Fuel 90 (2011) 728–738

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Fuel

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Three-dimensional modelling of in-furnace coal/coke combustion in a blast furnace

Y.S. Shen a, B.Y. Guo a, A.B. Yu a,⇑, P.R. Austin b, P. Zulli b

a Lab for Simulation and Modelling of Particulate Systems, School of Materials Science and Engineering, University of New South Wales, Sydney, NSW 2052, Australiab BlueScope Steel Research, P.O. Box 202, Port Kembla, NSW 2505, Australia

a r t i c l e i n f o a b s t r a c t

Article history:Received 18 January 2010Received in revised form 19 August 2010Accepted 23 August 2010Available online 12 October 2010

Keywords:Pulverized coal injectionMathematical modellingBlast furnace lower zoneIn-furnace

0016-2361/$ - see front matter � 2010 Elsevier Ltd. Adoi:10.1016/j.fuel.2010.08.030

⇑ Corresponding author. Fax: +61 2 93855956.E-mail address: a.yu@unsw.edu.au (A.B. Yu).

A three-dimensional mathematical model of the combustion of pulverized coal and coke is developed.The model is applied to the region of lance-blowpipe-tuyere-raceway-coke bed to simulate in-furnacephenomena of pulverized coal injection in an ironmaking blast furnace. The model integrates not onlypulverized coal combustion model in the blowpipe-tuyere-raceway-coke bed but also coke combustionmodel in the coke bed. The model is validated against the measurements under different conditions.The comprehensive in-furnace phenomena are investigated in the raceway and coke bed, in terms of flow,temperature, gas composition, and coal burning characteristics. The underlying mechanisms for thein-furnace phenomena are also analysed. The simulation results indicate that it is important to includerecirculation region in the raceway and the coke bed reactions for better understanding in-furnacephenomena. The model provides a cost-effective tool for understanding and optimizing the in-furnaceflow-thermo-chemical characteristics of the PCI operation in full-scale blast furnaces.

� 2010 Elsevier Ltd. All rights reserved.

1. Introduction

Blast furnace (BF) is the most widely used technology to pro-duce iron, where coke is the dominant fuel in the process. One ofthe most significant recent improvements in BF operation is pul-verized coal injection (PCI), where pulverized coal works as anauxiliary fuel to partly replace relatively expensive coke. In thisprocess, pulverized coal is injected via tuyere and then combustsin the raceway cavity and the surrounding coke bed (Fig. 1). ThePCI rate has increased due to economic, operational and environ-mental benefits. This has resulted in reduced coke consumptionand thus production costs; enhanced furnace stability; greater flex-ibility in BF operation; and reduced overall emissions from steelplants [1,2]. In a modern BF, over 200 kg of coal per tonne of hotmetal (kg/t-HM) can be injected; and over 300 kg/t-HM is undertest [3]. However, as the PCI rate increases to a higher level, thecoal combustibility will be reduced to a certain degree. As a result,this could have an adverse effect on the in-furnace operation. Be-cause more unburnt char particles are swept into the coke bed,the permeability of the surrounding coke bed could deteriorateresulting in the improper distribution of gas flow and composition(Fig. 1) [4]. Higher coal burnout and proper gas species distributionis necessary for furnace stability and cost reduction [5,6]. There-fore, it is important to understand the in-furnace aerodynamicand physicochemical behaviours for the whole region of lance-blowpipe-tuyere-raceway-surrounding coke bed (LBTRC) in the

ll rights reserved.

lower part of a BF, especially in terms of coal burnout and gas spe-cies distributions.

In a real BF, actual measurements of such in-furnace phenomena,especially the LBTRC region, are extremely difficult due to the severepractical environment (high temperature, high pressure etc.). Thelaboratory experimental studies via replicating the in-furnacephenomena related to PCI process are laborious and very expensive.As a result, only a few such attempts have been reported in the liter-ature [6–9] and they are mainly on gas compositions along tuyereaxis in actual BFs [7,8] or pilot-scale experiments [6,9].

As an alternative, a mathematical approach provides an efficientmethod in investigating the in-furnace phenomena of PCI opera-tion [5,10,11]. A brief summary of early PCI models (one- andtwo-dimensions) can be found elsewhere [1]. These models em-ployed numerous assumptions and some important operationalfeatures were not included, especially relating to the spatial repre-sentation of the process. Three-dimensional (3D) modelling ismore reliable for practical problems. In this connection, some 3Dnumerical studies of coal combustion were reported [2,12,13],without including the coke bed region. To date, few 3D integratedmodels of coal/coke combustion of PCI operation were found in theliterature [14–16]. Gu et al. [15] described a 3D Eulerian–Eulerianmodel of pulverized coal combustion for the tuyere-raceway-coke bed region. But coke reactions were not considered. More-over, only one coal size group was considered. In practice, thecoal size range is large, typically 5–300 lm. The Eulerian–Eulerianapproach needs multiple phases and then multiple sets of govern-ing equations for the multiple size groups, leading to expensivecomputation. Nogami et al. [16] reported a 3D transient-state

Nomenclature

A1, A2 pre-exponential factors of devolatilization reactions, s�1

Ac pre-exponential factors in Gibb (m s�1 K�1)/Field(kg m�2 s�1) models

Ap particle projected area, m2

As constant in Gibb model, 0.0004B coal burnoutC0 mass of raw coal, kgC1, C2 turbulent model constantsCD drag coefficientCp particle heat capacity, J kg�1 k�1

