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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2002.11329 |
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| _version_ | 1866929721213714432 |
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| author | Dutta, Sourav Farthing, Matthew W. Perracchione, Emma Savant, Gaurav Putti, Mario |
| author_facet | Dutta, Sourav Farthing, Matthew W. Perracchione, Emma Savant, Gaurav Putti, Mario |
| contents | In this work, we develop Non-Intrusive Reduced Order Models (NIROMs) that combine Proper Orthogonal Decomposition (POD) with a Radial Basis Function (RBF) interpolation method to construct efficient reduced order models for time-dependent problems arising in large scale environmental flow applications. The performance of the POD-RBF NIROM is compared with a traditional nonlinear POD (NPOD) model by evaluating the accuracy and robustness for test problems representative of riverine flows. Different greedy algorithms are studied in order to determine a near-optimal distribution of interpolation points for the RBF approximation. A new power-scaled residual greedy (psr-greedy) algorithm is proposed to address some of the primary drawbacks of the existing greedy approaches. The relative performances of these greedy algorithms are studied with numerical experiments using realistic two-dimensional (2D) shallow water flow applications involving coastal and riverine dynamics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2002_11329 |
| institution | arXiv |
| publishDate | 2020 |
| record_format | arxiv |
| spellingShingle | A greedy non-intrusive reduced order model for shallow water equations Dutta, Sourav Farthing, Matthew W. Perracchione, Emma Savant, Gaurav Putti, Mario Computational Physics Computational Engineering, Finance, and Science Fluid Dynamics 41A05, 65D05, 65M60 In this work, we develop Non-Intrusive Reduced Order Models (NIROMs) that combine Proper Orthogonal Decomposition (POD) with a Radial Basis Function (RBF) interpolation method to construct efficient reduced order models for time-dependent problems arising in large scale environmental flow applications. The performance of the POD-RBF NIROM is compared with a traditional nonlinear POD (NPOD) model by evaluating the accuracy and robustness for test problems representative of riverine flows. Different greedy algorithms are studied in order to determine a near-optimal distribution of interpolation points for the RBF approximation. A new power-scaled residual greedy (psr-greedy) algorithm is proposed to address some of the primary drawbacks of the existing greedy approaches. The relative performances of these greedy algorithms are studied with numerical experiments using realistic two-dimensional (2D) shallow water flow applications involving coastal and riverine dynamics. |
| title | A greedy non-intrusive reduced order model for shallow water equations |
| topic | Computational Physics Computational Engineering, Finance, and Science Fluid Dynamics 41A05, 65D05, 65M60 |
| url | https://arxiv.org/abs/2002.11329 |