Analysis of thermal characteristics for MHD peristaltic movement of hybrid nanofluid with electro-osmosis, Ohmic heating and Hall effects

Abstract

This study investigates the entropy generation for peristaltic motion of hybrid nanofluid within a 2D asymmetric channel. The flow is influenced by the combined impacts of an applied magnetic field and electro-osmosis. The hybrid nano liquid is composed of iron oxide nanoparticles mixed with multi-walled carbon nanotubes (MWCNTs) suspended in ethylene glycol (EG) base fluid. A novel mathematical model is developed to investigate the unique behavior of this hybrid nanofluid in the context of Magnetohydrodynamics (MHD) peristaltic motion, taking into account the effects of electro-osmosis. Notably, this aspect of the hybrid nanofluid has not been previously examined. Convective temperature and velocity slip boundary conditions are taken into consideration for the analysis. Further, this investigation focuses on the significant effects of Ohmic heating, heat absorption/generation, viscous dissipation, Hall current, and Joule heating. Governing equations are simplified using lubrication theory and Debye-Hückel linearization assumptions. Subsequently, numerical solutions are obtained by using shooting-based algorithm NDSolve in Mathematica. Graphical illustrations are presented to explain the influences of several emerging parameters on temperature distribution, pressure gradient, axial velocity, Bejan and entropy generation numbers. Additionally, thermal transfer rates are discussed through bar charts. The outcomes of this examination demonstrated that the temperature profile increases for elevated values of Hartmann number, iron oxide nanoparticles, and heat generation. It is also observed that temperature profile rises with increasing values of Joule heating and electro-osmotic parameters. Furthermore, it is noted that axial velocity rises in the left part of the channel for increasing values of Helmholtz–Smoluchowski velocity. Moreover, augmenting Joule heating parameter intensifies the of Bejan and entropy generation numbers.