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Transcript
1
8nd International Conference on Physical and Numerical Simulation of Materials Processing, ICPNS’16
Seattle Marriott Waterfront, Seattle, Washington, USA, October 14-17, 2016
Numerical Simulation on the Combustion Characteristic of Iron
Ore Sintering with Flue Gas Recirculation
Gan Wang1, Zhi Wen1, 2, Guofeng Lou1, *, Ruifeng Dou1, Xunliang Liu1, Fuyong Su1, Sizong Zhang1
of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China.
2Beijing Key Laboratory of Energy Saving and Emission Reduction for Metallurgical Industry, University of
Science and Technology Beijing, Beijing 100083, China.
1School
ABSTRACT
Flue gas recirculation sintering (FGRS) technology can reduce pollutant emissions and reuse waste heat
effectively in iron ore sintering. The incoming gas conditions such as temperature, velocity, composition and
contents, may differ across processes because the sources of recirculated gas vary. Numerical simulations have
been developed to predict sintering behavior quantitatively. To model FGRS, reactions which O 2, CO2, CO, and
H2O participate in as reactants and products should be taken into account. A relatively comprehensive
mathematical model for a sinter bed, related to the application of FGRS and the comparison with the
conventional sintering (CS), is built. Multiphase theory is employed. This model involves most of the major
gaseous and gas-solid reactions that affected significantly by incoming gas conditions. Heat transfers are
described in improved manners compared to the previously models. To date, six sinter pot tests based on FGRS
technology have been used for model validation, and good agreements between simulated and measured
results are obtained. Parametric studies focused on the quantitatively evaluation of the effects of various
incoming gas conditions on the combustion characteristics in the sintering process, compared to CS. Results
show FGRS can significantly increase the maximum temperature in the sinter bed, improve the uneven
distribution of heat, but slightly reduce flame front speed. Thus, the quality of sintered ores, especially for the
upper bed, are enhanced, while the productivity is restricted. Velocity exerts the most significant effect, followed
by O2 content, and then, temperature.
Keywords: Flue gas recirculation; Iron ore sintering; Numerical simulation; Multiphase; Gaseous reaction; Gassolid reaction; Sinter pot test; Combustion characteristics.
1. INTRODUCTION
Iron ore sintering produces 20% pollutant of iron and
steel industry. To reduce the emission of flue gas
and reuse waste heat effectively, several types of
flue gas recirculation sintering (FGRS) processes
have been developed in last 20 years such as EOS,
LEEP, Eposint. FGRS has been applied in industrial
production in China since 2013, and five sets of
systems have been built. The main incoming gas
conditions for FGRS technology such as velocity,
temperature, composition and contents, may differ
across methods because the sources of recirculated
gas vary. A series of effects in combustion
characteristics are then generated during the
sintering process, which is worth further study.
Mathematical models have been developed to
predict quantitatively the sintering performance. Most
of these models are 1D transient process, and
transfer phenomena along the directions of grate
length and width are negligible. Shibata1) and
Patisson et al.2) concentrated on predicting the
moisture transfer process. Venkataramana et al.3)
focused on the effects of operating parameters
including suction applied, ignition time and ignition
gas temperature, while Nath et al.4,5) and
Pahlevaninezhad et al.8) analyzed on kinetic
parameters such as coke contents, coke particles
size, limestone particles size and velocity of the
incoming air. Zhou et al.6) treated solid particles with
characteristic size distributions. Zhao et al. 7) applied
an granulation model to provide a novel description
of coke positioning within granules. Ramos et al.9)
described geometric changes by combining various
reactions and gas-solid heat transfer with granule
movement. Mitterlehner et al.10) regarded the
increase in bed porosity as coke particle shrinkage
with combustion. Yang et al.’s model11-13) considered
* Corresponding author: Guofeng Lou. Tel.: +86 10 62332730; fax: +86 10 62329145; E-mail: [email protected]
2
coke particle shrinkage, generation of internal pores,
and porosity changes. Komarov et al.14) built a 2D
model in which molten iron ores were regarded as
the non-fluid medium. Ahn et al.15,16) conducted a
commercial flowsheet process simulator to build a
2D model, which was the first reported research on
the simulation study of FGRS process. Castro et
al.17,18) developed a 3D model and used soft-melting
experimental data to calculate geometric
parameters. Yamaoka et al.19) built a 3D model in
which five state parameters were selected to
express the geometric structure of the bed.
The current simulations lack of investigation on the
effects of incoming gas conditions on sintering
process. The purpose of this present study is to build
a relatively more comprehensive mathematical
model for a sinter bed related to the application of
FGRS, with a special focus on the quantitatively
evaluation of combustion characteristics in the sinter
bed. Multiphase theory11-13,17,18), which treats sinter
solid materials as multiple solid phases, is employed
to describe heat transfer within/between different
solid and gas phases in a better manner. This
present model involves most of the major
physicochemical changes that affected significantly
by incoming gas conditions, many of these
phenomena have not been considered in current
models. To date, six sinter pot tests based on FGRS
technology are used for validation studies. Then,
four quantitative parameters, namely, maximum
temperature (MaxT), flame front speed (FFS),
combustion zone thickness (CZT), and melting zone
thickness (MZT), are selected to study the
differences of combustion characteristics between
the FGRS and CS processes, as well as the effects
of temperature, O2 content, and velocity of the
incoming gas on it. This work lays the foundation for
further optimization of the FGRS process.
2. Description of the Mathematical Model
The sintering process in this study is considered a
1D transient process. Figure 1 shows that the 1D
and 2D representations are undoubtedly6).
Multiphase theory is applied, meaning each
component of the solid phases, as shown in Table 1,
has characteristic chemical compositions and
particle sizes, different temperatures and physical
properties. No temperature or species concentration
gradient exists within a single particle because of the
moderate thermal conductivity. The liquid phase, i.e.,
the molten iron ores, moves together with the
remaining solid phase due to viscosity.
Figure 1 Extension of 1D transient model to 2D steady model.
2.1 Governing Equations
Table 2 shows the detailed governing equations for
each phase, including continuity equations, energy
equations, and the component equation simplified by
Ergun’s pressure drop equation. The terms on the
right side of solid energy equation comprise a
diffusion term that includes conduction and radiation
between solid phases, convection between solid and
gas phases, the heat of various reactions, heat loss
from the release of gas produced by the reactions,
convection between solid phases, and radiation
between solid particles (in the same solid phase),
respectively. The terms on the right side of gas
energy equation are similarly defined as the first four
terms on the right side of solid energy equation.
Table 1 Raw proportion and chemical composition of the solid phases (wt. %).
Composition
Solid Phases
Proportion
Fe total
CaO
MgO
Al2O3
SiO2
MnO
S
Moisture
Iron ore fines
62.48
59.62
1.42
0.76
1.60
4.73
0.24
0.02
7.95
Return fines
26.04
58.83
8.76
1.56
1.82
4.98
0.28
0.02
0.32
Burnt-lime
1.47
0.08
52.66
0.47
0.34
1.09
0.04
0.04
0
Limestone
4.15
0.11
52.91
1.07
0.57
1.89
0.02
0.05
5.2
Dolomite
2.56
0
31.47
20.65
0.38
0.74
0
0.01
3.67
Coke
3.3
0.42
0.49
0.05
3.96
5.45
0
0.75
13.62
3
Table 2 Governing equations for each solid and gas phase.
Transfers
Solid:
Mass6,11)
Gas:
Equation

