A data-driven surrogate modeling approach for time-dependent incompressible Navier-Stokes equations with dynamic mode decomposition and manifold interpolation
CC BY
Lưu vào:
| Tác giả chính: | , , |
|---|---|
| Định dạng: | Sách |
| Ngôn ngữ: | English |
| Nhà xuất bản: |
Springer
2023
|
| Chủ đề: | |
| Truy cập trực tuyến: | https://link.springer.com/article/10.1007/s10444-023-10016-4 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7605 |
| Từ khóa: |
Thêm từ khóa
Không có từ khóa, Hãy là người đầu tiên đánh dấu biểu ghi này!
|
| id |
oai:localhost:PNK-7605 |
|---|---|
| record_format |
dspace |
| spelling |
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 |
| institution |
Digital Phenikaa |
| collection |
Digital Phenikaa |
| language |
English |
| topic |
data-driven model reduction Rayleigh-Bénard cavity problem |
| spellingShingle |
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 |
8.893527 |