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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/11099
Title: Mathematical analysis of two-phase blood flow through a stenosed curved artery with hematocrit and temperature dependent viscosity
Authors: Sharma, Bhupendra Kumar
Keywords: Mathematics
MHD
Variable viscosity
Heat transfer
Issue Date: 2021
Publisher: IOP
Abstract: Atwo-phase blood flow model is considered to analyze the fluid flow and heat transfer in a curved tube with time-variant stenosis. In both core and plasma regions, the variable viscosity model (Hematocrit and non linear temperature-dependent, respectively) is considered. A toroidal coordinate system is considered to describe the governing equations. The perturbation technique in terms of perturbation parameter ε is used to obtain the temperature profile of blood flow. In order to find the velocity, wall shear stress and impedance profiles, a second-order finite difference method is employed with the accuracy of 10−6 in the each iteration. Under the conditions of fully-developed flow and mild stenosis, the significance of various physical parameters on the blood velocity, temperature, wall shear stress (WSS) and impedance are investigated with the help of graphs. A validation of our results has been presented and comparison has been made with the previously published work and present study, and it revels the good agreement with published work. The present mathematical study suggested that arterial curvature increase the fear of deposition of plaque (atherosclerosis), while, the use of thermal radiation in heat therapies lowers this risk. The positive add in the value of λ1 causes to increase in plasma viscosity; as a result, blood flow velocity in the stenosed artery decreases due to the assumption of temperature-dependent viscosity of the plasma region. Clinical researchers and biologists can adopt the present mathematical study to lower the risk of lipid deposition, predict cardiovascular disease risk and current state of disease by understanding the symptomatic spectrum, and then diagnose patients based on the risk.
URI: https://iopscience.iop.org/article/10.1088/1402-4896/ac454a/pdf
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/11099
Appears in Collections:Department of Mathematics

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