Particulate Sintering of Iron Ore and Empirical Analysis of Sintering Time Based on Coke Breeze Input and Ignition Temperature

IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE)
e-ISSN: 2278-1684,p-ISSN: 2320-334X, Volume 7, Issue 4 (Jul. - Aug. 2013), PP 42-51
www.iosrjournals.org
www.iosrjournals.org 42 | Page
Particulate Sintering of Iron Ore and Empirical Analysis of
Sintering Time Based on Coke Breeze Input and Ignition
Temperature
C. I. Nwoye1
, E. E. Nnuka1
, V. O. Nwokocha1, 2
and S. O. Nwakpa1
1
Department of Materials and Metallurgical Engineering, Nnamdi Azikiwe University Awka, Nigeria
2
Federal Ministry of Works, Abuja
Abstract: Particulate sintering of iron ore has been carried out using the necessary ingredients. Empirical
analysis of the sintering time based on the coke breeze input concentration and ignition temperature were also
successfully obtained through first principle application of a derived model which functioned as a evaluative
tool. The derived model;
S = (√T)0.95
+ 0.0012α
indicates that amongst ignition temperature and coke breeze input, sintering time is more significantly affected
by the coke breeze input concentration. This is based on the higher correlation it makes with sintering time
compared to applied ignition temperature, all other process parameters being constant. The validity of the
model was rooted in the core expression S – Kα ≈ (√T )N
where both sides of the expression are correspondingly
approximately almost equal. Sintering time per unit rise in the operated ignition temperature as obtained from
experiment, derived model and regression model were evaluated as 0.0169, 0.0128 and 0.0159 mins. / 0
C
respectively. Similarly, sintering time per unit coke breeze input concentration as obtained from experiment,
derived model and regression model were evaluated as 4.0, 3.0183 and 3.7537 mins./ % respectively indicating a
significant proximate agreement and validity of the model. The standard error (STEYX) incurred in predicting
sintering time for each value of the ignition temperature and coke breeze input concentration considered, as
obtained from the experiment, derived model and regression model are 1.6646, 0.7678 and 2.98 x10-5
% as well
as 2.2128, 1.0264 and 1.2379% respectively. The maximum deviation of mode-predicted results from the
corresponding experimental values was less than 11%.
Keywords: Particulate Iron Ore Sintering, Sintering Time, Ignition Temperature, Coke Breeze Input.
I. Introduction
Sinter characteristics are basically a principal factor on which the blast furnace performance
significantly depends [1]. It is widely accepted that sintering increases the particle size, to form a strong
reducible agglomerate, to remove volatiles and sulphur, and to incorporate flux into the blast-furnace burden.
Report [2] has shown that in sintering, a shallow bed of fine particles is agglomerated by heat exchange and
partial fusion of the quiescent mass. Heat is generated by combustion of a solid fuel admixed with the bed of
iron bearing fines being agglomerated. The combustion is initiated by igniting the fuel exposed at the surface of
the bed, after which a narrow, high temperature zone is caused to move through the bed by an induced draft,
usually applied at the bottom of the bed. Within this narrow zone, the surfaces of adjacent particles reach fusion
temperature, and gangue constituents form a semi-liquid slag. The bonding is affected by a combination of
fusion, grain growth and slag liquidation. The generation of volatiles from the fuel and fluxstone creates a frothy
condition and the incoming air quenches and solidifies the rear edge of the advancing fusion zone. The product
consists of a cellular mass of ore bonded in a slag matrix.
One of the most important thermal operations in integrated iron and steel plant is sintering of raw iron
ore, mostly haematite (Fe2O3). In the sintering process, a mixture of iron ores, coke, lime or limestone, and iron
bearing residue (e.g blast flue dust, mill scale, scrap and other waste material recycled from within or outside the
steel plant.) is heated at high temperatures and sintered into a porous, calibrated feedstock acceptable to the blast
furnace. Almost all types of ferro waste available in iron and steel works can be utilized in appropriate
proportions to produce quality sinters [3].
Studies [3] have shown that approximately 6.7% of the total energy consumed in iron and steel
production is required for sinter production. Development and growth in the iron and steel industries all over the
world has militated against the availability of prime coking coal with adequate properties to yield metallurgical
coke. This situation has increasingly becoming more severe, making procurement of such coke expensive [3].
A several researches in the sintering area include energy consumption and productivity process control.
Significant reduction in energy have already been achieved in sintering plant as a result of utilization of
improved raw materials characteristics of ores and coke breeze in terms of size and composition [3]. This