 1    g  Y j
t

  g   i

t
  1    g u s  Yi   
   g u g   i  
x

Solid:
  M j ,k R j ,k
k j
  M i ,k Ri ,k
k i
 1   j  s , j C ps , j Ts , j
t
x
  u s  s , j C ps , j Ts , j  
x
Ts , j
 
 s , j ,eff
x 
x

   hconv, j Assa , j Tg  Ts , j
 j





  M j ,k R j ,k H j ,k    M j ,k R j ,k C ps , j Ts , j   h jj  j Assa , j Ts , jj  Ts , j   Q rad
11,12)
k j

Energy
  g C pg Tg
t
Gas:
   g C pg u g Tg  
jj  j
k j
Tg 
 
    hconv, j Assa , j Ts , j  Tg
 g
x
x 
x  k j
  1   M i ,k Ri ,k H i ,k    M j ,k R j ,k C ps , j Ts , j

k
Component20,21)
P

 323
H
 jd p

1   
2
2
3
u g  3.78
2.2 Sub-models
H2O content in sintering flue gas is as high as
10~14%, though mixed with ambient air before
recirculation, the H2O content in recirculated gas
should be higher than air, as similar to CO2 and CO.
To model quantitatively and accurately the
combustion characteristics of FGRS process and
make some comparison with CS process, it is
necessary to take reactions which O2, CO2, CO,
H2O, H2 participate in as reactants and products into
consideration in reaction sub-models. In this study,
seven kinds of major gas-solid reactions and five
major gaseous reactions that affected significantly by
incoming gas conditions are considered to calculate
the source terms of the conservation equations
mentioned in Table 2.
2.1.1 Gas-solid Reactions
Table 3 shows the seven major gas-solid reactions
considered in this established model. Among these,
drying of water in sintering raw mix is seen to occur
in two distinct periods2, 6). The major solid-gas
reactions in sinter bed are coke combustion and
limestone calcination, which are regarded as
unreacted-core shrinking models. A stoichiometric
coefficient κ is proposed to characterize the degree
of incomplete combustion of coke22). The kinetic
parameters for coke gasification and combustion are
listed in Table 4. Other reactions are simply
described as functions of temperature and TGA
conversion in previous studies24-27). Iron oxides are
considered to be reduced by CO and H2 in a
stepwise manner during sintering, and a three-step
mechanism is postulated, given that the solid
temperature lasts long above 570 °C. The kinetic
jj  j

k j
g 1  2
ug
 jd p  3
parameters for iron oxide reductions are listed in
Table 5. Melting and solidification are controlled by
bed temperature, whereas the initiation temperature
of melting, Tm1, and its completion temperature, Tm2,
are derived from the CaO-Fe2O3 phase diagram.
Gas species participate in reactions as reactants or
products.
2.1.2 Gaseous Reactions
For a CS process, as ambient air used for the
incoming gas, only convection heat transfer between
high-temperature bed and low-temperature air
occurs in the upper bed, i.e., the sintered zone.
However, gaseous reactions in the gas phase in the
sintered zone may also take place because of the
presence of additive CO2, CO, H2O, NOx, and SO2 in
the recirculated gas via FGRS process. Meanwhile,
CO2, CO, H2O, H2, and CH4 generated via the coke
reactions mentioned earlier flows downward through
the sinter bed with the high-temperature gas. Then,
the gaseous reactions in raw mix zone occur. The
homogenous gas reactions are depended on the
contents of the reactants and products in the gas
atmosphere. The present model has considered
wider range of these reactions, compared to the
most of previous models, as listed in Table 65,8,10,28).
2.3 Heat Transfers
In this work, one single solid particle has a
representative temperature and gas concentration.
Thus, the complicated modes of heat transfer in a
sinter bed are summarized as convection/radiation
between gas and solid phases, conduction/radiation
among different solid phases or within the same
solid phase, and conduction in the gas phases.
4
Table 3 Gas-solid reactions considered in the established model.
Reactions
Expression
(1) Drying and Condensation
H2O(l)↔H2O(g)

Rdry     H 2O  Assa Rg Tg PH 2O  PH
2,6)
2O
 , where, ω=W
H2O/Wcr.
When ω>=1, χ=1, when ω<1, χ=1-(1-ω)∙(1-1.796ω+1.0593ω2).

