Analysis of SO2 and NO x Emissions Using Two-Fluid Method

Article pubs.acs.org/EF

Analysis of SO2 and NOx Emissions Using Two-Fluid Method Coupled with Eddy Dissipation Concept Reaction Submodel in Circulating Fluidized Bed Combustors Guangbin Yu,†,‡,∥ Juhui Chen,*,†,‡ Jiuru Li,‡ Ting Hu,§ Shuai Wang,∥ and Huilin Lu∥ †

The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province, Harbin University of Science and Technology, Harbin, 150080, China ‡ School of Mechanical Engineering, Harbin University of Science and Technology, Harbin, 150080, China § No. 703, Research Institute of China Shipbuilding Industry Corporation, Harbin 150001, China ∥ Harbin Institute of Technology, Harbin, 150001, China ABSTRACT: Large eddy simulation (LES) of the gas-second order moment (SOM) of particles model based on the two-fluid method coupled with the subgrid-scale (SGS) reaction submodel is applied to investigate SO2 and NOx emissions in circulating fluidized bed (CFB) combustors. The SGS reaction submodel based on the eddy dissipation concept (EDC) model is developed considering the effect of particles to calculate the SGS reaction rates. The predicted results by the model are in good agreement with the experimental data. The flow characteristics including concentration and SOM of particles are analyzed. The simulation results show the particles including coal particles and desulfurizer particles are mixed sufficiently. The velocity fluctuation of particles is enhanced for the combustion process, and the velocity fluctuation in the axial direction is about 2 times higher than that in the radial direction. The reaction characteristics including the molar fraction of species and the distribution of chemical reaction rates with concentrations are also obtained. It can be found that the SGS reaction rates not only improve the homogeneous reactions of gas but also influence the heterogeneous reactions.

1. INTRODUCTION CFB combustors have been widely used with good advantages of low emissions, easy temperature control, and fuel flexibility. However, there are still a few pollutants such as SO2 and NOx released to the environment. It is important for us to understand the reaction mechanism of pollutants and predict emissions of SO2 and NOx correctly.1 There is a certain amount of sulfur and nitrogen in coal particles, most of which are released as volatile during coal devolatilization.2 Volatile-S is released as SO2 in the combustion process. Volatile-N mainly exists in the form of HCN and NH3, the proportion of which relates with the kind of coal, the operating temperature, and so on. The nitrogen oxides generated during the combustion process is mainly nitric oxide and account for more than 90%. Nitrous oxide is easy to generate under the operating temperature for the combustion process in CFB combustors and is also considered in the simulation. The mixture of NO and N2O is called NOx. Numerical simulation is an effective means for studying gas− solid flow and the pollutant emission process in CFB combustors. Krzywanski et al.3 presented a coal combustion model and developed the computer code to evaluate gas emissions from solid fuels under an oxygen-enriched environment. Gungor4 modeled the process of pollutant emissions and predicted the coal combustion process in a CFB combustor. Jin et al.5 studied NOx release characteristics along the boiler during pulverized coal combustion by numerical simulation. Chen et al.6 developed a reaction-diffusion model for a single particle and studied the process of Char-N reactions. Wang et al.7 numerically analyzed the effect of clusters on the process of © 2014 American Chemical Society

NOx emission and desulfurization in a CFB combustor. Most scholars had focused on modeling the pollutant emissions process under steady conditions. Whereas, the fuel combustion process is dynamic and complicated due to gas−solid turbulence, dissipation of particles collision, and multicoupling between the gas and solid phases. In addition, the coexistence of homogeneous and heterogeneous reactions and variation of temperature due to heat exchange of reactions increase the complexity. Zhou et al.8 performed a simulation to investigate nitrogen and sulfur oxides emissions using two-fluid model on the basis of the kinetic theory of granular flow (KTGF) considering heat transfer and chemical reactions. Khongprom et al.9 used the multiphase CFD method to analyze the process of CO2 emission and designed a CO2 absorber for the CFB combustor. Wang et al.10 simulated the flow and reaction behaviors of particles in the chemical looping combustor using the two-fluid method. Though some of scholars have focused on the dynamic model research, there is still no universal numerical model applicable to the reactive gas−solid process in fluidized bed combustors in the open literature up until now. Current mathematical models from different researchers based on some assumptions are only valid under certain circumstances. Therefore, development of mathematical models plays an important role on studying the reactive gas−solid flow process. Received: December 1, 2013 Revised: February 12, 2014 Published: February 12, 2014 2227

dx.doi.org/10.1021/ef402341p | Energy Fuels 2014, 28, 2227−2235

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∂ ∂ ( αgρg Hg) + ( αgρg ug̃ i Hg) ∂t ∂xi ⎡ Hg μgt ⎞ ∂ Tg ⎤ ∂ ⎢ ⎛⎜ ⎥ + h (T − T ) + S H ⎟ = αg ⎜λg + gs g s gs g Tg Prt ⎟⎠ ∂xi ⎥⎦ ∂xi ⎢⎣ ⎝