Particulate Sintering of Iron Ore and Empirical Analysis of Sintering Time Based on Coke Breeze
invariably results to reduction in sintering time since association reactions are increasingly vigorous. Coke
breeze-less sintering has been found [3] advantageous for profitable investment because usage sintering machine
is more economical than rotary kiln or other reduction facilities. Coke breeze is has been found [2] the most
common solid fuel, but other carbonaceous materials can be used. When sintering a high sulphur material, such
as a pyrite, the oxidation of the sulfur may satisfy completely the fuel requirements. It has also become common
practice to incorporate limestone fines into the sinter mix, and this material may now be considered as a usual
constituent in a typical sinter mix. This composite of fine material is well mixed and placed on the sinter strand
in a shallow bed, seldom less than 6 inches or more than 20 inches in depth. Upon ignition, within a furnace
which straddles the bed, the surface of the bed is heated to about 23000
to 2500 0
F, combustion of the fuel is
initiated, and the fine particles at the surface are fused together. As air is drawn through the bed, the high
temperature zone of combustion and fusion moves downwardly through the bed and produces a bonded, cellular
structure.
It has been established [4] during a sintering process, that part of the solid fuel can be replaced by
treating the charge with hot gases following ignition. Returned process gases from the sintering operation or
other suitable gases are mixed with oxygen and are applied to the charge from a burner hood which overhangs
part of the sintering strand. The length of the hood generally in use is about one-third of the length of the
sintering strand, and the gas temperature, depending on the sinter mixture used, is between 700° C. and 1200° C.
Previous efforts to ensure uniformity of the sinter by finding an optimum combination of hood length and gas
temperature, while at the same time maintaining the thermal efficiency of the operation, have been generally
unsuccessful. Reduced hood length was not desirable since the coke fine content had to be increased
substantially. The report shows that a noticeable decrease in efficiency occurred with a longer hood. The
researchers stated that selection of too high a gas temperature entailed the danger of excessive slagging of the
charge surface.
The aim of this work is sintering of iron ore and empirically analyzing sintering time based on coke
breeze input concentration and ignition temperature.
II. Materials and Methods
2.1 Sinter Production
Sinters were produced from iron ore and other ingredients such as limestone, coke etc considering a
range of ignition temperature (864-11000
C) and operation time range of 27-31 mins and coke breeze input: 5-
6.2%, in order to evaluate the sintering time. Details of the experimental procedures and equipment used are as
stated in the report [5].
2.2 Model Formulation
Results from the experimental work [5]were used for the model derivation. These results are as
presented in Table 1 and their computational analysis using C-NIKBRAN [6] resulted to Table 2 which indicate
that;
S – Kα ≈ (√T )N
(1)
Adding Kα to both sides of equation (1) reduces it to:
S = (√T )N
+ Kα (2)
Introducing the values of K and N to (equation (2) gives:
S = (√T)0.95
+ 0.0012α (3)
Where
S = Sintering time (mins.)
T = Ignition temperature (0
C)
K= 0.0012: Ore - coke breeze interaction factor (determined using C-NIKBRAN, [6])
N= 0.95: Coefficient of reaction resistance due to Ore-temperature interaction (determined using C-
NIKBRAN, [6])
(α)= Concentration of coke breeze (%)
Equation (3) is the derived model.
Table 1: Variation of the sintering time with ignition temperature [5]

