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Two level algorithms for partitioned fluid–structure interaction computations

✍ Scribed by A.H. van Zuijlen; S. Bosscher; H. Bijl


Publisher
Elsevier Science
Year
2007
Tongue
English
Weight
314 KB
Volume
196
Category
Article
ISSN
0045-7825

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✦ Synopsis


In this paper we use the multigrid algorithm -commonly used to improve the efficiency of the flow solver -to improve the efficiency of partitioned fluid-structure interaction iterations. Coupling not only the structure with the fine flow mesh, but also with the coarse flow mesh (often present due to the multigrid scheme) leads to a significant efficiency improvement. As solution of the flow equations typically takes much longer than the structure solve, and as multigrid is not standard in structure solvers, we do not coarsen the structure or the interface. As a result, the two level method can be easily implemented into existing solvers.

Two types of two level algorithms were implemented: (1) coarse grid correction of the partitioning error and (2) coarse grid prediction or full multigrid to generate a better initial guess. The resulting schemes are combined with a fourth-order Runge-Kutta implicit time integration scheme. For the linear, one-dimensional piston problem with compressible flow the superior stability, accuracy and efficiency of the two level algorithms is shown. The parameters of the piston problem were chosen such that both a weak and a strong interaction case were obtained.

Even the strong interaction case, with a flexible structure, could be solved with our new two level partitioned scheme with just one iteration on the fine grid. This is a major accomplishment as most weakly coupled methods fail in this case. Of the two algorithms the coarse grid prediction or full multigrid method was found to perform best. The resulting efficiency gain for our one-dimensional problem is around a factor of ten for the coarse to intermediate time steps at which the high-order time integration methods should be run. For two-and three-dimensional problems the efficiency gain is expected to be even larger.


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