Three-dimensional transient modelling of coal and coke co-combustion in the dynamic raceway of ironmaking blast furnaces

Applied Energy 261 (2020) 114456

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Three-dimensional transient modelling of coal and coke co-combustion in the dynamic raceway of ironmaking blast furnaces Yuting Zhuo, Yansong Shen

T

⁎

School of Chemical Engineering, University of New South Wales, Sydney, New South Wales 2052, Australia

HIGHLIGHTS

GRAPHICAL ABSTRACT

3D transient model is developed to • Astudy in-furnace phenomena in a blast furnace.

dynamic raceway and coal-coke • The co-combustion performance are quantified.

of blast rate on raceway evo• Effects lution and coal combustion are characterized.

higher blast rate • Afurnace efficiency.

improves blast

ARTICLE INFO

ABSTRACT

Keywords: Transient model Blast furnace Raceway Coal Coke Combustion

The blast furnace is a highly efficient but energy-intensive chemical reactor for iron production. Two types of solid fuels, viz. coarse coke particles and fine pulverized coal powders, are combusted simultaneously, forming the dynamic cavities (termed raceway) at the lower part of the blast furnace, and their behaviour affects each other considerably, although this has not been clearly established in the past. In this study, a three-dimensional transient model is developed for describing the complex co-combustion of pulverized coal and coke coupled with the dynamic raceway evolution under industrial-scale blast furnace conditions. The model couples a gas-coke combustion model with a gas-coal combustion model in a transient state by means of two-way coupling scheme. The model is then validated against experimental measurements. The typical transient in-furnace phenomena are illustrated in terms of raceway shape and size, gas-solid-powder flow, temperature fields, gas composition and coal and coke combustion. As time progresses from 0 s to 7.0 s, the raceway size increases in depth, width and height; and the coal burnout slightly increases. At around 7.0 s, the raceway profile and coal and coke combustion approach a relatively stable state. Additionally, the effects of blast rate on the in-furnace phenomena are studied. Under the simulated conditions, when the blast rate is increased from 140 m/s to 180 m/s, a larger raceway is formed and the depth is increased by 22.2%. Subsequently, the average burnout of pulverized coal is improved by 3.6% and the reducing gas, i.e., CO, is increased by 1%. This model offers a cost-effective tool to optimize coke/coal co-combustion in blast furnaces for energy saving and operation stability.

⁎

Corresponding author. E-mail address: [email protected] (Y. Shen).

https://doi.org/10.1016/j.apenergy.2019.114456 Received 19 September 2019; Received in revised form 11 December 2019; Accepted 24 December 2019 0306-2619/ © 2019 Elsevier Ltd. All rights reserved.

Applied Energy 261 (2020) 114456

Y. Zhuo and Y. Shen

Nomenclature

Ap cp CD C1 C2 d D D0 fh g Hreac h Kc k km kri K m Mi p pox Q R Rk Re

ri rki kki t T T v vi Yi

surface area of the particle (m2) heat capacity of the particle (J/kg K−1) drag force coefficient mass diffusion-limited rate constant kinetics-limited rate pre-exponential factor particle diameter (m) diffusion coefficient (m2 s−1) diffusion rate coefficient of oxygen, m2/s Heat absorb fraction gravitational acceleration (m s−2) heat released by surface reaction (J) convective heat transfer coefficient (W/m2 K−1) equilibrium constant heat-transfer coefficient (W m−2 K−1) mass-transfer coefficient (m s−1) kinetics rate of heterogeneous reaction I (m s−1) interphase momentum exchange coefficient (kg m−3 s−1) mass-transfer rate (kg m−3 s−1) molar weight (kg kmol−1) pressure (Pa) partial pressure of oxidant species in the gas surrounding the combusting particle, (Pa) intensity of heat exchange (W m−3) universal gas constant (J mol−1 K−1) kinetic rate, s−1 Reynolds number

reaction rate (kmol m−3 s−1) heterogeneous reaction rate (kmol m−3 s−1) kinetic rate of heterogeneous reaction i (m s−1) time (s) temperature (K) local temperature of continuous phase K velocity (m/s) stoichiometric coefficient of reactant i mass fraction of the ith species

Greek Symbols

µ ¯ p

volume fraction density (kg m−3) dynamic viscosity (Pa s) thermal conductivity (W m−1 K−1) stress tensor (Pa) particle porosity Stefan-Boltzmann constant (5.67*10−8 W/m2 K−4)

Subscripts

VM g H2 O Moi s p

1. Introduction

volatile matter gas phase vapour moisture solid phase coal particle

technology for reducing production costs by replacing a portion of the expensive coke particles in the raceway and is now practised in most BFs [6,7]. A high coal combustion efficiency is usually desired in the raceway so that less unburnt coal will enter the surrounding coke bed and bed permeability can be retained for stable BF operation as well as energy-saving during blasting. Notably, the raceway dynamics and pulverized coal combustion strongly interact and need to be comprehensively considered. Generally, raceway dynamics and pulverized coal combustion efficiency affect both energy consumption and BF performance stability in terms of heat and reducing gas generation. Therefore, it is important to understand these dynamic in-furnace phenomena and the interactions between raceway evolution and co-combustion of coke and pulverized coal, in terms of flow and thermochemical behaviours for stable and low-cost (viz. low-energy consumption) BF operation. In the past, raceway evolution and coke or pulverized coal combustion have been studied separately but have not been studied in a combined way. Due to the harsh internal environment inside an operating BF, such as the high temperature, high pressure and harsh nature of the flows, it is difficult to conduct in-situ plant tests. Some lab-scale experiments have been conducted in an effort to understand raceway

