Large eddy simulation of non-premixed pulverized coal combustion in corner-fired furnace for various excess air ratios

Applied Mathematical Modelling 74 (2019) 694–707

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Applied Mathematical Modelling journal homepage: www.elsevier.com/locate/apm

Large eddy simulation of non-premixed pulverized coal combustion in corner-fired furnace for various excess air ratios Wenjing Sun a,b, Wenqi Zhong a,∗, Tarek Echekki b a

Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Sipailou 2#, Nanjing 210096, Jiangsu, P.R. China b Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, USA

a r t i c l e

i n f o

Article history: Received 16 January 2019 Revised 4 May 2019 Accepted 15 May 2019 Available online 20 May 2019 Keywords: Pulverized-coal combustion Excess air NOx emissions Corner-fired furnace

a b s t r a c t Large-eddy simulations (LES) were carried out to study the effects of burning atmosphere on the coal combustion process in a corner-fired furnace. The LES for the turbulent gas was coupled with the discrete phase model (DPM) for coal particles trajectories and the non-premixed mixture fraction probability density function (MF-PDF) combustion model for pulverized coal combustion. The coal combustion processes, including the flame characteristics, burning coal behaviors and NOx pollutant emissions, for different burning atmospheres are analyzed qualitatively and quantitatively. The heat and momentum transfer between burning coal and turbulent gas are greatly enhanced by the corner-fired flow. With a given particle size, the char particles present a similar distribution in the whole chamber. For a fuel-rich atmosphere, the concentration is obviously much higher and exhibits much higher spatial variability than the other two conditions. The coal combustion efficiency decreases in oxygen-rich and fuel-rich burning atmospheres, but the flame stability is more affected at the fuel-rich atmosphere by the lack of oxygen. NO pollutant is obviously reduced at the fuel-rich atmospheres, and the NO pollutant emissions are more affected by the reducing atmosphere than the low temperature. These findings may provide insight into strategies to design and monitor tangentially-fired pulverized coal boilers. © 2019 Elsevier Inc. All rights reserved.

1. Introduction Pulverized coal fired furnace are widely applied to provide low-cost power in Asian power plants [1]. However, coal combustion generates a disproportionate amount of pollutants, including NOx , mercury, sulfur dioxides and particulate matter. Measures to reduce NOx emissions include the lowering of the combustion temperatures and the use of a reducing atmosphere during pulverized coal combustion. The impinging rotational flow caused by such corner-fired coal jets increases the heat and mass transfer between the coal particles and turbulent gas [2]. For decades, numerous simulations of these coal boilers have been performed to predict coal combustion and NOx emissions [2–7]. Zhang et al. [3] investigated the HBC in a 200 MWe tangentially-fired pulverized coal boiler with emphasis on NOx emissions. Choi and Kim [4] studied the flow, coal combustion and NOx emission affected by over-fire air (OFA) in

∗

Corresponding author. E-mail address: [email protected] (W. Zhong).

https://doi.org/10.1016/j.apm.2019.05.017 0307-904X/© 2019 Elsevier Inc. All rights reserved.

W. Sun, W. Zhong and T. Echekki / Applied Mathematical Modelling 74 (2019) 694–707

Nomenclature As a Ak C Cdiff Cs d ds D0 Din f fW,0 g G Gw hfg hgs Hg ksgs Ls ms Mgn n p pOX Prt qr qr,w R R1 , R2 Rk Sm SV SH Tg Ts Tw ug us V Ygn

surface area of particle; m2 absorption coefficient; dimensionless arrhenius coefficient for char combustion; dimensionless linear-anisotropic coefficient; dimensionless diffusivity constant for char combustion; dimensionless smagorinsky constant; dimensionless distance to the closest wall; m diameter of pulverized coal; μm diffusion rate coefficient; dimensionless inner-diameter of injector; m mixture fraction; dimensionless initial moisture mass fraction; dimensionless gravity constant; m/s2 incident radiation; J/(m2 s) incident radiation at the wall; J/(m2 s) latent heat of vaporization; J/kg heat transfer coefficient between gas and solid; W/(m2 K) enthalpy of gas-phase; J subgrid-scale kinetic energy; J subgrid length scale; m solid mass; kg molar mass of species n; dimensionless refractive index of the medium; dimensionless pressure; Pa partial pressure of oxidizer around the particle during combustion; Pa turbulent Prandtl number (Prt = 0.72); dimensionless radiative flux, J/kg radiative flux at the boundary wall, J/kg universal gas constant (R = 8.314); J/(mol K) devolatilization rates of the two competing steps kinetic reaction rate; dimensionless source term of mass transfer source term of momentum transfer source term of energy transfer temperature of gas-phase; K temperature of pulverized coal; K temperature of boundary wall; K gas velocity; m/s particle velocity; m/s gird cell volume; m3 mass fraction of species n; dimensionless

