Investigation of pollutant reduction by simulation of turbulent non-premixed pulverized coal combustion

Applied Thermal Engineering 73 (2014) 1220e1233

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Applied Thermal Engineering journal homepage: www.elsevier.com/locate/apthermeng

Investigation of pollutant reduction by simulation of turbulent non-premixed pulverized coal combustion Behnam Rahmanian e, Mohammad Reza Safaei a, S.N. Kazi a, **, Goodarz Ahmadi b, Hakan F. Oztop c, *, Kambiz Vafai d a

Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia Department of Mechanical and Aeronautical Engineering, Clarkson University, Potsdam, NY 13699-5700, USA Department of Mechanical Engineering, Technology Faculty, Firat University, Elazig, Turkey d Department of Mechanical Engineering, University of California, Riverside, CA 92521, USA e Department of Mechanical Engineering, Payam Noor University, Jahrom Branch, Jahrom, Iran b c

h i g h l i g h t s
The simulations of pulverized coal combustion is studied.
The effect of some pollutant reducers is tested.
Low temperature gives to improvement in reducing pollutant emissions.
The NOx reduction in pulverized coal combustion is higher due to injection of CO2.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 11 February 2014 Accepted 6 September 2014 Available online 16 September 2014

In this work, a computational model was developed and used to study NOx reduction during pulverized coal combustion. The finite volume method with a structured grid arrangement and a SIMPLE algorithm were utilized to model the pulverized coal combustion process. The effect of dilution of the oxidizer by participating gases including Air, Helium, Argon, Steam and CO2 were studied, and the corresponding reductions in the rate of NOx production are compared. The cases when 10 and 20 percent of oxidizer was diluted by the participating gases were analyzed. The Probability Density Function (PDF) model was used for modeling the interaction between turbulence and chemistry, and the Discrete Phase Model (DPM) model was used for modeling the solid particle trajectory analysis including the interaction with turbulence. A QUICK scheme was adopted for the discretization of all convective terms of the advective transport equations. The static temperature, mass fraction of pollutant NOx and velocity distribution along the centerline of the burner as well as temperature and NOx contours for different dilution percentages were presented. It was shown that as result of injection of CO2 into the oxidizer the peak temperature and/or flow velocities of the combustion gases decrease more as compared to injection of steam or other neutral gases. Also, the results showed that the NOx reduction in pulverized coal combustion was highest due to injection of CO2 into the oxidizer in comparison to injection of steam, Argon or Helium.

Keywords: Turbulent Non-premixed Combustion Probability Density Function Model Implicit Solver NOx Reduction Discrete Phase Model

© 2014 Elsevier Ltd. All rights reserved.

1. Introduction

* Corresponding author. Tel.: þ90 424 237 0000x4248; fax: þ 90 424 236 7064. ** Corresponding author. Tel.: þ60 7967 4582; fax: þ 60 7967 5317. E-mail addresses: [email protected] (B. Rahmanian), CFD_Safaei@ yahoo.com (M.R. Safaei), [email protected] (S.N. Kazi), [email protected] (G. Ahmadi), [email protected], [email protected] (H.F. Oztop), Vafai@engr. ucr.edu (K. Vafai). http://dx.doi.org/10.1016/j.applthermaleng.2014.09.016 1359-4311/© 2014 Elsevier Ltd. All rights reserved.

There has been a worldwide concern about atmospheric pollution, and its consequences on the atmosphere ozone balance and climate change [1]. During the combustion, the nitrogen in the air and/or fossil fuel reacts with oxygen to form NOx [2,3]. The product of NOx finally forms nitric acid vapor and generates fine particles after reacting with ammonia, moisture and other compounds [4,5].

B. Rahmanian et al. / Applied Thermal Engineering 73 (2014) 1220e1233

Nomenclature E Ibl x,y d h0j fv0 ! g h k Yj m fw,0 Nu _p m Pr P Rj Re Cp ! al T k

activation energy, E ¼ 7.4  107 (J kmol1) black body intensity (W m2) Cartesian coordinates (m) diameter of particles (m) enthalpy of formation of species j (Jol mol1) fraction of volatile subsequent at the beginning of reaction gravitational acceleration (m s2) heat transfer coefficient (W m2 K1) kinetic rate (s1) local mass fraction of the jth species (kg) mass (kg) mass fraction of evaporating/boiling material (kg) Nusselt number (cp m K1) particles mass flow rate (kg s1) Prandtl number (y a1) pressure (N m2) rate of formation of species j per unit volume (mol dm3 s1) Reynolds number (Re ¼ V D y1) specific heat capacity (J kg1 K1) spectral absorption coefficient (m1) temprature (K) thermal conductivity (Wm1 K1)