The ironmaking industry, as an energy-intensive production technology, is emitting about 650 million tons of CO2 per year and is the fourth biggest industry using fossil fuels [1]. The sector is a major contributor to greenhouse gas emissions, accounting for 7% of total global CO2 emissions [2]. Recently, global concern on climate change and energy resource depletion have driven discussion on the challenges facing the ironmaking industry in terms of energy-saving and emission reduction. Improving energy efficiency, including fuel switching, optimized process control, and increasing the thermodynamic efficiency of the specific production process, is an effective method to achieve this objective [3]. The blast furnace (BF) is a highly efficient chemical reactor and plays the predominant role in the ironmaking process to date and will continue to do so in the near future. Unfortunately, it is an energy-intensive reactor, accounting for over 90% of the energy consumption in a steel plant. Consequently, improving the energy application efficiency in BFs directly determines the energy consumption and gas emissions in the ironmaking industry. BF itself is an extremely complicated system, in which a variety of minerals, such as iron ore, coke and pulverized coal are used as main raw materials and fuels, and complex multiphase flow and thermochemical phenomena are involved. In the lower part of a BF, the preheated high-speed gas, usually together with pulverized coal, is laterally blasted into a packed bed of coke particles through ~30 tuyeres, forming a void or cavity adjacent to each tuyere [4]. As schematically shown in Fig. 1, the cavity, called the ‘raceway’ in BFs, refers to the recirculating flow of gas-coke-pulverized coal particles. Here coke and pulverized coal are co-combusted to provide heat and reducing gases for the smelting process in the upper part of the BF, and therefore it strongly affects BF performance [5]. Specifically, the raceway evolution (or formation) process represents an intense and dynamic gas-coke reactive flow and should be well maintained for stable BF operation and energy-saving purposes during blast generation from the large electricity consumption. Pulverized coal injection (PCI) represents a recent

Fig. 1. Schematic of raceway evolution and PCI operation at a lower part of a BF [7]. 2

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Y. Zhuo and Y. Shen

evolution or PCI operation. For example, Hatano et al. [8] examined raceway evolution using a lab-scale test rig; Li et al. [9] considered PCI operation under a range of operating conditions using a pilot-scale test rig. They provided substantial measurement data at lab or pilot scale only but could not provide in-furnace phenomena in industrial BFs. Experimental studies still lack a fundamental understanding of the complex hydrodynamic and reactive characteristics in the large and complicated BF reactor. With the development of computer technology, numerical modelling has become an effective tool for understanding and optimizing complex flows and/or reaction systems [10,11]. To obtain a comprehensive and in-depth understanding of in-furnace phenomena related to raceway evolution and/or PCI operation in BFs, numerical modelling is the preferred option [12,13]. Some numerical studies have been undertaken with regard to predicting raceway evolution in terms of shape and size or understanding in-furnace phenomena related to pulverized coal combustion. Mondal et al. [14] developed a 2D multiphase flow model and evaluated the raceway boundary under various blast air velocities and the coke bed properties, although their models used a simplified geometry for the BF, and both heat transfer and chemical reactions were not considered. Selvarasu et al. [15] developed a 3D multiphase flow model to quantify the multiple raceways in a BF under different operating conditions. Further, Rangarajan et al. [16] developed a Two-Fluid-Model (TFM) to investigate the raceway shape variation due to the changes in gas injection velocity and angles. Safronov [17] developed a CFD model to predict the raceway shape and size and also a reduced-order model to predict the raceway based on a force balance. Apart from the continuum-based CFD models, the discrete-based CFD-DEM (discrete element method) model is a recent approach to investigate particle behaviour in BFs and offers particle-scale information, where particle phase is modelled by the DEM approach. For example, Feng et al. [18] studied the effects of loading pressure on the raceway shape using a 3D CFD-DEM model at lab scale. Nogami et al. [19] developed a CFD-DEM model and investigated the proper blast conditions for raceway control at lab scale as well. Yuu et al. [20] developed a full-scale BF model that considered the melting zones’ effect and studied the raceway shape under different injection angles. Miao et al. [21] developed a 2D slot model to simulate the raceway characteristics and identified different types of raceways under different operating conditions, although did not consider heat and mass transfer in the chemical reactions. Baniasadi et al. [22] developed a CFD-DEM model to investigate the hydrodynamic behaviour of fluid phases passing through a packed bed of solid particles, in which the liquid effects on the BF’s internal flow pattern were considered. Umekage et al. [23] developed a CFD-DEM

cold flow model to study the raceway vicinity flow regime and its relationship with the cohesive matter on the furnace wall. However, due to limitations of current computational capability, the CFD-DEM model is difficult to implement to simulate a full-scale BF, where the particle number is immense whereby the CFD-DEM method cannot manage it. On the other hand, some numerical models have been developed to describe PCI operation. For example, Du et al. [24] developed a PCI model, where a variety of injection conditions were considered to study pulverized coal combustion in the blowpipe and tuyere. Gu et al. [25] developed a PCI model to study the effect of the tuyere diameter on the pulverized coal combustion characteristics in the raceway. Shen et al. [26] developed a full-scale steady-state PCI model using the Euler-Lagrangian method to investigate pulverized coal combustion, in which the raceway was assumed as a pre-set fixed cavity region based on a CFD-DEM model. Subsequently, Wu et al. [27,28] used a similar strategy to study the particle segregation phenomena during PCI operation in a BF, where the raceway boundary was also pre-set based on simulation by a TFM-based raceway submodel. Although these PCI models could effectively reflect the coal combustion characteristics and evaluate the combustion efficiency, they all used a pre-set raceway with a fixed shape based on the simulation results of CFD-DEM or TFM models under a fixed blast condition. That is, the inter-related in-furnace states between the co-combustion of coke and pulverized coal and raceway variation were not considered in these models and has remained a constant challenge. Consequently, the collected effect of blast conditions (e.g. blast rate as one key BF operation parameter) on the interactions between raceway evolution and PCI combustion cannot be studied using these models. This is regarded as a longstanding topic in the field of co-combustion of coke and coal in BFs [26]. Therefore, it is necessary to model the dynamic raceway evolution and co-combustion of coke and pulverized coal simultaneously and in a two-way coupled manner. In the present work, a transient 3D integrated model is developed to describe the complex co-combustion of coke and pulverized coal in connection with the dynamic evolution of raceway under industry-scale BF conditions. The model firstly illustrates the flow and thermochemical behaviours inside the furnace in terms of raceway shape and size, flow fields, temperature and gas composition distributions in a dynamic environment, and understand the correlation between the blast conditions and BF’s performance in terms of energy consumption and fuel combustion efficiency. The model is then used to study the effects of blast rate on the collected results of both dynamic raceway evolution and co-combustion of coke and pulverized coal under industry-scale BF conditions. From an energy application point of view,

