Second law of thermodynamics analysis of hydro-magnetic nano-fluid slip flow over a stretching permeable surface

Jafari, Seyed Sajad; Freidoonimehr, Navid

doi:10.1007/s40430-014-0250-z

Cited by 23 publications

(9 citation statements)

References 39 publications

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“…The local rate of generation of entropy for MHD nanofluid flow in a porous medium is given by [52,53] The entropy generation for the flow in consideration is due mainly to four components. The first term on the righthand side is the entropy generation due to heat transfer, the second due to fluid friction/viscous dissipation, the third term due to Darcy viscous dissipation as a result of the presence of porous medium and the fourth term due to the presence of magnetic field.…”

Section: Second Law Analysismentioning

confidence: 99%

Entropy generation in MHD nanofluid flow with heat source/sink

Tlau

Ontela

2019

SN Appl. Sci.

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This work investigates the generation of entropy in the presence of a heat source/sink in a sloping channel filled with porous medium in magnetohydrodynamic nanofluid flow. The regulating equations are nonlinear and coupled thermal and hydrodynamic equations. Homotopy analysis method is used in the handling of equations. Comparisons with existing literature have been produced and were discovered to be in excellent accord, which are a particular situation of the present issue. The impact on entropy generation, Bejan number, Nusselt number and skin friction of pertinent fluid parameters is addressed, developed and displayed graphically. Entropy generation was found to be minimum just above the center of the channel throughout the study. Skin friction and Nusselt number were found to be higher for the case of heat generation than heat absorption.

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Section: Second Law Analysismentioning

confidence: 99%

Entropy generation in MHD nanofluid flow with heat source/sink

Tlau

Ontela

2019

SN Appl. Sci.

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“…Bejan [27][28][29] introduced this subject and focused on the different reasons behind entropy generation in applied thermal engineering. Many investigators focused on the entropy generation and heat transfer of nanofluid in some engineering problems [30][31][32][33]. A parametric analysis and entropy generation minimization of unsteady MHD flow over a stretch rotating disk was completed by Rashidi et al [34], using an artificial neural network and particle swarm optimization algorithm.…”

Section: Introductionmentioning

confidence: 99%

Entropy generation analysis of mixed convection with considering magnetohydrodynamic effects in an open C-shaped cavity

2019

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This paper studies the effect of a constant magnetic field on the mixed convection heat transfer and the entropy generation of CuO-water nanofluid in an open C-shaped cavity with a numerical method. The governing equations are presented by control volume method and they are solved simultaneously by the SIMPLE algorithm. This study examines the effect of the Hartman number, aspect ratio, Reynolds number, and Richardson number parameters for different solid volume fraction of nanoparticles. Also Nusselt number, entropy generation, thermal performance criteria and coefficient of performance is studied in this research. The calculated parameters are the Hartman number, aspect ratio, Reynolds number, Richardson number, nanofluid solid volume fraction, Nusselt number, and coefficient of performance. The results show that increasing the Hartmann number reduces the entropy generation. However, the thermal performance increases. Increasing the aspect ratio raises heat transfer and thermal performance. The effects of nanofluid solid volume fraction on mixed convection heat transfer and entropy generation are also investigated and discussed.

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“…Rashidi et al [6] have analyzed the entropy generation in a MHD flow over a rotating porous disk considering variable physical properties of the fluid. Jafari et al [7] extended the formulation to MHD nano-fluid and developed a solution strategy based on the Homotopy Analysis Method (HAM) [8][9][10][11][12][13][14][15][16][17]. The HAM is a semi-analytical technique, proposed first time by Liao [18] to solve nonlinear differential equations.…”

Section: Introductionmentioning

confidence: 99%