Rconden   H 2O  Assa Rg Tg PH
 PH 2O
 1
 jd p



   k  Sh  D
 B

e
 DO2
c ,i
CO2 ,eff
j

Rcoke,i  nC  4rc2  C i
(2) Coke Gasification and Combustion5,8,11,22)
C(s)+H2O(g)↔CO(g)+H2(g)
C(s)+2H2(g)↔CH4(g)
C(s)+CO2(g)↔2CO(g)
κC(s)+O2(g)→2(κ-1)CO(g)+(2-κ)CO2(g)
2O


 , where, i represent O ,
2




H2O, CO2 and H2, respectively, and rc  r0  mc m0 1 3 , kc  A  Ts , j  exp  E Rg Ts , j ,
Sh  2  0.7 Re
0.7


nL  4rc2  CCO
 CCO
2
Rlim ist 
 jd p
23)
(3) Limestone Calcination
CaCO3(s)→CaO(s)+CO2(g)
Sc
2
r
r
2
 0 1.41
  0
rc  J  DCO
 rc
2
Sh  DCO2 ,eff
13


,   r0  rc .
2

, where, CCO

2


 4.1868K eq

 k R T
c g s, j

K eq
1000Rg Ts , j
K eq  101325exp 7.0099 8202.5 Ts , j , kc  1.52103 exp  20143.4 Ts , j

(4) Dolomite Calcination24)
CaMg(CO3)2(s)→CaO(s)+MgO(s)+2CO2(g)
 190.67 103  0.4 0.6
m m
Rdolom  1.628107 exp 
c
0

Rg Ts , j 

(5) Combined Water Release25)
Ca(OH)2(s)→CaO(s)+H2O(g)
 280.4  103  P  exp  138.5  103 Rg Ts , j

Rdiss  1.18 1018 exp 
 S 0  mc , where p* =

Rg Ts , j 
Rg Ts , j

1.834 × 108 atm, S0 = (8.3 ± 1) × 103 m2∙kg−1.




(6) Iron Oxides Reduction26,27)
3Fe2O3(s)→2Fe3O4(s)→6FeO(s)→6Fe(s)
,
Rreduc  A  exp  E R g Ts , j  m10 3  m1c 3

2
 m10 3
M f  minTs  Tm1  Tm2  Tm1 ,1 while Ts  Tm1
Rmelt  0.001 Ts  Tm1  s
(7) Melting and Solidification5, 6)
Solid Mixture(s)→Molten(s,l)→Precipitated
Minerals and Phase(s)
Tm1  1380 21.22Al2O3  3.35SiO2 1.8 flux , where Al2O3, SiO2, and flux indicate the
corresponding mass contents in raw mix.
Table 4 Kinetic parameters for coke gasification and combustion.
Vulue
O2
H2O
CO2
H2
A (s-1)
1.715
3.42
589
3.42×10-3
E (J∙mol-1)
74.83×103
129.7×103
222.82×103
129.7×103
Table 5 Kinetic parameters for different steps of iron oxide reductions.
Fe2O3 → Fe3O4
Fe3O4 → FeO
FeO → Fe
Reducing substance
A (s-1)
E (J∙mol-1)
A (s-1)
E (J∙mol-1)
A (s-1)
E (J∙mol-1)
CO
1.32×106
114~125.4×103
3.06×105
68.6×103
1.91×105
66×103
H2
3.49×106
75.9~137.9×103
3.63×107
96.2×103
2.19×106
75.5×103
Table 6 Rates of gaseous reactions considered in the model.
Reaction
Rgas (mol∙m-3∙s-1)
A (s-1)
E (J∙mol-1)
(1) CO+0.5O2→CO2
A exp( E RgTg )  CCOCO0.52 CH0.52O
1.3×108
125.54×103
(2) CO2→CO+0.5O2
A exp( E RgTg )  CCO2
7.5×1011
386.6×103
(3) CO+H2O→CO2+H2
A exp( E RgTg )  CCOCH2O
2.78
12.55×103
(4) H2+CO2→CO+H2O
A exp( E RgTg )  CH 2 CCO2
93.96
46.59×103
(5) H2+0.5O2→H2O
A exp( E RgTg )  CH 2 CO2
1011
42×103
5
Table 7 Modes of heat transfer used in the established model.
Heat transfers
Expression
hconv, j 
(1) Convection between solid and gas phase
(2) Conduction and radiation between solid phases
 g Nu
 jd p




g  1  1.5 1   j 2  Re0.6 Pr1 3



 jd p
s , j ,eff  1   j s , j  4 j d p , jTs3, j
29)
h jj  j  2
(3) Convection among solid phases30)

Q rad  Assa  I   I 
31)
(4) Radiation within the solid particles of the same phase
The major modes of heat transfer considered are
listed in Table 7. (1+1.5(1−εj)) is the correction factor
based on the porous media assumption to calculate
convective heat transfer between solid and gas
phases. An effective thermal conductivity term λs,j,eff
is used to calculate conductive and radiative heat
transfer between solid phases29). A form of the
convective heat transfer coefficient hjj-j is used to
express heat exchange among solid phases30). The
two-flux model is used to calculate radiative heat
transfer within solid particles31).
3. Sinter Pot Test
1   j s , j  s , j C ps , j   j  g  g C pg
 1   j Ts   j Tg 
 W
m
3