Table 1 Governing equations of gas, coke and coal phases. Gas phase t

t t

(

g g Yi )

+

(

g g Yi vg )

(

g g vg )

+

(

g g vg vg )

( g g hg ) +

(1)

= mi + Si + mp

=

g

p+

p + ¯g : g t

( g g vg hg ) =

¯g +

g gg

vg

+ Ksg ( vs

vg ) + Ftd, g

msg vsg

qg + Sg + Qsg + msg hsg + Q gp + Sp + Qrad

Solid phase (coke) t t t

(

s s Yj )

+

(

s s Yj vs )

(

s s vs )

+

(

s s vs vs )

(

s s hs )

+

(

s s vs hs )

p

s

p s t

=

ps + + ¯s :

¯s +

vs

s sg

+ K gs (vg

qs + Ss + Qgs

d up dt

= =

mp Cp

dTp dt

up r

+

g( p

= hAp (T

p

)

fh

(5) (6)

(8)

+F

Tp)

msg vsg

(7)

m u

vs ) + Ftd, s

msg hsg + Qrad

Powder phase (pulverized coal) dmp dt

(3)

(4)

= mj + Sj

=

(2)

dmp Hreac dt

(9)

+ Qrad ;

3

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Y. Zhuo and Y. Shen

the model is a cost-effective tool for optimizing operating conditions and process design, which contributes to enhancing PCI efficiency and BF performance.

2.1.3. Gas-coke flow model (Submodel 1): turbulence model for the closure of the gas phase constitutive equation The effective dynamic viscosity (shear viscosity) is calculated from the molecular and turbulent viscosities as follows:

2. Model description

µeff , g = µg + µt , g

The turbulent viscosity, µt , g , is modelled by the modified k closure equations for turbulence. A modified k model is applied for this purpose, where the standard k model is supplemented with extra terms that include the interphase turbulent momentum transfer. The turbulent viscosity, µt , g , is written as follows:

In the present model, the computational domain considers the entire region of the lower part of the BF including blowpipe, tuyere, lance and the coke bed. 2.1. Model details In the present work, an integrated model is developed for describing the co-combustion of coke and pulverized coal and the dynamic raceway evolution under industrial-scale BF conditions. This is accomplished by coupling two submodels for gas-coke reacting flow (Submodel 1) and gas-coal reacting flow (Submodel 2) in two-way fashion.

µt , g =

t

K=

3 Cd, s 4

s

+ 1.75

g g

g

| vs

s

|vs

vg | g

g ds

vg | g

ds

2.65

g

> 0.8

t

u

up r

is the drag force per unit particle mass and

=

µt , g k

g g vg k g )

kg ) +

g Gk , g

g g g

+ (ksg

2kg )

(15)

(

g g g)

=

·(

g

+ µt , g

·(

g g vg g )

g)

+

g

g

kg

(C1 Gk, g

C2

g g)

+ C3

g

kg

(ksg

2k g )

k

= 1.0,

= 1.3

2.1.5. Chemical reaction models In this model, the complex pulverized coal combustion is regarded as a multistage process involving: (1) preheating; (2) devolatilization of raw coal, producing VM (volatile matter) and char; (3) combustion of volatile gases; and (4) oxidation and gasification of residual char. The devolatilization process, for the sake of computational efficiency, is modelled by the so-called two-competing-reactions model [35]. The raw coal is pyrolyzed, the process being controlled by a pair of firstorder reactions (R1, R2) with different kinetic parameters (k1, k2) and VM yields. The combustion of volatile gases is modelled by the so-called eddy-dissipation model (EDM) [36]. The coke combustion and

(12)

r

g

·(

2.1.4. Gas-coal flow model (Submodel 2) A transient gas-coal model is developed based on the EulerLagrangian framework for describing the combustion of pulverized coal. The interaction forces between coal powders are not considered in tracking the discrete particle trajectories since the dispersed coal phase is a dilute phase. Particle movements are calculated based on Newton’s second law, where the gas drag force and the turbulence dispersion are taken into account. The temperature variation of a coal particle is determined by three heat transfer models, viz. convective heat transfer, latent heat transfer accompanied by the mass transfer, and radiative heat transfer. The gas mixture phase is described as a continuous phase, which is defined by the unsteady-state Reynolds averaged NavierStokes equations closed by the standard k - turbulence model equations. The full coupling of mass, momentum and energy exchange between coal powders and gas phases is undertaken. The governing equations for the coal powder phase are shown in Table 1.

F is an additional acceleration for the powder phase momentum exchange,

·(

+

Cµ = 0.09, C1 = 1.44, C2 = 1.92, C3 = 1.2,

(11)

s

g g kg )

(16)

Further, the turbulent dispersion force is described by the equation proposed by Lopez De Bertodan [34], which is expressed as follows:

Ftd, s = Ctd g k g

(14)

g

Gk, g is the production of turbulent kinetic energy in the gas phase. In both the equations, the last term represents the influence of the coke solid phase on the gas phase. The constants for the k model are taken as

24 where Cd, s is the interphase drag coefficient: Cd, s = Re (1 + 0.15Res0.687) , s ds | vs vg | . and the relative Reynolds number is defined as Res = s µ g

Ftd, g =

kg2

Turbulent kinetic energy dissipation rate ( )

(10)

0.8

( =

2.1.2. Gas-coke flow model (Submodel 1): interphase forces In this model, the momentum exchange (i.e. interphase forces) between gas phase and coke solid phase is mainly driven by the drag force and turbulent dispersion force. The interphase momentum exchange coefficient K, is calculated according to the Gidaspow model [31], which is a combination of the Wen and Yu [32] model and Ergun’s equation [33]. When g > 0.8, the gas-solid exchange coefficient K is calculated based on the drag force acting on solid particles, when g 0.8, K is described by the Ergun’s equation for a dense granular system. 2 s µg 2 2 g ds

g Cµ

where kg and g are the turbulent energy and turbulent kinetic energy dissipation rates, respectively, which are determined by their respective conservation equations. Turbulent kinetic energy (k )

