COMPUTATIONAL COMBUSTION 2007, ECCOMAS Thematic Conference
K. Bashirnezhad, M. Moghiman and L. Mirboroun
18-20 July 2007, Delft, The Netherlands
EFFECT OF SWIRL NUMBER ON SOOT FORMATION IN
TURBULENT GAS FIRED DIFFUSION FLAMES
Kazem Bashirnezhad*, Mohammad Moghiman† and Leili Mirboroun‡
*Islamic Azad University – Mashhad Branch,
Faculty of ENG, Mashhad, Iran
e-mial: bashirnezhad@yahoo.com
†
Ferdowsi University, Faculty of ENG, Mashhad, Iran
e-mial: mmoghiman@yahoo.com
‡
e-mial: mirboroon@gmial.com
Key words: Soot, Swirling Flow, Methane Flame, Turbulent Flame
Abstract. The present study is concerned with measuring and simulating soot and flame
structure of non-premixed gas fired swirl stabilized combustor. Filter paper technique is used
to measure soot volume fraction inside the combustor. The numerical simulation is based on
the solution of the fully-coupled conservation equations for swirling turbulent flow, chemical
species kinetic modeling, fuel combustion and soot formation and oxidation. The soot particle
number density and the mass density based on the acetylene concentrations are used to model
the soot emission in confined swirling turbulent diffusion flame. The comparison between
predictions and measurements over a range of different swirl numbers shows good
agreement. The results reveal the significant influence of swirl intensity on combustion
characteristics and soot concentration in diffusion flames. The results show that an increase
in swirl number enhances the mixing rate, peak temperature, and soot volume fraction inside
the flame zone. The locations of the maximum temperature and soot concentration shift closer
to the combustor inlet with increase in swirl number.
Nomenclature
ag
absorption coefficient of gas
c1
scaling factor for the soot inception model (s-1)
c2
c3
scaling factor for the soot growth (kg.m.kmol-1.s-1)
c4
scaling factor for the OH oxidation rate (kg.m.kmol-1.k0.5.s-1)
Db
burner throat diameter (m)
G
axial flux of angular momentum (kg.m2.s-2)
scaling factor for the O2 oxidation rate (kg.m.kmol-1.k0.5.s-1)
Kazem Bashirnezhad, Mohammad Moghiman and Leili Mirboroun
Gx
h
m
M
N
NA
r
R
Rj
SN

Sh
T
u
v
w
W
x
axial flux of linear momentum (kg.m.s-2)
enthalpy (j.kg-1)
mass fraction
soot mass density (kg.m-3)
soot particle number density(m-3)
Avogadro's number
radial direction (m)
universal gas constant (j.kg-1.k-1)
reaction rate mass of the j th species
swirl number
energy conservation equation source term
mean temperature (k)
axial velocity component (m.s-1)
radial velocity component (m.s-1)
swirl velocity (m.s-1)
molecular weight (kg.kmol-1)
axial direction (m)
Greek letters



