A data-driven surrogate modeling approach for time-dependent incompressible Navier-Stokes equations with dynamic mode decomposition and manifold interpolation
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2023
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oai:localhost:PNK-76052023-04-06T02:05:19Z A data-driven surrogate modeling approach for time-dependent incompressible Navier-Stokes equations with dynamic mode decomposition and manifold interpolation Martin W., Hess Annalisa, Quaini Gianluigi, Rozza data-driven model reduction Rayleigh-Bénard cavity problem CC BY This work introduces a novel approach for data-driven model reduction of time-dependent parametric partial differential equations. Using a multi-step procedure consisting of proper orthogonal decomposition, dynamic mode decomposition, and manifold interpolation, the proposed approach allows to accurately recover field solutions from a few large-scale simulations. Numerical experiments for the Rayleigh-Bénard cavity problem show the effectiveness of such multi-step procedure in two parametric regimes, i.e., medium and high Grashof number. The latter regime is particularly challenging as it nears the onset of turbulent and chaotic behavior. 2023-04-06T02:05:19Z 2023-04-06T02:05:19Z 2023 Book https://link.springer.com/article/10.1007/s10444-023-10016-4 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7605 en application/pdf Springer |
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English |
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data-driven model reduction Rayleigh-Bénard cavity problem |
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data-driven model reduction Rayleigh-Bénard cavity problem Martin W., Hess Annalisa, Quaini Gianluigi, Rozza A data-driven surrogate modeling approach for time-dependent incompressible Navier-Stokes equations with dynamic mode decomposition and manifold interpolation |
description |
CC BY |
format |
Book |
author |
Martin W., Hess Annalisa, Quaini Gianluigi, Rozza |
author_facet |
Martin W., Hess Annalisa, Quaini Gianluigi, Rozza |
author_sort |
Martin W., Hess |
title |
A data-driven surrogate modeling approach for time-dependent incompressible Navier-Stokes equations with dynamic mode decomposition and manifold interpolation |
title_short |
A data-driven surrogate modeling approach for time-dependent incompressible Navier-Stokes equations with dynamic mode decomposition and manifold interpolation |
title_full |
A data-driven surrogate modeling approach for time-dependent incompressible Navier-Stokes equations with dynamic mode decomposition and manifold interpolation |
title_fullStr |
A data-driven surrogate modeling approach for time-dependent incompressible Navier-Stokes equations with dynamic mode decomposition and manifold interpolation |
title_full_unstemmed |
A data-driven surrogate modeling approach for time-dependent incompressible Navier-Stokes equations with dynamic mode decomposition and manifold interpolation |
title_sort |
data-driven surrogate modeling approach for time-dependent incompressible navier-stokes equations with dynamic mode decomposition and manifold interpolation |
publisher |
Springer |
publishDate |
2023 |
url |
https://link.springer.com/article/10.1007/s10444-023-10016-4 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7605 |
_version_ |
1762456091234402304 |
score |
8.891053 |