Greek letters α excess air ratio; dimensionless β gs drag coefficient; dimensionless  local grid scale; m f filter size; m εs particle emissivity; dimensionless εw wall emissivity; dimensionless θR radiation temperature; K κ von Kármán constant; dimensionless ksgs subgrid-scale kinetic energy; J λg thermal conductivity of gas-phase; W/(m K) μg gas dynamic viscosity; Kg/(m s) μgt subgrid dynamic viscosity of the gas; Kg/(m s) ν gas kinematic viscosity; m2 /s ρg gas density; kg/m3

695

696

σ σs σt τg τ gt τr

s Subscripts s g sgs i, j and k

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stefan–Boltzmann constant (σ = 5.67 × 10−8 ); W/(m2 K4 ) scattering coefficient, dimensionless constant number (σ t = 0.85), dimensionless stress tensor of gas-phase; dimensionless subgrid stress tensor of gas-phase; dimensionless pulverized coal particle relaxation time; s pulverized coal mass flux; dimensionless coal particle gas subgrid general index

a 500 MWe tangentially-fired pulverized coal boiler to understand the mechanism of NOx formation by thermal and fuel effects. Similarly, Yin et al. [5] investigated NOx formation influenced by the gas flow deviation and non-uniform wall temperatures in the crossover pass in a 609 MWe tangentially-fired pulverized coal boiler. Zhou et al. [6] studied the effects of a multi-group arrangement of the separated over-fire air on the performance of a 10 0 0 MWe tangentially-fired pulverized coal boiler to reduce NOx emissions. Guo et al. [7] simulated a 200 MWe tangentially fired boiler to investigate a compatible configuration strategy for burner streams. Chen et al. [8] studied the different tangential arrangements of burners in a 600 MWe tangentially fired boiler. In the bulk of these studies, the Reynolds-averaged Navier–Stokes (RANS) approach has been the most common approach to predict the macroscopic coal combustion process under different operation conditions. However, the coal combustion flame characteristics are greatly influenced by the unsteady pulverized coal motion and the turbulent gas-phase behaviors, which cannot be predicted by the RANS simulations. Based on the suitability of LES to investigate the micro- and meso-scale flow behaviors of turbulent two-phase flow, the combustion mechanism of pulverized coal flame has been studied in recent years [9–17]. The Japanese Central Research Institute of Electric Power Industry (CRIEPI) applied LES on the pulverized coal jet flame [9–11]. In these papers, Kurose et al. [9,10] focused on the interactions between the dispersion, evaporation and combustion of coal particles in a turbulent jet flame. Muto et al. [11] studied the effects of oxygen concentration on NOx formation in a pulverized coal jet flame by using LES. Wen et al. [12,13] simulated the pulverized coal combustion by using a velocity-scalar joint filtered density function model in the LES framework. Pedel et al. [14] solved a pulverized coal jet flame ignited by a preheated gas flow by using LES coupled with direct quadrature method of moments. The simulation results for different inlet stoichiometric ratios are compared qualitatively and quantitatively to the experimental observations captured by Franchetti et al. [15]. Rieth et al. [16] investigated the coal combustion with detailed devolatilization by a flamelet LES model. There are, of course, inherent differences between simple canonical flame configurations and applications that closely resemble the practical applications, including complexities in flow features and the presence of more complex mixing scenarios and boundary conditions. A few studies adapted LES to relatively more complex laboratory-scale flow configurations [18–20]. For example, Franchetti et al. [18] investigated oxy-coal combustion in a swirling test facility in a LES framework, and they showed the potential of LES to solve more complex combustion processes and paved the way for industrial applications. Wen et al. [19] established a gas-coal cross-flow to investigate the turbulent pulverized coal combustion characteristics in a tangentially-fired furnace by employing LES model. Adamczyk et al. [20] simulated the air-staging process of an industrial scale pulverized coal boiler by using an LES-CFD tool. A turbulent corner-injected impinging flow was established to represent the flow regime of the pulverized coal tangentially-fired furnace in our previous work [21]. Hence, LES is implemented to investigate the pulverized coal combustion process in such a laboratory-scale corner-fired flow. As is known, the applied horizontal bias combustion (HBC) is an effective low NOx technique in a coal-fired furnace. And its low NOx combustion mechanism is to make the pulverized coal burn at oxygen-rich and fuel-rich atmospheres. Hence, the oxygen-rich and fuel-rich combustion atmospheres are set to compare the coal combustion process and NOx formation in this study. To be specific, the corner-fired coal combustion processes are analyzed at a given standard stoichiometric ratio. Based on the analysis, the influences of the combustion atmosphere on the burning coal particle behaviors, the turbulent flame characteristics and the NOx pollutant emissions are systematically discussed. 2. Numerical modeling 2.1. Gas-phase governing equations The simulations are performed based on ANSYS 18.0. The implemented turbulent coal combustion model is the coupling of the LES and the non-premixed mixture fraction-PDF (MF-PDF) combustion model under a non-adiabatic extension. The equilibrium chemistry for coal combustion is controlled by the functions of the mixture species mass fractions. The gasphase governing equations for mass, momentum, energy and mixture fractions are filtered by the Favre method, as well as

