
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| Atıf Sayıları | |
| Web of Science | 1 |
| Scopus | 1 |
| Google Scholar | 1 |