Viscoelastic dynamic arterial response.

计算机科学 生物医学工程 动脉壁 医学
作者
Haralambia P. Charalambous,Panayiotis C. Roussis,A.E. Giannakopoulos
出处
期刊:Computers in Biology and Medicine [Elsevier BV]
卷期号:89: 337-354 被引量:9
标识
DOI:10.1016/j.compbiomed.2017.07.028
摘要

Abstract Background Arteries undergo large deformations under applied intraluminal pressure and may exhibit small hysteresis due to creep or relaxation process. The mechanical response of arteries depends, among others, on their topology along the arterial tree. Viscoelasticity of arterial tissues, which is the topic investigated in this study, is mainly a characteristic mechanical response of arteries that are located away from the heart and have increased smooth muscle cells content. Methods The arterial wall viscosity is simulated by adopting a generalized Maxwell model and the method of internal variables, as proposed by Bonet and Holzapfel et al. The total stresses consist of elastic long-term stresses and viscoelastic stresses, requiring an iterative procedure for their calculation. The cross-section of the artery is modeled as a circular ring, consisting of a single homogenized layer, under a time-varying blood pressure. Two different loading approximations for the aortic pressure vs time are considered. A novel numerical method is developed in order to solve the controlling integro-differential equation. Results A large number of numerical investigations are performed and typical response time-profiles are presented in pictorial form. Results suggest that the viscoelastic arterial response is mainly affected by the ratio of the relaxation time to the characteristic time of the response and by the pressure-time approximation. Numerical examples, based on data available in the literature, are conducted. Conclusions The investigation presented in this study reveals the effect of each material parameter on the viscoelastic arterial response. Thus, a better understanding of the behavior of viscoelastic arteries is achieved.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Pisces完成签到 ,获得积分10
刚刚
南茶北暖完成签到,获得积分10
刚刚
乐观尔芙完成签到,获得积分10
刚刚
1秒前
1秒前
1秒前
yyyyy发布了新的文献求助20
1秒前
万能图书馆应助瘦瘦采纳,获得10
1秒前
1秒前
田様应助淡淡东蒽采纳,获得10
1秒前
科研通AI6.1应助哈七采纳,获得10
2秒前
3秒前
英吉利25发布了新的文献求助10
3秒前
乐观尔芙发布了新的文献求助10
3秒前
1111发布了新的文献求助10
3秒前
achoo发布了新的文献求助10
3秒前
H_123完成签到,获得积分10
3秒前
日富一日的fighter完成签到,获得积分10
4秒前
4秒前
xh发布了新的文献求助10
4秒前
4秒前
4秒前
mt完成签到 ,获得积分10
5秒前
余德熙发布了新的文献求助10
6秒前
6秒前
6秒前
6秒前
搜集达人应助十年负一生采纳,获得10
7秒前
planck完成签到 ,获得积分10
7秒前
7秒前
YiLu发布了新的文献求助10
7秒前
7秒前
Alane发布了新的文献求助10
8秒前
8秒前
深情安青应助科研狂人采纳,获得10
9秒前
9秒前
9秒前
kk完成签到 ,获得积分20
9秒前
xh完成签到,获得积分10
9秒前
yiyi完成签到 ,获得积分10
9秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Introduction to Helicopter and Tiltrotor Flight Simulation, Second Edition 2500
卤化钙钛矿人工突触的研究 2000
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 600
Bounds for Statistical Estimation in Semiparametric Models 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6500253
求助须知:如何正确求助?哪些是违规求助? 8295484
关于积分的说明 17703437
捐赠科研通 5596922
什么是DOI,文献DOI怎么找? 2918291
邀请新用户注册赠送积分活动 1895341
关于科研通互助平台的介绍 1756247