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用于不可压缩纳维-斯托克斯方程的嵌套块预处理技术,重点在于血流动力学模拟。

The nested block preconditioning technique for the incompressible Navier-Stokes equations with emphasis on hemodynamic simulations.

作者信息

Liu Ju, Yang Weiguang, Dong Melody, Marsden Alison L

机构信息

Department of Pediatrics (Cardiology), Department of Bioengineering, and Institute for Computational and Mathematical Engineering, Stanford University, Clark Center E1.3, 318 Campus Drive, Stanford, CA 94305, USA.

出版信息

Comput Methods Appl Mech Eng. 2020 Aug 1;367. doi: 10.1016/j.cma.2020.113122. Epub 2020 May 27.

DOI:10.1016/j.cma.2020.113122
PMID:32675836
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7365595/
Abstract

We develop a novel iterative solution method for the incompressible Navier-Stokes equations with boundary conditions coupled with reduced models. The iterative algorithm is designed based on the variational multiscale formulation and the generalized- scheme. The spatiotemporal discretization leads to a block structure of the resulting consistent tangent matrix in the Newton-Raphson procedure. As a generalization of the conventional block preconditioners, a three-level nested block preconditioner is introduced to attain a better representation of the Schur complement, which plays a key role in the overall algorithm robustness and efficiency. This approach provides a flexible, algorithmic way to handle the Schur complement for problems involving multiscale and multiphysics coupling. The solution method is implemented and benchmarked against experimental data from the nozzle challenge problem issued by the US Food and Drug Administration. The robustness, efficiency, and parallel scalability of the proposed technique are then examined in several settings, including moderately high Reynolds number flows and physiological flows with strong resistance effect due to coupled downstream vasculature models. Two patient-specific hemodynamic simulations, covering systemic and pulmonary flows, are performed to further corroborate the efficacy of the proposed methodology.

摘要

我们针对具有边界条件并与简化模型耦合的不可压缩纳维-斯托克斯方程开发了一种新颖的迭代求解方法。该迭代算法基于变分多尺度公式和广义格式设计。时空离散化在牛顿-拉夫逊过程中导致所得一致切线矩阵具有块结构。作为传统块预条件器的推广,引入了一种三级嵌套块预条件器以更好地表示舒尔补,这在整体算法的稳健性和效率中起着关键作用。这种方法为处理涉及多尺度和多物理场耦合问题的舒尔补提供了一种灵活的算法方式。该求解方法已实现,并与美国食品药品监督管理局发布的喷嘴挑战问题的实验数据进行了基准测试。然后在几种情况下检验了所提技术的稳健性、效率和并行可扩展性,包括中等高雷诺数流动以及由于耦合下游血管模型而具有强阻力效应的生理流动。进行了两个针对特定患者的血液动力学模拟,涵盖全身和肺部流动,以进一步证实所提方法的有效性。

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Fluid-structure interaction modeling of blood flow in the pulmonary arteries using the unified continuum and variational multiscale formulation.使用统一连续体和变分多尺度公式对肺动脉血流进行流固耦合建模。
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