D external diffusion coefficient of oxygen in Gibb model,m2 s�1

d particle diameter, md0 particle diameter at the start of devolatilization, mDref dynamic diffusivity in Field/Gibb model, 1.8 � 10�5

kg m�1 s�1

e void fraction of char particlesE1, E2 activation energy of devolatilization reactions, KfD drag force from a particle, NH enthalpy, J kg�1

hg heat transfer coefficientHreac reaction heat, J kg�1

I radiation intensity, W m�2 s�1

[i] molar fraction of reactant species ik turbulent kinetic energy, m2 s�2

k1, k2 devolatilization rate constant, s�1

k1 rate of external diffusion in Gibb model, s�1

i2 rate of surface reaction rate in Gibb model, s�1

k3 rate of internal diffusion and surface reaction in Gibbmodel, s�1

kc char oxidation rate in Gibb model, m s�1

kc oxidation rate of coke reactions in Field model,kg m�2 s�1

kd diffusion rate of coke reactions in Field model, kg m�2

s�1

_m mass transfer rate from a particle, kg s�1

ma ash mass fractionma,0 original ash mass fractionmc mass of char, kgMc molecular weight of carbonMo2 molecular weight of oxygen moleculemrc rate of change of mass of the raw coal, kg s�1

mrc,0 mass of the raw coal at the start of the devolatilization, kg

np particle number per unit volume, m�3

Nu Nusselt numberp pressure, PaP local pressurePA atmospheric pressureq heat transfer from a particle, WR resistance to flow in porous media (R = 0 for cavity)rp particle radius, mri reaction rate of gas species i, mol m�3 s�1

Re Reynolds numberSU source terms due to the interaction between the gas

phase and the particle phase/coke bedT temperature, KTc activation energy in Gibb/Field model, KTref reference temperature, 293 KTs constant in Gibb model, 6240 KU mean (true) velocity of gas, m s�1

u, v, w gas velocity components, m s�1

vi stoichiometric coefficient of species i.Wi reaction rate of species i (per unit volume), kg m�3 s�1

Yi mass fraction of species i

Greek lettersa volume/internal surface area ratio in Gibb modela1, a2 volatile yielde turbulent dissipation rate, m2 s�3

ep particle emissivityk thermal conductivity, W m�1 k�1

rk, r turbulence model constantrB Stefan–Boltzmann constant, 5.67 � 10�8 W m�2 k�4

/ mechanism factor in Gibb modelq density, kg m�3

c volume porosity (c = 1 for cavity)l dynamic viscosity, Pa slt turbulent viscosity, Pa sCi molecular diffusivity of species i, kg m�1 s�1

Subscriptsc charcoke cokeg gasp particle

Active Coke Zone/Dripping ZoneBlast

Raceway

Cohesive Zone

Tuyere

PC lance

Deadman

Char particles swept into the coke bed

Zone of PCI Influence

Active Coke Zone/Dripping Zone

Raceway

Cohesive Zone

Active Coke Zone/Dripping Zone

Raceway

Cohesive Zone

Fig. 1. Schematic of pulverized coal injection in the lower part (lance-blowpipe-tuyere-raceway-coke bed) of a BF [6].

Y.S. Shen et al. / Fuel 90 (2011) 728–738 729

model for a laboratory-scale test rig, where the reactions of bothcoal and coke were considered. The so-called discrete element

method (DEM) was used for coke movement so that the racewaystructure could be predicted directly. This approach is generallydifficult to apply to a practical system where the number of par-ticles is huge, and thus the computation will be extremely expen-sive. Therefore, these models are not suitable for simulating thein-furnace phenomena of PCI operation based on the numericalresults.

To overcome these deficiencies, in this study, a comprehensive3D integrated model is developed for simulating the coal/cokecombustion in the LBTRC region under practical conditions. Thismodel is considered superior to previous models for its threedimensionality and inclusion of coke bed and its reactions. Themodel is validated against the measurements under different con-ditions. The comprehensive in-furnace phenomena of the LBTRCregion are then simulated and analysed, in terms of flow andcombustion characteristics. The underlying mechanisms of thein-furnace phenomena are also examined.

730 Y.S. Shen et al. / Fuel 90 (2011) 728–738

2. Model formulation

In the present model, one single computational domain coversthe lance, blowpipe, tuyere, raceway and coke bed, so that the ef-fects of operational conditions and coke bed properties on coalcombustion could be directly evaluated in real time. The blow-pipe-tuyere-raceway region is treated as a cavity. The coke bed istreated as a porous media. The model includes the following phys-ical and chemical processes: (1) turbulent gas-particle flow; (2)coal combustion (devolatilization, volatile combustion, and charreactions); (3) coke combustion and gasification; (4) heat transfersin the considered gas-particle-coke bed. On the other hand,assumptions are made in this model for simplicity: (a) coal andcoke particles are spherical; (b) there is no break-up or coalescenceof particles; (c) liquid flow in the raceway-coke bed region is notconsidered; (d) unburnt char particle accumulation at the racewayboundary is not considered; (e) raceway shape is assumed and nocoke falling into the raceway; and (f) gas dissociation under hightemperature and reactions of secondary species such as Si and Sare not considered. The model is described below.