These small particles can damage the sensitive lung tissues resulting in premature death in extreme cases. Furthermore, these particles may cause or further escalate respiratory diseases such as bronchitis or emphysema, and might also worsen existing cancer and heart diseases [6]. Coal is still the largest fossil fuel source for electricity generation in the world. With the large consumption of coal (7.25 billion tons in 2010 [7]), it is one of the top source of CO2 emission. Gross carbon dioxide emission from coal amounted to a total of 8666 million tons of CO2 worldwide in 1999 [7]. About 2000 pounds of CO2 per megawatt/hour is generated by coal power plants, which is nearly twice that emitted from the natural gas power plant [8]. One of the newly developed approaches is the integrated coal gasification combined cycle (IGCC). In this method, coal is gasified, prior to the combustion and the impurities are removed from the gas, which results in a reduction in gaseous pollutant [9]. Another popular method is the fluidized bed combustion (FBC). In the fluidized bed coal combustion, the coal is suspended and exposed to air which allows for a more effective mixing of solids and gas thus augmenting the heat transfer. A major advantage of fluidizedbed coal combustion (FBC) approach is its low operating temperature and low nitrous oxide formation [10]. In pulverized coal combustion method, the coal is pulverized and is pumped into a standard combustion chamber. Pulverized coal combustion is one of the most common means of energy production in many applications such as electric power plants and train locomotives. This approach, however, has a substantial negative impact on air pollution [11]. Sahajwalla, Eghlimi and Farrell [12] used the FLUENT software to simulate the pulverized coal combustion. The techniques used were generalized by the finite rate formulation (Magnussen model) and the mixture fraction/PDF formulation. They showed that the Probably Density Function (PDF) model is computationally more efficient compared to Magnussen model due to lower number of species transport equations that need to be solved. Sijer
ci c, Belo
sevi c and Stefanovic [13] studied the use of plasma torches for stabilization of

t K Dt Kt R u,v

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time (s) turbulence kinetic energy (m2 s2) turbulent mass diffusivity (m2 s1) turbulent thermal conductivity (W m1 K1) universal gas constant, R ¼ 8.314472 (J K1 mol1) velocities components in X and Y directions (m s1)

Greek symbols r density (kg m3) ε dissipation rate of turbulent kinetic energy (m2 s3) m dynamic viscosity (Pa s) y kinematics viscosity (m2 s1) sD Prandtl dispersion coefficient am thermal diffusivity (mm r1 m ) b thermal expansion coefficient (K1) sT turbulent thermal diffusivity (m2 s1) l wavelength (mm) Subscripts In cell entry Out cell exit 0 inlet conditions p particles pyrol pyrolysis j species j T turbulent pulverized coal combustion process. They presented selected results of their 3-D numerical model developed for simulation of flow in a duct with plasma system for pulverized coal combustion and ignition. Qinglin, Artur, Weihong and Blasiak [14] investigated the properties of pulverized coal combustion at high temperatures. They suggested that adding steam into the oxidizer suppresses the formation of NOx, and also coal injection velocity affects the NOx formation. A number of multivariate regressions for predicting pulverized coal ignition temperature were described by Gou, Zhou, Liu and Cen [15]. Ettouati, Boutoub, Benticha and Sassi [16] studied the effects of gas and particles distributions on radiative heat transfer in an axisymmetric cylindrical pulverized coal combustor. Their investigation showed that good agreement between the simulation results and experimental data is observed when the wall's radiative heat flux was considered in the analysis. They also showed that the particles have a strong effect on radiative heat transfer, particularly on the radiative source term. Ghazikhani and Rahmanian [17] used a 2-D model to study the effect of steam injection on pollutant reduction in pulverized coal combustors. It was observed that the reduction rate of some pollutants like NOx, CO and C emissions may be enhanced by injecting steam into the incremented oxidizer. In all earlier works, pulverized coal combustion was investigated at high temperatures along with the cutback of NOx as a result of flue gas recirculation. In this study, NOx reduction in a pulverized coal combustor by injecting four participating gases, namely Helium, Argon, Carbon Dioxide and steam, is investigated. Two cases in which the oxidizer was diluted by 10% and 20% with each participating gas were considered. At the inlet, a core highspeed air stream entered at 30 m/s and a radius of 0.125 m. Around the core jet, air entered at 10 m/s in an annulus with radius between 0.125 and 0.5 m. Both airflows had a temperature of 1400 K. The coal particles with an average diameter of 1.34  104 m (134 microns) and mass flow rate of 0.1 kg/s were supplied to the furnace at the center of the high-speed airstream. Here, the coal particles were tracked using the Discrete Phase Model (DPM). The geometry of the combustor is shown in Fig. 1.

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B. Rahmanian et al. / Applied Thermal Engineering 73 (2014) 1220e1233

2 _ p;0 6 m Q¼ 4 mp;in  mp;out hpyrol mp;0 ZTp;in þ mp;in

TZp;out

Cp;p dTmp;out Tref

3

(8)

7 Cp;p dT 5

Tref

The keε turbulent model [21] was used in the present study to account for turbulent effects. Turbulent kinetic energy transport (K) equation:

   vðrkÞ m ! þ V$ðr u kÞ ¼ V$ m þ t Vk þ Gk  rε þ PK vt sk

Fig. 1. Schematic of the studied combustion chamber.