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the ideal gas equations.

Mass equations

 ∂ ρg ∂  + ρg u˜g, j = Sm , ∂t ∂xj

Momentum equations

Energy equations

(1)

  ∂ ∂  ∂ p¯ ∂ τg ∂   ρ u˜ + ρ u˜ u˜ = − + + ρ u˜ u˜ − ∂ t g g,i ∂ x j g g,i g, j ∂ xi ∂ x j ∂ x j g g,i g, j    u + ρg gi − βgs u˜g,i − us,i + SV,i , g,i ug, j

 ∂   ∂   =− ∂ ρH + ρ u˜ H ∂t g g ∂ x j g g, j g ∂xj  

 λg +

 g ∂ T g μgt H P rt Tg ∂ x j

+ hgs T g − Ts + SH ,

Mixture fraction equations

Ideal gas equation

1

ρg

=

(2)

(3)

   ∂  ˜ ∂  ∂ μgt ∂ f˜ ρg f + ρg u˜g, j f˜ = − + Sm , ∂t ∂xj ∂ x j σt ∂ x j

N RT g Y gn , Mgn p¯

(4)

(5)

n=1

In these equations, Sm , SV and SH represent the source terms for the gas mass density, the momentum compo Ng nents and the energy, and these spatially filtered source terms are calculated as Sm = n=1 Sgn , SV,i = u˜g,i · Sm and SH = Hg · Sm , respectively. In the momentum equations, the spatially filtered stress tensor of gas, τg , is computed as τg =

μg (

∂ u˜g,i ∂ u˜g, j 2 ∂ u˜g,k ∂ x j + ∂ xi − 3 ∂ xk δi j ), where

μg is the filtered dynamic viscosity of gas. The subgrid stress tensor of gas, τgt = ∂ u˜

∂ u˜

∂ u˜

g,i g, j g,k 2 ρg (u˜g,i u˜g, j − u g,i ug, j ), is modeled as μgt ( ∂ x + ∂ x − 3 ∂ x δi j ) where μgt is the gas subgrid dynamic viscosity. The term j i k βgs (u˜g,i − us,i ) in the momentum equations represents the gas–solid interaction force, where β gs is the drag coefficient be-

tween gas and coal/char particles [22]. In the energy equation,

μgt Hg P rt Tg

is used to evaluate the subgrid thermal conductivity of

the gas-phase. The energy transfer from gas to pulverized coal is modeled as hgs (Tg − Ts ), where hgs is the heat transfer coefficient between gas and coal/char particles [22]. The mass-weighted mixing law is used to determine the density, viscosity and absorption coefficient of the gas phase mixture [23]. The dynamic subgrid scale kinetic energy model [24] is used to model μgt as follows:

μgt = ck ρg k1sgs/2 .

