Computational Fluid Dynamics Study of Pulverized Coal Combustion

Sep 25, 2009 - The findings are useful in the study of coal combustion under PCI ...... flow rate of the bosh gas is less than that in the conventiona...
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Computational Fluid Dynamics Study of Pulverized Coal Combustion in Blast Furnace Raceway Y. S. Shen,† D. Maldonado,‡ B. Y. Guo,† A. B. Yu,*,† P. Austin,‡ and P. Zulli‡ Lab for Simulation and Modelling of Particulate Systems, School of Materials Science and Engineering, UniVersity of New South Wales, Sydney, NSW 2052, Australia, and BlueScope Steel Research, P.O. Box 202, Port Kembla, NSW 2505, Australia

In this work, a numerical model is used to study the flow and coal combustion along the coal plume in a large-scale setting simulating the lance-blowpipe-tuyere-raceway region of a blast furnace. The model formulation is validated against the measurements in terms of burnout for both low and high volatile coals. The typical phenomena related to coal combustion along the coal plume are simulated and analyzed. The effects of some operational parameters on combustion behavior are also investigated. The results indicate that oxygen as a cooling gas gives a higher coal burnout than methane and air. The underlying mechanism of coal combustion is explored. It is shown that under the conditions examined, coal burnout strongly depends on the availability of oxygen and residence time. Moreover, the influences of two related issues, i.e. the treatment of volatile matter (VM) and geometric setting in modeling, are investigated. The results show that the predictions of final burnouts using three different VM treatments are just slightly different, but all comparable to the measurements. However, the influence of the geometric setting is not negligible when numerically examining the combustion of pulverized coal under blast furnace conditions. 1. Introduction The combustion of pulverized coal is widely practiced in coalfired boilers of power plants1 and ironmaking blast furnaces.2 At present, pulverized coal injection (PCI) operation in ironmaking blast furnaces is used to reduce the furnace operational costs and decrease the emissions of carbon dioxide. Hence, methods to increase the PCI rate have become an important issue in blast furnace ironmaking.3,4 One key factor affecting the maximum PCI rate is the extent of coal combustion (burnout) within the tuyere and raceway region.5 In particular, the final burnout along the coal plume plays a direct and significant role in determining the permeability of the birdnest region (Figure 1).6 Practically, coal burnout can be increased to a certain degree through adjusting some operational parameters, such as blast temperature, oxygen enrichment, coal blend, and so on.7,8 It is important to understand the in-furnace phenomena along the coal plume under actual conditions and find out the underlying mechanisms controlling coal burning. It is difficult to measure the combustion behavior of pulverized coal in a practical blast furnace directly, because of the hazardous and high temperature in-furnace environment. Since the 1980s, mathematical modeling, mainly based on computational fluid dynamics (CFD), has become a powerful tool to investigate the scientific and industrial aspects of coal combustion behavior.2,5 Ishii outlined some CFD models for the PCI process. They are mainly in one or two dimensions.2 A threedimensional model is necessary to generate more reliable results for practical problems.9-12 Nogami et al.9 reported a threedimensional (3D) coal combustion model for PCI operation considering coke particle movement using a discrete element approach. Shen et al.10 reported a coal combustion model in a pilot-scale test rig. However, actual geometry and conditions of the blast furnace were not considered in either model. Murai * To whom correspondence should be addressed. E-mail: a.yu@ unsw.edu.au. † University of New South Wales. ‡ BlueScope Steel Research.

Figure 1. Schematic of pulverized coal injection in blast furnaces.

et al.12 reported a 3D model for the blowpipe-tuyere region, without the raceway region. To date, a comprehensive picture about coal burnout in a blast furnace has not as yet been developed. To overcome these problems, in this paper, a coal combustion model is applied to a large-scale setting to simulate the lance-blowpipe-tuyere-raceway region of a blast furnace. This model aims to describe the coal combustion behavior along the coal plume under practical conditions. The model is first validated against measurements for both low and high volatile coals. Then, the typical in-furnace phenomena of PCI operation are described. The effects of some key operational parameters on coal combustion are also examined under practical conditions, e.g. the type of cooling gas. Moreover, two related issues are considered in this work: treatment of volatile matter (VM) and geometric setting in modeling. The findings are useful in the study of coal combustion under PCI conditions. 2. Mathematical Model 2.1. Model Description. The model is an extended version of the model detailed elsewhere.10 It is briefly outlined below for completeness. In the model, the gas flow field is described by a set of 3D, steady-state, Reynolds-averaged, Navier-Stokes equations, closed by the standard k-ε turbulence model

