Computer Simulation of Blood Flow with Nanoparticles in a Magnetic Field as a Third Grade Non-Newtonian Through Porous Vessels by Flex PDE SoftwareAkbari N1, Ganji DD2*, Gholinia M3 and Gholinia S2
- *Corresponding Author:
- Ganji DD
Department of Mechanical Engineering
Babol University of Technology, P.O. Box 484
Tel: +98 111 32 34 501
E-mail: [email protected]
Received date: March 21, 2017; Accepted date: April 20, 2017; Published date: April 27, 2017
Citation: Akbari N, Ganji DD, Gholinia M, Gholinia S (2017) Computer Simulation of Blood Flow with Nanoparticles in a Magnetic Field as a Third Grade Non-Newtonian Through Porous Vessels by Flex PDE Software. Innov Ener Res 6:160.
Copyright: © 2017 Akbari N, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
In this paper, we used Flex-PDE software to study the blood flow with nanoparticles in a magnetic field as a third grade non-Newtonian through porous vessels. Viscosity of Nano fluid is clear via Constant, Vogel’s and Reynolds’ patterns. The performance of Flex-PDE software is briefly raised and employed to derive solution of nonlinear equations. Attempts are performed in order to indicate the validity and performance of the present software in comparison with Collocation Method (CM). Comparison between the Flex-PDE software and analytical conclusions of the issue, illustrates excellent complying in solving this nonlinear differential equation. As well as, in the present perusal, the impact of various physical parameters like: Grashof number, pressure gradient, thermophoresis parameter, Brownian motion parameter and magnetic field intensity on concentration, velocity and temperature profiles are examined. Conclusions displays that velocity profile has direct relationship with thermophoresis parameter Nt but Brownian motion Parameter Nb has reverse relationship with velocity profile V(r). In addition, this study illustrate that Flex-PDE is strong software to solve nonlinear differential equations, such as the issue introduced in this research.