Original Paper

Computational Mechanics

, Volume 46, Issue 1, pp 17-29

Multiscale sequentially-coupled arterial FSI technique

  • Tayfun E. TezduyarAffiliated withMechanical Engineering, Rice University, MS 321 Email author 
  • , Kenji TakizawaAffiliated withMechanical Engineering, Rice University, MS 321
  • , Creighton MoormanAffiliated withMechanical Engineering, Rice University, MS 321
  • , Samuel WrightAffiliated withMechanical Engineering, Rice University, MS 321
  • , Jason ChristopherAffiliated withMechanical Engineering, Rice University, MS 321

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Abstract

Multiscale versions of the Sequentially-Coupled Arterial Fluid–Structure Interaction (SCAFSI) technique are presented. The SCAFSI technique was introduced as an approximate FSI approach in arterial fluid mechanics. It is based on the assumption that the arterial deformation during a cardiac cycle is driven mostly by the blood pressure. First we compute a “reference” arterial deformation as a function of time, driven only by the blood pressure profile of the cardiac cycle. Then we compute a sequence of updates involving mesh motion, fluid dynamics calculations, and recomputing the arterial deformation. The SCAFSI technique was developed and tested in conjunction with the stabilized space–time FSI (SSTFSI) technique. Beyond providing a computationally more economical alternative to the fully coupled arterial FSI approach, the SCAFSI technique brings additional flexibility, such as being able to carry out the computations in a spatially or temporally multiscale fashion. In the test computations reported here for the spatially multiscale versions of the SCAFSI technique, we focus on a patient-specific middle cerebral artery segment with aneurysm, where the arterial geometry is based on computed tomography images. The arterial structure is modeled with the continuum element made of hyperelastic (Fung) material.

Keywords

Cardiovascular fluid mechanics Fluid–structure interaction Sequentially-coupled arterial FSI Multiscale Space–time methods Cerebral aneurysm Hyperelastic material Patient-specific data