An efficient temporal multiscale algorithm for simulating a long-term plaque growth problem in relation to power-law blood flows

IF 2.6 2区 数学 Q1 MATHEMATICS, APPLIED Journal of Computational and Applied Mathematics Pub Date : 2025-04-04 DOI:10.1016/j.cam.2025.116666
Xinyu Li , Ping Lin , Weifeng Zhao
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Abstract

This paper discusses the problem of non-Newtonian fluids with time multiscale characteristics, especially considering the type of power-law blood flow in a narrowed blood vessel due to plaque growth. In the vessel, the blood flow is considered as a fast-scale periodic motion, while the vessel wall grows on a slow scale. We use an auxiliary temporal periodic problem and an effective time-average equation to approximate the original problem. The approximation error is analyzed only for a largely simplified linear system, where the simple front-tracking technique is used to update the slow vessel wall growth. An effective multiscale method is then designed based on the approximation problem. The front-tracking technique also makes the implementation of the multiscale algorithm easier. Compared with the traditional direct solving process, this method shows a strong acceleration effect. Finally, we present a concrete numerical example. Through comparison, the relative error between the results of the multi-scale algorithm and the direct solving process is small, which is consistent with the theoretical analysis.
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模拟与幂律血流有关的长期斑块生长问题的高效时间多尺度算法
本文讨论了具有时间多尺度特征的非牛顿流体问题,特别是考虑了由于斑块生长而导致的血管狭窄的幂律血流类型。在血管中,血流被认为是一个快尺度的周期性运动,而血管壁的生长则是一个慢尺度的运动。我们使用一个辅助的时间周期问题和一个有效的时间平均方程来逼近原问题。本文只分析了一个很大程度上简化的线性系统的近似误差,其中使用简单的前跟踪技术来更新缓慢的血管壁生长。然后基于近似问题设计了一种有效的多尺度方法。前跟踪技术也使多尺度算法的实现更加容易。与传统的直接求解方法相比,该方法具有较强的加速效应。最后,给出了一个具体的数值算例。通过比较,多尺度算法与直接求解过程的结果相对误差较小,与理论分析一致。
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来源期刊
CiteScore
5.40
自引率
4.20%
发文量
437
审稿时长
3.0 months
期刊介绍: The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.
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