LES as a common method is widely used for simulating turbulence behavior of the gas.11−13 Small eddies which only take the effect of dissipation in the flow process into account must be considered during the reaction process. Because the scales of chemical reactions are usually smaller than that of small eddies, there is need to be modeled in small eddies.14 The EDC model is a common method for the mean reaction rates based on a steady rate, which considers that the total space is divided into two sections, the “fine structures” and the “surrounding fluid”. The homogeneous reactions are assumed to occur on “fine structures” with dimensions of the order of the Kolmogorov scale, and the fluid state is determined by the surrounding state.15−17 As the scales of the fine structure and turbulent kinetic energy dissipation are in 1 order of magnitude, the EDC model is extended into the LES field through analogy of the SGS parameters as the mean parameters. Fureby et al.18 used the EDC model to simulate the bluff body stabilized flames in the combustion process by LES. Yaga et al.19 developed a new EDC model to calculate the reaction rate by introducing an eddy characteristic time derived from large-scale motion and estimated combustion characteristics in the combustor. Xiouris et al.20 described LES of an unconfined partially premixed propane-air burner with a swirl using the EDC model. However, the EDC model applied in LES has been only used for homogeneous chemical reactions of gas at the present. For the fuel combustion process in CFB combustors, the solid fuels such as coal and biomass are usually used and gas−solid heterogeneous reactions will occur. Obviously, the EDC model needs to be revised when applied to the combustion process in CFB combustors. In this paper, the LES-SOM model based on the two-fluid method coupled with SGS reaction submodel is presented. We consider the effect of particles and introduce the volume fraction to represent the share of gas. The EDC model is developed for combustion process in CFB combustors. For the particles-phase in the framework of two-fluid model, the kinetic theory of granular flow is widely adopted for closure.21−23 The velocity fluctuations of particles show a clear discrepancy at each direction in CFB combustors, hence the SOM model based on KTGF is employed to consider the anisotropic behavior of particles.24

(3)

∂ ∂ ( αgρg Ygn) + (ρ αgug̃ j Ygn) ∂t ∂xj g =

Ng

Sgs =

∑

Sgn

n=1

and Sgn is the mass exchange of nth species. The mass exchange exists not only between gas species, but also between gas−solid two phases. For homogeneous reactions of gas, the mass transfer is only considered between gas species, which can be expressed as Sgn =

∑ Mgnυgn( R gn + R gn,sgs)

(5)

where Mgn, υgn, R gn, and Rgn,sgs are the molar mass, the stoichiometric coefficient, the filtered reaction rate and the SGS reaction rate of nth species, where Rgn,sgs need be modeled using SGS reaction submodel based on EDC model. Considering the effect of particles, the mass fraction γ* and the residence time scale τ*of the fine structure are defined as27 ⎛ μ εsgs ⎞3/4 gt ⎟ γ * = 9.67⎜⎜ ⎟ α ⎝ gρg ksgs ⎠

(6)

⎛ μ ⎞1/2 gt ⎟ τ * = 0.41⎜⎜ ⎟ α ρ ⎝ g g εsgs ⎠

(7)

where ksgs, εsgs, and μgt represent SGS turbulent kinetic energy, SGS dissipation, and SGS dynamic viscosity, respectively. The SGS turbulent kinetic energy ksgs and SGS dissipation εsgs can be obtained by solving the SGS turbulent kinetic energy equation. The SGS dynamic viscosity μgt can be obtained by the SGS turbulent kinetic energy model.28 The mass fraction of nth species in fine structure Ygn * can be obtained by the equation as follows:

2.1. LES of Gas Model. Assuming that the changes of mass during the reaction process have nothing to do with the surface velocity of gas, the governing equations for reacting flow are expressed as follows:25,26

(1)

dY g*n dt

∂ ∂ ( αgρg ug̃ i) + ( αgρg ug̃ iug̃ j) ∂t ∂xj

=

Ygn − Y g*n R g*nMgn + αgρg (1 − γ *)τ *

(8)

where Rgn * represents the reaction rate of nth species in fine structure and

∂ τg ∂p ∂ [ αgρg (ug̃ iug̃ j − ugiu͠ gj)] + αgρg gi + = − αg ̅ + ∂xj ∂xj ∂xi − βgs(ug̃ i − usi) + ug̃ i · Sgs

(4)

Equations 1−4 represent mass, momentum, energy, and species conservation equation of gas, respectively, where Sgs denotes mass exchange between gas and solid phases.