III. Boundary and Initial Conditions
In a sintering machine with height of sintering layer; 200mm, sinter mix was place prior to application
of heat and pressure. The percent of coke breeze added; 5-6.2%, and the operation temperature range 864-
11000
C. Operation time range; 27-31 mins. Range of pressure used; 6Kpa-1.2 Mpa.
The boundary conditions considered for the sinter production includes: assumption of a zero gradient
for the gas phase at the top of particles. It was assumed that atmospheric oxygen interacted with the flowing
gases, produced at the top and bottom of the mix. The sides of the mix particles were assumed to be symmetries.
IV. Results and Discussions
The derived model is equation (3). Computational analysis of experimental results presented in Table 1
gave rise to Table 2.
Table 2: Variation of S – 0.0012α with (√T)0.95
The derived model indicates that amongst ignition temperature and coke breeze input, sintering time is
more significantly affected by the coke breeze input concentration. This is based on the higher correlation it
makes with sintering time compared to applied ignition temperature, all other process parameters being
constant.
4.1 Model validation
The validity of the model is strongly rooted on equation (1) (core model equation) where both sides of
the equation (on introducing the values of K, α, T and N into equation (1)) are correspondingly approximately
equal. Table 2 also agrees with equation (1) following the values of S – Kα and (√T)N
evaluated from the experimental results in Table 1. Furthermore, the derived model was validated by comparing
the sintering times predicted by the model and that obtained from the experiment. This was done using various
analytical techniques which include: computational, statistical, graphical and deviational analysis.
4.1.1 Computational Analysis
Sintering time per unit rise in ignition temperature
The sintering times per unit rise in ignition temperature obtained by calculations involving experimental results
and model-predicted results were compared to ascertain the degree of validity of the model.
Sinteringtime per unit rise in the ignition temperature StT, (mins / 0
C)was calculated from the equation;
StT = St / T (4)
Therefore, a plot of sintering time against ignition temperature, as in Fig. 1 using experimental results in Table 1,
gives a slope, S at points (27, 864) and(31, 1100) following their substitution intothemathematicalexpression
StT = ΔSt /ΔT (5)
Equation (5)isdetailedas
StT = St2 – St1 / T2 - T1 (6)
Where
Sintering time (mins.) C % T (0
C)
27
26
29
25
28
29
31
5.0
5.5
5.7
6.2
5.0
6.0
6.0
864
897
917
963
987
1053
1100
S – 0.0012α (√T)0.95
26.9940
25.9934
28.9932
24.9926
27.9940
28.9928
30.9928
24.8224
25.2683
25.5344
26.1350
26.4424
27.2680
27.8395

ΔSt = Change in the sinteringtimes St2, St1 attwo temperature values T2, T1. Considering the points (27, 864) and
(31, 1100) for (St1, T1) and (St2, T2) respectively, and substituting them into equation (6), gives the slope as 0.0169
mins. / 0
C which is the sintering time per unit rise in the ignition temperature during the actual experimental process.
R2
= 0.6003
24.5
25.5
26.5
27.5
28.5
29.5
30.5
31.5
800 900 1000 1100 1200
Temperature (0
C)
SinteringTime(mins.)
Fig. 1: Coefficient of determination between sintering time and ignition
temperature as obtained from experiment
Also similar plot (as in Fig. 2) using model-predicted results gives a slope. Considering points (24.8284,
864) and (27.8467, 1100) for (St1, T1) and (St2, T2) respectively and substituting them into equation (6) gives the
value of slope, S as 0.0128 mins. / 0
C. This is the model-predicted sintering time per unit rise in the ignition temperature.
Similarly, a plot (as in Fig. 3) using regression model-predicted results of points (26.1916, 864) and (29.9453,
1100) for (St1, T1) and (St2, T2) respectively and substituting them into equation (6) gives the slope, S as 0.0159 mins. /
0
C. This is the regression model-predicted sintering time per unit rise in the ignition temperature.
R2
= 0.6232
24.5
25
25.5
26
26.5
27
27.5
28
28.5
800 900 1000 1100 1200
Temperature (0
C)
temperature as obtained from derived model
R2
= 1
24.5
25.5
26.5
27.5
28.5
29.5
30.5
850 950 1050 1150
Temperature (0
C)
temperature as obtained from regression model