(6)

In this equation, the kinetic energy is defined as ksgs = port equation:

1  2 (ug,i ug, j

− u˜g,i u˜g, j ), which is modeled with the following trans-

 /2 k3sgs ∂ u˜g,i ∂ ∂ ∂ μgt ∂ ksgs − c ε ρg + , (ρg ksgs ) + u˜g, j (ρg ksgs ) = −τgt ∂t ∂xj ∂xj f ∂ x j σk ∂ x j

(7)

In the above Eqs. (6) and (7), the model coefficient, ck and cε , are determined dynamically. σ k is set to 1.0 and f is the filter-size computed form f ≡ V1/3 , where V is the grid cell volume. To construct the filtered species mass fractions, a presumed β -PDF shape is used based on the transported filtered mix ture fraction and its subgrid scale variance,  f 2 . In the present formulation, this subgrid scale variance is modeled as follows [25]:





2  f  2 = Cvar L2s ∇ f˜ .

(8)

Here the constant Cvar is computed dynamically from the dynamic stress model and the subgrid length scale, Ls , is computed using Ls = min(k d, Cs ). Here, k is the von Kármán constant, d is the distance to the closest wall, Cs is the Smagorinsky constant and  is the local grid scale. 2.2. Solid-phase governing equations The governing equations for pulverized coal particles are established in a Lagrangian framework. The discrete phase model (DPM) is employed to predict the trajectory of the dispersed coal particles. Only the gravity and the Stokes force are considered for particles motion, and the equation can be written as:

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W. Sun, W. Zhong and T. Echekki / Applied Mathematical Modelling 74 (2019) 694–707 Table 1 The main combustion reactions of char and volatiles. C< s > + O2 = CO2 C< s > + 0.5O2 = CO C< s > + CO2 = 2CO C< s > + H 2 O = O2 + H 2 CH4 + 2O2 = CO2 +2 H2 O CO+ 0.5O2 = CO2 H2 + 0.5O2 = H2 O

Heterogeneous reaction

Homogeneous reaction

 u dusi gi − usi = + gi , dt τr

(9)

The two-competing-rates model is used to predict the devolatilization of coal particles [26],

mV (t ) = (1 − fW,0 )ma



 

t

(α1 R1 + α2 R2 ) exp −

0

t 0



(R1 + R2 )dt  dt,

(10)

where R1 = A1 e−(E1 /RTs ) , R2 = A2 e−(E2 /RTs ) . The kinetics/diffusion surface reaction rate model is selected to solve the coal combustion [27,28],

d ms D0 Rk = −As pOX , dt D0 + Rk

(11)

where the diffusion coefficient rate, D0 , is calculated using D0 = Cdi f f

0.75 [ (Ts +T g )/2] , ds

and the kinetic reaction rate, Rk , is ex-

pressed as Rk = Ak e−(E/RTs ) . The convective heat transfer and the absorption/emission of radiation at the particle surface is calculated as:

ms cs

    dTs d ms = hgs As T g − Ts + h f g + As εs σ θR4 − Ts4 , dt dt

(12)

2.3. Radiation model The P-1 radiation model is applied to solve the gray radiation heat transfer because of the low CPU demand [29,30], and its radiation flux, qr , is written as

qr =

1 ∇ G, 3 ( a + σs ) − C σs

(13)

where a is the absorption coefficient, and it is specified by the weighted-sum-of gray-gases model (WSGGM). σ s is the scattering coefficient, G is the incident radiation, and C is the linear-anisotropic coefficient. The interaction of particles with radiation field is considered in this P-1 model, and the governing equation is



σT4 −∇ · qr = −4π an + E p + (a + a p )G, π 2

(14)

Furthermore, the boundary wall radiative heat flux, qr,w , is computed as follows:

qr,w =

εw



2 ( 2 − εw )