1  j
1   jj
until the flue gas temperature slightly increases to a
peak value; time for cooling: after moving the
recirculation hood and until flue gas temperature
drops to below 100 °C; temperature for ignition: 1150
oC; suction negative pressure during ignition,
sintering, and cooling: 8.83, 14.71, and 7.87 kPa,
respectively.
The velocity, temperature, and species
concentrations of the simulated recirculated gas, the
bed temperature profiles, as well as the temperature
and species concentrations of the flue gas in the
wind box are measured. In this study, the results for
only two cases, i.e., CS and T200-19, are shown.
In both the present study and the most of the
previous work10-14), the mathematical models are
validated by comparing the model predictions with
the sinter pot test data. A detailed description of the
conducted sinter pot tests is provided in the previous
work32).The raw materials for tests are obtained on
site from a single batch to ensure consistency in
chemical composition and mix proportion, as also
listed in Table 1. The schematic illustrations of the
installation of the experimental facility and that of the
sintering process are shown in Figure 2.
The tests are categorized based on the temperature
and O2 content of the recirculated gas by considering
FGRS technology. The values are set as close as
possible to the values used in industrial production
conditions. And case CS is also investigated for
comparison, as shown in Table 9.
The following are the main laboratory scale
operational conditions for the tests: time of ignition: 2
min; time for flue gas recirculation: after ignition and
Figure 2 Schematic diagram of the facility installation for the
sinter pot tests.
Table 9 Experimental cases of the sintering pot tests.
Case
T150-19
T200-19
T250-19
T200-18
T200-20
CS
Temperature (oC)
150
200
250
200
200
30
O2 content (Vol. %)
19
19
19
18
20
21
6
CO2 content (Vol. %)
3.88
3.64
4. Results and Discussion
4.1 Model Validation
The experimental conditions of the sinter pot tests
are used to validate the mathematical model in this
study by defining the initial and boundary conditions.
The contrasting results between the simulated and
measured bed temperatures and the flue gas
species concentrations for cases CS and T200-19,
along with other fixed operating parameters, are
shown in Figure 3. The simulated results of the bed
temperatures are close to the experimental data with
regard to MaxT at given locations and duration times
at high temperatures. The times of temperature
increase for the simulation show a slight difference
with the measured ones at each corresponding
location. This observation may be explained through
the simplified analysis of bed shrinkage in this
model, in which shrinkage presumably occurs only
during melting and solidification. Bed shrinkage
caused by combustion and decomposition reactions
will be considered in a future work. The predicted
flue gas species concentrations of O2, CO2, and CO
also exhibit a reasonable agreement with the
experimental data, even though a slight difference
exists near burn through because of combustion rate
overestimation.
MaxT and FFS are also selected for the quantitative
comparison of the modeling and measured results.
MaxT is defined as the maximum temperature of a
solid material at a given time, which indicates the
degree of heat concentration in the bed, whereas
FFS can be defined as11)
Dis tan ce between po int A and B at 973K
FFS 
Tim e consum ed for propagation m in
cm
where points A and B represent the locations of x =
525 mm and x = 225 mm, respectively, where
thermocouples are installed in the sinter pot tests.
The 973 K represents the initiation temperature of
coke combustion. The comparison of the six cases
between the modeling and measured results is
presented in Figure 4.
The modeling bed temperatures at the location of x =
525 mm, i.e., the upper bed, agree well with the
measured data, whereas the relative error at the
location of x = 225 mm, i.e., the middle and lower
beds, increases significantly and is valued at ~5%.
The reason for this finding is that the temperature
3.43
3.53
3.47
0
difference between the two points is not obvious in
the sinter pot tests. In fact, the temperature
difference between the two points is close to the
modeling results. Two reasons may cause the
experimental error: the sensitivity of the
thermocouple sensor on the one hand and the
influence of the gas flow in the combustion zone on
the thermocouple sensor on the other hand. The
temperature of gas flow in the combustion zone is
lower than that of the solid material because of the
violent exothermic reaction during coke combustion.
Good agreements are achieved for FFSs, and the
relative error is less than 5%.
(a)
7
4.2. Combustion Characteristics in the
Sintering Process
(b)
Figure 3 Comparison between simulated and measured data for
cases CS and T200-19: (a) bed temperature profiles and (b) flue
gas species concentration profiles.
(a)
(b)
Figure 4 Comparison between the modeling and measured
results: (a) MaxT and (b) FFS.
The 1D transient model can be converted into a 2D
steady process in the Cartesian coordinate system
when the abscissa uses sintering time and the
ordinate uses bed height. The 2D modeling results of
bed temperature and melt fraction distributions within
the sinter bed, for case CS, are presented in Figure
5. After ignition, sintering is sustained by coke
combustion. The temperature of air/gas supplied to
the combustion zone increases because of
convection heat transfer from the heated particles in
the upper bed of the high-temperature zone; the
combustion zone tends to widen, and peak
temperature increases as the combustion front