(9)

Dissipation of turbulent kinetic energy transport (ε) equation: 2. Physical and mathematical models The coal particles were injected into the flow in the core region and were carried by the flowing gas. The particles were assumed to be spherical and initially had the same velocity as the local airflow. The other properties were assumed to be constant. The governing equations are [12,18,19]: Continuity equation:

vr ! þ V$ðr u Þ ¼ 0 vt

(2)

X

Yj Hj


 Cm rh3 1  hh 0

1þ

bh3

(12)

Using the PrandtleKolmogorov relation, the eddy viscosity can be expressed as follows:

k2 ε

(13)

(4)

(5)

"    #  2  vu 2 vv vu vv 2 þ Pk ¼ yt 2 þ2 þ vx vx vy vy

Gk ¼ gb

yt vT st vy

! !! ! ! V$ðIl ð r ; s Þ s Þ þ ðal þ ss ÞIl ð r ; s Þ

Here, h0j ðTref;j Þ is the formation enthalpy of species j at the reference temperature, Tref,j. Sh in Equation (4), is the source of energy due to chemical reaction:

Sh ¼ S

Mj

ss 4p

Z4p

! !0 ! !0 Il r ; s 4 s ; s dU0

(16)

0

(6)

Tref;j

h0j

(15)

The model constants in the above equations are listed in Table 1. Discrete Ordinates (DO) radiation model for spectral intensity is [22]:

¼ al n2 Ibl þ
 Cp;j dT þ h0j Tref;j

(14)

The buoyancy term, Gk, is defined as:

where

Hj ¼

(11)

The turbulence energy production term, Pk, can be obtained by:

(3)

j

ZT

ε2 k

Sk ε

yt ¼ Cm fm

The total enthalpy, H, is given by:

H¼

Rε ¼

h¼

where I is the identity matrix. The energy equation for the Non-Premixed Combustion Model:

  v kt ! ðrHÞ þ V$ðr u HÞ ¼ V$ VH þ Sh vt Cp

(10)

and

The fluid stress tensor t, can be presented by:


  2 ! ! ! t ¼ m ðV u Þ þ ðV u ÞT  V$ u I 3

   m ε m þ t Vε þ ðC1 PK þ C2 þ C3 Gk Þ  Rε k sε

where

(1)

Momentum equation:

  v
! !! ! r u þ V$ r u u ¼ Vp þ V$ðtÞ þ r g vt

vðrεÞ ! þ V$ðr u εÞ ¼ V$ vt

! ! ! ! The total intensity ðIð r ; s ÞÞ in direction s at position r is calculated by:

X ! ! ! ! Ið r ; s Þ ¼ Ilk ð r ; s ÞDlk

(17)

k

where the summation is over the wavelength bands. Table 1 Coefficients for RNG k-ε turbulent model [24].

Rj

The heat interphase exchanges equation is given as [20]:

(7)

Cm 0.0845

sk

sε

C1

C2

h0

b

K

1

1.3

1.42

1.68

4.38

0.012

0.41

B. Rahmanian et al. / Applied Thermal Engineering 73 (2014) 1220e1233

Mean mixture fraction (f ):

Discrete Phase Model:

mp

d! v p X! ¼ F dt

(18)

! where F is an external force. Here, for fine particles with high density ratio, the drag and buoyancy forces are the main forces acting on the particle [23]. Accordingly, the equation of motion becomes:

  g rp  r d! vp ¼ FD ! v ! vp þ dt rg

18m rp d2p

FD ¼



02

Mean mixture fraction variance (f ):


02  v rf vt

 
02 
2 02 m ε 02 ! þ V$ rf u ¼ V$ t Vf  2r f þ 2:86mt Vf k sg

f0 ¼ f  f CD Rep 24

(25)

where:

 (20)



 vp! rdp ! v

m

(21)

The Drag coefficient, CD, as a function of particle Reynolds number is defined by Refs. [27,28]:

CD ¼

vt

  
_ p;0  m m ! þ V$ rf u ¼ V$ t Vf þ mp;in  mp;out st mp;0

(26)

In this equation, Rep is the particle Reynolds number, which is given as [26]:

Rep ¼


 v rf

(19)

where [24,25]

!

1223

 ð  0:8271ÞRe 24
1 þ 11:2355Re0:653 þ Re 8:8798 þ Re

(22)

(27)

The fuel type and combustion products determined the selection of species to be included in the analysis. In this paper, an equilibrium system comprising 15 different species is considered, as per Table 2: C, C(s), Ar, He, H, H2, H2O, CO, CO2, N, N2, O, O2, OH and CH4. Since the fuel stream shall be defined in terms of C, H, O, and N mass fractions, these species are accounted for. The pulverized coal particle motions were investigated with the discrete phase model (DPM) in FLUENT software. This model estimated the trajectories of individual coal particles. Momentum, heat and mass transfer between coal particles and gas flow were accounted for by solving the governing equations of the discrete phase trajectory and gas phase continuum. During the coal combustion, NOx can form though three main mechanisms. These are:

Coal devolatilization [20]:

 

dmp ¼ k mp  1  f v;0  f w;0 mp;0 dt

1. Oxidation of atmospheric nitrogen by thermal NO mechanisms. 2. Prompt NO mechanisms. 3. Oxidation of nitrogen including organic components in nitrogen-bearing fuels by the fuel-bound NO mechanisms [29].