Sintering time per unit coke breeze input concentration
The sintering times per unit coke breeze input concentration obtained by calculations involving
experimental results and model-predicted results were also compared to ascertain the degree of validity of the
model.
Sinteringtime per unit coke breeze input concentration SC, (mins / %)was calculated from the equation;
SC = St / C (7)
Therefore, a plot of sintering time against coke breeze input concentration, as in Fig. 4 using experimental results
in Table 1, gives a slope, S at points (27, 5) and (31, 6) following their substitutionintothemathematicalexpression
SC = ΔSt /ΔC (8)
Equation (8)isdetailedas
SC = St2 – St1 / C2 - C1 (9)
Where
ΔSt = Change in the sintering times St2, St1 at two coke breeze input concentrations C2, C1. Considering the points
(27, 5) and (31, 6) for (St1, C1) and (St2, C2) respectively, and substituting them into equation (9), gives the slope as
4.0 mins./ % which is the sintering time per unit coke breeze input concentration during the actual experimental
process. Similarly, considering points (24.8284, 5) and (27.8467, 6) for (St1, C1) and (St2, C2) respectively from
model-predicted results (as in Fig. 5) and substituting them into equation (9) gives the slope, S as 3.0183 mins./ %. This
is the model-predicted sintering time per unit coke breeze input concentration
R2
= 0.6149
24.5
25.5
26.5
27.5
28.5
29.5
30.5
31.5
5 5.5 5.7 6.2 5 6 6
Conc. of coke breeze (%)
Fig. 4: Coefficient of determination between sintering time and coke breeze
input concentration as obtained from experiment
R2
= 0.6393
23
24
25
26
27
28
29
5 5.5 5.7 6.2 5 6 6
input concentration as obtained from derived model
Also, substituting points (26.1916, 5) and (29.9453, 6) for (St1, C1) and (St2, C2) respectively from
regression model-predicted results (as in Fig. 6) and substituting them into equation (9) gives the slope, S as 3.7537
mins./ %. This is the regression model-predicted sintering time per unit coke breeze input concentration. A critical

analysis and comparison of these three sets of sintering times; per unit rise in ignition temperature and per unit coke
breeze input concentration shows proximate agreement and a significantly high level of derived model validity.
R2
= 0.9936
24
25
26
27
28
29
30
31
5 5.5 5.7 6.2 5 6 6
input concentration as obtained from regression model
4.1.2. Statistical analysis
Statistical analysis of model-predicted, regression-model predicted and experimentally evaluated
sintering time for each value of the ignition temperature applied and coke breeze input concentration considered
shows a standard error (STEYX) of 0.7678, 2.98 x10-5
& 1.6646 % and 1.0264, 1.2379 & 2.2128 % respectively.
The standard error was evaluated using [7].
The correlations between sintering time and ignition temperature as well as sintering time and coke breeze input
concentration as obtained from derived model, regression model and experimental results were calculated. This was done
by consideringthe coefficients ofdetermination R2
from Figs. 1-6, usingtheequation;
R = √R2
(10)
The evaluated correlations are shown in Tables 4 and 5. The model was also validated by comparing its
results of evaluated correlations between sintering time and ignition temperature as well as sintering time and coke breeze
input concentration with that evaluated using experimental andregression model-predicted results. Tables 4 and 5 showthat the
correlationresult from experiment, derived model andregression model are in proximate agreement.
Table 4: Comparison of the correlations between sintering time and ignition temperature as evaluated from
experimental (ExD), derived model (MoD) and regression-model (LSM) predicted results
Table 5: Comparison of the correlations between sintering time and coke breeze input concentration as evaluated
from experimental, derived model and regression-model predicted results
4.1.3 Graphical Analysis
Comparative graphical analysis of Figs. 7 and 8 shows very close alignment of the curves from derived
model and experiment. Figs. 9 and 10 also indicate a close alignment of curves from derived model, regression-
model predicted results as well as experimental results of sintering time. It is strongly believed that the degree of
alignment of these curves is indicative of the proximate agreement between ExD, MoD and LSM predicted
results.
Analysis Based on ignition temperature
ExD MoD LSM
CORREL 0.7748 0.7894 1.0000
Analysis Based on coke breeze input concentration
ExD MoD LSM
CORREL 0.7842 0.7996 0.9968