10.1021/ie900853d CCC: $40.75  2009 American Chemical Society Published on Web 09/25/2009

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a

Table 1. Governing Equations for the Gas and Particle Phases

for the gas phase mass ∇·(FU) )

∑ m˙ np

momentum

energy

(

(

(

(

(

(

(

µt ∇k ) (Pk - Fε) σk

(

(

µt ε ∇ε ) (C1Pk - C2Fε) σε k

∇· FUH -

gas species i

) )

µt λ + ∇H ) Cp σH

∇· FUYi - Γi +

turbulent kinetic energy

∇· FUk - µ +

turbulent dissipation rate

) ∑f

2 ∇·(FUU) - ∇·((µ + µt)(∇U + (∇U)T)) ) -∇ p + Fk + 3

∇· FUε - µ +

D

np

∑q np

) )

µt ∇Yi ) Wi σYi

)) ))

for a particle in the particle phase mass

dmp ) -m ˙ dt

momentum mp

dUp ) -fD dt

1 -fD ) πdp2FCD |U - Up |(U - Up) 8 energy mpCp

dTp ) -q dt

-q ) πdpλNu(Tg - Tp) +

a

∑

dmp H + Apεp(πI - σBTp4) dt reac

µt ) CµF(k2/ε); Pk ) (µ + µt)∇U · (∇U +(∇U)T); CD ) max(24(1 + 0.15Re0.687)/Re, 0.44); i ) O2, CO2, CO, VM, H2, H2O.

equations. They are solved for pressure (p), velocity (u, V, w), turbulence kinetic energy (k), turbulence dissipation rate (ε), enthalpy (H), and several gas species mass fractions (Yi). Particles of pulverized coal are modeled using the Lagrangian method, where the trajectories of the discrete particles are determined by integrating Newton’s second law of motion. The drag force (fD) and turbulence dispersion are included. Full coupling of mass, momentum, and energy of particles with the gas phase is implemented. The change of particle temperature is governed by three physical processes: convective heat transfer, latent heat transfer associated with mass transfer, and radiative heat transfer. The governing equations for the gas and particle phases are summarized in Table 1. Coal combustion is regarded as a multistage overlapping process: (1) preheating, (2) the devolatilization of raw coal, modeled using the two-competing-reactions model,13 releasing volatile matter, (3) followed by the gaseous combustion,

modeled using the eddy dissipation model,14 and then (4) the oxidation/gasification of the residual char, modeled using the Gibb model.15 The coal combustion reactions and their rates expressions are summarized in Table 2. Note that the devolatilization plays an important role in determining the final burnout.10 In the section below, the different treatments of VM composition are investigated to examine their influences on the predictions of final burnout. 2.2. Treatment of VM Composition. The so-called twocompeting-reactions model is used for simulating the devolatilization. A pair of reactions with different rates (k1, k2) and volatile yields (R1, R2) compete to pyrolyse the raw coal.

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Table 2. Reactions of Coal Considered and Their Rates Expressions (for One Particle) reactions

models

coal ) VM + char

reaction rates expressions

two-competing-reactions model

rate constants A1 ) 3.7 × 105 s-1, E1 ) 18000 K

dVM ) (R1k1 + R2k2)CO dt

A2 ) 1.46 × 1013 s-1, E2 ) 30189 K

k ) A exp(-E/Tp) R1 ) VM (daf); R2 ) 1.25R12 + 0.92R1

VM +O2 ) CO2 + H2O

eddy dissipation model

char + O2 ) CO + CO2

Gibb model

char + CO2 ) 2CO

CA ) 4.0

( )

ε [i] ri ) CA min κ νi′

Ac ) 14 m s-1 K-1, Tc ) 21580 K

dmc 3φ MC F∞ -1 )(k + (k2 + k3)-1)-1mC dt 1 - e MO2 Fc 1

Ac ) 20230 m s-1 K-1, Tc ) 39743 K

( )

Ts 2(φ - 1) ) As exp 2-φ Tp

k1 ) char + H2O ) CO + H2

D , rp2

D)

(

)

Dref Tp + Tg R , F 2Tref

k2 ) (1 - e)

kc rp Ac ) 606.9 m s-1 K-1, Tc ) 32406 K

k3 ) kcTp(β coth β - 1)/β2a

kc ) AcTp exp(-Tc /Tp),

β)R

( ) kc DPea

0.5

Table 3. Comparison of Three Treatments of VM Composition treatment of VM

fuel gas in computation

composition of VM (VM1 vs VM2)

