2014
DOI: 10.1155/2014/413213
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Parametric Analysis of Entropy Generation in Magneto-Hemodynamic Flow in a Semi-Porous Channel with OHAM and DTM

Abstract: The magneto-hemodynamic laminar viscous flow of a conducting physiological fluid in a semi-porous channel under a transverse magnetic field has been analyzed by the optimal Homotopy Analysis Method (OHAM) and Differential Transform Method (DTM) under physically realistic boundary conditions first. Then as the main purpose of this study the important designing subject, entropy generation of this system, has been analyzed. The influence of Hartmann number (Ha) and transpiration Reynolds number (mass transfer par… Show more

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Cited by 19 publications
(10 citation statements)
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“…This leads to a rise in temperatures. Similar observations have been made by Aïboud and Saouli [30] for non-Newtonian viscoelastic flow and by Rashidi et al for magnetic convection flows [31]. Figure 10 elucidates the effect of couple stress parameter s 2 on the entropy generation number Ns.…”
Section: Resultssupporting
confidence: 83%
“…This leads to a rise in temperatures. Similar observations have been made by Aïboud and Saouli [30] for non-Newtonian viscoelastic flow and by Rashidi et al for magnetic convection flows [31]. Figure 10 elucidates the effect of couple stress parameter s 2 on the entropy generation number Ns.…”
Section: Resultssupporting
confidence: 83%
“…After employing Equation (31) on the solutions for f I are obtained by solving iteratively Equation (33). We obtain the solution for f pζq from solving Equation (34) and now Equations (13) and (14) are now linear therefore, we will apply Chebyshev pseudo-spectral method directly, we get:…”
Section: Methodsmentioning
confidence: 99%
“…They described that entropy generation rate achieved at its maximum point in the absence of porosity and magnetic field. Some more pertinent studies on entropy generation can be found in references [31][32][33][34][35][36][37][38].…”
Section: Introductionmentioning
confidence: 99%
“…This method has been successfully implemented in numerous multiphysical mechanics, fluid dynamics, and heat transfer problems in recent years. These include nonlinear thermal conduction, hypersonic heating in boundary layers, haemotological filtration dynamics, swirl vortex nuclear magnetic propulsion thermodynamics, digestive transport modeling, thermo‐solutal convection in porous media, nanoscale fluid dynamics, micropolar fluid flows, chemically reacting flows in permeable materials, and biomagnetic entropy generation in hemodynamics . DTM has been shown to be very efficient in these studies.…”
Section: Solution Of the Problemmentioning
confidence: 99%