proceeds downward12), as shown in Figure 5(a).
This finding fully testifies to heat accumulation in the
lower bed. The coke combustion rate also increases
as bed temperature increases. Heat accumulation
also causes additional melting of iron ores, which
decreases bed permeability, as shown in Figure
5(b). This phenomenon is observed in practice,
which implies that the sintered ore from the lower
bed is stronger than that from the upper bed.
Temperature is considered the most important
parameter in studying combustion characteristics in
the sinter bed. The most important quantitative
parameters, namely, MaxT, CZT, and MZT, should
be discussed in detail because they significantly
affect bed permeability. CZT and MZT are defined as
the thickness of the combustion zone and the
melting zone whose bed temperature is over the
initial temperatures of coke combustion and iron ore
melting, respectively. As shown in Figure 6, MaxT
gradually increases, which implies heat
accumulation in the lower bed. CZT and MZT, which
are determined to be highly dependent on bed
temperature, also tend to increase as the process
progresses. The increase in MaxT, CZT, and MZT in
the lower bed indicate that the quality of the sintered
ores enhance because increased strength should be
guaranteed with increased temperature. However,
they also mean that the bed permeability in the lower
bed decreases since the increased degree of melt
fraction. Thus, the total pressure drop of the
combustion zone and the melting zone in the lower
bed increase significantly.
8
(a)
(b)
Figure 5 Combustion Characteristics within the sinter bed: (a) bed
temperature distributions and (b) melt fraction distributions.
Figure 7 Schematic diagram of industrial FGRS system.
4.3.2. Simulation cases
Therefore, the calculation cases in this study are
performed for various sets of the three main
operating parameters of the recirculated gas,
namely, average temperature, O2 content, and gas
velocity. The cases listed in Table 10 cover all
ranges of the operating conditions that are available
in industrial FGRS, in which CS is used as the
reference case. Ambient air is used as the incoming
gas in the exposure region, of which the velocity is
equal to that of the recirculated gas in the
recirculation region.
Figure 6 Simulated results of MaxT, CZT, and MZT curves for
cases CS and T200-19.
4.3. Parametric Study on FGRS Process
4.3.1. Boundary and initial conditions of an
industrial FGRS process
The industrial production conditions for the no. 2
sinter strand in Baoshan Stainless Steel Co., Ltd. in
China are used to define the initial and boundary
conditions. The schematic diagram of the industrial
FGRS system of this manufacturer is shown in
Figure 7. During ignition, the inlet gas temperature is
set to 1150 °C for 4.0 m and then to 850 °C for 3.8 m
(heat preservation). Subsequently, a recirculated gas
temperature is set for 21.5 m, after which ambient
temperature is set. Inlet gas velocity is set to the
values determined from the surface of the 700 mmhigh sinter bed, at the bottom of which is the 30 mmhigh hearth ore. The traveling speed of the sintering
strand is 1.24 m∙min-1. The volume fractions of all the
gas species are specified, and inlet pressure is
defined as 1.0 atm. The gradient of all the gas
species concentrations at the outlet is set to 0. The
chemical compositions of the raw mixtures, which
are also used as initial conditions in this study, are
presented in Table 1.
4.3.3. Combustion characteristics of the reference
case
To quantify the combustion characteristics, MaxT,
FFS, sintering time (ST), and terminal temperature
(TT) are introduced. To define ST, x = 75 mm is
used as a base level, and the time when flame front
reaches the point is calculated. TT is defined as the
solid temperature when time reaches ST. The
quantitative parameters for CS are below: ST = 1822
s, FFS = 2.320 cm∙min-1, MaxT for x = 525 mm, 375
mm, 225 mm, and 75 mm are 1553.45 K, 1598.38 K,
1632.87 K, and 1662.59 K, respectively, and TT are
464.73 K, 863.54 K, 1381.60 K, and 1662.59 K,
respectively.
Table 10 Calculation cases categorized under various the
incoming gas conditions.
Case
names
Temperature
(oC)
O2 content
(vol. %) a
Gas velocity
(Nm∙s-1)
CS
30
21
0.3
GasT-**
150~250,
Δ=50
19
0.3
GasO2-**
200
17~21, Δ=1
0.3
19
0.24~0.38,
Δ=0.2
GasV-**
a
200
The total content of O2 and CO2 is 21 vol. %.
4.3.4. Effect of incoming gas temperature
Figure 8 shows the modeling results of the bed
temperature profiles for various incoming gas
9
temperature and for a fixed gas supply. The
combustion zone appears broader at higher
incoming gas temperature. Interestingly, temperature
increase and MaxT at a specific location show hardly
difference because of the convective heat transfer
between the heated particles and the heating gas.
However, high incoming gas temperature results in
relieved cooling progress of the sintered ore in the
upper bed, which slightly improves the unevenly
distributed heat concentration.
Figure 8 Modeling results of the bed temperature profiles at
various incoming gas temperatures.
Compared with the CS process, the TTs of the cases
with various incoming gas temperatures at specific
locations, as shown in Table 11, all demonstrate a
significant increase, and more notable increase is
observed at the location of x = 525 mm, i.e., the
upper bed. Simultaneously, the coke combustion
rate is limited by O2 diffusion at high temperatures,
which slightly reduces FFS for higher incoming gas
temperatures. Actually, a higher incoming gas
temperature leads to a larger suction applied to
obtain a consistent gas supply, which implies that
the power consumption and loading of the main fan