1 fuel gas 6 fuel gases 2 fuel gases

CxHyO C2H2, C2H4, C3H8, C4H8, CO, H2 Cx1Hy1O, Cx2Hy2O

VM1 ) VM2 VM1 * VM2 VM1 * VM2

The rate constants, k1 and k2, are in the Arrhenius format.10 The treatment of the VM composition varies in different investigations.9-11,16,17 They are usually simplified as a mixture of several fuel gases in the simulations of industrial problems. In this study, three treatments of VM composition are investigated, as described below. Treatment 1. In our previous paper,10 considering computational efficiency, VM1 or VM2 were simply treated as one single substance (one fuel gas), i.e., VM1 and VM2 are same in composition, VM (CxHyO), but different in quantity. That is, VM is one fuel gas. The composition of VM (CxHyO) depends on the ultimate and proximate analyses of the coal, as well as the Q factor, based on mass balance. Then, VM (CxHyO) will combust with oxygen.

(

VM(CxHyO) + x +

1 y y - O2 f xCO2 + H2O 4 2 2

)

(2)

The prediction accuracy of this treatment was thought to be a model limitation.10 In order to investigate this, in this study, a sensitivity test is carried out against the other two VM treatments. Treatment 2. More realistically, each of VM1 and VM2 is treated as a mixture of six fuel gases. They are H2, CO, and a range of hydrocarbons (C2H2, C2H4, C3H8, and C4H8). That is, VMi(CxiHyiO) f CO + Cxi-1Hyi-2zi + ziH2

(3)

Thus, VM is basically a mixture of six fuel gases. The compositions of VM1 (CO + Cx1-1Hy1-2z1 + z1H2) and VM2 (CO + Cx2-1Hy2-2z2 + z2H2) are generally different. They are determined by the ultimate/proximate analyses of coal and the Q factor, based on mass balance. The six fuel gas species are assumed to combust with oxygen, respectively.

(

CRHβ + R +

β β O f RCO2 + H2O 4 2 2

)

(4)

1 H2 + O2 f H2O 2

(5)

1 CO + O2 f CO2 2

(6)

This treatment is considered less efficient in computation. This is because six transport equations need to be solved for these fuel gas species. Moreover, the overall composition of VM1 (Cx1Hy1O) and VM2 (Cx2Hy2O) is often of main interest, compared with the detailed information of six fuel gas species (H2, H2O, CO, C2H2, C2H4, C3H8, and C4H8) when investigating the coal burnout for industrial problems. Treatment 3. As a compromise between computational cost and prediction accuracy, another VM treatment is tested. VM1 and VM2 are here treated as two different substances, VM1 (Cx1Hy1O) and VM2 (Cx2Hy2O), i.e. VM is a mixture of two

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Figure 2. Geometry of the large-scale simulated rig (rig 1): (a) main dimensions and (b) lance cross-section details.

different fuel gases. The composition of each fuel gas is determined by two steps. In step 1, taking VM1 for example, VM1 is first assumed as a mixture of CH4, CO, H2, and H2O before solving the transport equations. Its composition is also determined by the ultimate/proximate analyses of coal and Q factor, based on mass balance. Then, in step 2, the mixture of these gas species is contained to one substance VM1 (Cx1Hy1O). As a result, VM1 (Cx1Hy1O) and VM2 (Cx2Hy2O) could be different in both composition and quantity. Then in computation, these two fuel gases will combust with oxygen and their mass fractions are solved by two transport equations.

(

VMi(CxiHyiO) + xi +

)

yi yi 1 - O2 f xiCO2 + H2O 4 2 2 (7)

where i ) 1, 2. Table 3 gives a summarized comparison of the three treatments. Note that more complicated VM treatments using the so-called network models (FG-DVC,18 FLASHCHAIN,19 and CPD20) are also available, especially for fundamental studies. But they are much more expensive in computation, so they are not investigated in this study. 3. Simulation Conditions The model is used to simulate the lance-blowpipe-tuyereraceway region of a blast furnace. The setting of this largescale simulated rig (Figure 2) is designed based on a commercial blast furnace of BlueScope Steel. The lance, blowpipe, and tuyere are sourced from this furnace’s design. The lance enters the blowpipe with an inclination angle of 10°. The lance is coaxial, with the coal and conveying gas (nitrogen) in the inner tube, and a cooling gas in the annular region. The cooling gas protects the coal from excessive heating in the blow pipe, to prevent in-lance coking. The raceway is modeled as a tube of 1 m long with a divergence angle of 3°. Note that, this geometric setting could avoid the formation of flow recirculation, so that this simulated rig mainly focuses on the flow and combustion behaviors of pulverized coal in the coal plume formed, which plays a significant role in determining the permeability of the birdnest.