(23)

where: E RT

K ¼ A1 exp

(24)

The Mixture Fraction/PDF Modeling [12,20]:

The main source of NOx formation from combustion, however, is the alteration of fuel-bound nitrogen to NOx in fossil fuels (oils and coals). The nitrogen in fuel is unbounded and released due to combustion as a free radical, and creates free N2 or NO. About 50%

Table 2 Concentration of reactants. Species

Air Mole fraction

CO2 Atom fraction

a) 10 percent air diluted C 0.58 21 O2 H 0.39 N 0.02 N2 79 O 0.01 H2O CO2 Argon Helium b) 20 percent air diluted C 0.58 O2 21 H 0.39 N 0.02 N2 79 O 0.01 H2O CO2 Argon Helium

Mole fraction

Argon Atom fraction

Mole fraction

0.58 21

Helium Atom fraction 0.58

21 0.39 0.02

69

Mole fraction

69

Mole fraction

0.58 21

0.39 0.02

0.01

Steam Atom fraction

0.58 21

0.39 0.02 69

0.01

Atom fraction

0.39 0.02 69

0.01

0.01 10

10 10 10 0.58 21

0.58 21

0.39 0.02 59

0.58 21

0.39 0.02 59

0.01

0.58 21

0.39 0.02 59

0.01

0.39 0.02 59

0.01

0.01 20

20 20 20

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Fig. 3. Comparison of the temperature and CO2 concentration along the axis of the down-fired combustor with the work of Lu, Zhu, Niu, Song and Na [36]. Fig. 2. Comparison of the predicted mass fraction of pollutant NOx and axial velocity distribution along the centerline of the burner with the experimental data of Ghazikhani and Rahmanian [17].

and 80% of combustion products contain NOx when burning oil and coal, respectively [30]. Two primary paths of NOx formation are identified, though the detail mechanism is not fully understood. In the first path, oxidation of fugacious nitrogen species in the primitive stages is recognized as the starting point. Nitrogen reacts to form several intermediate substances and is then oxidized to form NO before its oxidation. The evolved nitrogen is transformed to N2 gas instead of NOx, if the volatiles evolve in a reducing atmosphere. The second path includes combustion of nitrogen held in the char matrix within the combustion of the fuels char portion. In comparison to the volatile phase, this reaction takes places more slowly. About 20% of char nitrogen is finally produced as NOx. The NOx formed in this procedure is diminished to nitrogen by the char,

which is almost unadulterated carbon form [29]. However, the easiest way to reduce NOx, especially for internal combustion engines, is to add steam to the combustor. water vapor could decrease the O radical concentration by following scavenging reaction: H2O þ O / 2OH. The pulverized coal combustion process can be expressed as:

½C þ HðfuelÞ þ ½O2 þ N2 ðAirÞ/½CO2 þ H2 O þ N2 ðHeatÞ

(28)

Some other reactions were considered in this work are:

C þ 1=2O2 /CO C þ CO2 /2CO C þ H2 O/CO þ H2 H2 þ 1=2O2 /H2 O CO þ 1=2O2 /CO2

(29)

B. Rahmanian et al. / Applied Thermal Engineering 73 (2014) 1220e1233

Fig. 4. Grid independence tests for the present study by comparison mass fraction of NOx in various mesh concentration.

The Nusselt number of the pulverized coal combustion for inert heating is evaluated by Refs. [12,17]:

hD ¼ 2 þ 0:6Re1=2 Pr1=3 Nu ¼ k

(30)

It should be pointed out that the present model employed a oneway coupled assumption that is reasonable for a relatively dilute suspension. In this approach, the gas flow moves the particles, but the particles' effect on flow is neglected. In addition, the influence of gas flow turbulence on particle dispersion was also insignificant. The effect of turbulence fluctuation velocity diminished for large particles when the particle relaxation time was much greater than the turbulence time scale. It is worth noting that by using the PDF model, the significant effect of turbulence on the chemical reaction is included in the model.

1225

Fig. 6. Static temperature distribution along the centerline of the burner for case 2.

3. Numerical procedure and boundary conditions In order to solve the partial differential equations governing multispecies flow, the FLUENT commercial code was used. The code employs the finite volume method, which is a specific case of the weighting residual approach. In this method the computational domain is divided into finite control volumes, where each node corresponds to a control volume. The partial differential equation is subsequently integrated over each finite volume [31,32]. The QUICK scheme was adopted for the discretization of all convective terms, while the SIMPLE algorithm [33] was used for pressure/velocity coupling. The Probability Density Function (PDF) model [34] was utilized to model the interaction between chemistry and turbulence. This model solves a single transport equation to conserve a scalar (the mixture fraction). The PDF approach is believed to produce more realistic results compared to the Magnussen technique with respect to oxygen concentration and char burnout rate [12]. The Discrete Phase Model (DPM) with particle tracking served to analyze the trajectories of the injected coal particles. The calculation was concluded once the residuals for all equations dropped below 107. The inlet velocity and wall conditions in the combustor body are specified so as to solve the problem. The coal combustor studied in this work is a non-adiabatic system and includes heat transfer to the mixture at the combustor wall. The combustor walls were at a constant temperature of 1200 K; therefore, isothermal boundary conditions for the combustor walls were defined. Due to the symmetry, only half the combustor was modeled, and the axisymmetric condition was imposed on the centerline. Finally, the pressure outlet condition was applied at the combustor exit. The mixture was approximated as an incompressible flow because the Mach number was below 0.3 and the compressiblity effects were negligible [35]. 4. Validation 4.1. Validation with numerical study

Fig. 5. Static temperature distribution along the centerline of the burner for case 1.

