The International Conference for High Performance Computing, Networking, Storage and Analysis
Investigating Flow-Structure Interactions in Cerebral Aneurysms.
Authors: Joseph A. Insley (Argonne National Laboratory), Paris Perdikaris (Brown University), Leopold Grinberg (IBM Corporation), Yue Yu (Brown University), Michael E. Papka (Argonne National Laboratory), George Em. Karniadakis (Brown University)
Abstract: Modeling flow-structure interaction (FSI) in biological systems, where elastic tissues and fluids have almost identical density (low mass ratio problem), is one of the most challenging problems in computational mechanics. One of the major challenges in FSI simulations at low mass ratio is the stability of semi-implicit coupled fluid-structure solvers. Based on our recent advances in developing stable numerical algorithms we have developed a solver capable of tackling problems with mass ratios approaching zero, enabling high-resolution FSI simulations of biological systems, such as blood flow in compliant arteries. Our coupled solver, NekTar, is based on high-order spectral/hp element discretization and iterative coupling between the fluid and structure (solid) domains. Realistic FSI simulations produce very large and complex data sets, yielding the need for parallel data processing and visualization. Here we present our recent advancements in developing an interactive visualization tool which now enables the visualization of such FSI simulation data. Specifically, we present a ParaView-NekTar interface that couples the ParaView visualization engine with NekTar’s parallel libraries, which are employed for the calculation of derived fields in both the fluid and solid domains with spectral accuracy. This interface significantly facilitates the visualization of complex structures under large deformations. The animation of the fluid and structure data is synchronized in time, while the ParaView-NekTar interface enables the visualization of different fields to be superimposed, e.g. fluid jet and structural stress, to better understand the interactions in this multiphysics environment.