4n2 σ Tw4 − Gw ,

(15)

where ε w is the wall emissivity. 2.4. Coal combustion model The non-premixed model is applied to solve the combustion of coal particles. The volatiles and the char are defined as two different types of fuel by two mixture fractions [31]. The char component is considered as C< s > , and the volatiles consist of CH4 , CO, H2 , and H2 S. The flue gas species include CH4 , CO, CO2 , H2 , OH, H2 O, O2 , N2 , SO2 , SO3 , H2 S, CS and CS2 . The composition of these species is based on the ultimate analysis of the coal and by balancing the heat release of the mixture with the heating value of the coal. The default combustion reaction scheme of gases (ignoring sulfur reaction) is shown in Table 1. 2.5. NOx formation model The NOx concentration is predicted by solving the transport equations for nitrogen compounds (NO/HCN/NH3 ) concentration, which based on a given temperature field and combustion solutions. Hence, the NOx is seen as a post-processing

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Fig. 1. A sketch of cross-section in corner-fired furnace, the structured grids in the nozzle inlet, cross-section and vertical-section.

step in this simulation. Thermal NOx and fuel NOx are considered as two main sources, while the prompt NOx is too small to be neglected in this model. Thermal NOx is generated by oxygen and nitrogen in the combustion air at a relatively high temperature environment [32]. On the bias of the Zel’dovich mechanism, three highly temperature-dependent chemical reactions governing the formation of thermal NOx are as follows: O + N2 ⇔N + NO, N + O2 ⇔O + NO, N + OH⇔H + NO. The partial equilibrium approach is considered to estimate the O-atom concentration. The fuel NOx is formed by the oxidization of nitrogen from pulverized coal in the excess air atmosphere. For coal combustion, the fuel nitrogen comes from the volatile components and fixed carbon, and the ratio is assumed as 7:3 in this injected Shenhua bituminous coal. During the fuel NOx formation, two main intermediate species, HCN and NH3 , are generated. And only HCN is produced by char-N (nitrogen in char), while an HCN/NH3 partition ratio of 9:1 is given to volatile-N (nitrogen in volatiles). 3. Simulation parameters and conditions 3.1. Computational domain A laboratory-scale corner-fired furnace is established to investigate the pulverized coal combustion. The horizontal cross section of the reaction chamber is 200 mm (about 20 Din ) in both width and depth, and the height is also given as 300 mm. A sketch of the cross-section of this corner-fired furnace is shown in Fig. 1. The coal particles are introduced into the reaction chamber by reheated air from four round nozzles (Din = 10 mm). In order to describe turbulent flow behaviors clearly, the whole corner-fired flow was divided into four areas, near-nozzle area, impinging area, central area and near-wall area. Simulation data was extracted from the cross-section along four lines to describe the turbulent flow quantitatively. Line A runs through the near-wall area and the near-nozzle area. Line B is close to the lateral-edge of the combustion flame. Line C is selected to show the flame characteristics in the impinging areas. Line D is the centerline, crossing the near-wall area, impinging area and central area. A total of 12 M hexahedron structured cells are created, with very fine grids ( ≈ 0.5 mm) in combustion area and coarse grids ( ≈ 2 mm) in outflow boundaries. The structured grids in the nozzle inlet, cross-section and vertical-section are shown in Fig. 1. 3.2. Computational settings In the BMCR working conditions of Datang Nanjing Power Plant, the excess air ratio, α , is about 1.2. The initial gas velocity is given as 10 m/s based on the better flow field observation in our pervious experiment. Hence, the coal mass flux is set as 0.0 0 012 kg/s for the standard conditions (α = 1.2). The coal mass fluxes for the oxygen-rich and fuel-rich are given as 0.0 0 0 06 (α = 2.4) and 0.0 0 024 (α = 0.6) kg/s. The burning coal in this study is the Shenhua bituminous coal. The parameters for this coal based on proximate and ultimate analysis and the run conditions are listed in Table 2. The initial gas and particle temperatures are both set as 368 K. The temperature of the wall boundary is set as 573 K, and the internal emissivity is 0.85 for the gray radiation. The ignition process is carried out by setting a high temperature at the combustion area by using UDFs. The simulations are performed on a calculation platform with 32 processors; and each case takes 20 days (approximately 15,360 CPU hours) for 10 0,0 0 0 0 flow steps (or a total integration time of approximately 10 s).