Using the PDF and discrete phase model, Ghazikhani and Rahmanian [17] investigated the effect of steam injection on pulverized

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Fig. 7. Contour of Temperature distribution for case 1.

B. Rahmanian et al. / Applied Thermal Engineering 73 (2014) 1220e1233

Fig. 8. Contour of Temperature distribution for case 2.

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Fig. 9. Velocity distribution along the centerline of the burner for case 1.

coal combustion to reduce NOx pollution. The air was diluted by injecting 0%e20% steam. The problem described by Ghazikhani and Rahmanian [17] was solved using the current model and the results were compared with earlier work. The FLUENT commercial code utilizing PDF models was used to simulate non-premixed combustion in a 2-D combustion chamber. Comparisons between prior simulations by Ghazikhani and Rahmanian [17] and present model predictions are shown in Fig. 2a and b. It is clear that the present model's predictions for NOx concentration and axial velocity along the combustor axis are in good agreement with Ghazikhani and Rahmanian [17]. 4.2. Validation with experimental study Lu, Zhu, Niu, Song and Na [36] experimentally studied the performance of pulverized coal combustion in a circulating fluidized bed (CFB) in a down-fired combustor with 3000 mm height and

Fig. 10. Velocity distribution along the centerline of the burner for case 2.

Fig. 11. Mass fraction of pollutant NOx for case 1.

220 mm diameter. Air entered the CFB at atmospheric temperature through a 100 mm inlet. The furnace temperature was kept constant at about 1373 K and the pulverized coal feed rate was 2.0 kg/hr. The present computational model was applied and the CFB combustor of Lu, Zhu, Niu, Song and Na [36] was simulated under conditions identical to the experiment. The variations in temperature and CO2 concentration along the down-fired combustor's axis were evaluated and the results were compared with the experimental data of Lu, Zhu, Niu, Song and Na [36] in Fig. 3a and b. It is evident that the present model simulations are in good agreement with the experimental data. The small discrepancies observed in these figures between the current model and Lu, Zhu, Niu, Song and Na [36] may be due to some small uncertainties in data input to the CFD model. 4.3. Grid independence The computational domain was discretized using a structured, non-uniform grid. The grid is more refined in the vicinity of walls

Fig. 12. Mass fraction of pollutant NOx for case 2.

B. Rahmanian et al. / Applied Thermal Engineering 73 (2014) 1220e1233

Fig. 13. NOx concentration contours for various participating gases for case 1.

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Fig. 14. NOx concentration contours for various participating gases for case 2.

B. Rahmanian et al. / Applied Thermal Engineering 73 (2014) 1220e1233

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where significant temperature and velocity gradients occur. Several grid distributions were tested to assure that the computational results are grid-independent. Fig. 4 illustrates the result for mass fraction of NOx along the combustor axis for different grids. Based on the presented results, a 1200  50 grid was selected for all modeling cases. 5. Results and discussion The computational model was applied to study NOx reduction during pulverized coal combustion in a 2-D combustor. In the first set of simulations, the air was diluted by injecting 10% participating gases. The rate of dilution was then increased to 20% and the effect on NOx reduction was evaluated and discussed. The simulation results for the pulverized coal combustion and effects of participating gases on NOx generation are discussed in this section. Figs. 5,7,9,11,13 and 15 illustrate the pulverized coal combustion at the rate of 10% by mole fraction of the participating gases (Argon, Helium, CO2 and steam) [Case 1], while Figs. 6,8,10,12,14 and 16 show the combustion simulation at the rate of 20% by mole fraction of the same additives [Case 2]. The results are shown at the centerline of the combustion chamber. The mixture's temperature distributions along the centerline of the combustor for 10% mole fraction dilution for all participating gases are shown in Fig. 5. Similar results for 20% participating gases are presented in Fig. 6. It is clear from these graphs that the temperature of the mixture along the centerline in the presence of CO2 reached a peak of nearly 1880 K, which is lower than other gases for 10% dilution. For 20% dilution, the mixture temperature reached a peak of roughly 1885 K at the combustor centerline in the presence of Argon, which was a lower temperature than other gases. Figs. 7 and 8 present the temperature distribution contours of the mixture in the combustion chamber for 10% and 20% dilutions with Argon, CO2, Helium, and steam. Obviously, the maximum mixture temperature in the combustion chamber occurred at about 0.4 m from the entrance to the burner and near the chamber's centerline for both dilution rates. In Figs. 9 and 10 the velocity distributions along the combustor centerline are displayed. As can be seen, the flow velocity of the combustion gases decreases when participating gases are injected into the oxidizer. In Fig. 9, the flow velocity of the combustion gases reached a peak of about 30.5 m/s by injecting participating gases into the oxidizer. When injecting CO2 into the oxidizer, however, the reduction of combustion gases flow velocity was greater than for Helium and Argon; but the differences were minimal. Fig. 10 representing 20% dilution shows a very similar trend to those seen in Fig. 9. A peak was reached at just over 30 m/s, similar to the velocity distribution in case 1. It is also evident that the velocities diminished owing to the injection of neutral gases into the oxidizer, especially CO2. Figs. 11 and 12 show the mass fraction of NOx pollutant along the centerline of the burner for 2 mol fractions, 10% and 20% of additives, respectively. From the figures, it is clear that the rate of NOx reduction when injecting CO2 into oxidizer is higher than the other cases. In Fig. 11, at 10% mole fraction of participating gases injected into the oxidizer, there was marked difference between the maximum NOx concentration with CO2, steam, Argon and Helium injection. The maximum NOx concentration value with steam injection was about 0.0095 ppm, while in the case of CO2 it was around 0.008 ppm. Fig. 12 indicates that when 20% mole fraction of participating gases was injected into the oxidizer, the maximum NOx concentration with steam injection was nearly 0.0068 ppm, while for CO2 injection the value was approximately 0.0055 ppm. Therefore, the NOx reduction in case of 20% steam injection versus

