Abstract
We present the multiscale space–time techniques we have developed for fluid–structure interaction (FSI) computations. Some of these techniques are multiscale in the way the time integration is performed (i.e. temporally multiscale), some are multiscale in the way the spatial discretization is done (i.e. spatially multiscale), and some are in the context of the sequentially-coupled FSI (SCFSI) techniques developed by the Team for Advanced Flow Simulation and Modeling \({({\rm T} \bigstar {\rm AFSM})}\). In the multiscale SCFSI technique, the FSI computational effort is reduced at the stage we do not need it and the accuracy of the fluid mechanics (or structural mechanics) computation is increased at the stage we need accurate, detailed flow (or structure) computation. As ways of increasing the computational accuracy when or where needed, and beyond just increasing the mesh refinement or decreasing the time-step size, we propose switching to more accurate versions of the Deforming-Spatial-Domain/Stabilized Space–Time (DSD/SST) formulation, using more polynomial power for the basis functions of the spatial discretization or time integration, and using an advanced turbulence model. Specifically, for more polynomial power in time integration, we propose to use NURBS, and as an advanced turbulence model to be used with the DSD/SST formulation, we introduce a space–time version of the residual-based variational multiscale method. We present a number of test computations showing the performance of the multiscale space–time techniques we are proposing. We also present a stability and accuracy analysis for the higher-accuracy versions of the DSD/SST formulation.
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Takizawa, K., Tezduyar, T.E. Multiscale space–time fluid–structure interaction techniques. Comput Mech 48, 247–267 (2011). https://doi.org/10.1007/s00466-011-0571-z
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DOI: https://doi.org/10.1007/s00466-011-0571-z
Keywords
- Fluid–structure interaction
- Space–time formulations
- Multiscale techniques
- Sequential coupling techniques
- NURBS
- Space–time variational multiscale method