will increase. Therefore, considering the safety of
equipment and costs, incoming gas temperature
becomes unsuitable at over high levels and is
frequently controlled at the range of 200~250 °C in
industrial production.
4.3.5. Effect of O2 content in incoming gas
Figure 9(a) shows that at low O2 content, bed
temperature increase at a specific location is
delayed, whereas that at the lower bed becomes
increasingly significant, which implies that the flame
front propagates slowly through the sinter bed. From
Figure 9(b), an increase in CO2 content can be
observed in the case of low O2 content. Meanwhile,
an increase in CO content indicates that fuel
consumption rate decreases and the incomplete
combustion degree of fuel increases during sintering.
Therefore, heat loss and carbon residues that exit
the sintered ore will increase, whereas fuel heat
efficiency will significantly decrease33-35). Coke
combustion within the sinter bed is a complex
reaction that is assumed as an unreacted-core
shrinking model with characteristic size distributions.
Theoretically, combustion rate proportionally
decreases along with O2 potential. Therefore, FFS
decreases along with O2 content in the incoming
gas, whereas ST exhibits the opposite trend, as
listed in Table 12. In particular, low O2 content
decelerates FFS and extends ST during the entire
process, which inhibit productivity.
Coke combustion rate decreases along with O2
content, which reduces MaxT at a specific location of
the sinter bed, as illustrated in Figure 10. A low
MaxT in the sinter bed frequently deteriorates the
tumble index of the sintered ore because additional
silicate slags are produced in the reaction as a result
of the reduced oxygen potential in the sinter bed. At
x = 525 mm, MaxT of case GasO2-17 is extremely
close to that of CS, which indicates that if O2
concentration continues to decrease, the melting
conditions of the upper bed may be worse than that
in CS, which contradicts the original intention of
FGRS technology.
Table 11 Quantitative parameters at various incoming gas
temperatures.
Quantitative
parameter
GasT150
GasT200
GasT250
x=525mm
1564.69
1567.17
1569.53
x=225mm
1662.37
1666.10
1669.85
x=525mm
553.71
589.41
626.76
x=225mm
1425.09
1436.53
1448.15
1838
1860
1880
2.293
2.256
2.218
MaxT (K)
TT (K)
ST (s)
-1
FFS (cm∙min )
(a)
10
(b)
Figure 10 Modeling results of MaxT under various O2 contents in
incoming gas.
Figure 9 Modeling results of (a) bed temperature profiles and (b)
flue gas species emissions under various O2 contents in incoming
gas.
Table 12 STs and FFSs under various O2 contents in the incoming gas.
Characteristic Temperature
GasO2-17
GasO2-18
GasO2-19
GasO2-20
GasO2-21
ST (s)
1889
1875
1860
1844
1830
FFS (cm∙min-1)
2.189
2.224
2.256
2.289
2.314
4.3.6. Effect of incoming gas velocity
Figure 11 shows the results of bed temperature and
flue gas emissions under various gas velocities. For
a high gas velocity, temperature increase at a
specific location is significantly advanced, which
implies that the flame front propagates rapidly
through the sinter bed. According to Yang et al.33),
coke particles in the upper bed requires a long time
to burn out under a low gas supply, and thus, the
lower bed is slightly affected. From Figure 11(b),
CO2 content is decreased under low gas velocity,
whereas coke consumption rate is decreased under
slow combustion propagation. That is, higher gas
velocity results in larger coke combustion rate.
(b)
Figure 11 Modeling results of (a) bed temperature profiles and (b)
flue gas species contents under various incoming gas velocities.
(a)
MaxT at a specific location slightly increases, as
shown in Figure 12(a), which indicates that the
quality of the sintered ore will not be compromised
by high gas velocity. Figure 12(b) shows that FFS
proportionally increases along with incoming gas
velocity, whereas ST exhibits the opposite trend.
High gas velocity accelerates FFS and saves ST
during the entire process to enhance productivity.
Given that high gas velocity increases the fan power
and capacity of the flue gas treatment system,
system costs are obviously increased. By contrast,
gas supply must not be too small for a designed
sintering strand speed (1.24 m∙min-1 in this study).
For a low incoming gas velocity and using 0.24
11
Nm∙s-1 as an example, the flame front does not
completely penetrate into the bed, and when
unloading sintered ore into the cooler, the quality of
sintered ore in the lower bed may not satisfy
production requirements. Therefore, a low incoming
gas velocity can directly reduce productivity.
MaxT and combustion zone thickness of the sinter
bed. Therefore, gas flow resistance is slightly
increased, whereas FFS is slightly decreased. These
results imply that the operating parameters, with
regard to FGRS technology, must be adjusted
reasonably to maximize the utilization of the
advantages of such technology, that is, to improve
the quality of the sintered ore while maintaining
stable productivity.
5. Conclusions
(a)
(b)
Figure 12 Modeling results of (a) MaxT and (b) FFS and ST under
various incoming gas velocities.
As confirmed by the simulation results, the effect of
incoming gas velocity is greater than those of O2
content and temperature. For a fixed O2 content and
temperature of the recirculated gas, a low incoming
gas velocity reflects a low O2 supply per unit mass of
coke, which results in a low combustion rate. Figure
12(b) shows that FFS in case GasV-0.32 is higher
than that in CS. Therefore, FFS becomes consistent
in CS as velocity slightly increases. However, by
producing additional fan power, an increase in
incoming gas velocity directly increases costs. O2
content in the incoming gas for FGRS is inevitably