0
5
10
15
20
25
30
35
40
850 950 1050 1150
Temperature (0
C)
ExD
MoD
Fig. 7: Comparison of the sinteringtimes (relative to ignition temperature) as obtained from
experiment and derived model.
0
5
10
15
20
25
30
35
40
5 5.5 5.7 6.2 5 6 6
ExD
MoD
Fig. 8: Comparison of the sinteringtimes (relative to conc. of coke breeze) as obtained from
experiment and derived model.
Comparison of derived model with standard model
The validity of the derived model was further verified through application of the Regression Model [7] in
predicting the trend of the experimental results for the values of ignition temperatures and coke breeze input
concentrations considered. Results predicted by the Regression Model (LSM) were plotted; sintering time against
ignition temperature and coke breeze input concentration respectively along with results from the experiment and
derived model to analyze its spread and trend relative to results from experiment and derived model.
0
5
10
15
20
25
30
35
40
850 950 1050 1150
Temperature (0
C)
ExD
M o D
LSM
Fig. 9: Comparison of the sinteringtimes (relative to ignition temperature) as obtained from
experiment, derived model and regression model

Comparative analysis of Figs. 9 and 10 shows very close alignment of curves and significantly similar trend of
data point’s distribution for experimental (ExD), derived model-predicted (MoD) and regression model (LSM)
predicted results of sintering time.
0
5
10
15
20
25
30
35
40
5 5.5 5.7 6.2 5 6 6
ExD
M o D
LSM
Fig. 10: Comparison of the sinteringtimes (relative to conc. of coke breeze ) as obtained from
experiment, derived model and regression model
4.1.4 Deviational Analysis
The formulated model was also validated by evaluating the deviation of the model-predicted sintering
time from the corresponding experimental values. The recorded deviation is believed to be due to the fact that
the surface properties of the ore, and the physiochemical interactions between the ore and the other ingredients
believed to have played vital roles (during the process) were not considered during the model formulation. It is
expected that introduction of correction factor to the model-predicted sintering time, gives exactly the
corresponding experimental values.
Deviation (Dv) (%) of model-predicted sintering time from the corresponding experimental value is
given by
Dv = PS – ES x 100 (11)
ES
Where
PS = Model-predicted sintering time (mins.)
ES = Sintering time obtained from experiment (mins.)
Since correction factor (Cv) is the negative of the deviation,
Cv = - Dv (12)
Substituting equation (11) into equation (12) for Dv,
Cv = -100 PS – ES
ES (13)
It was observed that addition of the corresponding values of Cv from equation (13) to the model-
predicted sintering time gave exactly the corresponding experimental values [5].

23
23.5
24
24.5
25
25.5
26
26.5
27
27.5
28
28.5
864 897 917 963 987 1053 1100
Temperature (0
C)
-14
-12
-10
-8
-6
-4
-2
0
2
4
6
Deviation(%)
MoD
Deviation
Fig. 11: Variation of model-predicted sintering time (relative to ignition temperature)
with its associated deviation from experimental values
23
23.5
24
24.5
25
25.5
26
26.5
27
27.5
28
28.5
5 5.5 5.7 6.2 5 6 6
-14
-12
-10
-8
-6
-4
-2
0
2
4
6
Deviation(%)
MoD
Deviation
Fig. 12: Variation of model-predicted sintering time (relative to conc. of coke breeze)
with its associated deviation from experimental values
Figs. 11 and 12 show that the maximum deviation of the model-predicted sintering time from the
corresponding experimental values is less than 11% and quite within the acceptable deviation limit of
experimental results. These figures show that least and highest magnitudes of deviation of the model-predicted
sintering time (from the corresponding experimental values) are + 4.57 and -10.17% which corresponds to
sintering times: 26.1424 and 27.8467 mins, ignition temperatures; 963 and 11000
C and coke breeze input
concentrations: 6.2 and 6.0 % respectively.
23
23.5
24
24.5
25
25.5
26
26.5
27
27.5
28
28.5
864 897 917 963 987 1053 1100
Temperature (0
C)
-6
-4
-2
0
2
4
6
8
10
12
14
Correctionfactor(%)
MoD
Corr.factor
Fig. 13: Variation of model-predicted sintering time (relative to ignition temperature)
with its associated correction factor

