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首页> 外文期刊>Journal of Computational Physics >A nonlinear elimination preconditioned inexact Newton method for blood flow problems in human artery with stenosis
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A nonlinear elimination preconditioned inexact Newton method for blood flow problems in human artery with stenosis

机译:一种非线性消除预处理鼻腔血流问题的预处理牛顿方法

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Simulation of blood flows in the human artery is a promising tool for understanding the hemodynamics. The blood flow is often smooth in a healthy artery, but may become locally chaotic in a diseased artery with stenosis, and as a result, a traditional solver may take many iterations to converge or does not converge at all. To overcome the problem, we develop a nonlinearly preconditioned Newton method in which the variables associated with the stenosis are iteratively eliminated and then a global Newton method is applied to the smooth part of the system. More specifically, we model the blood flow in a patient-specific artery based on the unsteady incompressible Navier-Stokes equations with resistive boundary conditions discretized by a fully implicit finite element method. The resulting nonlinear system at each time step is solved by using an inexact Newton method with a domain decomposition based Jacobian solver. To improve the convergence and robustness of the Newton method for arteries with stenosis, we develop an adaptive restricted region-based nonlinear elimination preconditioner which performs subspace correction to remove the local high nonlinearities. Numerical experiments for several cerebral arteries are presented to demonstrate the superiority of the proposed algorithm over the classical method with respect to some physical and numerical parameters. We also report the parallel scalability of the proposed algorithm on a supercomputer with thousands of processor cores. (C) 2019 Elsevier Inc. All rights reserved.
机译:人动动脉血流的模拟是理解血流动力学的有希望的工具。血流通常在健康的动脉中平滑,但可能在狭窄的患病动脉中局部混乱,结果,传统的求解器可能需要多次迭代来融合或根本不收敛。为了克服这个问题,我们开发了一种非线性预处理的牛顿方法,其中与狭窄相关的变量迭代地消除,然后将全球牛顿方法应用于系统的平滑部分。更具体地,我们基于由完全隐含的有限元方法离散化的电阻边界条件的不稳定不可压缩的Navier-Stokes方程来模拟患者特异性动脉中的血流。通过使用具有基于域分解的雅比亚求解器的域分解的不适的牛顿方法来解决每个时间步骤的所得到的非线性系统。为了提高具有狭窄动脉的牛顿方法的收敛性和稳健性,我们开发了一种自适应限制的基于区域的非线性消除预处理器,该校正者进行子空间校正以去除本地高非线性。提出了几种脑动脉的数值实验,以展示关于一些物理和数值参数在经典方法上提出的算法的优越性。我们还报告了具有成千上万处理器核心的超级计算机上所提出的算法的并行可扩展性。 (c)2019 Elsevier Inc.保留所有权利。

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