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W. Sun, W. Zhong and T. Echekki / Applied Mathematical Modelling 74 (2019) 694–707 Table 2 Main parameters. Simulation conditions Pulverized coal mass flux ( s ) Initial gas velocity (ug0 ) Excess air ratio (α )

kg/s m/s –

Oxygen-rich

Standard

Fuel-rich

0.0 0 0 06 10 2.4

0.0 0 012 10 1.2

0.0 0 024 10 0.6

Numerical setting parameters Particle size (ds ) Initial gas temperature (Tg0 ) Diameter of nozzles (Din ) Number of the grids Flow time step (tg ) Particle time step (ts ) Number of simulation step Boundary conditons Inlet Outlet Walls

μm K mm – s s – Gas Velocity inlet Outflow Tw = 573 K ε w = 0.85

10 573 10 12 million 0.0 0 0 01 0.0 0 0 01 10 × 104 Particles Mass flow rate inlet Escape Reflect

Proximate & ultimate analysis of pulverized coal Proximate analysis (%, ar)

Elementary analysis (%, ar)

LHV (ar)

Ash Volatile Fixed carbon Moisture C H O N S Qar,net (KJ/kg)

29.55 22.16 40.29 8 51.92 3.53 5.04 1.1 0.86 20,258

3.3. Model validation Fig. 2(a) and (b) compare time-averaged gas velocity contours based on the LES and experimental results, respectively, along a cross-section of the furnace. The experimental measurements are based on particle image velocimetry of the same furnace configuration [21]. The comparison is carried out to demonstrate the LES formulation capability to predict the flow in this multiple impinging jet configuration and to illustrate how well the model elements for momentum closure and the implementation of boundary conditions are able to predict the flow. The contours exhibit strong similarities between the computed and measured velocity contours. The maximum velocity is located in the near-nozzle area, while an impinging circle is formed by the four adjacent jets. The corresponding averaged velocity ratios (u/u0 ) along Lines C and D are compared in Fig. 3(c) and (d), respectively. Although some differences can be seen in the profiles, the trends are well-captured by the simulations, including the presence of peaks and their locations and the magnitudes of the velocities. Note that some of the differences may be attributed to limitations in the experimental measurements near physical boundaries. Nonetheless, the simulations capture the flow characteristics inside the furnace.

4. Numerical results and discussions 4.1. General flame characteristics The instantaneous temperature of flame and particles for the standard combustion condition are shown in Fig. 3(a) and (b), and the time-averaged temperature of burning coal and flame along four lines are compared in Fig. 3(c)–(f). The highest temperature appears around the coherent gas vortices along the impinging circle, where the char particles are burning rapidly and are completely mixed with air. The solid lines and the dashed lines represent the gas and particle, respectively. When the particle temperature is greater than the gas temperature, the energy is transferred from the burning char particles to the surrounding gas. In near-nozzle area, the particle temperature increases sharply so that the endothermic devolatilization process happens instantly. The temperature of the particles changes more rapidly than that of gas in the impinging area because of the rapid exothermic and endothermic chemical reactions occurring at and near the particle surface. The energy is then transferred between pulverized coal and air in the chamber. Moreover, the burning particles are at a greater temperature than the surrounding gas in most other areas during the whole coal combustion process.

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Fig. 2. (a) The time-averaged gas velocity in calculation results, (b) the averaged velocity vector in previous experiment [21] and (c, d) the comparison of averaged velocity ratio (u/u0 ) for numerical and experimental results along Line C and D.