2.1. Governing equations for gas-particle flow in cavity and porousmedia

The model formulation of gas-particle flow and coal combustionhas been detailed elsewhere [2,12]. They are outlined below forcompleteness. The new features relating to coke bed are describedin detail.

2.1.1. Gas-particle flowThe gas phase is described by a set of 3D, steady-state Reynolds

averaged Navier–Stokes equations closed by the standard k–e tur-bulence model equations, as used before [12,13]. Specifically, thevariables in the governing equations solved for the gas phase in-

Table 1Governing equations for the gas and particle phases.

For the gas phaseMass r � ðqUÞ ¼

Momentum r � ðqUUÞ �

Energy r � qUH ��

Gas species i r � qUYi ��

Turbulent kinetic energy r � qUk��

Turbulent dissipation rate r � qUe��

For a particle in the particle phaseMass dmp

dt¼ � _m

Momentum mpdUp

dt¼ �

�fD ¼18pd

EnergympCp

dTp

dt¼

�q ¼ pdpkN

where lt ¼ Clq k2

e ; Pk ¼ ðlþ ltÞrU � ðrUþ ðrUÞT Þ; CD ¼maxð2

clude mass (m), momentum (u, v, w), turbulence kinetic energy(k), turbulence dissipation rate (e), enthalpy (H) and a number ofspecies (Yi), including O2, CO2, CO, H2, H2O and volatiles, as summa-rized in Table 1. Coal particles are treated as a dispersed phase andmodelled using the Lagrangian method. Particle behaviours aretracked along the discrete particle trajectories without consideringinteraction between coal particles. Newton’s second law of motionis used to calculate their movements. The drag force (fD) and turbu-lence dispersion are considered. The change of particle tempera-ture is determined by three heat transfer modes: convective heattransfer, latent heat transfer associated with mass transfer, andradiative heat transfer. Full coupling of mass, momentum and en-ergy of particles with the gaseous phase is carried out.

2.1.2. Coke bedThe coke bed is treated as an isotropic porous media for compu-

tational efficiency. This is because based on the experiment obser-vation [14] and previous DEM modelling [16], only a limitednumber of coke particles are moving, which would not affect thecoal combustion much. The general form of the governing equa-tions of gas flow in the porous media is

r � ðqcUUÞ � r � ðCeff crUÞ ¼ cSU ð1Þ

The momentum source through the coke bed is formulated usingErgun equation,

rP ¼ 150lð1� cÞ2

c2d2p

Uþ 1:75qð1� cÞcdp

Uj jU ð2Þ

In real BFs, the temperature of coke bed is much lower than theraceway due to the effects of various complicated phenomena,such as FeO-Coke reaction (highly endothermic), solid-liquid heattransfer, Si and metalloids reactions, and convection of coke solidflow. At present, these phenomena are difficult to be included in

Xnp

_m

r � ððlþ ltÞðrUþ ðrUÞTÞÞ ¼ �r pþ 23qk

� �þX

np

fD

kCpþ lt

rH

� �rH

�¼X

np

q

Ci þlt

rYi

� �rYi

�¼Wi

lþ lt

rk

� �rk�¼ ðPk � qeÞ

lþ lt

re

� �re�¼ e

kðC1Pk � C2qeÞ

fD

2pqCD jU� UpjðU� UpÞ

�q

uðTg � TpÞ þX dmp

dtHreac þ ApepðpI � rBT4

pÞ

4ð1þ 0:15Re0:687Þ=Re;0:44Þ; i = O2, CO2, CO, VM, H2, H2O.

Y.S. Shen et al. / Fuel 90 (2011) 728–738 731

the coal combustion model to avoid the complexity. For example,in a previous study [17], the coke bed temperature was simply as-sumed as 0.8 Tg. In this study, in order to account for these effects,a heat sink is used, allowing for the consideration of more coke bedproperties.

sourceT;coke ¼ �hgAcokeðTg � T0Þ ð3Þ

Acoke ¼6ð1� eÞudcoke

;hg ¼kgNug

udcoke; T0 ¼ maxð0:75Tg ;1773½K�Þ ð4Þ

The value of hg is estimated to be 128.2 W m�2 K�1 based on thedata from a BF, where kg is equal to 0.117 W m�1 K�1, / is equal to0.85 and dcoke is assumed to be 0.03 m. Nu number is calculatedbased on the Wakao equation [18].

Nug ¼ 2þ 1:1Re0:6cokePr1=3 ð5Þ

2.2. Chemical reactions of coal and coke

The various reactions considered in this model and their model-ling methods are listed in Table 2. The coal reaction model assumescoal consists of volatiles, char and ash, and the coke reaction modelassumes a pure carbon. The model has been successfully used invarious investigations [2,12,13].

The coal reaction model has been described in our previouswork [12]. The devolatilization process is modelled by the so-called

Table 2Reactions of coal and coke considered and their rates expressions.

