Simulation of blood flow through stenotic and branched arteries
Wishah, MI 2007, Simulation of blood flow through stenotic and branched arteries , PhD thesis, Salford : University of Salford.
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Mathematical and physical models have been developed in order to study blood flow through arteries, numerically and experimentally. The aim of these models was to understand, apply and verify using realistic models how both flow and geometry interact through and downstream of stenosed and branched arteries. This interaction is examined in two ways; initially by investigating the influence of stenosis and branches on flow and then by examining the influence of flow haemodynamics parameters such as Reynolds number, stenosis severity, stenosis shape and bifurcation area ratio on the development of stenosis. In addition, a parametric study was performed to determine the actual influence of the geometry on flow and vice versa. The ability to describe the flow through a stenosed artery provides the possibility of developing imaging enhancement that gives medical staff the ability to diagnose the disease with high accuracy in its early stages and the opportunity of treatment before atherosclerosis becomes severe and dangerous. At the end we conclude that, sites of high wall shear stress just upstream of the stenosis throat, were factors in the process of the development of stenosis through platelet activation, as well as in the rupture of the stenosis cap triggering the process of thrombosis. Low shear stress plays a significant role in initiating the disease in the region of flow stagnation where flow cannot follow the geometry of arteries. The results presented, favour and support the theory of low wall shear stress and its important role in the initiation of atherosclerosis, and the high shear stress theory in the development of the disease. CFD in conjunction with flow visualisation and MRI can be used in the early prediction of artery stenosis and gives more accurate and reliable estimates of the stenosis severity.
|Item Type:||Thesis (PhD)|
|Contributors:||Myring, DF (Supervisor)|
|Schools:||Schools > School of Computing, Science and Engineering
Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre (SIRC)
|Depositing User:||Institutional Repository|
|Date Deposited:||03 Oct 2012 13:34|
|Last Modified:||29 Oct 2015 00:12|
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