Fig. 15. Mass fraction of CO for case 1.

combustion without participating gases was about 39.7% and for CO2 injection roughly 50%. Figs. 13 and 14 illustrate the NOx concentration contours in the combustor. Comparisons with Figs. 7 and 8 signify that NOx emissions reached a peak rate at the highest gas mixture temperature values. Increasing thermal NOx may provide a good explanation for this phenomenon, which strongly depends on flame temperature. Thermal NOx is generated by a series of chemical reactions in the presence of oxygen and nitrogen in the combustion, which subsequently react to form nitrogen oxides. The main participating chemical reactions are known as the Zeldovich mechanism, and these occur in the high-temperature region of the combustion chamber [37]. The Zeldovich mechanism postulates that thermal NOx formation rises exponentially with increasing temperature values and linearly with increasing residence time. Flame temperature is dependent on the air-fuel ratio. The air-fuel stoichiometric ratio is the highest theoretical temperature point at which a flame burns [2].

Fig. 16. Mass fraction of CO for case 2.

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Figs. 15 and 16 demonstrate the mass fraction of CO emissions for both cases, respectively. Fig. 15 shows that the minimum amount of CO emissions occurred in combustion with steam present and certainly in stoichiometric combustion. In this case, the graph reached a peak of about 0.0026 ppm at a distance of 3 m from the combustion inlet while the maximum CO mass fraction value occurred in combustion with Helium. Fig. 16 presents the CO mass fraction distribution in case 2. Regarding this graph, the maximum CO formation rate is related to combustion with an oxidizer that was diluted by 20% CO2. On the other hand, the minimum CO mass fraction value occurred in combustion where steam was present. 6. Conclusions and future work Simulations of pulverized coal combustion in a 2-D combustion chamber were performed under a range of conditions. Particular consideration was given to the effects of injecting a number of pollutant-reducing gases, such as CO2, He, Ar and steam. The static temperature, velocity distribution and mass fraction of NOx for different participating gas concentrations were evaluated and the results were presented in graph form. According to the simulation results, NOx concentration reached a peak stoichiometric value and then dropped at both rich and lean fuel concentrations. It was particularly noted that injecting CO2 into the combustion chamber led to a lower maximum temperature along the chamber's centerline in case 1. In addition, the combustion gas product velocities decreased owing to CO2 and steam injection into the oxidizer. Evidently, Carbon Dioxide injection resulted in substantial reduction of NOx formation. The simulation results confirmed that the CO emissions reduction was mainly correlated with the decrease in combustion chamber temperature. Lowering the temperature additionally led to considerable improvement in reducing pollutant emissions, particularly NOx and CO. Injecting small amounts of participating gases, i.e., steam, Helium, Argon or CO2 into the combustor was shown to reduce the local concentration of oxygen and led to decreased flame temperature. As a result, the formation of fuelbound and thermal NOx was diminished. Such injections typically reduced the efficiency of the combustion unit by 1e2% [38]. In a future work the plan is to include the effects of two-way coupling and turbulence fluctuation on particle dispersion in a computational model [39e42]. The aim is also to study the effect of pulverized coal diameter on coal combustion and pollutant production (NOx, CO, CO2 and Cx). Eliminating SO2 during combustion using “stack scrubber” technology, as well as supplementing with other solid fuels in the reaction mixture will also be addressed in the future [43]. An interesting method of assessing these phenomena is to analyze the local thermal non-equilibrium (LTNE). In this technique, temperature gradient bifurcation is processed by studying the specifications of convection heat transfer within a fluidized bed combustor using the porous media approach. This method has been analyzed in detail in works by Vafai et al. [44e49] for a rectangular channel similar to a fluidized bed combustor. Conflicts of interest The authors declare that there is no conflict of interest regarding the publication of this paper. Acknowledgements The authors gratefuly acknowledge High Impact Research Grant UM.C/625/1/HIR/MOHE/ENG/45, UMRG RP012D-13AET and Faculty of Engineering, University of Malaya, Malaysia for support in conducting this research work.