The mean flame temperature distribution of cross-section along calculation time is shown in Fig. 4(a). The red line represents the coal combustion in standard combustion conditions, while the black and blue represent the coal combustion at oxygen-rich and fuel-rich atmospheres, respectively. It is easy to find that the continuously injected pulverized coal can react with enough oxygen, so that the steady flame occurs at t = 2.5 s. However, the combustion flame when α =0.6 would die due to the lack of oxygen, and the flame temperature for α =2.4 is decreasing gradually because of the continuously injected coal air. The pulverized coal combustion at dense/dilute areas only happens at the beginning of the coal combustion in industrial HBC furnace. Hence, we discussed the coal combustion and NOx formation from t = 1.5 to t = 2.5 s. The temperature contours of cross-section at different reaction times (t = 1.5 s, 2.0 s and 2.5 s) for three different combustion atmospheres are compared in Fig. 4(b). For all conditions, and as expected, the highest flame temperature occurs at the lateral- and insideedge of the combustion flame. More burning particles accumulate in the impinging area for fuel-rich atmosphere due to the dense particle concentration. As time evolves, there is a decay in the flame temperature as the fuel is burning. For fuel-rich atmosphere, the flame temperature reaches peak values at t = 1.5 s and, then, decay sharply afterwards and the flame subsequently is extinguished as shown in the temperature contours at 2.5 s. Hence, the combustion stability is more affected by the fuel-rich atmosphere. 4.2. Burning coal behaviors The coal combustion process in the furnace is highly influenced by the pulverized coal particles’ distribution. Fig. 5 compares the pulverized particle concentration in different areas on the same horizontal cross-section. For all coal combustion conditions, the particle concentrations exhibit similar spatial distributions along the entire cross-section. The concentration reaches its peak value in near-nozzle area, exhibits strong spatial variability in the impinging area and reaches a minimum in near-wall area. For a fuel-rich atmosphere, the concentration is obviously much higher and exhibits much higher spatial variability than for the other two conditions. For oxygen-rich atmosphere and standard atmosphere, the char concentration

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Fig. 3. (a) The instantaneous flame temperature, (b) the instantaneous particle temperature and (c–f) the averaged-temperature distribution of dispersedparticles and carrier-gas along four lines.

in the outer circle area fluctuates in the narrow range between 0 and 0.02 kg/m3 , which means that the pulverized coal particles are evenly distributed to achieve better coal combustion. Fig. 6 shows the instantaneous volatile and char mass fraction distribution in three combustion conditions at t = 2.5 s. The dispersed coal particles can react with enough oxygen with the decreasing coal-particle quantity. As is mentioned, the pulverized coal combustion process is composed of the volatile combustion and the char combustion. For all combustion conditions, the maximum particle volatile mass fraction occurs in the near-nozzle area, and it drops rapidly in the impinging area. It shows that the coal devolatilization process occurs once introduced into the combustion chamber, and the volatile burning quickly in the impinging area. As for the particle char mass fraction, it reaches a peak value in the impinging area

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Fig. 4. (a) The mean flame temperature fluctuation plotted against calculation time, and (b) the instantaneous temperature distribution on cross-section at different reaction times (t = 1.5 s, 2.0 s and 2.5 s) for three different combustion atmospheres.

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Fig. 5. The averaged pulverized particle concentration distribution along four lines at three combustion atmospheres.

and declines rapidly with the development of turbulent combustion with enough oxygen. But for the fuel-rich combustion atmosphere, the char cannot burn completely because of the lack of oxygen. Hence, the char mass fraction decays slowly and maintains a high value in the entire chamber. The mean particle concentration and the flame temperature (both averaged over horizontal planes of the furnace) plotted versus the furnace height are compared for the different combustion atmospheres in Fig. 7. The flame temperature shows an obvious increase and the particle concentration decreases near the corner-fired cross-section. For the oxygen-rich atmosphere and standard atmosphere, the particle concentration and the flame temperature remain reasonably uniform from the combustion area to the outflow boundary. But for the fuel-rich atmosphere, the particle concentration fluctuates and the flame is not stable because of oxygen depletion. 4.3. Species component distribution Fig. 8 exhibits the O2 , CO2 and CO, mole fraction contours on the same cross-section at different reaction times (t = 1.5 s, 2.0 s and 2.5 s) for three different combustion atmospheres. As the combustion occurs, the O2 is consumed at different rates for the different reducing atmospheres. For the oxygen-rich atmosphere, the pulverized coal is matched with sufficient oxygen during the entire combustion process. For the standard combustion atmosphere, the oxygen is consumed completely in the impinging area because of the intensity of the combustion process in that zone. For the fuel-rich atmosphere, the eventual flame extinction at later times causes the deficient oxygen peak concentration to slightly increase at the onset of extinction. CO2 is an indicator of the completion of the combustion process and may, therefore, play a complementary role to temperature. The CO2 mole fraction increases significantly with the decrease of the excess air ratio at the fuel-rich atmosphere. The CO2 production is in direct proportion to the amount of fuel supply. However, its rate exhibits different trends at the different reducing atmosphere. The figure shows that the CO2 production rate decreases sharply with limited oxygen even with double the supply rate of coal. This trend may be attributed to the onset of extinction at later times.

