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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/123456789/11097
Title: Entropy generation for MHD two phase blood flow through a curved permeable artery having variable viscosity with heat and mass transfer
Authors: Sharma, Bhupendra Kumar
Keywords: Mathematics
Two-phase blood flow
Variable viscosity
Permeability
Heat and mass transfer
MHD
Entropy generation
Issue Date: Apr-2022
Publisher: Elsevier
Abstract: Present study deals with the analysis of entropy generation of MHD blood flow through a stenosed permeable curved artery with heat source and chemical reaction. Blood flow is considered in two-phases; core and plasma region, respectively. Viscosity of the core region is considered as temperature-dependent, while constant viscosity is considered in plasma region. The governing equations of the proposed two-phase blood flow model are considered in the toroidal coordinate system. The second-order finite difference method is adopted to solve governing equations with 10−6 tolerance in the iteration process. A comparative study of darcy number (Da) is performed to understand the influence of permeable and impermeable wall conditions. The effect of various physical parameters such as magnetic field (M), viscosity variation parameter (λ1), Darcy number (Da), Brinkman number (Br), heat source (H), chemical reaction parameter (ξ) etc. are displayed graphically on the flow velocity, temperature, concentration, wall shear stress (WSS), frictional resistance profile and entropy generation profiles. A comparison with published work has also been displayed through the graph to validate the present model, and it is in fair agreement with the existing work. The present study suggested that the curvature and permeability of the arterial wall raise the risk of atherosclerosis formation, while the implication of heat source on the blood flow lower this risk. Clinical researchers and biologists can use the current mathematical research to lower the risk of lipid deposition and predict the risk of cardiovascular disease, and then diagnose patients based on risk.
URI: https://www.sciencedirect.com/science/article/pii/S0735193322000768
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/11097
Appears in Collections:Department of Mathematics

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