2. MATHEMATICAL MODEL

∂ ∂ ( αgρg ) + ( αgρg ug̃ i) = Sgs ∂t ∂xi

⎡ ⎛ μgt ⎞ ∂ Ygn ⎤ ∂ ⎢ ⎥ ⎟ αgρg ⎜⎜ Dgn + ⎟ ∂x ⎥ + Sgn ρ ∂xj ⎢⎣ Sc j ⎦ ⎝ g t⎠

R g*n = γ * R gn

(2)

So, the SGS reaction rate is obtained: 2228


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γ* (Y g*n − Ygn) (1 − γ *)τ *

H2 +

(9)

(10)

∂ ∂ (αsρs us, i) + (αsρs usiusj) ∂t ∂xj N

=

∑ [χ(msCi)l ] − l=1

∂p ∂ Ξij − αs + αsρs gi ∂xj ∂xi

+ βgs(ugĩ − us, i) + us, i ·Ssg

(11)

∂ ∂ (αsρs Hs) + (αsρs usiHs) ∂t ∂xi ∂T ⎞ ∂ ⎛ = ⎜αsλs s ⎟ + hsg ( Tg − Ts) + SsgHs ∂xi ⎝ ∂xi ⎠

(12)

∂ ∂ (αsρs Ysm) + (ραsusjYsm) = Ssm ∂t ∂xj s

(13)

3. CHEMICAL REACTIONS MODEL Coal combustion includes coal devolatilization, carbon combustion, volatile combustion, NOx emissions, and the desulfurization process in CFB combustors. It is assumed that the particles include two phases, the first phase is coal particles, which consists of three components (fixed carbon, volatile, and ash); the second phase is desulfurizer particles, which consists of three components (calcium oxide CaO, calcium carbonate CaCO3, and calcium sulfate CaSO4). The gas phase consists of 14 components (methane CH4, ethane C2H6, carbon monoxide CO, carbon dioxide CO2, hydrogen H2, water vapor H2O, hydrogen cyanide HCN, cyanotic oxide CNO, ammonia NH3, nitric oxide NO, nitrous oxide N2O, nitrogen N2, sulfur dioxide SO2, and oxygen O2). The coal combustion reactions of coal devolatilization, carbon combustion, and volatile combustion can be expressed as dry coal → char + volatile + ash

(R2) (R3)

1 O2 → CO2 2

(R4)

CO +

CH4 + C2 H6 +

3 O2 → CO + 2H 2O 2 5 O2 → 2CO + 3H 2O 2

1 O2 → CNO 2

(R8)

CNO +

1 O2 → NO + CO 2

(R9)

CNO + NO → N2O + CO

(R10)

NH3 +

5 3 O2 → NO + H 2O 4 2

(R11)

NH3 +

3 1 3 O2 → N2 + H 2O 4 2 2

(R12)

The generated NOx in CFB will continue reacting and be reduced to N2. Hence, it plays a crucial role on controlling the NOx emissions process by studying the reaction mechanism of NOx. The detailed reactions are considered as reactions R13−R19.

(R1)

C(s) + CO2 (g) → 2CO(g)

HCN +

The NH3 can react with O2 directly under sufficient oxygen conditions. The nitrogen in NH3 can convert into NO or N2 according to the proportion of NH3 and O2. The corresponding reactions are considered as reactions R11 and R12:

⎛ ⎛2 ⎞ 1 2⎞ O2 (g) → ⎜2 − ⎟CO(g) + ⎜ − 1⎟CO2 (g) ⎝ ⎝κ ⎠ κ κ⎠

C(s) +

(R7)

