Error analysis of proper orthogonal decomposition data assimilation schemes with grad–div stabilization for the Navier–Stokes equations
The error analysis of a proper orthogonal decomposition (POD) data assimilation (DA) scheme for the Navier–Stokes equations is carried out. A grad–div stabilization term is added to the formulation of the POD method. Error bounds with constants independent on inverse powers of the viscosity paramete...
| Authors: | , , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2022 |
| Country: | España |
| Institution: | Universidad de Sevilla (US) |
| Repository: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/134932 |
| Online Access: | https://hdl.handle.net/11441/134932 https://doi.org/10.1016/j.cam.2022.114246 |
| Access Level: | Open access |
| Keyword: | Data assimilation Navie–Stokes equations Uniform-in-time error estimates Proper orthogonal decomposition Fully discrete schemes Mixed finite elements methods |
| Summary: | The error analysis of a proper orthogonal decomposition (POD) data assimilation (DA) scheme for the Navier–Stokes equations is carried out. A grad–div stabilization term is added to the formulation of the POD method. Error bounds with constants independent on inverse powers of the viscosity parameter are derived for the POD algorithm. No upper bounds in the nudging parameter of the data assimilation method are required. Numerical experiments show that, for large values of the nudging parameter, the proposed method rapidly converges to the real solution, and greatly improves the overall accuracy of standard POD schemes up to low viscosities over predictive time intervals. |
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