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Fig. 6. The coal volatile mass fraction distribution (top) and the char mass fraction distribution (bottom) on cross-section at various atmospheres.

Fig. 7. The mean particle concentration (a) and the flame temperature (b) along the furnace height at various atmospheres.

For the oxygen-rich atmosphere, the maximum CO2 mole fraction is located in the lateral-edge of combustion flame, and the CO2 mole fraction decreases slightly with the development of coal combustion process. As an intermediate, the CO may be considered as an indicator of chemical activity and a reasonable marker for the flame. The CO mole fraction increases slightly with the decreasing excess air ratio, while it rockets when the excess air ratio is less than 1. For the oxygen-rich atmosphere, the CO mole fraction decreases slightly with the development of coal combustion process due to the injection of oxygen and the evolution towards more complete combustion. For the fuel-rich atmosphere, the CO mole fraction decays sharply as the flame is extinguished. In this study, NO is calculated in a post-processing step (as discussed earlier) based on the combustion results at t = 2.5 s, and only NO pollutant is considered because the NO makes up the bulk of the NOx emissions (i.e., more than 90%). Fig. 9 shows the NO ppm contours on the same cross-section as in the previous figures and at three different combustion atmospheres at t = 2.5 s. The figure shows that the NO concentration at the standard combustion atmosphere is highest compared to other two combustion atmospheres in the central area. There is another set of peaks along in the impinging area, which approximately coincide with the flame; although, by 2.5 s, the fuel-rich condition is already undergoing flame extinction. For the oxygen-rich atmosphere, the maximum NO is located in the impinging area, and the area-averaged NO pollutant

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Fig. 8. The instantaneous O2 , CO2 and CO, mole fraction distribution on cross section at different reaction times (t = 1.5 s, 2.0 s and 2.5 s) for three different combustion atmospheres.

Fig. 9. The NO pollutant distributions on cross section at three different combustion atmospheres.

on the cross-section is about 70% of the same average at the standard combustion condition. With enough oxygen, the NO distribution is highly affected by the temperature distribution. For the fuel-rich atmosphere, the NO concentration is too low caused by the reducing atmosphere and the flame extinction. Overall, creating a reducing atmosphere can be very effective in reducing NOx emissions.

5. Conclusion LES coupled with the non-premixed MF-PDF combustion model is performed to simulate the turbulent pulverized coal combustion in a laboratory-scale corner-fired furnace. The goal is to investigate the effects of burning atmospheres on pulverized coal combustion. More specifically, the flame characteristics, burning coal behaviors and NOx pollutant emissions, affected by three different excess air ratio (α = 0.6, 1.2 and 2.4) are analyzed qualitatively and quantitatively. Some important observations can be made about the results from the present study: (1) The heat and momentum transfer between burning coal and turbulent gas are greatly enhanced by the corner-fired flow. (2) For all coal combustion conditions, the particle concentrations exhibit similar spatial distributions along the entire furnace cross-section. For a fuel-rich atmosphere, the concentration is obviously much higher and exhibits much higher spatial variability than for the other. (3) The coal combustion efficiency decreases in oxygen- and fuel- rich burning atmospheres. And the flame stability is more affected at the fuel-rich atmosphere by the lack of oxygen. To be specific, the volatile combustion is not greatly affected by burning atmosphere because of the rapid coal-devolatilization process and rapid homogeneous reaction, but the char combustion in a fuel-rich atmosphere is more influenced due to the lack of oxygen. (4) Because of the predominance of fuel NO, the NO pollutant emissions are more affected by the reducing atmosphere than the temperature. Hence, creating reducing atmosphere is a more effective way to reduce the NOx emissions.

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