2.1.1. Gas-coke flow model (Submodel 1): governing equations A transient gas-coke multiphase flow model is developed based on the Euler-Euler framework to describe the reacting flow of the gas phase and the coke phase. Both are treated as interpenetrating continua, and their volume fractions are assumed to be continuous fractions in space and time. The two phases are described as a set of 3D unsteady-state Reynolds averaged Navier-Stokes equations closed by standard k turbulence model equations. Heat transfer in terms of convection, conduction, and radiation is considered. The Gunn model [29] is adopted to describe the interphase heat transfer. The P-1 radiation model [30] is adopted to simulate the thermal radiation, where the heat source due to radiation is calculated by Qrad = aG 4an2 T 4 , where ɑ is the absorption coefficient, n is the refractive index of the medium, G is the incident radiation, σ is the Stefan-Boltzmann constant. The chemical reactions associated with coke combustion and gasification are modelled. The governing equations of each phase, including the conservations of mass, momentum, and energy are shown in Table 1.

K = 150

(13)

2

p dp 24 , 18µ Cd Re

here r is the particle relaxation time, up is the particle velocity, µ is the molecular viscosity of the fluid. Other typical interphase forces in the Eulerian-Eulerian model, such as virtual mass force and lift force, are not included in the model for simplification. 4

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Y. Zhuo and Y. Shen

gasification are modelled by the so-called unreacted shrinking core reaction model [37–40]. The reaction rate expressions are listed in Table 2.

are ignored; (iii) liquid flow in the raceway and coke bed is not considered; (iv) for computational convenience, the deadman is assumed as a computational domain in which the coke particles are stationary. The deadman profile is chosen according to the simulation results of the full-scale BF model [44]; (v) the so-called bird-nest region is also considered and treated as a porous zone, in which the porosity is much lower than other regions [45,46].

2.2. Coupling scheme In this integrated model, the two submodels are two-way coupled by exchanging gas phase quantities in terms of flow, temperature and gas species concentrations. Fig. 2 shows the coupling framework of this model. Particularly, in this model, the discrete coal powders are fully coupled with the gas phase at each time step, in which the data is transferred between the gas and coal phases through the related source term. In contrast, the exchange of mass, momentum and energy between the continuous gas and coke phases is conducted through the related source terms. The physical collisions between coal particles, and between coal-coke phases are not considered for computational efficiency. As the gas-coke raceway model (Submodel 1) and the pulverized coal combustion model (Submodel 2) are two-way coupled, the complex interphase chemical reactions related to raceway evolution and coke/coal co-combustion are modelled, and the interaction between the pulverized coal and raceway vicinity environment could be considered. It should be noted that, compared to the previous PCI or raceway models [26,43] in which the raceway was just assumed as a pre-defined cavity zone with a fixed shape and the surrounding coke bed is treated as a porous medium; the present model integrates a multiphase gascoke flow model to simulate the raceway evolution and related heterogeneous coke chemical reactions with a Lagrangian-based gas-coal model for simulating the pulverized coal combustion. This allows the mutual interaction between the raceway evolution and coke-coal cocombustion to be considered, whereby the model can quantify the raceway boundary in conjunction with the coal combustion performance under various operating conditions. Other key assumptions used in the model include: (i) the coal and coke particles are spherical, and the coke particles are uniform in size and density; (ii) the cracking and break-up of coke and coal particles

2.3. Numerical setting The code is developed based on the framework of ANSYS-FLUENT v17.2. The phase coupled semi-implicit method is adopted for pressurelinked equations (PC-SIMPLE). In the PC-SIMPLE method, velocities are solved coupled by phases. For spatial discretization, the second-order upwind scheme for convective kinematics scheme is applied to discretize the convection term of each scalar. The Green-Gauss cell based method is applied to estimate the gradients. Under relaxation factors are set to 0.7 for the pressure and momentum equation, volume fraction, turbulent kinetic energy and dissipation rates and other scalars are set to 0.8. Time discretization is characterized by the CFL number, which is considered under 1.0 so as to improve computational stability and solution convergence. The time step, t = 10−3 s, and the iteration number per time step, 40, are adopted to enable the residual values to be under 4 × 10−5. The mesh includes around 1.5 million cells, which is locally refined in the shear layers with the highest resolution of 1 mm. The mesh independence is studied, indicating that a finer mesh (2 million cells) has little impact on the simulation results relative to when the 1.5 million mesh was used. Therefore, the present grid resolution is considered to provide accurate results. 3. Simulation conditions 3.1. Geometry The computational domain is set up based on a practical BF (Fig. 3). The BF geometry information is listed in Table 3. Other related

Table 2 Considered reactions of coal and coke and their reaction rates’ expression. Reactions

Raw coal

Reaction rate

VM + Char

k1

raw coal dVM dt

k2

1 VM1

+ (1

1) char 1

2 VM2

+ (1

2 ) char 2

= ( 1 k1 +

Models

Ref.

Two-competing reaction model

[35]

Eddy dissipation model

[36]

Kinetic/Diffusion rate model

[41]

Unreacted shrinking core model

[38–40]

Unreacted shrinking core model

[42]

2 k2) C0

k = A exp( E /RTp) 1

= VM (daf );

2

= 1.25

2 1

+ 0.92

A1 = 3.7e5s 1, E1 = 18000K A2 = 1.46e13s 1, E 2 = 30189K VM + O2

CO2 + H2 O

Char + O2

[i] vi

r1 = CA min( ) ; CA = 4.0 k

CO2

dmp dt

D R = Ap pox 0 k D0 + Rk [(Tp + T ) / 2]0.75 D0 = C1 dp

Rk = C2 e (E / RTp) C1 = 5e 12; C2 = 450

Coke +

r k1 +1 O +2 2

2 CO +2

+

+2

CO2

r ki =

( )

km =

ShD ds

1 viMi

Av i 1 1 + km kki

1

= 2500 exp( 6420/Tg ) kk1 = 0.685Ts exp( 9000/Ts) Coke + CO2

rk2

2CO

kk2 = 5.89 × 10 2Ts exp( 26800/Ts)