Reactions Models Reaction rates

Coal reactionsCoal = VM + Char Two-competing–

reactions modelk1

k2 22 1(VM αα −+11 1(VM αα −+

raw coal

dVMdt¼ ða1k1 þ a2k2ÞCO

k ¼ A expð�E=TpÞ

a1 = VM (daf.); a2 = 1.25a21 + 0.92a1

VM + O2 = CO2 + H2O Eddy dissipation model ri ¼ CAej

mini½ �m’i

� �

Char + O2 = CO + CO2 Gibb model dmc

dt¼ � 3/

1� eMC

MO2

q1qcðk�1

1 þ ðk2 þ

2ð/� 1Þ2� /

¼ As exp � Ts

Tp

� �;

k1 ¼Dr2

p;

D ¼ Dref

qTp þ Tg

2Tref

� �0:75

;

k2 ¼ ð1� eÞ kc

rp;

k3 ¼ kcTpðb coth b� 1Þ=b2a;

kc ¼ AcTp expð�Tc=TpÞ;

b ¼ Rkc

DPea

� �0:5

Char + CO2 = 2CO Gibb model

Char + H2O = CO + H2 Gibb model

Coke reactionsCoke + O2 = CO Field model dmcoke

dt¼ ðk�1

d þ k�1c Þ

�1½i�4pr2coke

PPA

kd ¼Dref

rcoke

Tcoke þ Tg

2Tref

� �0:75 PA

P;

kc ¼ Ac exp � Tc

Tcoke

� �Coke + CO2 = 2CO Field model

two-competing-reactions model [19]. A pair of first-order reactions(R1, R2) with different rate parameters (k1, k2) and volatile yields(a1, a2), compete to pyrolyse the raw coal. The Gibb model [20]is used for char oxidation and gasification, where the diffusion rateof reacting gas within the pores of a char particle (k3) is consideredas well as the external diffusion rate (k1) and surface reaction rate(k2). Their equations are respectively given in Table 2.

The important coke reactions are considered in the porous mediaregion where the consumption of coke is refilled continuously togive an unchanged simulation domain. The Field model [21] is usedfor coke reactions in the coke bed, including coke solution loss andcoke combustion. The overall rate at the surface of a coke particle isdetermined by a combination of chemical reaction and diffusion ofreacting gas, as shown in Table 2. This is controlled by the smallerone of the rates kd and kc [i] is the molar fraction of the reactinggas specie i (i = O2 for coke combustion, and CO2 for coke solutionloss reaction).

In connection with our previous studies [2,12,13], the so callededdy dissipation model (EDM) [22,23] is used to model the gas com-bustion. Compared to several new gas combustion models such asUSM (unified second-order moment) model [24], laminar flameletmodel [25], and PDF (probability density function) model [26], theEDM model may have limitations in some applications, especiallyfor gas only combustion, due to neglecting chemistry rate [24].However, it is certainly applicable to the combustion of pulverisedcoal under blast furnace conditions where the temperature isextremely high (�2800 K) and the fast chemistry assumption is

Rate constants

22 )char

11)char (R1, Low temperature)

(R2, High temperature)

A1 = 3.7 � 105 s�1 E1 = 18000 KA2 = 1.46 � 1013 s�1 E2 = 30189 K

CA = 4.0

k3Þ�1Þ�1mCAc = 14 m s�1 K�1 Tc = 21580 K

Ac = 20230 m s�1 K�1 Tc = 39743 K

Ac = 606.9 m s�1 K�1 Tc = 32406 K

Ac = 3.26 � 106 kg m�2 s�1 Tc = 10855 K

Ac = 4.71 � 109 kg m�2 s�1 Tc = 29018 K

Table 3Boundary conditions and operating conditions.

Operating conditions Proximate analysis (ad.)

Working volume 2749 m3 Moisture, % 3.2Productivity 2.4 tHM/m3 day Volatile matter, % 32.5Tuyere number 28 Ash, % 9.8Reference

pressure461.0 kPa Fixed carbon, % 54.5

Boundary conditions Gross specificenergy, MJ/kg

30.08

O2 enrichmentin blast

6000 Nm3/h Ultimate analysis (daf.)

Blast (22.9% O2) 300,000 Nm3/h 1200 �C C, % 83.5Cooling gas

(100% O2)5000 Nm3/h 327 �C H, % 5.3

Conveying gas(100% N2)

1317 Nm3/h 45 �C N, % 1.95

Coal 35 t/h(127.3 kg/tHM)

45 �C S, % 0.6

O (by diff), % 8.6

732 Y.S. Shen et al. / Fuel 90 (2011) 728–738

correct [27]. In fact, EDM has been widely accepted in this area[1,2,11–13,16,17]. As a model sensitivity check, we tested the socalled two-step (EDM – finite chemistry) model, available inANSYS-CFX, and found that this more complicated model yieldsalmost the same results in terms of gas composition and coal burn-out. Therefore, the EDM offers a good compromise between accu-racy and computational effort and is considered to be suitable forthe present work.

The composition of gas species (O2, CO, CO2, H2, H2O and N2) isthe consequence of coal and coke reactions at respective reactionrates. The rate constants listed in Table 2 also come from the pub-lished literature and are experiment-based. The gas compositionsin the LBTRC region are obtained by solving the governing equa-tions of each gas species.