Table 4. Operational Conditions of the Blast Furnace Considered (per Tuyerea) conditions blast (24.5% O2) cooling gasc conveying gas (100% N2) coal (mean size: 45 µm)

flow rate b

3

temperature (°C) -1

10929 N m h 179 N m3 h-1 47 N m3 h-1 1250 kg h-1

1200 150 45 45

a 28 tuyeres are used in the blast furnace. b Blast is composed of air (10 714 N m3 h-1) and O2 (214 N m3 h-1). c Cooling gas may be oxygen, air, or methane. Oxygen is used in the base case.

Typical plant operational parameters and conditions are used as the boundary conditions for the model (Table 4). Coal 3 is used as the base case for general analysis. Note that the typical pressure of blast furnace is ∼450 kPa. The high pressure could influence volatile yield and therefore coal combustion rate.21 This effect is not considered in this study. 4. Results and Discussion In this section, the model is first validated against the measurements in a pilot-scale physical test rig. Then the typical results of the base case are evaluated for general analysis. The model is then used to examine the effects of some operational parameters on coal combustion behavior. Finally, the influence of the geometric setting on PCI simulation is examined by comparing two geometries, a large-scale simulated rig (denoted as rig 1) vs a relatively small test rig (denoted as rig 2). 4.1. Model Validation. Before applying this model formulation to the large-scale simulated rig (rig 1) describing the pulverized coal combustion in a real blast furnace, the model is validated against the measurements obtained from a pilotscale test rig (rig 2). Details of this relatively small test rig have been described elsewhere.6 The computational geometry for model validation is shown in Figure 3. Three different gas streams enter the domain, namely, conveying gas (nitrogen), cooling gas (air, oxygen, or methane), and hot blast. Five types of coals have been used in this study, with VM contents ranging from 12.4 to 39.1% on an air-dried basis (ad). The proximate and ultimate analyses of the coals considered are given in Table 5. Laser diffraction analyses are summarized in Figure 4. Table 6 lists the boundary conditions of the validating cases in the test rig.

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Figure 3. Geometry of the test rig (rig 2) for validation (units millimeters). Table 5. Proximate/Ultimate Analyses of the Coals Considered (ad) coal 1

coal 2

coal 3

coal 4

3.4 32.6 9.3 54.8 31.15 1.45

5.6 39.1 2.7 52.6 30.47 1.35

84.7 5.6 2.1 0.7 7.0

79.4 5.6 1.5 0.6 12.9

proximate analysis moisture, % volatile matter, % ash, % fixed carbon, % gross specific energy, MJ/kg Q factor

0.9 12.4 8.0 78.7 32.98 1.1

1.2 20.0 9.7 69.1 32.05 1.1

ultimate analysis C H N S O (by diff)

91.3 4.0 1.9 0.5 2.3

89.1 4.7 1.7 0.4 4.1

The model formulation is validated against the measurements in terms of coal burnout.22 Coal burnout is evaluated according to an ash balance, which represents the total weight loss of the organic fraction of the coal due to volatile release and char oxidation and gasification reactions:

(

burnout ) 1 -

)

Xa,0 /(1 - Xa,0) Xa

(8)

Table 6 indicates that the predictions of final burnout using treatment 2 are always slightly higher than those using treatments 1 and 3, but the differences among them are insignificant. They are all comparable to the experimental measurements, obtained by Mathieson et al.6 and Rogers.22 That is, they are all acceptable for predicting the final burnout for the given coals. The treatment of 2 fuel gases is used in this study. The agreements between the measured and predicted burnouts also confirm the validity of the model. 4.2. General Analysis of the Base Case. The flow pattern of gas-particle phases is investigated. Figure 5a shows the gas velocity vectors along the symmetry plane. It shows that the gas velocities are ∼140 m/s inside the blowpipe and ∼15 m/s at the lance tip. After the tuyere, the gas flow is accelerated to nearly 220 m/s. There is a slight reversed-flow region of low speed at the center near the end of the raceway due to the expansion after the tuyere. This specific phenomenon is related to the geometric setting for combustion study, which will not affect the main results discussed. Note that in a practical blast furnace, the raceway consists of a high-speed jet and a large region in which coke recirculation occurs above the jet. In this study, no large-scale coke recirculation is included in this setting and the investigation focus is put on the combustion behavior along the coal plume, since the final burnout at the end of coal plume plays a significant role in determining the permeability of the birdnest and then affecting the gas distributions. Figure 5b shows the typical particle trajectories colored by particle mean diameters de. It is observed in the simulation that