References [1] B.K. Yun, M.Y. Kim, Modeling the selective catalytic reduction of NOx by ammonia over a Vanadia-based catalyst from heavy duty diesel exhaust gases, Appl. Therm. Eng. 50 (2013) 152e158. [2] S.R. Turns, An Introduction to Combustion: Concepts and Applications, McGraw-hill, New York, U.S.A, 1996. [3] K. Kang, S.-K. Hong, D.-S. Noh, H.-S. Ryou, Heat transfer characteristics of a ceramic honeycomb regenerator for an oxy-fuel combustion furnace, Appl. Therm. Eng. 70 (2014) 494e500. [4] V. Gogulancea, V. Lavric, Flue gas cleaning by high energy electron beam e modeling and sensitivity analysis, Appl. Therm. Eng. (2014), http://dx.doi.org/ 10.1016/j.applthermaleng.2014.05.046. [5] J. Shen, J. Liu, H. Zhang, X. Jiang, NOx emission characteristics of superfine pulverized anthracite coal in air-staged combustion, Energy Convers. Manage. 74 (2013) 454e461. [6] O.M. Roger, Lung cancer in rats from prolonged exposure to high concentrations of carbonaceous particles: Implications for human risk assessment, Part. Sci. Technol. 14 (1996) 89e122. [7] Quickiwiki, Coal (last accessed: 12 August, 2014), www.quickiwiki.com/en/ Coal, 2006. [8] R. Nuwer, A 20-Year Low in U.S. Carbon Emissions, 2012. green.blogs.nytimes. com/2012/08/17/a-20-year-low-in-u-s-carbon-emissions/ (last accessed: 12 August, 2014). [9] F. Emun, M. Gadalla, T. Majozi, D. Boer, Integrated gasification combined cycle (IGCC) process simulation and optimization, Comput. Chem. Eng. 34 (2010) 331e338. [10] P. Chindaprasirt, U. Rattanasak, Utilization of blended fluidized bed combustion (FBC) ash and pulverized coal combustion (PCC) fly ash in geopolymer, Waste Manage. 30 (2010) 667e672. [11] D.T. Pratt, L. Smoot, D. Pratt, Pulverized-coal Combustion and Gasification, Springer, New York, U.S.A, 1979. [12] V. Sahajwalla, A. Eghlimi, K. Farrell, Numerical simulation of pulverised coal combustion, in: Inter Conf on CFD in Mineral & Metal Processing and Power Generation CSIRO, 1997, pp. 195e204. [13] M. Sijer
ci c, S.V. Belo
sevi c, P. Stefanovi c, Modeling of pulverized coal combustion stabilization by means of plasma torches, Therm. Sci. 9 (2005) 57e72. [14] Z. Qinglin, S. Artur, Y. Weihong, W. Blasiak, Properties of Pulverized Coal Combustion in High Temperature Air/Steam Mixture, Royal Institute of Technology, Division of Energy and Furnace Technology, School of Industrial Engineering and Management, 2006. [15] X. Gou, J. Zhou, J. Liu, K. Cen, Research on regression model of pulverized coal ignition temperature, Energy Educ. Sci. Technol. Part A Energy Sci. Res. 28 (2011) 143e150. [16] H. Ettouati, A. Boutoub, H. Benticha, M. Sassi, Radiative heat transfer in pulverized coal combustion: effects of Gas and particles distributions, Turkish J. Eng. Environ. Sci. 31 (2007) 345e353. [17] M. Ghazikhani, B. Rahmanian, Effect of steam injection in pulverized coal combustion to reduce pollutants, in: The 6th International Chemical Engineering Congress, Kish Island, Iran, 2009 article code: 04185. [18] T. Echekki, E. Mastorakos, Turbulent combustion: concepts, governing equations and modeling strategies, in: Turbulent Combustion Modeling: Advances, New Trends and Perspectives, Springer Netherlands, 2011, pp. 19e39. [19] Z. Li, F. Wei, Y. Jin, Numerical simulation of pulverized coal combustion and NO formation, Chem. Eng. Sci. 58 (2003) 5161e5171. [20] B. Yan, Y. Cheng, Y. Jin, C.Y. Guo, Analysis of particle heating and devolatilization during rapid coal pyrolysis in a thermal plasma reactor, Fuel Process. Technol. 100 (2012) 1e10. [21] M.R. Safaei, H.R. Goshayeshi, B.S. Razavi, M. Goodarzi, Numerical investigation of laminar and turbulent mixed convection in a shallow water-filled enclosure by various turbulence methods, Sci. Res. Essays 6 (2011) 4826e4838. [22] M. Goodarzi, M.R. Safaei, H.F. Oztop, A. Karimipour, E. Sadeghinezhad, M. Dahari, S.N. Kazi, N. Jomhari, Numerical study of entropy generation due to coupled laminar and turbulent mixed convection and Thermal radiation in an enclosure filled with a semitransparent medium, Sci. World J. 2014 (2014), http://dx.doi.org/10.1155/2014/761745. Article ID 761745. [23] E. Sistani, PIV Measurements Around a Rotating Single Gear Partially Submerged in Oil within Modelled SAAB Gearbox, Diploma Work e Department of Applied Mechanics, Vol. Master's Thesis, Chalmers University of Technol€teborg, Sweden, 2010. ogy, Go jek, Validation of an effervescent spray model with secondary [24] J. Broukal, J. Ha atomization and its application to modeling of a large-scale furnace, Appl. Therm. Eng. 31 (2011) 2153e2164. [25] R.I. Singh, A. Brink, M. Hupa, CFD modeling to study fluidized bed combustion and gasification, Appl. Therm. Eng. 52 (2013) 585e614. [26] X. Cui, K. Chua, W. Yang, K. Ng, K. Thu, V. Nguyen, Studying the performance of an improved dew-point evaporative design for cooling application, Appl. Therm. Eng. 63 (2014) 624e633. [27] M. Habib, R. Ben-Mansour, H. Badr, S. Said, S. Al-Anizi, Erosion in the tube entrance region of a shell and tube heat exchanger, Int. J. Numer. Methods Heat Fluid Flow 15 (2005) 143e160. [28] M. Habib, H. Badr, S. Said, R. Ben-Mansour, S. Al-Anizi, Solid-particle erosion in the tube end of the tube sheet of a shell-and-tube heat exchanger, Int. J. Numer. Methods Fluids 50 (2006) 885e909.