5

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Y. Zhuo and Y. Shen

the method in Ref. [47]. Another small stagnant zone with low porosity, the so-called bird-nest, is also assumed based on the Refs. [45,46]. 3.2. Material properties In the transient model, two fuels are considered. Coke is assumed as uniform in size and density. The pulverized coal size distribution is experimentally measured, and described using the Rosin-Rammler curve (Fig. 4) where the mean size of the coal particles is 76 um and the spread parameter is 3.5. The detailed simulation conditions and the material properties are listed in Table 4 and Table 5, respectively. 4. Results and discussion In this section, the typical in-furnace phenomena in terms of dynamic raceway evolution and coke/coal co-combustion will be illustrated and analysed. Further, on utilizing the integrated transient model, the effect of blast rate on the pulverized coal combustion and BF operation will be studied. 4.1. Model validation It is known that the measurements of thermochemical phenomena inside the furnace are extremely difficult. The model is first validated against the measurements of gas component distribution in a commercial BF [48], where a GQJ-2 raceway probing device was used to collect infurnace gas and coke samples [49]. Fig. 5 compares the simulations and measurements of the mass fraction distributions of the three gas components, O2, CO2 and CO, along the tuyere centre line. The simulation results show good agreement with the experimentally measured data from the furnace. The model was also applied to a laboratory-scale drop tube furnace and validated against the measurements in terms of gas velocity, temperature and oxygen concentration [50]. Fig. 6 compares the simulation results with the measurements in terms of gas velocity, temperature and O2 concentration. The simulation results also show good agreement with the experimentally measured laboratory data. 4.2. Typical in-furnace phenomena 4.2.1. Raceway evolution in terms of shape and size Fig. 7 provides snapshots of the raceway profile evolution in front and left views at different times. The raceway profile is characterized by an isosurface of the initial coke volume fraction, i.e., 0.51. It is apparent that as time progresses from 0 s to 7.0 s, the raceway size increases in depth, width and height; and the raceway volume increases accordingly. The raceway shape changes dynamically from a horizontally-extended balloon to a balloon with the front end extending upwards significantly. This is a typical raceway shape as observed in some lab-scale experiments and modelling but, for the first time, described here under full-scale BF conditions. This phenomenon is the collected result of the intense momentum exchange between gas and coke particles and the strong resistance from both the deadman of lower porosity, as well as the inclined blowpipe and tuyere. Further, Fig. 8 quantifies raceway boundary in terms of depth, width and height at different times. It is seen that all three dimensions increase as time goes from 1.0 s to 7.0 s, and the increase in width and height are more pronounced than the increase in depth. At around 7.0 s (Fig. 7(d)), the raceway profile is found to be relatively stable in terms of both shape and size under the present conditions (Table 4), where the raceway depth, width and height can reach 1.1 m, 0.45 m, and 0.76 m, respectively. For this reason, the below results will be predominantly discussed at time 7.0 s which is when the raceway profile stabilizes. Fig. 9 shows the gas streamlines with an obvious gas acceleration at the tuyere region, up to 280 m/s, arising from the tapering tuyere design, which improves the gas movement energy as it enters the coke bed. Additionally, gas recirculation can be seen downstream near the boundary region of the raceway. The model provides a cost-effective tool for understanding the

Fig. 2. Solution flow chart of the model.

simulation conditions applied in this model are listed in Table 4. Note that in this transient model, the initial computational domain is a coke particle packed bed, in which a dynamic raceway will be formulated which evolved dynamically when the high-speed blast is injected into the bed with time. This approach is different from previous steady-state PCI models [26,28], where a pre-set raceway was assumed. As a result, they cannot be used to study the interaction between blast rate and PCI operation. In addition, different from previous raceway and PCI models [26,28], here the detailed tuyere and lance configurations are defined in terms of their inclination and the insert depth, as shown in Fig. 3(b–d). For example, the co-axial lance is introduced into the blowpipe at an inclination angle of 5° with its tip at the centreline. Three gas streams (i.e. conveying gas, cooling gas and hot blast) are introduced into the tuyere and raceway region. Hot blast (air) is transported within the blowpipe, while pulverized particles and conveying gas (100% N2) are transported within the inner tube of the lance. The cooling gas (100% O2) is transported within the outer tube of the lance. The top of the domain is set as the flow outlet. The detailed model geometry including tuyere, lance, blowpipe, coke bed are shown in Fig. 3(b) and (d). For computational efficiency, the lower component relating to one tuyere is considered, as the in-furnace phenomena adjunct to each tuyere will be very similar; the geometry is regarded as a plane-symmetric; in the coke packed bed, a stagnant zone of low porosity near the furnace centre (termed deadman in BFs) is assumed using 6

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Fig. 3. BF geometries and dimensions: (a) Computational domain and main dimensions; (b) Detailed dimensions of blowpipe and tuyere; (c) Tuyere geometry configuration; (d) Detailed dimensions of coal lance (unit /mm). Table 3 Geometry of computational domain.

Diameter: Length:

Tuyere 160 mm 1450 mm

Cooling tube diameter: Coal inlet diameter:

12.7 mm 9.5 mm

Mass fraction >d, Yd

Blowpipe

Rosin-Rammler fit curve Experimentally measured data

1.0

Table 4 Simulation conditions applied in the model, including boundary conditions and initial conditions. Boundary conditions Blast rate O2 enrichment in blast Cooling gas (100% O2,) Conveying gas (100% N2) Coal Coal average diameter Spread parameter Cooling gas temperature Conveyer gas temperature Blast temperature Working volume Productivity Tuyere number Reference pressure Coke diameter Coke density Turbulent intensity of gas inlets Turbulent viscosity ratio of gas inlets Turbulent intensity of outlet Turbulent viscosity ratio of outlet Initial conditions Initial coke volume fraction Initial coke temperature Initial gas temperature

Spread number: 3.5 Average diameter: 76 µm

0.8

0.6

0.4

0.2

420,000 Nm3/h (including 99,540 Nm3/h O2, and 15 g/m3 H2O 15,000 Nm3/h 8800 Nm3/h 3000 Nm3/h 72 t/h 76 µm 3.5 600 K 318 K 1523 K 4706 2.23 tHM/m3 day 40 425 kPa 30 mm 1100 kg/m3 5% 10

