World Journal of Mechanics, 2012, 2, 272-279
doi:10.4236/wjm.2012.25033 Published Online October 2012 (http://www.SciRP.org/journal/wjm)
Natural Convection Flow and Heat Transfer Enhancement
of a Nanofluid past a Truncated Cone with Magnetic
Field Effect
Sameh E. Ahmed, A. Mahdy
Mathematics Department, Faculty of Science, South Valley University, Qena, Egypt
Email: sameh_sci_math@yahoo.com, mahdy4@yahoo.com
Received August 2, 2012; revised September 1, 2012; accepted September 12, 2012
ABSTRACT
A nonsimilarity analysis is per formed to investigate the laminar , free convection boundar y layer flow over a permeable
isothermal truncated cone in the presence of a transverse magnetic field effect. A suitable set of dimensionless variables
is used and non-similar equations governing the problem are obtained. Fourth order Runge-Kutta with shooting tech-
nique is employed for the numerical solution of the obtained equations. Different water-based nanofluids containing Cu,
Ag, CuO, Al2O3, and TiO2 are taken into consideration. The effects of pertinent parameters such as the solid volume
fraction of nanoparticles, and magnetic field parameter have been investigated. Furthermore, different models of nan-
ofluid based on different formulas for thermal conductivity and dynamic viscosity on the flow and heat transfer charac-
teristics are discussed. Various comparisons with previously published work for the case of a vertical plate are per-
formed and the results are found to be in excellent agreement.
Keywords: Nanofluid; Truncated Cone; Magnetic Field; Natural Convection; Non-Similarity Solution
1. Introduction
As it is well known that the natural convection phenom-
ena arise in nature as well as in industries. Therefore,
laminar free-convection boundary-layer flow of an elec-
trically conducting fluid in the presence of a magnetic
field has been investigated by many researchers due to its
frequent encounter in industrial and technological appli-
cations. For instance, Lin and Chen [1] have studied
mixed convection on a vertical plate for fluids on any
Prandtl number. The laminar natural convection over a
slender vertical frustum of a cone has been reported by
Na and Chiou [2,3]. Chamkha [4] investigated the lami-
nar, coupled heat and mass transfer by natural convective
boundary layer flow over a permeable isothermal trun-
cated cone in the presence of magnetic field Raptis and
Singh [5] have solved the problem of hydromagnetic
natural convection flow past an accelerated vertical plate.
Kao [6] has reported on the local nonsimilarity solution
for laminar natural convection adjacent to a vertical sur-
face. Na [7] has considered natural convective flow past
a nonisothermal vertical flat plate and reported a nu-
merical solution. The laminar natural convection from a
nonisothermal cone was analyzed by Roy [8] and Hering
and Grosh [9]. An approximate method of solution for
the overall heat transfer from vertical cones in laminar
natural convection was reported by Alamgir [10]. Takhar
and Ram [11] have studied magneto-hydrodynamic
natural convection flow of water through a porous me-
dium.
On the other hand, nanofluids have been widely used
in industry, because of the growing use of these smart
fluids. Many studies [12-17] explained that nanofluids
clearly exhibit enhanced thermal conductivity, which
goes up with increasing volumetric fraction of nanoparti-
cles. Nanofluid concept is utilized to describe a fluid in
which nanometer-sized particles are suspended in con-
ventional heat transfer basic fluids. Conventional heat
transfer fluids, including oil, water, and ethylene glycol
mixture are poor heat transfer fluids, since the thermal
conductivity of these flu ids play an important role on the
heat transfer coefficient between the heat transfer me-
dium and the heat transfer surface. Therefore, numerous
methods have been taken to improve the thermal conduc-
tivity of these fluids by suspending nano/micro or lar-
ger -sized particle materials in liquids [18]. Choi et al. [19]
showed that the addition of a small amount (less than 1%
by volume) of nanoparticles to convention al heat transfer
liquids increased the thermal co nductivity of the fluid up
to approximately two times. Mahdy and Sameh [20] re-
ported numerical analysis for laminar free convection
over a vertical wavy surface embedded in a porous me-
dium saturated with a nanofluid. Khan and Pop [21] in-
Copyright © 2012 SciRes. WJM
S. E. AHMED, A. MAHDY 273
vestigated numerically the problem of laminar fluid flow
resulting from the stretching of a flat surface in a nan-
ofluid. The used model for the nanofluid incorporated the
effects of Brownian motion and thermophoresis. Hojjat
et al. [22] investigated experimentally laminar convec-
tion heat transfer behavior of three different types of
nanofluids flowing through a uniformly heated horizontal
circular tube. Nanofluids were made by dispersion of
Al2O3, CuO, and TiO2 nanoparticles in an aqueous solu-
tion of carboxymethyl cellulose (CMC). All nanofluids
as well as the base fluid exhibited shear-thinning behave-
ior.
The goal of the present investigation is to find nu-
merical solutions for the problem of boundary layer flow
and heat transfer characteristics utilizing nanofluids past
a truncated cone in the presence of a transverse magnetic
field effect. The effects due to uncertainties of thermal
conductivity and dynamic viscosity have been under-
taken and discussed.
2. Analysis of the Problem
We consider steady state, laminar, and heat transfer by
natural convection, boundary layer flow of an electrically
conducting and optically dense fluid about a truncated
permeable cone with a half angle
A
as shown in Fig-
ure 1. The fluid is a water based nanofluid containing
different types of nanoparticles such as Copper Cu, Sil-
ver Ag, Alumina Al2O3, Copper oxide CuO and Titanate
TiO2. It is assumed that the base fluid and the nanoparti-
cles are in thermal equilibrium and no slip occurs be-
tween them. The thermo physical properties of the nan-
ofluid are given in Table 1 as [23,24]. In addition, the
origin of the coordinate system is placed at the vertex of
the full cone where
x
represents the distance along the
Figure 1. Physical model and coordinate system.
Table 1. Thermo-physic al properties of water and nanopar -
ticles [23,24].

