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首页> 外文期刊>Journal of Computational Physics >Scalable parallel methods for monolithic coupling in fluid-structure interaction with application to blood flow modeling
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Scalable parallel methods for monolithic coupling in fluid-structure interaction with application to blood flow modeling

机译：整体耦合在流固耦合中的可扩展并行方法及其在血流建模中的应用

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摘要

We introduce and study numerically a scalable parallel finite element solver for the simulation of blood flow in compliant arteries. The incompressible Navier-Stokes equations are used to model the fluid and coupled to an incompressible linear elastic model for the blood vessel walls. Our method features an unstructured dynamic mesh capable of modeling complicated geometries, an arbitrary Lagrangian-Eulerian framework that allows for large displacements of the moving fluid domain, monolithic coupling between the fluid and structure equations, and fully implicit time discretization. Simulations based on blood vessel geometries derived from patient-specific clinical data are performed on large supercomputers using scalable Newton-Krylov algorithms preconditioned with an overlapping restricted additive Schwarz method that preconditions the entire fluid-structure system together. The algorithm is shown to be robust and scalable for a variety of physical parameters, scaling to hundreds of processors and millions of unknowns.
机译：我们引入并数值研究可扩展并行有限元求解器，以模拟顺应性动脉中的血流。不可压缩的Navier-Stokes方程用于对流体建模，并耦合到用于血管壁的不可压缩的线性弹性模型。我们的方法的特点是能够建模复杂几何形状的非结构化动态网格，允许移动流体域发生大位移的任意Lagrangian-Eulerian框架，流体与结构方程之间的整体耦合以及完全隐式的时间离散化。在大型超级计算机上，使用可扩展的Newton-Krylov算法进行了基于源自患者特定临床数据的血管几何结构的模拟，该算法采用了重叠的受限加性Schwarz方法进行预处理，该方法将整个流体结构系统一起进行了预处理。该算法针对各种物理参数显示出鲁棒性和可扩展性，可扩展到数百个处理器和数百万个未知数。

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