0.0

0

20

40

60

80

100

120

140

160

180

Diameter, d (µm) Fig. 4. Rosin-Rammler curve fit for the coal particle size distribution. Table 5 Proximate and ultimate analyses of pulverized coal. Proximate analysis (air dry)

5% 10 0.51 2000 K 2000 K

7

Moisture, % VM Ash, % Fixed carbon, % Gross specific energy MJ/kg

2.1 17.4 7.2 73.3 30.1

Ultimate analysis (daf.) C, % H, % N, % S, % O, %

83.5 5.3 1.95 0.6 8.6

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0.40 0.35

1.0

1.02

1.05

1.07

at 1.0 s at 3.0 s at 5.0 s at 7.0 s

1.1

0.25

0.8

CO-Simulated CO 2-Simulated O 2-Simulated

0.20

/m

Mass fraction

0.30

CO-Exp. measured CO 2-Exp.measured

0.15

0.76

0.61

0.6

0.55 0.5 0.45

O 2-Exp.measured

0.4

0.4

0.10

0.3 0.25

0.2

0.05 0.00

0.0

0.5

1.0

1.5

2.0

2.5

0.0

3.0

Distance from lance tip /m

Velocity (m/s)

16

width

height

Raceway size

Fig. 5. Comparison between measured data and simulation results at t = 7.0 s [48].

12

depth

Fig. 8. Raceway evolution in terms of depth, width, and height at different times, from 1.0 s to 7.0 s.

Predicted Measured

8 4

1600 1200

O2 concentration /%

Temperature /°C

0

800 20 16 12 8 4 0 -0.4

-0.3

-0.2

-0.1

0.0

0.1

Distance to axis /m

0.2

0.3

0.4

Fig. 6. Model validation in terms of: gas velocity, temperature and O2 concentration against measurements in laboratory experiments.

Fig. 9. Flow pattern of gas in the BF at t = 7.0 s.

dynamic behaviour of the raceway and is useful for optimizing blast operation, for example, to identify the optimal blast rate, temperature and composition are as a scheme for balancing stable raceway evolution and high coal burnout. For instance, the effect of blast rate will be considered further in Section 4.3.

(a), t =1.0 s

4.2.2. Temperature and gas species distribution Fig. 10 shows the contours of gas temperature and gas species (CO, CO2 and O2) mass fractions in the raceway and the surrounding coke bed at time 7.0 s when the raceway stabilizes (Fig. 9). It can be seen in

(b), t =3.0 s

(c), t =5.0 s

Fig. 7. Snapshots of raceway evolution at different times, from 1.0 s to 7.0 s. 8

(d), t =7.0 s

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Fig. 10(a) that a low-temperature region is observed near the lance tip, where the low-temperature conveying gas and coal powders are introduced into the tuyere. Then, as coal combustion proceeds, a hightemperature region of up to 2700 K can be observed downstream along the tuyere centre line. At this point, the so-called front flame phenomenon is observed due to the strong VM combustion along the coal plume in the downstream of the raceway. After exiting the raceway and entering the coke bed, a relatively higher temperature is observed around the raceway cavity due to the strong combustion of local fine coal powder, which is referred to as the PCI influence zone (Fig. 10(a)). It is apparent that the gas temperature is largely dependent on the local supply of O2 and carbon. The in-furnace distributions of gas species are shown in Fig. 10(b)–(d). It is observed that, as coal powder is injected into the BF, it is heated up rapidly which drives the devolatilization reaction that produces combustible VM and residence char. They are then burnt with the high-temperature O2 in the raceway vicinity, generating a large amount of heat and CO2. It is shown that the CO2 concentration increases along with the coal plume after it enters the tuyere, approaching a maximum mass fraction value of 0.27 at the endpoint of the tuyere centreline in the raceway. Subsequently, after exiting the raceway, the generated CO2 will further react with the coke bed to produce the reducing gas, CO.

previous models [26,28,51] where the raceway is treated as a pre-defined cavity region with no internal coke movement and combustion, this model is capable of predicting the pulverized coal combustion in a dynamic raceway where coke particles are moving and burning at the same time. The coal burnout is defined according to the ash balance, which represents the mass loss resulting from devolatilization and char combustion [26], as follows:

Burnout = (1

ma,0 )/(1 ma

ma,0 )

(17)

Fig. 11(a) depicts a snapshot of coal particle trajectories coloured by burnout in the evolving raceway vicinity at times from1.0 s to 7.0 s. It is apparent that, as time progresses from 1.0 s to 7.0 s, the burnout becomes higher in a larger raceway. This is because the expanded raceway allows more coal particles to recirculate and reach a deeper location within the raceway, implying a longer residence time. At 7.0 s when the raceway profile stabilizes, the burnout is found to be higher in the downstream along the tuyere centreline compared to the upstream, and much higher in the recirculation region. The higher burnout is attributed to the longer particle travelling time, higher gas temperature and local O2 supply. Additionally, the coal burnout is quantified along the tuyere centreline over the timeframe of 1.0–7.0 s (Fig. 11(b)). It is found that as time moves from 1.0 s to 7.0 s, the coal burnout slightly increases in deeper regions of the raceway. In contrast, at 7.0 s when the raceway profile stabilizes, the burnout evolution can be divided into three phases based on its increasing rate: viz., initial heating-up phase (Phase I), fast-increase phase (Phase II), and levelling-off phase (Phase III). Within the initial phase, the burnout rises slowly; within the second

4.2.3. Coal combustion characteristics PCI operation is a key practice in the lower part of the BF, in addition to raceway evolution. To evaluate the combustion behaviour of the injected pulverized coal during BF operation, burnout is typically used to characterize the combustion efficiency [26]. Note that, unlike

Fig. 10. Phenomena inside the furnace: (a) Gas temperature; (b) O2 mass fraction; (c) CO2 mass fraction; and (d) CO mass fraction at t = 7.0 s. 9