Comparative analysis of Figs. 11-14 indicates that the orientation of the curve in Figs. 13 and 14 is
opposite that of the deviation of model-predicted sintering time (Figs. 11 and 12). This is because correction
factor is the negative of the deviation as shown in equations (12) and (13). It is believed that the correction
factor takes care of the effects of the surface properties of the ore, and the physiochemical interactions between
the ore and the other ingredients believed to have played vital roles (during the process) were not considered
during the model formulation. Figs. 13 and 14 indicate that the least and highest magnitudes of correction factor
to the model-predicted sintering times are – 4.57 and + 10.17 % which corresponds to sintering times: 26.1424
and 27.8467 mins, ignition temperatures; 963 and 11000
C and coke breeze input concentrations: 6.2 and 6.0 %
respectively.
It is important to state that the deviation of model predicted results from that of the experiment is just
the magnitude of the value. The associated sign preceding the value signifies that the deviation is deficit
(negative sign) or surplus (positive sign).
23
23.5
24
24.5
25
25.5
26
26.5
27
27.5
28
28.5
5 5.5 5.7 6.2 5 6 6
-6
-4
-2
0
2
4
6
8
10
12
14
Correctionfactor(%)
MoD
Corr.factor
Fig. 14: Variation of model-predicted sintering time (relative to conc. of coke breeze)
with its associated correction factor
V. Conclusion
Particulate sintering of iron ore has been carried out and empirical analysis of the sintering time based
on the coke breeze input concentration and ignition temperature were also successfully obtained through first
principle application of a derived model which functioned as a evaluative tool. The derived model; indicates that
amongst ignition temperature and coke breeze input, sintering time is more significantly affected by the coke
breeze input concentration. This is based on the higher correlation it makes with sintering time compared to
applied ignition temperature, all other process parameters being constant. The validity of the model was rooted
in the core expression S – Kα ≈ (√T )N
where both sides of the expression are correspondingly approximately
almost equal. Sintering time per unit rise in the operated ignition temperature as obtained from experiment,
derived model and regression model were evaluated as 0.0169, 0.0128 and 0.0159 mins. / 0
C respectively.
Similarly, sintering time per unit coke breeze input concentration as obtained from experiment, derived model
and regression model were evaluated as 4.0, 3.0183 and 3.7537 mins./ % respectively indicating a significant
proximate agreement and validity of the model. The standard error (STEYX) incurred in predicting sintering
time for each value of the ignition temperature and coke breeze input concentration considered, as obtained from
the experiment, derived model and regression model are 1.6646, 0.7678 and 2.98 x10-5
% as well as 2.2128,
1.0264 and 1.2379% respectively. The maximum deviation of mode-predicted results from the corresponding
experimental values was less than 11%.
References
[1] D. F. Ball, J. Dartnell, J. Davison, A. Grieve, R. Wild, Agglomeration of iron ores. Heinemann Educational books. American
Elsevier Publishing Company, Inc., USA. 1973.
[2] A. Gross, E. A. Anthony, Particulate Emissions Reduction in Sintering Operation. US Patent No. 3975185, Application No.
564590, August 17, 1976.
[3] N. A. El-Hussiny, M. E. H. Shalabi, Effect of Recycling Blast Furnace Flue Dust as Pellets on the Sintering Performance.
Science of Sintering, 42 (2010) 269-281.
[4] F. Cappel, W. Hastik, Sintering Process fro Iron Ore Mixture. U.S. Patent No. 4168154, Application No. 05/884352, September
18, 1979.
[5] V. I. Nwokocha, The Formation and Stabilization of Calcium Silicate In the Structure of Super Fluxed Sinters.Ph. D Thesis,
Nnamdi Azikiwe University, Awka, Anambra State, Nigeria, (2011).
[6] C. I. Nwoye, C-NIKBRAN: ‘‘Data Analytical Memory’’ (2008).
[7] Microsoft Excel Version 2003.

Particulate Sintering of Iron Ore and Empirical Analysis of Sintering Time Based on Coke Breeze Input and Ignition Temperature

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