mj
1
molecular viscosity of gas phase (kg.m-1.s-1)
gas phase density (kg.m-3)
collision efficiency of soot particles
laminar exchange coefficient
INTRODUCTION
The non-premixed flames often contain locally fuel-rich regions where the decomposition
products produce larger hydrocarbons instead of being oxidized to carbon dioxide and water.
This process, termed hydrocarbon growth, is normally undesirable since it ultimately
produces soot particles and carcinogenic polycyclic aromatic hydrocarbons (PAH) according
to Mecnally et al.1 and Roesler et al.2. The process of soot production from hydrocarbon fuels
consists of fuel pyrolysis, formation of polycyclic aromatic hydrocarbons, particle inception,
coagulation, surface growth, and oxidation3-5. The soot formation is strongly dependent on the
PAH concentration and temperature domain5. Early mechanistic models suggested that the
first aromatic ring was formed by the addition of acetylene to C4 radicals and that the key
growth process toward increasingly larger PAH occurred by continuous addition of C2H22.
The formation/combustion of soot in laminar and simple turbulent jet diffusion flames has
been studied by many researchers6-10. Brooks and Moss9 presented results of numerical
modeling of piloted axisymmetric turbulent methane-air simple jet (without swirl) flames
using an extended flamelet approach. Kronenburg et al.10 investigated the modeling of soot
formation and oxidation in the same flames by the conditional moment closure (CMC)
method. Generally the two models have showed good agreement with the experimental
measurements. Swirling flows are used in many technical applications particularly in furnaces
Kazem Bashirnezhad, Mohammad Moghiman and Leili Mirboroun
and gas turbines to improve flame stabilization, ignition stability, mixing enhancement,
pollutant reduction and blow-off characteristics11,12. Although the effect of many parameters
on soot formation has been investigated by many investigators, but the influence of swirl
intensity on soot formation has not been studied. The aim of this paper is to study the effect of
swirl intensity on soot formation and oxidation in swirling turbulent diffusion flames. The
investigation is conducted with both numerical simulation and experimental measurements.
2
EXPERIMENTAL SET-UP
A horizontal laboratory combustor with a circular cross-section designed and constructed
to confine the flame and prevent gas composition fluctuations resulting from the ambient air.
The combustor is 360 mm in diameter and 1000 mm in length, that ensures simulation of the
essential physics of combustor. An air swirler is installed at the front of the burner and the
swirl level is easily controlled by varying the swirler. A schematic diagram of the
experimental set-up is illustrated in figure 1.
THERMOMETER
SOOT METER
Air
Mhetane
Air
Figure 1: Schematic of the experimental set-up
Some circular slots are cut into the upper side of the combustor body so that the soot meter
and thermocouple probes can be inserted into the center of the cylindrical combustor. Soot
concentration is measured using the filter paper technique13. This technique is an optical
method whose results are dependent on soot reflective index. Even extremely low soot
concentration in the exhaust gas can be measured because the sample volume can be varied.
The temperature inside the combustor is measured using the ceramic-sheathed type Sthermocouples (radiation-shielded) with a thermal resistance up to 2000 K. The described
system measures temperatures within a tolerance of ±5 K.
Kazem Bashirnezhad, Mohammad Moghiman and Leili Mirboroun
Mass flow rate of the fuel and air are measured by using a Rota meter with the accuracy of
0.1lit/min. The temperature fluctuation of the inlet air and fuel is kept within the specified
margins of 3 K. The repeatability of the data is regularly checked during each experimental
session. On average, all of the data can be reproduced to within 10% of the mean value. The
combustor flow-gas is continuously monitored during the measurement program to sense any
change in the combustor operating conditions. In addition, although every effort is made to
eliminate sources of gas leakage in the combustor construction, the combustor pressure is
maintained close to atmospheric value.
3 MATHEMATICAL MODELING
In this study, the following basic assumptions are made to produce a mathematical model
for various processes inside the combustor:

One considers that an axisymmetric two-dimensional computational fluid dynamics
analysis of a turbulent diffusion flame is able to predict gas velocity, temperature and 14
species concentration profiles with sufficient accuracy.

The soot particle phase is considered to be dilute and is considered not to effect the gas
flow field.

The soot formation model is based of acetylene concentration and soot combustion
model is based OH and O2 concentration.

Buoyancy forces are neglected.

Methane is considered as the fuel.

The mathematical model is based on a typical Eulerian formulation. The time averaged
equations are as follows:
3.1 Continuity and momentum equations
u 1 

(rv)  0
x r r
(1)
____
____
1 

p
1 


(ruu)  (ruv)     2u 
(r u ' v')  (  u ' u ')

r  x
r
x
r r
x

(2)
____
____
1 

p
v
1 

1 ______
2
2
' '
' '
(
r

uv
)

(
r

vv
)


w




(

v

)

(
r

v
v
)

(

u
v
)

 w' w'

r  x
r
r
r r
x
r
r2

(3)
____
_____
1 

w
1 

1 ______

2
(
r

uw
)

(
r

vw
)


vw


(

w

)

(
r

v
'
w
'
)

(

u
'
w
'
)

 v' w'

r  x
r
r r
x
r
r2

(4)
The turbulent stresses are calculated from an algebraic stress model14. Furthermore, a
conventional wall-function approach is used in the near-wall region to bridge the viscous
sublayer. The swirl number (SN) which is a non-dimensional parameter, characterizes the
Kazem Bashirnezhad, Mohammad Moghiman and Leili Mirboroun
degree of swirl in a swirl flow and is defined as the ratio of the axial flux of angular
momentum to the axial flux of axial momentum11,14. At the air inlet of the burner chamber SN
is obtained from:
SN 
2G
Gx Db
Db / 2