reduced. When the velocity and temperature of the
recirculated gas are fixed, the melting conditions of
the upper bed may be worse than that in CS if O2
content is reduced to less than 17 vol.%, as shown
in Figure 10. Therefore, O2 content must be
maintained at higher than 17 vol.% as much as
possible. In addition, for a fixed velocity and O2
content of the recirculated gas, the increase in
temperature of the incoming gas can increase the
This study introduces a comprehensive 1D
mathematical model of the iron ore sintering process
by considering FGRS technology. This multiphase
theory-based model considers most of the primary
phenomena that occur in the sintering process. The
major gas-solid and gaseous reactions which O2,
CO2, CO, and H2O participate in as reactants and
products are taken into account. Many of these
phenomena have not been considered in currently
established models. Convective, conductive, and
radiative heat transfer modes within/between
different solid and gas phases are considered.
Geometric changes are not involved. Six carefully
controlled sinter pot tests based on FGRS
technology are used to validate the model.
Reasonable agreements are obtained.
The simulated results show that the combustion
zone tends to widen, and MaxT increases as the
combustion front proceeds downward, testifying the
heat accumulation in the lower bed, and MZT also
tends to increase as the process progresses. The
increase in MaxT, CZT, and MZT indicate that the
sintered ore from the lower bed is stronger than that
from the upper bed. However, the bed permeability
in the lower bed decreases since the increased
degree of melt fraction. Thus, the total pressure drop
of the combustion zone and the melting zone in the
lower bed increase significantly.
Parametric studies are performed at various
velocities, temperatures, and O2 contents of the
incoming gas. The modeling results also show the
improvement of the unevenly distributed heat
concentration in the bed via the FGRS process, due
to the additional heat supply by hot recirculated gas.
The decrease in O2 content may worsen the melting
conditions of the upper bed. The increase in
incoming gas velocity reflects more O2 supply per
unit mass of coke, which results in a higher
combustion rate and MaxT. However, FFS requires
further attention. And with the increase in
temperature or velocity, more power consumption
and larger loading of the main fan are needed.
Velocity exerts the greatest effect, followed by O2
12
content. The incoming gas conditions of FGRS must
be carefully determined, the temperature is
suggested to be 200~250 oC, the O2 content must be
controlled to be higher than 17 vol.%, and the
velocity should be slightly increased compared to CS
process. Work continues to further improve the
generality and accuracy of the proposed model, as
well as to further investigate the process optimization
of the FGRS technology.
t: Time, s
T: Temperature, K
u: Velocity, m∙s-1
Wcr: Critical solid moisture content, %
x: Spatial coordinate along the direction of bed
height, m
Y: Mass fraction of solid and gas phases, ΔH: Heat of reaction, J∙kg -1
Acknowledgments
This work was financially supported by the National
Natural Science Foundation of China (No.
50876011). Meanwhile, the authors wish to express
their thanks to EssayStar.com for providing language
help.
ΔP: Pressure drop across the sinter bed, Pa
Nu: Particle Nusselt number, Pr: Particle Prandtl number, Re: Particle Reynolds number, Sc: Particle Smit number, -
Nomenclature
Sh: Particle Sherwood number, -
A: Specific surface area,
factor, s-1
m 2∙m-3;
Pre-exponential
B: Parameters related to the surface structure of
coke, C: Molar concentration of gas phases, mol∙m-3
Cp: Specific heat, J∙kg-1∙K-1
Greeks
χ: Polynomial correlation of the characteristic drying
curve for iron ore particles, δ: Ash layer thickness, m
dp: Solid phase mean diameter, m
ε: Porosity of sinter bed or solid phases, -;
Emissivity, -
D: Mass diffusion coefficient of gas phases, m 2∙s-1
φ: Fraction of heat absorbed by solid, -
E: Activation energy,
J∙mol -1
h, hconv: Convection coefficient,
γ: Volume fraction of solid and gas phases, W∙m-2∙K-1
κ: Stoichiometric coefficient, -
H: Height of the sinter bed, m
λ: Conductivity, W∙m-1∙K-1
I: Radiation intensity, W∙m-2sr
μ: Gas dynamic viscosity, kg∙m-1∙s-1
kc: Reaction rate constant,
m∙s-1
ρ: Density, kg∙m-3
Keq: Reaction equilibrium constant, -
σ: Stefan-Boltzmann constant, W∙m-2∙K-4
m0: Mass density of the initial particle, kg∙m-3
ςj: Solid phase shape factor, -
mc: Mass density of the un-reacted part, kg∙m-3
M: Molecular weight, kg∙mol-1
n: Particle number density,
Subscripts and Superscripts
1∙m-3
g: Gas
P: Pressure, Pa
Q: Volumetric heat generation rate,
s: Solid
W∙m-3
r0: Radius of the initial particle, m
rc: Radius of the un-reacted part, m
R: Reaction rate, mol∙m-3∙s-1
Rg: Universal gas constant, J∙mol-1∙K-1
k: Reaction index
i: Gas species index (i = N2, O2, CO2, CO, H2, and
H2O)
j, jj: Solid species index (j = sinter feed, return fine,
coke, limestone, dolomite, hydrated lime)
C: Coke
13
L: Limestone
H2O: Vapor or solid moisture
eff: Effective diffusion
rad: Radiation
ssa: Specific surface area
*: Saturation vapor; Gas equilibrium concentration
ω: Phase change factor dependent on factors
REFERENCES
J. Shibata. (1988). Analysis of Sintering Process by
the Mathematical Model, Mathematical and
Computer Modeling, 11, 956-961.
F. Patisson, J.P. Bellot, D. Ablitzer. (1990). Study of
Moisture Transfer during the Strand Sintering
Process, Metallurgical Transaction B, 21, 37-47.
R. Venkataramana, S.S Gupta, P.C. Kapur, N.
(1998). Ramachandran. Mathematical Modelling
and Simulation of the Iron Ore Sintering Process,