Figure 4. Laser diffraction sizing results for the four coals considered.

the dispersion of the coal plume is not pronounced inside the tuyere; even in the raceway, the dispersion of coal plume, i.e., the mixing between coal particles and the gas phase, is still not significant. This is due to the high blast flow rates and the reduction in flow area at the tuyere nose. Fine particles (de < 50 µm) are found to disperse in the upper (axis +X) and radial (axis +Z) parts of the plume, whereas relatively large particles (de > 80 µm) are left in the lower part, resulting from the inclination arrangement of the lance. More fine particles are also found in the reversed-flow region. Figure 6 shows the distributions of various gas species. An O2-depleted and CO2/CO-rich zone is found along the plume. This indicates that O2 is converted to different products: CO2 largely at the surface of the plume but CO largely at the center of the plume, due to the difference in O2 supply locally. A VMrich core is found along the center of the plume in front of the tuyere, i.e., 0.2-0.6 m from the lance tip in the direction of axis +Y. This is because, at the center of the plume, after preheating, a very high heating rate from the surrounding hot blast leads to the rapid release of VM and at the same time less VM can be consumed in this O2-depleted zone. As a result, VM builds up at 0.2-0.6 m at the center of the plume. Near the end of the raceway, i.e., the reversed-flow region, CO2 decreases and CO increases in concentration, because CO2 and the fine char are in contact closely, so that the char gasification reactions are strong, producing a large amount of CO. Figure 7 shows the temperatures of gas and particle phases. It is observed in the simulation that the temperature of the gas does not start to increase until exiting the tuyere region at the distance of 0.2 m from the lance tip in the direction of axis +Y. This is consistent with the O2 distribution discussed above. The simulation results indicate that before the tuyere exit, coal combustion cannot occur because of the very short residence time; whereas in the raceway, the high temperature zone of about 3000 K is observed in an annular shape at the surface of the coal plume, where the higher O2 concentration (Figure 6a) leads to the rapid burning of VM (Figure 6d) and the strong heat release. Figure 7b shows that the particle temperature is higher in the upper part of the plume than the lower part, because the local fine particles with a higher surface area/mass ratio give a high heat transfer rate per unit mass of the particles, leading to a fast temperature increase. Figure 8 shows typical particle trajectories colored by mass fractions of ash, char, and burnout, respectively. After exiting the tuyere, raw coal particles are pyrolyzed quickly with ash and char. Then along the coal plume, the upper part of the plume shows a high ash mass fraction and a high burnout, which is consistent with the presence of fine particles in this region and the local O2 concentration in the gas phase. That is, burnout is strongly related to reducing the particle size, availability of oxygen, and residence time. It is implied that any techniques

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a

Table 6. Model Validations and Their Experimental Conditions

burnout at 925 mm, % case 1 2 3 4 5

coal coal coal coal coal coal

1 2 3 4 3

coal rate, kg h-1

cooling gas, N m3 h-1

measured

calculatedb

calculatedc

calculatedd

31.6 25.2 22.9 28.3 26.9

air, 3.2 air, 3.2 air, 3.2 air, 3.2 methane, 2.8

59.8 63.7 73.9 83.2 71.9

61.2 62.4 72.9 82.7 70.1

62.8 64.3 74.0 85.1 72.2

61.9 62.1 72.0 83.4 71.1

a For all cases, the flow rate is 300 N m3 h-1; blast temperature is 1200 °C; O2 mass fraction in blast is 21%. b VM is treated as one fuel gas. c VM is treated as a mixture of 6 fuel gases. d VM is treated as a mixture of 2 fuel gases.

Figure 5. Flow pattern of gas-particle flow: (a) gas velocity vectors along the symmetry plane and (b) particle trajectories colored by particle mean diameter.