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(a), t =1.0 s

(b), t =3.0 s

(c), t =5.0 s

(d), t =7.0 s

(a) Phase III

Phase II

Phase I

0.8

at 1.0 s at 3.0 s at 5.0 s at 7.0 s

0.7 0.6

Burnout

0.5 0.4 0.3 0.2 0.1 0.0

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Distance from lance tip /m

(b) Fig. 11. Raceway evolution and burnout profile in the raceway vicinity at the time from 1.0 s to 7.0 s: (a) Snapshot of raceway evolution and coal particle trajectories coloured by burnout; (b) Comparison of average burnout along the tuyere centreline. Phase I

Phase II

0.8 0.7

2500

0.6

2000

0.18 0.16 0.14 0.12

Burnout

0.5 1500

0.4

0.10 0.08

0.3

1000 0.06

0.2

0.04

0.1 0.0

phase (Phase I), the coal particles are heated up to 800 K, viz. reaching the devolatilization activation temperature; prior to this point, the VM within the coal is slightly decreased. Then, during Phase II, the particle temperature increases rapidly whereby the remaining VM content drops significantly due to strong devolatilization conditions and subsequent VM gas combustion, giving the fast burnout increase. In Phase III where the burnout stabilizes at around 0.65, VM combustion is almost complete, the particle temperature continues to increase, and only slow char combustion is dominant in this phase.

Phase III

Burnout Particle temperature (K) RVM

500 0.2

0.4

0.6

0.8

1.0

4.3. Effects of blast rate on raceway size and coal combustion

0.02

During real BF operation, blast rate is an important operating parameter to adjust the BF performance including raceway shape/size and coal/coke combustion in the dynamic raceway. Unfortunately, this has previously been challenging to study due to the fact that earlier models were not in a transient state and did not link the dynamics of raceway evolution with the thermochemical phenomena related to coal and coke combustion inside the raceway. In this section, using the integrated model, three cases with different blast rates, 140 m/s, 160 m/ s, and 180 m/s, are investigated to define the effect of blast rate on raceway shape and size evolution, gas component distribution, and coal burnout when other simulation conditions are fixed at their base values. The simulation cases with different blast rate are listed in Table 6 where, apart from the blast rate, other boundary conditions are fixed for comparison. Table 7 compares the simulation results for raceway profile and coal combustion characteristics under various blast rates conditions. Table 7(a) and (b) detail the simulated boundary profiles of the raceway under different blast rates at the time 7.0 s. It can be seen that, as blast rate increases, the raceway expands in size in terms of depth, width, and height. Specifically, Fig. 13 provides a quantitative

0.00

Distance from lance tip /m

Fig. 12. Coal combustion characteristics along the tuyere centreline in the raceway at t = 7.0 s. Table 6 Simulation cases with different blast rates. Blast rate (velocity) Case 1 Case 2 Case 3 (base case)

140 m/s 160 m/s 180 m/s

phase, the burnout increases rapidly to 0.65; and within the third phase, the burnout levels off at 0.65. In addition, other combustion characteristics, including the evolution of particle temperature and remaining VM content of coal, at 7.0 s are plotted and discussed so as to understand the reasons for the three phases (Fig. 12). During the initial 10

11

Blast rate

180 m/s

160 m/s

140 m/s

(a)

(b)

(c)

(d)

(e)

(f)

Table 7 Effect of blast rate on key in-furnace phenomena related to raceway and PCI operation at t = 7.0 s under different blast rates: (a) Raceway shape in side view; (b) Raceway shape in front view; (c) Coal particles coloured by burnout; (d) O2 mass fraction distribution (e) CO2 mass fraction distribution; and (f) CO mass fraction distribution.

Y. Zhuo and Y. Shen

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1.1

1.0

0.9 0.93

0.76

0.8

/m

higher burnout when the raceway is expanded by the increasing blast rate. The larger recirculation region affords the coal particles a longer travel time and the enriched O2 presence also contributes to coal combustion. Table 7(d–f) compares the mass fraction contours of O2, CO2 and CO, respectively, in the lower region of the BF. With increasing blast rate, the mass fraction contours of O2, CO2 and CO are largely similar in the coke bed due to excessive local coke although there are slight differences in the form of higher O2 and lower CO2 concentrations along the coal plume inside the raceway (downstream) when a larger blast rate is employed. This arises from the increased blast rate allowing for more O2 to enter the raceway which dilutes the generated CO2 and CO in this region. Alternately, the larger raceway facilitates greater O2 flow deeper into the coke bed, resulting in more CO2 and CO generated outside the raceway vicinity. Fig. 14(a) compares the gas species profiles along the tuyere centreline under different blast rates at time 7.0 s. Overall, their profiles are largely similar. O2 is rapidly converted to CO2 inside the raceway due to strong coal and coke combustion. The CO2 is then converted to CO after entering the coke bed due to strong coke gasification as excessive coke and less O2 is available. There also exist some slight differences in the profiles, namely, as the blast rate increases, more O2 travels into the deeper regions of the coke bed, which manifests itself as a deeper O2 depletion location or delayed O2 depletion. As a result, inside the raceway, the peak value of the CO2 mass fraction occurs further along the tuyere centre line with a higher value. Similarly, a lower blast rate during the initial stage gives a higher CO mass fraction, with the trend reversed in deeper locations within the coke bed. This is due to the amount of CO being determined by the extent of coke gasification. As more CO2 is generated when the blast rate increases, coke

blast rate 140m/s blast rate160m/s blast rate180m/s

0.6

0.45 0.4

0.45

0.32

0.3

0.23

0.2

0.0

depth

width

height

Fig. 13. Quantitative comparison of raceway size in terms of depth, width and height under different blast rates at t = 7.0 s.

comparison of the raceway’s size as the blast rate increases. It is apparent that when the blast rate increases from 140 m/s to 180 m/s, the raceway expands whereby its depth extends from 0.9 m to 0.11 m, width extends from 0.23 m to 0.45 m, and height extends from 0.3 m to 0.76 m. The extent to which the raceway expands in terms of width and height is more significant than that in its depth. Table 7(c) shows the coal particle trajectories coloured by burnout in the evolving raceway region at three different blast rates. It can be seen that, along with the coal plume, more coal particles travel deeper into the raceway with