3
kgm
r

11
Jkg K
p
c

11
Wm K
k

51
x10 K
b
H2O 997.1 4179 0.6130 21.0
Cu 8933 385.0 401.00 1.67
CuO 3620 531.8 76.500 1.80
Ag 10500 235.0 429.00 1.89
Al2O33970 765.0 40.000 0.85
TiO2 4250 686.2 8.9538 0.90
cone and represents the distance normal to the sur-
face of the cone. The cone surface is maintained at a
constant temperature w while the ambient temperature
far away from the surface of the cone is assumed to
be uniform. A uniform magnetic field is applied in the
-direction normal to the flow direction. The magnetic
Reynolds number is assumed to be small so that the in-
duced magnetic field is neglected. In addition, the Hall
effect and the electric field are assumed negligible. The
small magnetic Reynolds number assumption uncouples
the Navier Stokes equations from Maxwell’s equations.
By invoking all of the boundary layer and Boussineq, the
governing equations for this investigation can be written
as
y
TT
y
0
ru ru
xy

(1)
 
2
2
2
cos
n
fnf
f
n
TT A
uu u
u
Bgu
xy y



 



(2)

2
2
pnf nf
TT
cu
xy
k
y


T



(3)
The proper boundary and ambient conditions for this
problem can be written as
0, ,0t
a,,0
a
t
w
uv TT
u
y
TyT
 
 
(4)
where, and v are the velocity components along the
axes u
x
and , respectively, is the radius of the
truncated cone,
y r
, B
are the fluid electrical conductivity,
magnetic induction. nf
is the effective density of the
nanofluid, nf
is the effective dynamic viscosity of the
nanofluid, is the temperature of the nanofluid, nf
T
is the thermal expansion of the nanofluid,
g
is the ac-
celeration due to gravity. Now, for nanofluids, let us in-
troducing the expression for nf
, and
c
pnf
nf

of the nanofluid as
Copyright © 2012 SciRes. WJM
S. E. AHMED, A. MAHDY
Copyright © 2012 SciRes. WJM
274



 
 
,
,
1
1
1
nf
p
fs
pnf p
f
s
nff s
ccc

 

 



(5)
12
14
,
31
14 4
fr
f
Gr
ufUf
x
Gr f
vf
x




f

 




(7)
On the other hand, effective thermal conductivity can
be incorporated from the following expression:
 



11
1
sf f
nf f
sffs
knkn kk
kk knk kk
 


 


s
Substituting Equations (6) and (7) into Equations (2)
and (3) yields the following nonsimilar dimensionless
equations:
 


2
2
11
1
13
214
nf s
sff
f
g
fMf
fff
ff
ff







 





 









(8)
where is the empirical shape factor for the nanopar-
ticle. In particular, for spherical shaped nanopar-
ticles and
n
3
n
32n for cylindrical ones, Table 2 shows
four models of nanofluid based on different formulas for
thermal conductivity and dynamic viscosity. Furthermore,
is the solid volume fraction,
f
is the dynamic vis-
cosity of the base fluid,
f
and
s
are the thermal
expansion coefficients of the base fluid and nanoparticle,
respectively,
f
and
s
are the densities of the base
fluid and nanoparticle, respectively, nf is the thermal
conductivity and nf is the heat capacity of the
nanofluid,
k

p
c
f
k and
s
k are the thermal conductivities of
the base fluid and nanoparticle, respectively. The gov-
erning equations and boundary conditions can be made
dimensionless by introducing the stream function such
that