Figure 6. Distributions of gas species along the symmetry plane: (a) O2; (b) CO2; (c) CO; and (d) VM.

that can improve these factors could increase the burnout, such as using the long tuyere. At the reversed-flow region, fine char

Figure 7. Temperatures for the gas (a) and particle phases (b).

particles are nearly burnt off, i.e., only ash is left, due to the close contact of fine particles with CO2, causing stronger char gasification reactions. Figure 9 shows the combustion characteristics of particles with the distance from the lance tip along the center line (axis +Y). Before the tuyere, VM does not drop and coal burnout remains zero. Beyond the tuyere exit, i.e., 0.2 m, as the VM content drops, the burnout increases rapidly. This confirms that devolatilization plays an important role for burnout rise. In the reversed-flow region, the burnout increases at a faster rate, due to the stronger char gasification reactions resulting from a longer residence time. In addition, the particle temperature is also investigated along the center line. A fast increase is observed before 0.2 m in the direction of axis +Y, followed by a slow increase beyond 0.2 m in the direction of axis +Y. However, after 1.0 m in the direction of axis +Y, the particle temperature is increased at a faster rate due to the existence of fine particles. 4.3. Effects of Several Operational Parameters. The effects of several operational parameters were investigated numerically under various settings.9,12,23 However, some conclusions could be misleading for blast furnace practice due to the limits of model dimension and setting. In this study, the effects of some operational parameters are examined using the current setting. The effect of a specific parameter is quantified by fixing the others at their base values (Table 4). Effect of blast temperature. Figure 10a shows the effect of the blast temperature on coal burnout at 925 mm. It is shown that, within the concerned range, a high blast temperature gives a slightly increased burnout, from 65% to 70%, when blast temperature increases from 1150 to 1250 °C. This is because a higher blast temperature triggers a slightly earlier and stronger devolatilization, providing a larger amount of VM for the gas phase combustion (Figure 10b). As a result, additional heat is

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Figure 10. Effect of blast temperature: (a) final burnout and (b) VM contours.

Figure 8. Particle trajectories colored by (a) ash mass fraction, (b) char mass fraction, and (c) burnout.

Figure 9. Evolutions of burnout, VM content, and particle temperature (Tp) along the center line as a function of distance from the lance tip.

generated to enhance the downstream reactions. In addition, char particles have a longer residence time and thus are consumed more by the char reactions. The simulations indicate that there is a quantitative relationship between the burnout and the blast temperature. Effect of Oxygen Enrichment. Figure 11a shows the effect of oxygen enrichment on coal burnout, by setting different oxygen mass fractions in the blast, i.e. 21%, 24.5%, and 30%. The coal burnout is increased as more oxygen is added into the blast, with a quantitative relationship. This is because at a high oxygen enrichment level, more oxygen is available around the coal plume. For better clarification, the O2 distributions on a cross-section plane at the distance of 0.55 m from the lance tip in the direction of axis +Y are compared under different O2 enrichments (Figure 11b). More oxygen is available to the coal plume surface and even inside the coal plume with higher blast

Figure 11. Effect of oxygen enrichment: (a) final burnout and (b) O2 distributions on a cross-section plane of 550 mm from the lance tip.

oxygen enrichment. As a result, the VM combustion at the surface of the plume could access more oxygen from the gas phase, releasing more heat to the gas phase and giving a higher burnout. Effect of cooling gas type. Figure 12a shows the effect of cooling gas type on coal burnout. The three different types of cooling gas, methane (3000 N m3 h-1), air (5000 N m3 h-1) and oxygen (5000 N m3 h-1) (base value), are used in the blast furnace with 28 tuyeres. Note that the oxygen enrichment in blast is 6000 N m3 h-1 for all the three cases. It is shown that for the three types of cooling gas, oxygen gives the highest burnout of ∼67%. In addition, a linear relationship is found between the burnout and atomic O/C ratio in the gases delivered to the tuyere. This is because, comparing the O2 distributions on a cross-section at the distance of 550 mm from the lance tip

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Figure 12. Effect of cooling gas type: (a) final burnout and (b) O2 distributions at the cross-plane of 550 mm from the lance tip.

Figure 13. Effect of VM content on burnout.