D 
2
0
b
uwr 2 dr
Db / 2
0
u 2 rdr
(5)
3.2 Energy equation
____
_____

1

1 


2
(
r

uh
)

(
r

vh
)



h

(
r

v
'
h
'
)

(

u
'
h
'
)

S
h
h

r  x
x
r r
x

(6)

The energy addition due to combustion ( S h ) is determined by using a reduced mechanism
for methane combustion based on results from Chen15. The global steps of this 10-step
mechanism and 14 species include CH4, CH3, O, O2, H, H2, CO, CO2, OH, C2H2, C2H4,
C2H6, H2O, and CH2O are summarized below:
O2 + 2 CH3 + C2H4 = H + 2 CH4 + CO2 + 1/2 C2H2
O2 + 2 CH3 = H2 + CH4 + CO2
O2 + 3 CH3 = H + 2 CH4 + CO2
O2 + CH3 + CO = H + CO2 + CH2O
O2 + CO + C2H6 = CH4 + CO2 + CH2O
O2 + 2CO = 2 CO2
H + O2+ CO = OH + CO2
H2 + O2+ CO = H + OH + CO2
O2 + H2O + CO = 2OH + CO2
O2 + 1/2 C2H2 = H + CO2
(R1)
(R2)
(R3)
(R4)
(R5)
(R6)
(R7)
(R8)
(R9)
(R10)
In this study, the reaction rates that appear as source terms in species transport equations
(equation 6) are controlled by finite rate method. The conservation equation for jth species
takes the following general form:
______
______
1

1 


(rum j )  (rvm j )  mj  2 m j 
(r v' m j ')  (  u' m j ')  R j

r  x
r
r r
x

(7)
In this study, species conservation equation is solved for all of the 14 species.
3.3 Soot modeling
The emission of soot from a flame is determined by a competition between soot formation
and oxidation that must be considered when a soot modeling study is carrying out. In this
Kazem Bashirnezhad, Mohammad Moghiman and Leili Mirboroun
study, a recent soot model developed by Brookes et al.9 is used. The model describes the soot
formation in terms of the soot particle number density (N) and the soot particle mass density
(M) and takes into account the inception (nucleation), coagulation, growth, and oxidation
processes for the rates of these two parameters as:
DN  dN 
 dN 




Dt  dt  Inception  dt Coagulation
(9)
DM  dM 
 dM 
 dM 






Dt
 dt  Inception  dt Growth  dt Oxidation
(10)
The model proposed by Leung et al.16, is used to predict soot inception. In this model,
it is assumed that acetylene is primarily responsible for the nucleation and the growth of soot
particles. The inception step is treated simply as a one-step process:
C 2 H 2  2C SOOT  H 2
(11)
The rate of inception is assumed to be first order in acetylene concentration so that the rate
is calculated as:
 mC2 H 2
 dN 
 c1 N A  


 WC H
 dt  Inception
2 2

  21100/ T
 e


(12)
M  dN 
 dM 
 P 



 dt  Inception N A  dt  Inception
(13)
where Mp, the mass of a soot nucleus, has a value of 144 kg.kmol-1 based on the assumption
that the soot size corresponds to 12 carbon atoms and c1=54 s-1 determined by Brookes and
Moss9. Assuming the particles are mono-dispersed in size and spherical, the coagulation rate
and reaction surface or growth rate are given by:
1/ 2
 24 R 
 dN 

 



 dt coagulation
  Soot N A 
 mC H
 dM 
 c2   2 2


 WC H
 dt  growth
2 2

1/ 6
 6 


 

 Soot 
(14)
T 1 / 2 M 1 / 6 N 11/ 6
 21100/ T 
 6M
 e
 N 1 / 3 



 Soot






2/3




(15)
where  soot  2000kgm 3 and c2 =9000.6 kg · m · kmol-1 · s-1 according to Brookes et al.9.
The oxidation model takes into account combustion of soot by O 2 and OH radicals. In this
model, the rate of soot oxidation is given by:
m
 dM 
 c4  OH


