Multigrid methods for Large-Eddy simulation
The Large-Eddy simulation (LES) method can be used in order to break the multi-scale complexity within turbulent flow simulations, since not all turbulent length scales have to be resolved, but will be given by an appropriate subgrid model. Beside this filtering in space, a filtering in time allows...
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| Main Authors: | , , |
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| Format: | Chapter/Article |
| Language: | English |
| Published: |
2007
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| In: |
Reactive flows, diffusion and transport
Year: 2007, Pages: 375-396 |
| DOI: | 10.1007/978-3-540-28396-6_14 |
| Online Access: | Verlag, Volltext: http://dx.doi.org/10.1007/978-3-540-28396-6_14 Verlag, Volltext: https://link.springer.com/chapter/10.1007/978-3-540-28396-6_14 
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| Author Notes: | A. Gordner, S. Nägele, and G. Wittum |
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| 520 | |a The Large-Eddy simulation (LES) method can be used in order to break the multi-scale complexity within turbulent flow simulations, since not all turbulent length scales have to be resolved, but will be given by an appropriate subgrid model. Beside this filtering in space, a filtering in time allows for larger time steps as well and gives rise to implicit methods, where an algebraic system of equations has to be solved. Multigrid as a numerical multi-scale approach matches LES quite well with that respect and will be applied. It is essential to control the numerical error introduced by the discretisation and numerical solver in order to minimize the influence on the turbulent solution and hence, being able to identify the model error of the subgrid model. Two different stabilization methods, that are used within the collocated Finite Volume dicretisation for unstructured grids, are investigated with respect to their mass conservation error. The obtained solutions will be compared with benchmark solutions found in literature. The used subgrid model takes advantage of mesh dependent parameters. A practical solution within the multigrid procedure is to derive the model parameter on the finest grid level and inject it successively to the coarser grid levels. By this strategy good convergence rates result. | ||
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