(Figure 12b), by using methane as the cooling gas, a larger amount of O2 is consumed when the methane is burning together with the VM competitively. As a result, the VM combustion is slowed down, which decreases the final burnout significantly. In addition, the amount of O2 available to the subsequent char reactions is also reduced. Effect of VM Content of Coal. Figure 13 shows the effect of the initial VM content of the coal considered on the burnout for four different coals. As VM content of the coal increases from 12.4% to 39.1%, the burnout linearly increases from 41% to 77%. This indicates that injecting high VM coal should increase coal burnout. Such a quantitative relationship can be used to estimate the potential coal burnout of an unfamiliar coal. This is because the VM release and combustion play an important role in determining final burnout, compared to the char oxidation and gasification reactions. 4.4. Influence of Geometry on PCI Simulation. It is difficult to experimentally investigate the influence of geometric setting on PCI process due to the difficulties in accurate control of the conditions. Different geometries were used in the previous numerical studies,9,10,12 but few studies were made to examine the influence of geometric setting. In this study, this influence is numerically investigated. This is done by comparing the predictions using the geometry of a large-scale simulated rig (Figure 2), i.e., rig 1, with those generated using the geometry

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of a relatively small test rig (Figure 3), i.e., rig 2, under the same conditions and model formulation. Note that rig 1 is a representation of an actual furnace; rig 2 is a representation of a physical test rig in laboratory. The flow and combustion behaviors are first compared under a specific condition (Table 4). Under the same condition, e.g., the same blast velocity of 133 m s-1, the simulation for rig 1 shows a slightly shorter residence time along the center plume than for rig 2, 0.03 vs 0.05 s. The latter shows a slightly higher particle temperature, 2500 vs 2600 K, and a higher final burnout at 925 mm, 66% vs 72%. That is, the simulation under the geometry of rig 2 predicts a higher burnout under this specific condition. Coal type is one of the most concerning issues in PCI optimization. For this reason, the two geometries are further compared for a range of coals with different VM contents under the same conditions (Figure 13). It is observed that as the VM content of coal increases, the predicted final burnout increases for both rigs. However, the burnouts for rig 2 are consistently higher than those for rig 1 by ∼8% (absolute) on average. That is, the burnout predictions using the two geometries are qualitatively consistent, but different quantitatively. The reasons for the influence of geometric setting are explored as follows. The geometric settings of two rigs are different in terms of dimensions and shape, which causes different flow patterns. That is, in rig 1, only the coal plume is observed and investigated, whereas in rig 2, in addition to the coal plume, a recirculation region of fine particles near the wall was also found.10 This recirculation region leads to backmixing of gas and particles so that the ash is entrained into the plume, which will overwhelmingly increase the residence time and then cause a higher final burnout along the coal plume.10 Notably, the burnouts obtained from rigs 1 and 2 may be quite different if the operational conditions differ. This can be seen from the correlations generated by the two rigs, as shown in Figure 14. The predicted burnouts in the present work are always lower than those in the previous work23 for all parameters examined. The differences obviously result from the different conditions and settings in computation. Therefore, it is stressed that these approximate relationships should be used under the conditions specified, and any extrapolation must be used with caution. Therefore, as an alternative to physical experiment, a numerical approach is an effective way to investigate the coal combustion behaviors of PCI operations. However, the influence of geometric setting is not negligible when examining PCIrelated phenomena. It is probably necessary to employ the fullscale blast furnace geometry and conditions in order to quantify the in-furnace phenomena of PCI operation. 5. Conclusions A comprehensive coal combustion model has been applied toalarge-scalesettingtosimulatethelance-blowpipe-tuyere-raceway region of a blast furnace. The flow/combustion phenomena along the coal plume are simulated. The effects of some operational parameters are quantified. In addition, the influences of two issues in modeling are also examined in this work: treatment of volatile matter and geometric setting. The main conclusions are summarized below. The results of the simulation show that: (1) the dispersion of the coal plume is limited within the tuyere and not significant along the plume in the raceway; (2) coal does not start combustion until exiting the tuyere. Beyond the tuyere exit, an O2-depleted and CO/CO2-rich zone and a VM-rich core are

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enrichment in the blast can improve the coal burnout. Among the three types of cooling gases (methane, air, and oxygen), oxygen gives the highest coal burnout. Some quantitative relationships are found between coal burnout and these parameters. These correlations are system-dependent and, hence, must be used with caution. The influence of geometric setting on PCI predictions is examined by comparing two geometries under the same conditions. The tendencies of the burnout predictions using the two geometries are consistent qualitatively, but their predictions are different quantitatively. The influence of geometric setting should not be neglected in the model development when numerically examining PCI-related phenomena. It is necessary to employ the full-scale blast furnace geometry and conditions in order to quantify the in-furnace phenomena of PCI operation. Acknowledgment The authors thank the Australian Research Council and BlueScope Steel for their support of this project. Dr Harold Rogers (BHP-Billiton’s Newcastle Technology Centre) is acknowledged for providing the experimental data used in the model validation. Nomenclature

