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Adaptive Mesh Refinement Method Applied to Shallow Water Model: A Mass Conservative Projection

Authors :
F. Golay
R. Marcer
K. Pons
Institut de Mathématiques de Toulon - EA 2134 (IMATH)
Université de Toulon (UTLN)
Principia [La Ciotat]
This work has been done in the framework of the French national research project TANDEM (Tsunamis in the Atlantic and the English ChaNnel: De nition of the Effects through Numerical Modeling). This project is supported by the French government (Projets Investissement d'Avenir, agreement reference number ANR-11-RSNR-0023- 01).
Source :
Topical Problems of Fluid Mechanics 2017, Topical Problems of Fluid Mechanics 2017, Feb 2017, Prague, Czech Republic. ⟨10.14311/TPFM.2017.032⟩
Publication Year :
2017
Publisher :
HAL CCSD, 2017.

Abstract

International audience; In the tsunami waves context, efficient numerical methods are necessary to simulate multiscales events. One way to reduce the computational cost is to use an adaptive mesh refinement method on unstructured meshes. This approach is used in this paper with a finite volume scheme solving the multi-dimensional Saint-Venant system. The adaptive mesh refinement method follows a block-based decomposition (called BB-AMR), which allows quick meshing and easy parallelization. One step of the AMR method is the so-called projection step where the new mesh values have to be defined from the old ones. For vertically integrated model the bathymetry variation during the projection step plays a crucial role on the mass conservation. To avoid large deficit or excess of mass a special attention is given to the projection step. Finally a 3D test case simulation is compared to experimental results to illustrated the quasi conservation of the mass with an appropriated projection method.

Details

Language :
English
Database :
OpenAIRE
Journal :
Topical Problems of Fluid Mechanics 2017, Topical Problems of Fluid Mechanics 2017, Feb 2017, Prague, Czech Republic. ⟨10.14311/TPFM.2017.032⟩
Accession number :
edsair.doi.dedup.....0fd0d6e82f82e9abb8caef20beda139f
Full Text :
https://doi.org/10.14311/TPFM.2017.032⟩