3
14
Pr 1
f
p
nf
s
pf
c
c
f
f
kk
f



 











(9)

 
0:0, 1
:0,0
ff
f



  
(10)
,rru yx



where a prime denotes partial differentiation with respect
to
and
and using the following dimensionless variables
34
2
20
2,Pr ,
fwf g
f
fx
f
gTTx
x
B
GrM Gr



1/4
1/4
0
00
,,
(,), (,)
wf
xxx y
Gr
xx x
TT f
TT rGr


 

(6)
are the Grashof number, Prandtl number and square of
the Hartmann number.
Table 2. Models of nanofluid based on different formulas for thermal conductivity and dynamic viscosity.
Model Shape of nanoparticles Thermal conductivity Dynamic viscosity
I Spherical

22
2
sf fs
nf f
sf fs
kk kk
kk
kk kk
 
 


2.5
1
nf f
 

II Spherical

22
2
sf fs
nf f
sf fs
kk kk
kk
kk kk
 
 


2
1 7.3123
nf f


III Cylindrical (nanotubes)

0.5 0.5
0.5
sf fs
nf f
sffs
kk kk
kk kkkk
 



2.5
1
nf f
 

IV Cylindrical (nanotubes)

0.5 0.5
0.5
sf fs
nf f
sffs
kk kk
kk kkkk
 



2
1 7.3123
nf f


S. E. AHMED, A. MAHDY 275
The quantities of physical interest are the local skin
friction coefficient
f
C and the rate of heat transfer that
expressed in terms of local Nusselt number
x
Nu and
these are given by

2
2,
ww
fx
fw
fr
xq
CNu
kT T
U

(11)
where the skin friction w
and the heat transfer from the
sheet are given by
w
q
0
,
wnfw nf
y
u
qk
y

 

 
 
0y
T
y
(12)
Applying the non-dimensional transformations (5),
one obtain


1
4
1
4
2,0
,0
nf
fx f
nf
xx f
CGrf
k
Nu Grk











,
(13)
3. Numerical Procedure
The numerical algorithm used to solve the dimens ionless
equations (8) and (9) with the boundary conditions (10)
is based on the well-known fourth order Runge-Kutta
integration scheme. In the current technique, the differ-
ence between the forward and backward values of de-
pendent variables should be zero for a true solution. The
procedure uses a generalized Newton method to reduce
these differences to zero, by calculating corrections to the
estimated boundary values. This process is repeated it-
eratively until convergence is obtained to as specified
accuracy. This method was found to be suitable and gave
results that are very close to the results obtained in Refs.
[4,25,26]. Table 3 shows comparison of values of
0,0f and
0,0
for various values of Pr for pure
fluid. As it is observed, there is an excellent agreement
with the earlier publish ed results.
4. Results and Discussion
Steady state two-dimensional laminar magneto-hydro-
dynamics natural convection flow and heat transfer of a
nanofluid past a truncated cone has been studied nu-
merically. Parametric studies of the influence of various
parameters such as finite volume fraction (00.15
 ),
magnetic field parameter (0
g), different formu-
las of dynamic viscosity ratio (5M
nf f

) and thermal
conductivity ratio (nf f
kk) on the fluid flow and heat
transfer have been performed. In all the obtained results,
pure water with Pr 7
has been used as a base nan-
ofluid. Figures 2 and 3 display the effects of solid vol-
ume fraction on the local skin friction coefficient and the
rate of heat transfer for Cu-water nanofluid using model I.
It is found that, increasing in solid volume fraction re-
sults in an increase in rate of heat transfer and a reduction
in local skin friction coefficient. In fact, high values of
causes the fluid becomes more viscous. As results,
the natural convection is reduced which causes the fluid
flows is very slowly. This velocity reduction causes an
increase in thermal boundary layer thickness, which in
turn, increases the rate of heat transfer and decreases the
local Nusselt number.
The main objective from adding nanoparticles to the
classical fluid is enhancing the rate of heat transfer for
such fluids, so it is necessary to explain which the best
model can be used to reach to this goal. In Figures 4 and
5, a comparison among different formulas for nanofluid
dynamic viscosity and nanofluid thermal conductivity
was performed at 0.08
and. These formulas 1
g
M
Table 3. Comparison of values of

f0,0 and
0,0
for various values of Pr for pure fluid.

