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Numerical Heat Transfer, Part A: Applications
An International Journal of Computation and Methodology
Volume 72, 2017 - Issue 6
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Original Articles

Effect of uniform inclined magnetic field on natural convection and entropy generation in an open cavity having a horizontal porous layer saturated with a ferrofluid

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Pages 479-494 | Received 27 Jun 2017, Accepted 11 Sep 2017, Published online: 17 Oct 2017
 

ABSTRACT

Numerical analysis of natural convection combined with entropy generation in a square open cavity partially filled with a porous medium has been performed for a ferrofluid under the effect of inclined uniform magnetic field. Governing equations with corresponding boundary conditions formulated in dimensionless stream function and vorticity using Brinkman–extended Darcy model for porous layer have been solved numerically using finite difference method. An influence of key parameters on ferrofluid flow and heat transfer has been analyzed. It has been found that an inclusion of spherical ferric oxide nanoparticles can lead to a diminution of entropy generation in the case of similar flow and heat transfer structures.

Nomenclature

=

magnetic field

B0=

magnitude of magnetic field

Be=

local Bejan number

Beavg=

average Bejan number

cp=

specific heat at constant pressure

Da=

Darcy number

=

electromagnetic force

g=

gravitational acceleration vector

Ha=

Hartmann number

h=

height of porous layer

H1(ϕ), H2(ϕ), H3(ϕ), H4(ϕ), H5(ϕ,ε), H6(ϕ,ε)=

special functions

=

electric current

K=

permeability of porous layer

L=

length and height of the cavity

Nu=

local Nusselt number

=

average Nusselt number

=

dimensional pressure

Pr=

Prandtl number

Ra=

Rayleigh number

=

dimensional local entropy generation

=

dimensional local entropy generation due to heat transfer

=

dimensional local entropy generation due to fluid friction

=

dimensional local entropy generation due to magnetic field

Sgen=

dimensionless local entropy generation

Sgen,ht=

dimensionless local entropy generation due to heat transfer

Sgen,ff=

dimensionless local entropy generation due to fluid friction

Sgen,mf=

dimensionless local entropy generation due to magnetic field

Sgen,avg=

dimensionless average entropy generation

Sgen,ht,avg=

dimensionless average entropy generation due to heat transfer

Sgen,ff,avg=

dimensionless average entropy generation due to fluid friction

Sgen,mf,avg=

dimensionless average entropy generation due to magnetic field

=

additional parameters

T=

dimensional temperature

t=

dimensional time

Tc=

upper boundary temperature

Th=

bottom wall temperature

u, v=

dimensionless velocity components

=

dimensional velocity components

x, y=

dimensionless Cartesian coordinates

, =

dimensional Cartesian coordinates

α=

inclination angle of magnetic field

β=

thermal expansion coefficient

δ=

dimensionless height of porous layer

ε=

porosity of porous layer

η=

heat capacity ratio

θ=

dimensionless temperature

λ=

thermal conductivity

μ=

dynamic viscosity

ρ=

density

=

heat capacitance

ρβ=

buoyancy coefficient

σ=

electrical conductivity

τ=

dimensionless time

ϕ=

nanoparticles volume fraction

χ=

irreversibility factor

ψ=

dimensionless stream function

ω=

dimensionless vorticity

Subscripts=
avg=

average

c=

cold

f=

fluid

ff=

fluid friction

gen=

generation

h=

hot

ht=

heat transfer

max=

maximum value

mf=

magnetic field

mnf=

porous medium saturated with a nanofluid

nf=

nanofluid

p=

(nano) particle

s=

solid matrix of porous medium

Nomenclature

=

magnetic field

B0=

magnitude of magnetic field

Be=

local Bejan number

Beavg=

average Bejan number

cp=

specific heat at constant pressure

Da=

Darcy number

=

electromagnetic force

g=

gravitational acceleration vector

Ha=

Hartmann number

h=

height of porous layer

H1(ϕ), H2(ϕ), H3(ϕ), H4(ϕ), H5(ϕ,ε), H6(ϕ,ε)=

special functions

=

electric current

K=

permeability of porous layer

L=

length and height of the cavity

Nu=

local Nusselt number

=

average Nusselt number

=

dimensional pressure

Pr=

Prandtl number

Ra=

Rayleigh number

=

dimensional local entropy generation

=

dimensional local entropy generation due to heat transfer

=

dimensional local entropy generation due to fluid friction

=

dimensional local entropy generation due to magnetic field

Sgen=

dimensionless local entropy generation

Sgen,ht=

dimensionless local entropy generation due to heat transfer

Sgen,ff=

dimensionless local entropy generation due to fluid friction

Sgen,mf=

dimensionless local entropy generation due to magnetic field

Sgen,avg=

dimensionless average entropy generation

Sgen,ht,avg=

dimensionless average entropy generation due to heat transfer

Sgen,ff,avg=

dimensionless average entropy generation due to fluid friction

Sgen,mf,avg=

dimensionless average entropy generation due to magnetic field

=

additional parameters

T=

dimensional temperature

t=

dimensional time

Tc=

upper boundary temperature

Th=

bottom wall temperature

u, v=

dimensionless velocity components

=

dimensional velocity components

x, y=

dimensionless Cartesian coordinates

, =

dimensional Cartesian coordinates

α=

inclination angle of magnetic field

β=

thermal expansion coefficient

δ=

dimensionless height of porous layer

ε=

porosity of porous layer

η=

heat capacity ratio

θ=

dimensionless temperature

λ=

thermal conductivity

μ=

dynamic viscosity

ρ=

density

=

heat capacitance

ρβ=

buoyancy coefficient

σ=

electrical conductivity

τ=

dimensionless time

ϕ=

nanoparticles volume fraction

χ=

irreversibility factor

ψ=

dimensionless stream function

ω=

dimensionless vorticity

Subscripts=
avg=

average

c=

cold

f=

fluid

ff=

fluid friction

gen=

generation

h=

hot

ht=

heat transfer

max=

maximum value

mf=

magnetic field

mnf=

porous medium saturated with a nanofluid

nf=

nanofluid

p=

(nano) particle

s=

solid matrix of porous medium

Additional information

Funding

This work of Nikita S. Gibanov was conducted as a government task of the Ministry of Education and Science of the Russian Federation (Project Number 13.9724.2017/8.9). Hakan F. Oztop and Khaled Al-Salem extend their appreciation to the International Scientific Partnership Program ISPP at King Saud University for funding this research work through ISPP# 0030.

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