3. Simulation conditions

The model geometry is based on a commercial BF in BlueScopeSteel. The main dimensions of the model geometry are shown inFig. 2. Note that the lance, blowpipe and tuyere are in actualdimensions, the raceway is designed in the shape of a ‘balloon’,rather than a divergent ‘tube’, as used elsewhere [13], and the cokebed is assumed as a packed bed. In the previous studies, the shapeof raceway was determined by means of experiments [14], contin-uum approach [10,28], and DEM coupled with computational fluiddynamics (CFD) [16,29,30]. Under the present conditions (Table 3),a constant raceway profile is assumed as shown in Fig. 2, deter-mined based on the CFD-DEM simulations using a model similarto Feng et al. [29] and previous experimental/practical observa-tions [31]. Note that different operational conditions may give dif-ferent raceway shapes. This aspect will be studied in the future.The co-axial lance is introduced into the blowpipe at an inclination

Fig. 2. Geometry of the model: (a), the whole model; (b), porosity distribution; (c), blowradius: 90 mm, and length: 800 mm; (2) for tuyere, radius: 75/90 mm, and length: 13710 mm; and (4) for coke bed, depth: 3700 mm, height: 4500 mm, and width: 1000 mm

angle of 10 degrees with its tip on the centreline. Three gas streams(conveying gas, cooling gas and hot blast) are introduced into thedomain. The lance details are shown in Fig. 2(d), where an internaltube diameter for the conveying gas stream is 17 mm and an outerdiameter of the lance shell is 35 mm. The mesh structure for blow-pipe-tuyere-raceway-coke bed region is refined at the raceway,especially in front of the lance tip. The whole simulation domainis divided into four zones according to porosity, that is, theporosities for raceway (Zone 0), deadman (Zone 1), dripping zone(Zone 2) and cohesive zone (Zone 3) are 1.0, 0.25, 0.5 and 0.4,respectively, based on the actual measurements [8], as shown inFig. 2(b). A gradient transition zone of porosity is assumed at the

pipe and raceway; and (d), lance tip. The detailed dimensions are, (1) for blowpipe,5 mm; (3) for raceway, depth: 1600 mm, height: 1000 mm (925 + 75), and width:

.

0

20

40

60

80

100

1 10 100 1000Particle size, μm

Cum

ulat

ive

volu

me,

% .

Fig. 3. Particle size distribution of the pulverized coal considered.

0

8

16 measurements [31]

Vel

ocity

, m/s

prediction

800

1200

1600

Tem

pera

ture

, °C

-0.4 -0.2 0.0 0.2 0.40

10

20

O2 c

once

ntra

tion,

%

Distance to axis (m)

(a)

20

30

40

s m

ole

frac

tion,

% .

O2,calculatedCO2,calculatedCO,calculatedO2,measuredCO2,measuredCO,measured

(b)

Y.S. Shen et al. / Fuel 90 (2011) 728–738 733

raceway boundary, where porosity varies from 1.0 (raceway cav-ity) to 0.4 (surrounding coke bed).

The mathematic model outlined can be used to study the per-formance of different types of coal. In this work, in order to testthe applicability of the model, we are focused on one typical coalused in the BlueScope Steel. The operating conditions of the BFand the proximate/ultimate analyses of the coal considered aresummarized in Table 3. The size distribution of the coal is obtainedfrom laser diffraction measurement (Fig. 3), covering a size rangeof 5–250 lm. In the current simulation, 49 particle size classesare sampled in the range of 5–250 lm and a total of over 6000 rep-resentative particles are tracked.

0

10

-0.6 -0.3 0.0 0.3 0.6 0.9 1.2 1.5

Distance from tuyere, m

Ga

Fig. 4. Model validation in terms of: (a) gas velocity, temperature and O2

concentration against measurements in laboratory experiments [32]; and (b) gascompositions against measurements in a real BF [31].

4. Results and discussion

4.1. Model validation

The model is validated against the measurements from a labo-ratory scale experiment in terms of gas velocity, temperature andconcentration) [32]; and more importantly in a real BF in termsof gas composition [31], respectively. Fig. 4(a) shows the gasvelocity, temperature and concentration. It is clear that the predic-tions are comparable to the measurements. Fig. 4(b) shows that thepredicted gas composition in the region of raceway and coke bed isin good agreement with the measurements in a real BF (NewcastleNo. 4 BF in Australia) [31]. The model validity of coal burnout hasbeen confirmed elsewhere [2,12]. Note that the measurements ofin-furnace thermal and chemical properties are extremely difficult.On the other hand, coal burnout and gas composition are the mostimportant concerns in BF practice. Their distributions reflect thecollected effects of gas-particle flow, interphase heat transfer andvarious reactions of coal combustion.

In the following, the flow and associated thermal-chemicalbehaviours in the LBTRC region will be analysed in detail, aimingto establish a clear picture of in-furnace phenomena about PCIoperation in BF ironmaking.

4.2. Flow field

Fig. 5(a) shows the gas velocity vectors in the raceway cavity. Itis shown that inside the raceway, the blast stream, together withthe inclined low-speed gas flow of conveying stream and coolingstream from the inclined lance, is accelerated through the tuyere.As a result, a high-speed jet of up to 220 m/s forms along thetuyere axis. Subsequently, after reaching the raceway boundary,the gas flow is reduced to 20–30 m/s; at the same time, the gas

flow starts a large-scale recirculation above the main gas flow jetin the raceway. In addition, as shown in Fig. 5(b), the streamlinesof the central jet gradually disperse at the end of raceway and to-ward the side of raceway, i.e., in the direction of �Z. That is, insidethe raceway, the flow pattern can be divided into two parts: a high-speed jet and a large-scale recirculation. On the other hand, in thecoke bed, as shown in Fig. 5(b), gas velocities in the coke bed de-crease rapidly to <5 m/s within a very short distance once the gasflow exits the raceway cavity and enters the surrounding cokebed. Subsequently, the behaviours of low-speed gas flow differ inthe coke bed: the velocity is extremely low in the deadman;whereas it is relatively high in the dripping zone due to its highporosity.