Mass fraction

0.4

0.3 CO-blast rate 140m/s CO2-blast rate 140m/s O2-blast rate 140m/s CO-blast rate 160m/s CO2-blast rate 160m/s O2-blast rate 160m/s CO-blast rate 180m/s CO2-blast rate 180m/s O2-blast rate 180m/s

0.2

0.1

0.0

Average particle temperature /K

1.2

blast rate 140m/s blast rate 160m/s blast rate 180m/s

2500

2000

1500

1000

500 0.0

0.5

1.0

1.5

2.0

2.5

0.0

0.1

0.2

Distance from lance tip /m

0.3

0.4

(a)

0.6

0.7

0.8

0.9

1.0

(b)

0.20

blast rate 140m/s blast rate 160m/s blast rate 180m/s

0.18 0.16

blast rate 140m/s blast rate 160m/s blast rate 180m/s

0.7 0.6

0.14

0.5

0.12

Burnout

Volatile matter mass fraction of coal particle

0.5

Distance from lance tip /m

0.10 0.08 0.06

0.4 0.3 0.2

0.04 0.1

0.02 0.00

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0.0

1.0

Distance from lance tip /m

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Distance from lance tip /m

(c)

(d)

Fig. 14. Comparison of key in-furnace phenomena along the tuyere centreline at t = 7.0 s: (a) gas component distributions; (b) average particle temperature; (c) VM mass fraction; (d) average burnout. 12

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gasification is intense within the coke bed. Note that CO, as the reducing gas, strongly affects BF efficiency. A higher CO mass fraction means a higher reduction efficiency. Overall, increasing blast rate can improve BF operation. Fig. 14(b) describes the average particle temperature along the tuyere centreline under different blast rates. It can be seen that before 0.7 m, a lower blast rate leads to a higher particle temperature. Beyond 0.7 m the trend is reversed. The higher particle temperature is induced by the longer upstream travelling time when the blast rate is low. In contrast, on increasing the blast rate, the larger raceway and intense recirculation phenomenon extend the particle travel time which contributes to heat transfer between the gas phase and discrete particle phase. Consequently, the coal particles reach a higher temperature at a deeper point within the raceway. Fig. 14(c) shows the average remaining VM content in the coal along the tuyere centreline under different blast rates. The devolatilization process is driven by the coal particle temperature. A higher particle temperature accelerates the devolatilization reaction rate. It can be seen that before 0.7 m the devolatilization process has finished even under the highest blast rate. This indicates that, before approaching the raceway boundary, all the VM within the coal particles has been converted into combustible VM gases. Fig. 14(d) shows the average burnout of coal particles along the tuyere centreline under different blast rates. The processes of devolatilization and char combustion account for the mass loss after the coal has been injected into the BF. Similar to the coal particle temperature evolution, a lower blast rate leads to a higher burnout before 0.7 m due to the faster devolatilization reaction. The increased blast rate facilitates coal combustion as there is a greater O2 presence and longer particle travel time in the deeper regions of the raceway. The higher blast rate ultimately improves coal combustion and subsequently improves the production of reducing gas CO as well (Fig. 14(a)). Overall, the simulation results demonstrate that, to improve BF performance it is necessary to increase the blast rate. A higher blast rate expands the raceway volume and increases pulverized coal combustion efficiency, whereby more reducing gas, i.e., CO, is generated due to the stronger coke gasification reaction. On applying this model, the impact of blast conditions on pulverized coal combustion in the BF can be comprehensively evaluated and quantified. This enables the effective utilization of coal and coke in the BF and provides the optimized operating condition for enhanced BF performance.

lower part is also examined. The dynamic raceway profile strongly depends on the blast operating conditions. As the blast rate increases, the raceway expands in terms of depth, width and height. The larger raceway and accompanying greater O2 presence benefit pulverized coal combustion in the lower part of the blast furnace. A higher blast rate facilitates greater CO generation in the coke bed, which can improve blast furnace efficiency. Quantitatively, under the simulated conditions, when the blast rate is increased from 140 m/s to 180 m/s, a larger raceway formed where its depth increases by 22.2%. Consequently, the average burnout of the pulverized coal improves by 3.6% and the reducing gas, CO, increases by 1%. The findings indicate blast furnace performance in terms of energy-saving and blast furnace stability can be improved by increasing the blast rate. The developed transient three-dimensional model is a cost-effective tool which enables dynamic evaluation of the impact of blast conditions on pulverized coal combustion and blast furnace performance for energy-and cost-saving benefits. CRediT authorship contribution statement Yuting Zhuo: Conceptualization, Methodology, Software, Validation, Writing - original draft, Data curation, Visualization, Investigation, Formal analysis. Yansong Shen: Conceptualization, Supervision, Writing - review & editing, Project administration, Funding acquisition, Resources, Visualization. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements The authors thank the Australian Research Council (LP150100112, FT190100361) and Baosteel for the financial support of this project, and Baosteel for the useful discussion. References

5. Conclusions

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A three-dimensional transient model has been developed to describe the co-combustion of pulverized coal and coke in connection with dynamic raceway evolution under industrial-scale blast furnace conditions. The model couples two combustion submodels of two very different fuels in a two-way manner viz. a gas-coke combustion model (or a raceway evolution model) and a gas-coal combustion model. The integrated model is used to simulate the in-furnace phenomena inside the lower part of an industrial-scale blast furnace. The model allowed for dynamic raceway evolution, pulverized coal combustion characteristics, and coke-related reactions to be evaluated under different operating conditions. The model is also validated against the experimental measurements. Major conclusions drawn from the study are:

• Typical phenomena inside the furnace such as raceway shape and

•

size, flow pattern, temperature and gas component distributions, and the pulverized coal combustion characteristics can be evaluated. As time progresses from 0 s to 7.0 s, the raceway size increases in depth, width and height; and the coal burnout slightly increases in the deeper regions of the raceway. By approximately 7.0 s, the raceway profile and coal/coke combustion have become relatively stable. The effect of the blast rate on the performance of the blast furnace’s 13

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