Velocity Profiles of Unsteady Blood Flow through an Inclined Circular Tube with Magnetic Field

Vincent Mwanthi *

Department of Mathematics, School of Pure and Applied Sciences, Meru University of Science and Technology, P.O.Box 3285-60200 Meru, Kenya.

Eustance Mwenda

Department of Mathematics, School of Pure and Applied Sciences, Meru University of Science and Technology, P.O.Box 3285-60200 Meru, Kenya.

Kennedy K. Gachoka

Department of Mathematics, School of Pure and Applied Sciences, Meru University of Science and Technology, P.O.Box 3285-60200 Meru, Kenya.

*Author to whom correspondence should be addressed.


Abstract

The present paper is devoted to study the flow of incompressible viscous, electrically conducting fluid (blood) in a rigid inclined circular tube with magnetic field. The blood is considered to be Newtonian fluid and the flow is caused by varying pressure gradient with time. The physics of the problem is described using the usual Magneto hydrodynamic (MHD) principles and equations along with appropriate boundary conditions. The governing equations of the motion in terms of cartesian co-ordinates are reduced to ordinary differential equations. Using dimensionless parameters, the Navier-stokes equation is solved numerically using finite difference method of approximation and the expressions for velocity profile is obtained. The velocity profiles for various values of Hartmann number as well as varying the angle of inclination of the tube have been presented graphically and discussed in depth. The obtained results show that on increasing the inclination angle of the tube and Hartmann number leads to increase and decrease of the axial velocity of the blood respectively.

Keywords: Biomagnetic fluid, incompressible viscous fluid, Newtonian fluid, Hartmann number, inclined magnetic field


How to Cite

Mwanthi, Vincent, Eustance Mwenda, and Kennedy K. Gachoka. 2017. “Velocity Profiles of Unsteady Blood Flow through an Inclined Circular Tube With Magnetic Field”. Journal of Advances in Mathematics and Computer Science 24 (6):1-10. https://doi.org/10.9734/JAMCS/2017/36620.

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