It is shown in Fig. 5(c) that, corresponding to the gas flow, thecoal particle trajectories inside the raceway have two differentflow patterns: (i) an inclined main coal plume located along thelower part of the raceway, where fine particles are observed atthe upper part of the plume initially and then leave the main coalplume before reaching the end of the raceway; and (ii) a large-scalerecirculation of the fine particles of up to 70 lm around the race-way centre. Subsequently, the coke bed also shows two flow pat-terns of coal particles accordingly (Fig. 5(c)): (i) the main coalplume (relatively large particles of around 100 lm) penetrates intothe deadman zone; (ii) the recirculating fine particles exit mainly

Fig. 5. Flow pattern of gas-particle flow: (a), vectors of gas phase in the raceway; (b), streamlines of gas flow; (c), particle trajectories coloured by particle mean size; and (d),particle trajectories coloured by particle travelling time.

734 Y.S. Shen et al. / Fuel 90 (2011) 728–738

from the top of the raceway and then move upward into the drip-ping zone. This is because, the large particles tend to maintain theirinitial momentum and the fine particles are easier to be affected bythe turbulence and then dispersed more widely. Fig. 5(d) shows theparticle trajectories coloured by travelling time. The residence timeof coal particles along the main coal plume is around 10–50 ms be-fore reaching the end of the raceway, while the recirculating coalparticles may be up to 0.9 s in the raceway. On the other hand,compared with the raceway in the coke bed, the travelling timeof the particles penetrating the coke bed is quite long, around1.0 s. The travelling time is even longer in the deadman comparedto the dripping zone.

Fig. 6. Temperature contours along the symmetry plane.

4.3. Temperature and gas species

Fig. 6 shows the temperature contours of the raceway and sur-rounding coke bed. The main coal plume and recirculation regionshow a great difference in temperature. Along the main coal plume,a high temperature field of up to 2900 K forms at the downstreamof the coal plume and the nearby coke bed. In particular, an annu-lar high-temperature zone, the so-called flame front, is observed atthe surface of coal plume in front of tuyere. In the recirculation re-gion, the temperature is decreased to 2000 K. This temperature dif-ference results from the gas–solid flow in the raceway and itssubsequent heat releases from chemical reactions, as show in thefollowing sessions. Compared with the previous models [12,13],the present model predicts a lower raceway temperature due tothe recirculated cold gas flow from the surrounding coke bed. On

the other hand in the coke bed, the temperature is decreased toaround 1800 K when heating the surrounding coke bed.

Fig. 7 shows the distributions of gas species in the raceway cav-ity. Inside the raceway, the main coal plume and recirculation re-gion show different distributions. Fig. 7(a) shows the contour ofVM (fuel gas) in the raceway cavity. After exiting the tuyere, thecoal starts to release VM beyond the distance of 0.4 m and formsa VM-rich core at 0.4–0.9 m. Beyond this region, the VM is nearlyconsumed completely, especially in the recirculation region. Thisis because, the VM core is surrounded by the flame-front region

Fig. 7. Contours of gas species inside the raceway: (a), VM; (b), CO2; (c), CO, and (d), O2.

Y.S. Shen et al. / Fuel 90 (2011) 728–738 735

of high temperature �2800 K, resulting in the rapid generation andbuild-up of VM. Other gas species (CO2, CO, O2) change signifi-cantly along the coal plume and are then found relatively uniformin the recirculation region (Fig. 7(b–d)): Along the coal plume afterexiting the tuyere, CO2 is quickly increased to 0.22 (mass fraction)at the location of VM core, i.e., �0.4 m from the lance tip. CO con-centration is generally low in the whole raceway, where the maincoal plume is even lower than the recirculation region, resultingfrom the gas recirculation from the surrounding coke bed. Con-tours of O2 are shown in logarithmic scale for better clarification.A very fast decrease to zero is shown along the coal plume dueto the strong VM combustion, whereas a relatively high concentra-tion is shown near the surface of the plume. This explains the exis-tence of the flame-front temperature. To sum up, after theintroduction of blast, O2 is evolved into CO2 rapidly in front oftuyere due to the strong VM combustion, whereas in the upperpart of the raceway (i.e. recirculation region), the conversion ofO2 to CO2 is slow, controlled by slow char reactions. Note that,the concentration of CO in the raceway can be predicted using thismodel. This cannot be achieved using the previous models [12,13],especially in the recirculation region. The previous models did notconsider coke bed and its reactions, and therefore cannot or greatlyunder-predict the CO concentration in the recirculation region ofraceway cavity, e.g. �0.01 (mass fraction) in Ref. [12]. This problemis solved in this model after including the recirculation region andthe surrounding coke bed.

The gas species show more complex patterns in the coke bed(Fig. 8). CO2 is completely converted to CO in the coke bed dueto the strong coke reactions outside the raceway cavity. Their dis-tributions vary in the two directions: X and Y. Along the X direc-tion: CO2 is gradually converted to CO after the gas flow exits thetop of raceway. O2 content is quite low in the coke bed, even lower

in the deadman region (shown in Fig. 8(c) in logarithmic scale).Along the Y direction, more qualitative comparisons are madealong the tuyere axis as a function of distance from the lance tip(Fig. 8(d)). The conversion rate of CO2 to CO along Y direction ismuch faster compared to X direction. The variation of gas speciesalong the tuyere axis can be divided into three stages (Fig. 8(d)):In Stage 1, three gas species keep almost constant, where coal par-ticles are heated up before 0.4 m. In Stage 2, O2 is converted to CO2

quickly, raising CO2 up to 0.2 in mass fraction which is mainly dueto the strong VM combustion. In Stage 3, i.e., beyond the end ofraceway, CO2 is converted to CO by coke reactions in the fuel(coke)-rich region. Beyond the end of raceway, there is little O2 left.