0,0f

0,0
Pr [25] [26] [4] present [25] [26] [4] present
0.0001 1.4998 - 1.4997 1.49906 0.0060 - 0.0059 0.00598
0.001 1.4728 - 1.4727 1.47299 0.0189 - 0.0188 0.01859
0.01 1.3968 - 1.3965 1.38941 0.0570 - 0.0574 0.05738
0.1 1.2144 1.2104 1.2151 1.20918 0.1629 0.1637 0.1630 0.16312
1.0 0.9084 0.9081 0.9081 0.90813 0.4012 0.4009 0.4015 0.40131
10.0 0.5927 0.5930 0.5927 0.59268 0.8266 0.8266 0.8274 0.82664
100.0 0.3539 0.3564 0.3558 0.35557 1.5493 1.5495 1.5503 1.54928
1000.0 0.2049 - 0.2049 0.20468 2.8035 - 2.8044 2.80099
10000.0 0.1161 - 0.1161 0.11669
5.0127 - 5.0131 5.02900
Copyright © 2012 SciRes. WJM
S. E. AHMED, A. MAHDY
276
0.0 0.2 0.4 0.6 0.8 1.0
0.36
0.38
0.40
0.42
0.44
0.46
0.48
0.50
0.52
= 0.0, 0.03, 0.05 , 0. 08, 0.10, 0. 15
Pr = 7.0
Mg = 1.0
Cu-Water
f '' (0)
Figure 2. Profiles of skin-friction coefficient for different
values of volume fraction.
0.0 0.2 0.4 0.6 0.8 1.0
-0.72
-0.68
-0.64
-0.60
-0.56
-0.52
-0.48
= 0.0, 0. 03, 0.05, 0. 08, 0.10, 0.1 5
Cu-Water Pr = 7.0
Mg = 1.0
' (0)
Figure 3. Profiles of local Nusselt number for different val-
ues of volume fraction.
0.00.20.40.60.81
-0.68
-0.64
-0.60
-0.56
-0.52
-0.48
.0
Model IV
Model II
Model I
Model III
Cu-Water = 0.08
Pr = 7.0
Mg = 1.0
' (0)
Figure 4. Profiles of local Nusselt number for different mo-
dels.
were represented in the present study by model I, model
II, model III and model IV (Table 2). It is clear that,
spherical nanoparticles which represented by model II
give larger rate of heat transfer than model I. On the con-
trary, cylindrical nanoparticles represented by model III
give lower rate of heat transfer than model IV. Also,
spherical and cylindrical shapes of nanoparticles given
by model I and model III tend to decrease dynamic vis-
cosity of the nanofluid which increase the local sk in fric-
tion coefficient compared with model II and model IV.
Figures 6-9 display the effects of magnetic field pa-
rameter (0
g5M
) on velocity profiles, temperature
distributions, local skin friction coefficient and rate of
heat transfer for pure water and Cu-water nanofluid using
model I, respectively. It can be observed that, increasing
in magnetic field parameter results in a reduction in the
fluid motion and an increase in the fluid temperature.
0.0 0.2 0.40.6 0.8 1.0
0.42
0.44
0.46
Model III
Model IV
Model II
Model I
= 0.08
Pr = 7.0
Mg = 1.0
Cu-Water
f '' (0)
Figure 5. Profiles of skin-friction coefficient for different
models.
02 46810 12
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Mg = 0.0, 1. 0, 2 . 0, 3. 0, 4. 0, 5. 0
= 0.4
Pr = 7.0
= 0.10
Figure 6. Profiles of fluid temperature for different values
magnetic field parameter Mg (pure water , ··· Cu-Wa-
ter).
Copyright © 2012 SciRes. WJM
S. E. AHMED, A. MAHDY 277
02 46 81012
0
0. 05
0. 1
0. 15
0. 2
0. 25
f '
Mg = 0. 0, 1. 0, 2. 0, 3. 0, 4. 0, 5. 0
= 0.4
Mg = 1.0
= 0.10
Figure 7. Velocity profiles for different values magnetic
field parameter Mg (—pure water , ··· Cu-Water).
0.0 0.2 0.4 0.6 0.8 1.0
0.2
0.3
0.4
0.5
0.6
Pure water
Cu-W ater
Mg = 0.0, 1.0, 2.0, 3.0, 4.0, 5.0
Cu-Water
= 0.08
Pr = 7.0
f '' (0)
Figure 8. Profiles of skin-friction coefficient for different
values of magnetic field Mg.
0.0 0.2 0.4 0.6 0.8 1.0
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
Pure water
Cu-Water
Cu-Water = 0.08
Pr = 7.0
Mg = 0.0, 1.0, 2.0, 3.0, 4.0, 5.0
' (0)
This can be attributed to the existence of magnetic field
within the flow region which causes a force called Lor-
entz force. This force works opposite to the flow direc-
tion and it resists the flow. This reduction leads to de-
creases the local skin friction coefficient and increases
the boundary layer thickn ess which in turn, increases the
rate of heat transfer as well.