B. Rahmanian et al. / Applied Thermal Engineering 73 (2014) 1220e1233 [29] I. Glassman, R. Yetter, Combustion, Academic press, San Diego, U.S.A, 2008, pp. 409e494. [30] A. Williams, M. Pourkashanian, J. Jones, L. Rowlands, A review of NOx formation and reduction mechanisms in combustion systems, with particular reference to coal, J. Inst. Energy 70 (1997) 102e113. [31] S.V. Patankar, Numerical Heat Transfer and Fluid Flow, Hemisphere Publication Corporation, Washington DC, U.S.A, 1980. [32] M.R. Safaei, B. Rahmanian, M. Goodarzi, Numerical study of laminar mixed convection heat transfer of power-law non-Newtonian fluids in square enclosures by finite volume method, Int. J. Phys. Sci. 6 (2011) 7456e7470. [33] M. Goodarzi, M. Safaei, K. Vafai, G. Ahmadi, M. Dahari, S. Kazi, N. Jomhari, Investigation of nanofluid mixed convection in a shallow cavity using a twophase mixture model, Int. J. Therm. Sci. 75 (2014) 204e220. [34] I. Dhuchakallaya, P. Rattanadecho, P. Watkins, Auto-ignition and combustion of diesel spray using unsteady laminar flamelet model, Appl. Therm. Eng. 52 (2013) 420e427. [35] R.E. Neel, Advances in computational fluid dynamics: turbulent separated flows and transonic potential flows, Ph. D., in: Aerospace Engineering, Citeseer, Virginia Polytechnic Institute and State University, Blacksburg, U.S.A, 1997, p. 252 [36] Q. Lu, J. Zhu, T. Niu, G. Song, Y. Na, Pulverized coal combustion and NOx emissions in high temperature air from circulating fluidized bed, Fuel Process. Technol. 89 (2008) 1186e1192. [37] F. Normann, K. Andersson, B. Leckner, F. Johnsson, High-temperature reduction of nitrogen oxides in oxy-fuel combustion, Fuel 87 (2008) 3579e3585. [38] M. Karell, A. Chattopadhyay, NOx Emission Reduction Strategies, 2013. http:// www.pollutiononline.com/doc/nox-emission-reduction-strategies-0001 (last accessed: 12 August, 2014).

1233

[39] A. Li, G. Ahmadi, Deposition of aerosols on surfaces in a turbulent channel flow, Int. J. Eng. Sci. 31 (1993) 435e451. [40] H. Nasr, G. Ahmadi, The effect of two-way coupling and inter-particle collisions on turbulence modulation in a vertical channel flow, Int. J. Heat. Fluid Flow 28 (2007) 1507e1517. [41] H. Nasr, G. Ahmadi, J.B. McLaughlin, A DNS study of effects of particleeparticle collisions and two-way coupling on particle deposition and phasic fluctuations, J. Fluid Mech. 640 (2009) 507e536. [42] L. Tian, G. Ahmadi, Particle deposition in turbulent duct flowsdcomparisons of different model predictions, J. Aerosol Sci. 38 (2007) 377e397. [43] D. Coil, E. McKittrick, B.H. Higman, Coal Combustion Methods, 2012 (last accessed: 12 August, 2014), www.groundtruthtrekking.org/Issues/AlaskaCoal/ CoalCombustionMethods.html. [44] B. Alazmi, K. Vafai, Constant wall heat flux boundary conditions in porous media under local thermal non-equilibrium conditions, Int. J. Heat Mass Transfer 45 (2002) 3071e3087. [45] A. Amiri, K. Vafai, Analysis of dispersion effects and non-thermal equilibrium, non-Darcian, variable porosity incompressible flow through porous media, Int. J. Heat Mass Transfer 37 (1994) 939e954. [46] K. Yang, K. Vafai, Analysis of temperature gradient bifurcation in porous mediaeAn exact solution, Int. J. Heat Mass Transfer 53 (2010) 4316e4325. [47] K. Yang, K. Vafai, Transient aspects of heat flux bifurcation in porous media: an exact solution, J. Heat Transfer 133 (2011) 52602. [48] K. Yang, K. Vafai, Restrictions on the validity of the thermal conditions at the porous-fluid interface-an exact solution, J. Heat Transfer 133 (2011). [49] K. Yang, K. Vafai, Analysis of heat flux bifurcation inside porous media incorporating inertial and dispersion effectseAn exact solution, Int. J. Heat Mass Transfer 54 (2011) 5286e5297.