4.4. Coal combustion characteristics

The burnout is defined according to the ash balance,

Burnout ¼ 1�ma;0

ma

� �=ð1�ma;0Þ ð6Þ

It represents the total weight loss of the coal due to devolatiliza-tion and char reactions. Fig. 9(a) shows the particle trajectories col-oured by burnout in the raceway cavity. The recirculation regionshows a higher burnout than the main coal plume, �85% vs.�60%, resulting from the different residence time (Fig. 5(d)) andoxygen distribution (Fig. 7(c)). Specifically, in the following sec-tions, the detailed combustion characteristics are investigatedalong the tuyere axis and over the raceway surface, respectively.

Fig. 9(b) shows the evolutions of coal combustion characteris-tics along the tuyere axis. The burnout evolution can be dividedinto three parts: Part I, covering 0–0.4 m, where burnout does notrise; Part II, covering 0.4–1.0 m, where burnout increases rapidly;

Fig. 8. Distributions of gas species (a), CO2; (b), CO, (c), O2 along the symmetry plane, and (d), along the tuyere axis.

736 Y.S. Shen et al. / Fuel 90 (2011) 728–738

and Part III, covering the distance beyond 1.0 m, where burnoutkeeps increasing very slowly. Comparing evolution of burnout withthe particle temperature and VM content, it is found that in Part I,coal particles are heated, with almost no burnout rise and no VMcontent drop. The particle temperature increases slowly from 300to 800 K in this part after heating. In Part II, burnout increases veryrapidly up to �55%, and VM content starts to drop from 0.4 m at avery fast rate to nearly zero. The particle temperature in Part II is con-nected with Part I via a dent transition at about 0.4 m, resulting fromthe strong devolatilization (a strong endothermic reaction). Then theparticle temperature increases rapidly to �2400 K. In Part III, theburnout plateaus at around 57%. The particle temperature keepsincreasing to 2600 K. The results indicate that Part I corresponds tothe preheating stage of raw coal particles, the burnout is mainly con-trolled by devolatilization in Part II, and then followed by slow charoxidation in Part III. Moreover, compared to part III (slow charreactions control), Part II (fast devolatilization controls) plays a dom-inant role in determining final burnout along the tuyere axis.

In addition, it is noted that the current model predicts a lowerfinal burnout along the tuyere axis by �5% (absolute) comparedwith the previous models. In the previous studies [12,13] racewaywas assumed as a tube without considering recirculation region. Inthis study, when using the present model, the recirculation regionis included and as a result, the fine particles of higher burnoutleave the main coal plume at the downstream, leading to a lower

burnout prediction along the tuyere axis. It is true that the recircu-lation region does exist in real BFs [1,31], therefore the presentmodel could truly simulate the in-furnace phenomena related toPCI operation. On the other hand, this comparison also indicatesthat it is important to include recirculation region in the futurenumerical studies of PCI operation for better understanding of in-furnace phenomena.

The three combustion characteristics are further analysed forparticles of different sizes (Fig. 10). Six particle size groups areinvestigated. The burnout evolution curve for each size group canalso be divided into three parts, Part I (constant), Part II (increaserapidly), Part III (plateau), similar to the overall performance ofthese characteristics. However, the coal combustion performancevaries greatly for different size groups. Specifically, in Part I, the coalparticles less than 20 lm burn earlier at a distance of around 0.4 m,while the large coal particles of over 200 lm only start to burnbeyond the distance of 0.7 m. In Part II, where devolatilization con-trols, the burnout of the fine particles increases faster than the largeones. After the transitions, in Part III, where slow char reactions areprevalent, although the increasing rates for all the size groups areslowed down, the fine particles still increase faster compared withthe large ones. These are found to be consistent with the evolutionsof VM for each size group (Fig. 10(b)), where at 0.4 m, particlesbelow 30 lm have nearly completed devolatilization at the fasterrates, whereas those above 200 lm have hardly started beyond

0

20

40

60

80

100

0

10

20

30

40

0.0 0.2 0.4 0.6 0.8 1.0 1.2

500

1000

1500

2000

2500

3000

Par

ticle

tem

pera

ture

, K

VM

, %

Bur

nout

, %

Distance from lance tip, m

Burnout VM T

p

(a)

(b)

(c)

Fig. 9. Combustion characteristics of coal: (a), along particle trajectories in theraceway; (b), along the tuyere axis in the raceway; and (c), along particletrajectories in the coke bed.

0

20

40

60

80

0 0.2 0.4 0.6 0.8 1 1.2Distance from lance tip, m

Burn

out,

%

.

1-10 10-20 20-30 30-50 50-80 80-120 120-200

0

10

20

30

40

0 0.2 0.4 0.6 0.8 1 1.2Distance from lance tip, m

VM,%

1-10 10-20 20-30 30-50 50-80 80-120120-200

300

800

1300

1800

2300

2800

0 0.2 0.4 0.6 0.8 1 1.2Distance from lance tip, m

Par

ticle

tem

pera

ture

,K

1-10 10-20 20-30 30-50 50-80 80-120120-200

(a)

(b)

(c)

Fig. 10. Combustion characteristics along the tuyere axis inside the raceway fordifference size group: (a), burnout; (b), VM; and (c), particle temperature.