Figure 14. Comparisons of relationships obtained under different conditions and settings: (a) oxygen content in blast, (b) VM content of coal, and (c) blast temperature (Basic conditions for the previous relationships: de 50 µm; VM 32.5%; coal rate 25.5 kg h-1; Tblast 1200 °C; blast rate 301 N m3 h-1; oxygen enrichment (OE) 20.9%; rate of cooling gas 3.2 N m3 h-1 (21% O2); rate of conveying gas 2.0 N m3 h-1, etc. For details, see ref 23. Basic conditions for the present relationships: de 45 µm; VM 32.6%; coal rate 1250 kg h-1; Tblast 1200 °C; blast rate 10 929 N m3 h-1; OE 24.5%; rate of cooling gas 179 N m3 h-1 (100% O2); rate of conveying gas 47 N m3 h-1, etc. For details, see Table 4).

found at the center of the plume; (3) coal burnout increases continuously with the distance, higher in the upper part of the plume; (4) in addition, the burnout predictions using treatment 2 (as one fuel gas) are always higher than those using treatments 1 (as a mixture of six fuel gases) and 3 (as a mixture of two fuel gases), but their difference is insignificant. The comparisons with the measurement indicate that the different treatments are all acceptable for predicting final burnout. The coal burnout strongly depends on the availability of oxygen and residence time under the conditions examined. The model is sensitive to the changes in these operational parameters on coal burnout: increasing blast temperature or oxygen

A1, A2 ) pre-exponential factors of devolatilization reactions, s-1 Ac ) pre-exponential factors in Gibb model, m s-1 K-1 Ap ) particle area, m2 As ) constant in Gibb model, 0.0004 a ) exponent in Gibb model, 0.75 C0 ) mass of raw coal, kg C1, C2 ) turbulent model constants CD ) drag coefficient Cp ) particle heat capacity, J kg-1 K-1 D ) external diffusion coefficient of oxygen in Gibb model, m2 s-1 Dref ) reference dynamic diffusivity in Gibb model, 1.8 ×10-5 kg m-1 s-1 daf ) dry and ash free de ) particle mean diameter, µm e ) void fraction of char particles E1, E2 ) activation energy of devolatilization reactions, K fD ) drag force from a particle, N H ) enthalpy, J kg-1 Hreac ) reaction heat, J kg-1 I ) radiation intensity on particle surface, W m-2 [i] ) molar concentration of component i k ) turbulent kinetic energy, m2 s-2 k1, k2 ) devolatilization rate constant, s-1 k1 ) rate of external diffusion in Gibb model, s-1 k2 ) rate of surface reaction rate in Gibb model, s-1 k3 ) rate of internal diffusion and surface reaction in Gibb model, s-1 kc ) carbon oxidation rate in Gibb model, m s-1 m ˙ ) mass transfer rate from a particle, kg s-1 mc ) mass of char, kg Mc ) molecular weight of carbon MO2 ) molecular weight of oxygen molecule np ) particle number per unit volume, m-3 Nu ) Nusselt number OE ) oxygen enrichment in blast, % p ) pressure, Pa q ) heat transfer from a particle, W rp ) particle radius, m

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-1

ri ) reaction rate of gas species i, mol m s Re ) Reynolds number T ) temperature, K Tblast ) blast temperature, K Tc ) activation energy in Gibb model, K Tref ) reference temperature in Gibb model, 293 K Ts ) constant in Gibb model, 6240 K U ) mean velocity of gas, m s-1 u, V, w ) gas velocity components, m s-1 VM ) volatile matter of coal Vi ) stoichiometric coefficient of species i. Wi ) reaction rate of species i (per unit volume), kg m-3 s-1 Xa ) ash mass fraction Xa,0 ) original ash mass fraction Greek Letters R ) volume/internal surface area ratio in Gibb model R1, R2 ) volatile yield ε ) turbulent dissipation rate, m2 s-3 εp ) particle emissivity λ ) thermal conductivity, W m-1 K-1 σk, σε ) turbulence model constant σB ) Stefan-Boltzmann constant, 5.67 × 10-8 W m-2 K-4 φ ) mechanism factor in Gibb model F ) density, kg m-3 µ ) dynamic viscosity, Pa s µt ) turbulent viscosity, Pa s Γi ) molecular diffusivity of species i, kg m-1 s-1 Subscripts c ) char g ) gas p ) particle

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ReceiVed for reView May 25, 2009 ReVised manuscript receiVed September 1, 2009 Accepted September 6, 2009 IE900853D