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采用高效准确的浸入边界方法模拟颅内血液动力学。

Simulation of intracranial hemodynamics by an efficient and accurate immersed boundary scheme.

机构信息

Department of Physics, University of Patras, Rion, Greece.

Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Australia.

出版信息

Int J Numer Method Biomed Eng. 2021 Dec;37(12):e3524. doi: 10.1002/cnm.3524. Epub 2021 Sep 15.

Abstract

We use computational fluid dynamics (CFD) to simulate blood flow in intracranial aneurysms (IAs). Despite ongoing improvements in the accuracy and efficiency of body-fitted CFD solvers, generation of a high quality mesh appears as the bottleneck of the flow simulation and strongly affects the accuracy of the numerical solution. To overcome this drawback, we use an immersed boundary method. The proposed approach solves the incompressible Navier-Stokes equations on a rectangular (box) domain discretized using uniform Cartesian grid using the finite element method. The immersed object is represented by a set of points (Lagrangian points) located on the surface of the object. Grid local refinement is applied using an automated algorithm. We verify and validate the proposed method by comparing our numerical findings with published experimental results and analytical solutions. We demonstrate the applicability of the proposed scheme on patient-specific blood flow simulations in IAs.

摘要

我们使用计算流体动力学(CFD)模拟颅内动脉瘤(IA)中的血流。尽管针对贴体 CFD 求解器的准确性和效率的持续改进,但高质量网格的生成似乎是流模拟的瓶颈,并强烈影响数值解的准确性。为了克服这一缺点,我们使用浸入边界方法。所提出的方法在使用有限元法离散的矩形(盒)域上求解不可压缩的纳维-斯托克斯方程。浸入物体由位于物体表面的一组点(拉格朗日点)表示。通过使用自动算法进行网格局部细化。我们通过将我们的数值结果与已发表的实验结果和解析解进行比较,验证和验证了所提出的方法。我们在针对 IA 中的患者特定血流模拟的应用中展示了所提出方案的适用性。

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