Y.S. Shen et al. / Fuel 90 (2011) 728–738 737

0.8 m. With respect to particle temperature (Fig. 10(c)), fine parti-cles increase their temperature faster and always have a higherparticle temperature. To sum up, the fine particle group releasesVM earlier and always gives a higher particle temperature and ahigher burnout.

It is worth noting that the burnout at one final point of the tuyereaxis near the end of the raceway has been widely used in variousexperimental and numerical studies to represent the coal combus-tion efficiency. This method is not representative. In this study, theaverage burnout over the raceway surface is predicable. The averageburnout of the coal particles exiting the entire raceway surface isconsidered significant in providing more reliable information onthe amount of unburnt char entering the coke bed. This informationis not predicted by the previous models which do not consider theraceway. However, due to the inclusion of more complex settingssuch as recirculation region of raceway and surrounding coke bed,this information can be predicted using the present model. Specifi-cally, under the conditions in the current study, the burnout at theraceway end (at 1.3 m from lance tip) along tuyere axis is 57%; the

burnout over the raceway bottom is about 82%; the burnout overthe entire raceway surface is about 92%.

Moreover, Fig. 9(c) shows the coal burnout distribution alongthe particle trajectories in the coke bed. It is shown in the simula-tion that the burnouts vary greatly in different zones of the cokebed, nearly 100% in the dripping zone, and around 75% in the dead-man zone. This results from the local differences in oxidants(O2 + CO2 + H2O) and particle specific surface area. The drippingzone shows relatively higher oxidant concentration (Fig. 8(a,c))and the fine particle size distribution (Fig. 5(c)). As a result, thestronger char oxidation could occur there, yielding a higher coalburnout, compared to the deadman zone. Note that the interac-tions between the coal particles (treated as a dilute phase) and

738 Y.S. Shen et al. / Fuel 90 (2011) 728–738

the coke bed (treated as a packed bed) are not included in thismodel. This simplification could shorten the residence time of coalparticles in the coke bed and subsequently may underestimate thecoal burnout in the coke bed. How to address this issue needs fur-ther work in the future.

5. Conclusions

A three dimensional integrated model of coal/coke combustion isdeveloped and then applied to the lance-blowpipe-tuyere-raceway-coke bed region in a BF. One single computational domain is used,where the blowpipe-tuyere-raceway is treated as a cavity and cokebed as a porous media. The model is validated against measure-ments from laboratory experiments and real blast furnace, respec-tively. On this basis, the typical in-furnace phenomena of theraceway and surrounding coke bed are investigated. (1) Inside theraceway: main coal plume and recirculation region show differentpatterns. Compared to the recirculation region, the main coal plumeshows considerably higher gas velocity, shorter particle residencetime, higher gas temperature and significantly higher CO2 and VMconcentrations. The coal is heated and does not start burning untilexiting the tuyere; subsequently the burnout increases rapidly atthe upstream of the raceway due to strong devolatilization and thenplateaus at the downstream of the raceway due to slow char reac-tions. (2) In the coke bed: compared with the dripping zone, thedeadman shows slightly lower gas velocity and longer residencetime with large particle size, significantly higher CO, lower O2 con-centrations, and a lower burnout. (3) Coal devolatilization is themain contributor to raise the final burnout level in the raceway.Local coal burnout mainly depends on particle size, residence timeand oxygen availability in both the raceway and coke bed.

Compared with the previous 3D models [12,13], the presentmodel includes more complex settings, such as recirculation regionof raceway, surrounding coke bed and its reactions etc. When com-paring the simulations using the present model with the previousmodels, (a), in this study along the main coal plume, the dispersionof the coal plume is limited within the tuyere but more significantin the raceway. Then a large-scale recirculation of fine coal parti-cles forms in the upper part of raceway; (b), the present model pre-dicts a lower temperature in the raceway; (c), the previous modelswere found to greatly under-predict the CO concentration in theraceway; and (d), the current model predicts a lower final burnoutalong the tuyere axis by �5% (absolute). The inclusion of recircula-tion region in the raceway plays an important role in determiningburnout. These comparisons also indicate that it is important to in-clude recirculation region in the future numerical studies of PCIoperation for better understanding in-furnace phenomena. Moreimportantly, compared with final burnout at one point predictedin previous models, this model could give a more reliable burnoutprediction over the raceway surface, which could better representthe amount of unburnt char entering the coke bed. The averageburnout over the raceway surface is around 90% in the base case.

To our knowledge, this model is the first 3D model to simulatethe in-furnace phenomena of PCI operation in the literature.Considering the high cost for physical experiments or BF in situmeasurements, this model provides a cost-effective tool for under-standing the in-furnace flow-thermo-chemical behaviours of thePCI operation, and then optimizing operating conditions in full-scale BFs in the future.

Acknowledgements

The authors wish to thank the Australian Research Council andBlueScope Steel for their support of this project. Dr Harold Rogers

(University of Newcastle, formerly BHPBilliton’s Newcastle Tech-nology Centre) is acknowledged for providing the experimentaldata used in the model validation.

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