Tata Search, 50-55.
Heat front Propagation in the Iron Ore Sintering
Process, ISIJ International, 44, 11-20.
W. Yang, C. Ryu, S. Choi, E. Choi, D. Lee, W. Huh.
(2004). Modeling of Combustion and Heat Transfer
in an Iron Ore Sinter bed with Considerations of
Multiple Solid Phases, ISIJ International, 44, 492499.
W. Yang, C. Ryu, S. Choi, E. Choi, D.W. Ri, W. Huh.
(2004). Mathematical Model of Thermal Process in
an Iron Ore Sinter bed, Metals and Materials
International, 10, 493-500.
H. Kang, S. Choi, W. Yong, B. Cho. (2011).
Influence of Oxygen Supply in an Iron Ore
Sintering Process, ISIJ International, 51, 10651071.
S.V. Komarov, H. Shibata, N. Hayashi, E. Kasai.
(2010). Numerical and Experimental Investigation
on Heat Propagation through Composite Sinter
Bed with Non-Uniform Voidage: Part 1
Mathematical Model and Its Experimental
Verification, Journal of Iron and Steel Research,
International, 17, 01-07.
N.K. Nath, A.J. Da Silva, N. Chakraborti. (1997).
Dynamic Process Modeling of Iron Ore Sintering,
Steel Research, 68, 285-292.
H. Ahn, S. Choi, B. Cho. (2013). Process Simulation
of Iron Ore Sinter bed with Flue Gas Recirculation,
Part 1- Modelling Approach, Ironmaking and
Steelmaking, 40, 120-127.
N.K. Nath, K. Mitra. (2005). Mathematical Modeling
and Optimization of Two-Layer Sintering Process
for Sinter Quality and Fuel Efficiency Using Genetic
Algorithm, Materials and Manufacturing Processes,
20, 335-349.
H. Ahn, S. Choi, B. Cho. (2013). Process Simulation
of Iron Ore Sinter bed with Flue Gas Recirculation,
Part 2- Parametric Variation of Gas Conditions,
Ironmaking and Steelmaking, 40, 128-137.
H. Zhou, J.P. Zhao, C.E. Loo, B.G. Ellis, K. Cen.
(2012). Numerical Modeling of the Iron Ore
Sintering Process, ISIJ International, 52, 15501558.
J.A. de Castro, Y. Sazaki, J. Yagi. (2012). Three
Dimensional Mathematical Model of the Iron Ore
Sintering Process Based on Multiphase Theory,
Materials Research-IBERO-American Journal of
Materials, 15, 848-858.
J.P. Zhao, C.E. Loo, R.D. Dukino. (2014). Modelling
fuel combustion in iron ore sintering, Combustion
and Flame, 162, 1019-1034.
M. Pahlevaninezhad, M.D. Emami, M. Panjepour.
(2014). The Effects of Kinetic Parameters on
Combustion Characteristic in a Sinter bed, Energy,
73, 160-176.
M.V. Ramos, E. Kasai, J. Kano, T. Nakamura.
(2000). Numerical Simulation Model of the Iron Ore
Sintering Process Directly Describing the
Agglomeration Phenomenon of Granules in the
Packed Bed, ISIJ International, 40, 448-454.
J. Mitterlehner, G. Loeffler, F. Winter, H. Hofbauer,
H. Schmid, E. Zwittag, T.H. Buergler, O. Pammer,
H. Stiasny. (2004). Modeling and Simulation of
J.A. de Castro, N. Nath, A.B. Franca, V.S.
Guilherme, Y. Sasaki. (2012). Analysis by
Multiphase Multicomponent Model of Iron Ore
Sintering based on Alternative Steelworks Gaseous
Fuels, Ironmaking and Steelmaking, 39, 605-613.
H. Yamaoka, T. Kawaguchi. (2005). Development of
a 3-D Sinter Process Mathematical Simulation
Model, ISIJ International, 45, 522-531.
C.W. Crawford, O.A. Plumb. (1986). The Influence of
Surface Roughness on Pressure Drop and Fluid
Velocities through Beds of Particulates, Journal of
Fluids Engineering-Transactions of the ASME, 108,
343-347.
J. Hinkley, A.G. Waters, J.D. Litster. (1994). An
Investigation of Pre-ignition Air Flow in Ferrous
14
Sintering, International Journal of Mineral
Processing, 42, 37-52.
M.L. Hobbs, P.T. Radulovic, L.D. Smoot. (1993).
Combustion and Gasification of Coals in Fixedbeds, Progress in Energy and Combustion
Science, 19, 505-586.
R.W. Young. (1977). Dynamic Mathematical Model
of (Iron-Ore) Sintering Process, Ironmaking and
Steelmaking, 4, 321-328.
M. Hartman, O. Trnka, V. Vesely, K. Svoboda.
(1996). Predicting the Rate of Thermal
Decomposition of Dolomite, Chemical Engineering
Science, 51, 5229-5232.
A. Irabien, J.R. Viguri, I. Ortiz. (1990). Thermal
Dehydration of Calcium Hydroxide. 1. Kinetic
Model and Parameters, Industrial & Engineering
Chemistry, 29, 1599-1606.
W.K. Jozwiak, E. Kaczmarek, T.P. Maniecki, W.
Ignaczak, W. Maniukiewicz. (2007). Reduction
Behavior of Iron Oxides in Hydrogen and Carbon
Monoxide Atmospheres, Applied Catalysis A:
General, 326, 17-27.
A. Pineau, N. Kanari, I. Gaballah. (2006). Kinetics of
Reduction of Iron Oxides by H2. Part I: Low
Temperature Reduction of Hematite,
Thermochimica Acta, 447, 89-100.
C.D. Blasi. (2000). Dynamic behavior of stratified
downdraft gasifiers, Chemical Engineering
Science, 55, 2931-2944.
H. Thunman, B. Leckner. (2001). Ignition and
Propagation of a Reaction Front in Cross-current
Bed Combustion of Wet Biofuels, Fuel, 80, 473481.
P.R. Austin, H. Nogami, J. Yagi. (1997). A
Mathematical Model for Blast Furnace Reaction
Analysis Based on the Four Fluid Model, ISIJ
International, 37, 748-755.
D. Shin, S. Choi. (2000). The Combustion of
Simulated Waste Particles in a Fixed Bed,
Combustion and Flame, 121, 167-180.
G. Wang, Z. Wen, G.F. Lou, R.F. Dou, X.W. Li.
(2015). Experimental Study on the Effect of Waste
Gas Recovery on the Iron Ore Sintering, Heat
Transfer - Asian Research, (Published online),
http://onlinelibrary.wiley.com/doi/10.1002/htj.
21202.
W. Yang, S. Choi, E.S. Choi, D.W. Ri, S. Kim.
(2006). Combustion characteristics in an iron ore
sinter bed—evaluation of fuel substitution,
Combustion and Flame, 145, 447-463.
X.H. Fan, Z.Y. Yu, M. Gan, W.Q. Li, Z.Y. Ji. (2013).
Influence of O2 Content in Circulating Flue Gas on
Iron Ore Sintering, Journal of Iron and Steel
Research, International, 20, 01-06.
X.H. Fan, Z.Y. Yu, M. Gan, X.L. Chen, T. Jiang, H.L.
Wen. (2014). Appropriate Technology Parameters
of Iron Ore Sintering Process with Flue gas
recirculation, ISIJ International, 54, 2541-2550.