dt
W

 Oxidation
OH
 6M 

T (N )1 / 3 
  Soot 
2/3
 c3 
mO2
WO2
exp(
 19778
1 / 3  6M 

) T N  
T
  Soot 
2/3
(16)
where  is set to be 0.13 and c3= 8903.51kg·m·kmol-1·K1/2 c4 =105.81 kg · m · kmol-1·
Kazem Bashirnezhad, Mohammad Moghiman and Leili Mirboroun
K-1/2 · s-1, which are obtained by converting the rate of soot mass consumption9.
4 METHOD OF SOLUTION
The conservation equations are solved using a control-volume based computational
procedure17. The flow field pressure linked equations are solved by the SIMPLE algorithm
and the set of algebraic equations are solved sequentially with the line-by-line method which
is a combination of Gauss-Seidel method and tridiagonal-matrix algorithm. The convergence
criterion is determined by the requirement that the maximum value of the normalized
residuals of any equation must be less than 1  10-5. Under-relaxation factor is chosen as 0.25
for all dependent variables.
A numerical mesh of 350  230 grid nodes is used after several experiments, which shows
that further refinement in either direction does not change the result (maximum difference in
velocity and other scalar functions in the carrier phase) by more than 2%. The grid spacing in
axial and radial directions are changed smoothly to minimize the deterioration of the formal
accuracy of the discretization scheme due to variable grid spacing and in such a way higher
concentration of nodes occur near the inlet and the walls.
5 RESULTS AND DISCUSSION
Figure 2 shows the simulated contours of temperature inside the combustor for different
swirl numbers. The results show that an increase in swirl number increases the combustor
peak temperature. This occurs because an increased swirl number increases combustion
efficiency due to enhancement of mixing rates between the fuel and oxidant. The location to
give the maximum temperature shifts to forward with decrease in swirl number. This shift is
corresponding to the fact that the combustion zone of the diffusion flame is enlarged with
decrease in swirl number. This observation is in according with the results of Yapici et al.18.
Comparison between the computed and measured temperatures is shown in figure 3. It can
be seen that the predicted temperature profiles have very good agreement with measurement
results especially with respect to the maximum temperature value and its location. The results
show that the 10 steps reduced mechanism used in this paper as combustion model is able to
predict methane-air diffusion flame characterizations with sufficient accuracy15.
Figure 4 shows the distribution of soot volume fraction inside the furnace for different air
inlet swirl numbers. It can be seen that swirl intensity affects the peak soot concentration and
its location. The figure shows that an increase in swirl number although increases the peak
soot volume fraction, but decreases the soot emission from the furnace. This occurs because
an increase in swirl number enhances the rates of mixing and combustion. The soot
combustion rate is affected by O2 and OH concentration.
Measured and computed soot volume fractions are compared in figure 5, where the
centerline soot volume fraction profiles are plotted for different swirl numbers. It is observed
that the agreements between measured and predicted results are satisfactory. There is a slight
discrepancy between the predictions and measurements for condition SN=0.0. Measurements
show higher soot volume fraction in the vicinity of the point of the issue.
Kazem Bashirnezhad, Mohammad Moghiman and Leili Mirboroun
Considering the soot model equations specifies two main parameters that affect on soot
formation, i.e. acetylene concentration and soot particle density which need to be analyzed
more. Figure 6 show centerline acetylene concentrations for three swirl numbers 0.2, 0.4, and
0.6. Acetylene concentration plays effective role in soot nucleation and surface growth10,16. It
can be seen that as expected, the location of peak C2H2 mass fraction is in the vicinity of the
combustor inlet zone where the fuel concentration and temperature levels are high (see figures
2 and 3). The figure shows that swirl intensity can affect on peak value of acetylene
concentration and its location in combustor. It is seen that an enhancement in swirl number