Figures 10 and 11 show the profiles of fluid velocity
and fluid temperature for pure water (0
), Cu-water,
CuO-water, Al2O3-water, Ag-water and TiO2-water nano-
fluid with (0.08
) related with Model I at 1
g
M
and 0.4
. The results show that, the fluid motion
becomes very slowly by adding Al2O3 nanoparticles.
However, the CuO-nanoparticles give faster motion for
nanofluid than other nanoparticles. On the other hand,
the high value of thermal conductivity of Ag (Table 1)
causes to decrease the fluid temperature whereas, the
TiO2 nanoparticles leads to increase the fluid temperature.
The behaviors of velocity and temperatures mentioned
above have opposite effects on behaviors of local skin
friction coefficient and rate of heat transfer. It can be
noticed from Figures 12 and 13 which depicted the pro-
files of local skin friction coefficient and rate of heat
transfer for different nanoparticles, respectively, that,
TiO2-water nanofluid has a high value of skin friction
while the CuO-water nanofluid has a lower value of it. In
addition, the high rate of heat transfer can be obtained by
adding Ag-nanoparticles and TiO2 nanoparticles give a
lower value of it. The mean responsible of these effects is
the values of thermal conductivity for such nanoparticles
(Table 1). Similar behaviors are observed by Rana and
Bhargava [27] which make sure that the present results
are more accurate.
5. Conclusion
In this paper, the problems of MHD natural convection
02 46 810
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
Figure 9. Profiles of local nusselt number for different val-
ues of magnetic field Mg.
f '
0.8 11.2 1.4
0.15
0.155
0.16
0.165
f '
Pr =7.0
Mg = 1 .0
= 0.4
= 0. 08
Al2O3, TiO2, Ag, Cu, CuO
Figure 10. Velocity profiles for different nanoparticles.
Copyright © 2012 SciRes. WJM
S. E. AHMED, A. MAHDY
278
0 12 34 56
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1.2 1.22
0.32
0.33
0.34
Pr =7.0
Mg = 1. 0
= 0.4
= 0. 08
Ag, CuO, Cu, Al
2
O
3
, TiO
2
Fi t
nanoparticles.
gure 11. Profiles of fluid temperature for differen
0.0 0.2 0.4 0.6 0.8 1.0
0.42
0.44
0.46
0.48
0.50
0.52 = 0.08
Pr = 7 .0
Mg = 1 .0
CuO
Cu
Ag
Al 2O3
TiO2
Pure w a ter
f '' (0)
Figure 12. Profiles of skin-friction coefficient for different
nanoparticles.
0.0 0.2 0.4 0.6 0.8 1.0
-0.72
-0.68
-0.64
-0.60
-0.56 = 0.08
P r = 7 .0
M g = 1 .0
TiO2, Al2O3, C u , C u O, A g
Pure water
'
(0)
igure 13. Profiles of local nusselt number for diffe
ticles
and heat transfer of a nanofluid past a truncated cone are
investigated. The governing partial differential equations
for mass, momentum and energy are transformed to
non-similar equations by using a non-dimensional trans-
formation. These equations are solved numerically using
the well known fourth order Runge-Kutta method. The
eff ec ts of solid volume fraction, magnetic field parame ter,
different nanoparticles and different formulas of thermal
conductivity and dynamic viscosity are discussed. It is
found that, as the solid volume fraction increases, the rate
of heat transfer increases whereas the local skin friction
coefficient takes the inverse behaviors. Model II (sphere-
cal nanoparticles) is found to be the best model for en-
hancing the rate of heat transfer compared with other
models. In addition, increasing in magnetic field
F
nanopar rent
pa-
rameter leads to decrease both of the velocity and local
skin friction coefficient and increase the fluid tempera-
ture as well as the rate of heat transfer. Finally, among all
different type of nanoparticles given in this study,
Ag-nanoparticles give a higher rate of heat transfer and
TiO2 nanoparticles have a lower value of it.
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