increases C2H2 peak concentration. Figure 7 displays the centerline distributions of soot
particles density for three swirl numbers. It can be seen that soot particles density along the
combustor centerline increases to maximum and then decreases. As expected the trend of
variation of soot particles density is similar to the variation of temperature profiles (see figure
3). The distribution of the soot number density moves towards to combustor inlet with
increase in swirl number.
Figure 8 presents the influence of swirl number on soot volume fractions along the
combustor centerline. It can be seen that swirl intensity affects on the peak soot concentration
and its location. Clearly the distribution of soot volume fraction along the combustor
centerline strongly depends on the distribution of temperature and acetylene mass fraction
(see figures 2 and 6).
6 CONCLUSION
–
Burning behaviors of non premixed methane-air flame are experimentally and
computationally studied for different swirl numbers.
–
The soot particle number density and the mass density based on the acetylene
concentrations are used to model the soot emission in confined swirling turbulent
diffusion flame.
–
The results show the significant influence of swirl number on soot distribution inside
the combustor.
–
The results also show that an increase in swirl number enhances the mixing rate,
peak temperature, and peak soot volume fraction near the burner.
–
The results reveal that an increase in swirl number although increases peak soot
concentration, but decreases the soot emission from the furnace. This occurs because
an increase in swirl number enhances the rates of mixing and soot combustion.
–
The comparison of numerical predicted results with measurements show good
agreement.
Kazem Bashirnezhad, Mohammad Moghiman and Leili Mirboroun
a: SN=0.0
b: SN=0.2
1400
c: SN=0.4
d: SN=0.6
1400
1400
1500
1500
1500
1500
1529
1600
1400
1641
1200
1600
1600
1667
1724
800
1200
1300
1400
Figure 2: Effect of swirl number on predicted temperature contours
1600
1400
1200
1000
800
SN=0.0
600
Temperature (K)
Temperature (K)
1600
400
1400
1200
1000
800
600
400
0.25
0.5
0.75
1
Axial distance from burner (m)
1600
1800
1400
1600
1200
1000
SN=0.4
600
400
Temperature (K)
Temperature (K)
0.25
0.5
0.75
1
Axial distance from burner (m)
800
SN=0.2
1400
1200
1000
800
600
SN=0.6
400
0.25
0.5
0.75
1
Axial distance from burner (m)
0.25
0.5
0.75
1
Axial distance from burner (m)
Figure 3: Comparison between the computed (lines) and measured (symbols) centerline temperatures for
different swirl numbers
Kazem Bashirnezhad, Mohammad Moghiman and Leili Mirboroun
SN=0.0
SN=0.4
SN=0.2
7.19E-07
5.40E-07
4.79E-07
SN=0.6
3.46E-07
4.10E-07
6.48E-07
9.37E-07
1.07E-06
7.74E-07
9.25E-07
6.64E-07
1.22E-06
1.08E-06
1.29E-06
1.36E-06
1.15E-06
5.05E-08
1.32E-06
1.39E-06
2.80E-10
3.51 E-07
3.36E-07
2.45E-13
4.10E-07
6.67E-09
5.52E-09
2.66E-29
1.85E-11
1.16E-13
6.97E-08
2.31E-09
Figure 4: Soot volume fraction distributions inside the furnace
1.6E-06
Soot volume fraction
Soot volume fraction
1.6E-06
1.2E-06
8E-07
4E-07
0
0.0
SN=0.0
0.2
0.4
0.6
0.8
Axial distance (m)
Soot volume fraction
Soot volume fraction
4E-07
SN=0.2
0.2
0.4
0.6
0.8
Axial distance (m)
1.0
1.6E-06
1.2E-06
8E-07
0
0.0
8E-07
0
0.0
1.0
1.6E-06
4E-07
1.2E-06
SN=0.4
0.2
0.4
0.6
0.8
Axial distance (m)
1.0
1.2E-06
8E-07
4E-07
0
0.0
SN=0.6
0.2
0.4
0.6
0.8
Axial distance (m)
1.0
Figure 5: Comparison between the computed (lines) and measured (symbols) centerline soot volume fractions
for different swirl numbers
C2H2 Mass fraction
Kazem Bashirnezhad, Mohammad Moghiman and Leili Mirboroun
0.004
0.003
SN=0.2
SN=0.6
0.002
SN=0.4
0.001
0.2
0.4
0.6
0.8
1.0
Axial distance from burner (m)
Figure 6: Effect of swirl number on predicted centerline acetylene concentrations
5E+15
SN=0.6
SN
=0
.4
4E+15
.2
3E+15
=0
2E+15
SN
Soot particles density
0.0
1E+15
00.0
0.2
0.4
0.6
0.8
Axial distance from burner (m)
1.0
Figure 7: Effect of swirl number on predicted centerline soot particles density
.2
=0
0 .6
4
SN
8E-07
=0 .
1E-06
SN
1.2E-06
S N=
Soot volume fraction
1.4E-06
6E-07
4E-07
2E-07
0
0.0
0.2
0.4
0.6
0.8
1.0
Axial distance from burner (m)
Figure 8: Effect of swirl number on predicted centerline soot volume fractions
Kazem Bashirnezhad, Mohammad Moghiman and Leili Mirboroun
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