The reaction rate of coal devolatilization reaction R1 is used by the two-equation competition model,29 which is controlled by two different parallel reaction rates for low and high temperature together. The heterogeneous reaction rates of carbon combustion reactions R2 and R3 are usually used by shrinking nuclear model, which is controlled by a mix of external diffusion, ash layer diffusion, and surface reactions.30 The volatile matter consists of CH4, C2H6, CO, CO2, H2, H2O, and so on devolatilized by raw coal. The homogeneous reaction rates of volatile combustion reactions R4−R7 include two parts, filtered reaction rates, and SGS reaction rates. The filtered reaction rates are calculated by the Arrhenius equation,31−33 and the SGS reaction rates are modeled by the reversed EDC submodel. 3.1. NOx Emissions Model. The sulfur and nitrogen in the coal are mostly released as volatile during coal devolatilization, and a small amount is also retained in the char according to the different type of coal.2 In this paper, it is considered that the nitrogen and sulfur are all released as volatile. The mechanism of NOx formation is complex. At the beginning, the dominant source of NOx is HCN and NH3 combustion. The HCN can convert into CNO quickly under sufficient oxygen conditions, while CNO is only an intermediate product, which will further react with oxygen to produce NO and CO. When the concentration of NO reaches a certain level, the NO will react with CNO to produce N2O and CO. The corresponding reactions are considered as reactions R8−R10:

2.2. SOM of Particles Model. On the basis of the SOM model for gas−solid flow simulations,24 the SOM of particles equations are presented for the gas−solid reacting flow. The governing equations and the species equation of particles are given as follows: ∂ ∂ (αsρs ) + (αsρs usi) = Ssg ∂t ∂xi

1 O2 → H 2O 2

1 N2 + O2 2

(R13)

1 1 1 C → N2 + CO2 2 2 2

(R14)

NO + C →

NO +

(R5)

(R6) 2229

NO + CO →

1 N2 + CO2 2

(R15)

NO + NH3 +

1 3 O2 → N2 + H 2O 2 2

(R16)


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N2O + C → N2 + CO

(R17)

N2O + CO → N2 + CO2

(R18)

1 O2 → N2 + O2 2

(R19)

N2O +

located at 0.36 m above the distributor. The initial bed is filled with ash particles and limestone particles with a static height of 0.4 m, where the concentration of particles is 0.55. Fuel particles are supplied from the left inlet with a feeding rate of 7.28 kg/h, and the circulating particles are fed from the recirculating inlet. In this simulation, it is assumed that the mass flow at the recirculating inlet is equal to that at the outlet of the riser. Initially, the simulations start with a minimum fluidization velocity. The initial temperature is 1150 K. The boundary condition proposed by Johnson and Jackson is applied at the walls.38 It is assumed that there is no transfer of gas and solids across the bottom of the distributor. Considering the heat loss of the reaction process, the wall is assumed to be isothermal. The computation conditions and parameters can be found in Table 1.

All the filtered reaction rates of NOx emissions are determined by the Arrhenius equation, and details can be found in refs 34 and 35. For the NOx emission process, the reactions R8−R12, R15, R16, R18, and R19 are all homogeneous reactions of gas and consider the SGS reaction rates. Reactions R13, R14, and R17 are heterogeneous reactions and do not consider the SGS reaction rates. 3.2. Sulfur Emissions Model. Volatile-S is released as SO2 during devolatilization, and it will cause serious environment pollution. There are generally three kinds of methods for desulfurization, precombustion, combustion, and postcombustion. The combustion desulphurization method by means of the desulphurization agent during combustion process is widely used with the benefits of simplicity and low cost. The main component of desulfurization agent is currently calcium carbonate. The SO2 will become sulfate by reacting with calcium carbonate. Meanwhile, CaCO3 will also absorb a little SO2. The main reactions are considered as follows: CaCO3 → CaO + CO2

Table 1. Parameters Used in the Simulations parameters height of bed, H diameter of bed, D superficial velocity of gas, ug coal feeding rate, Gs diameter of coal particles, ds1 diameter of desulfurizer particles, ds2 density of coal particles, ρs1 density of desulfurizer particles, ρs2 excess air, EA calcium to sulfur ratio, Ca/S initial bed temperature, T0 restitution coefficient of particles, e restitution coefficient of wallparticles, ew number in z-direction × grid size

(R20)

1 CaO + SO2 + O2 → CaSO4 2

(R21)

1 CaCO3 + SO2 + O2 → CaSO4 + CO2 2

(R22)

where the corresponding reaction rates can be found in refs 34 and 36. For the SO2 emission process, the reactions R20−R22 are all heterogeneous reactions and do not consider the SGS reaction rates.

number in x-direction × grid size

4. COMPUTATIONAL RESULTS AND DISCUSSION 4.1. Initial and Boundary Conditions. In this study, a 50 kW pilot CFB combustor by Topal is adopted as the objective of the simulation as shown in Figure 1.37 The primary air is supplied from the distributor at the bottom of the bed with a superficial velocity of 3.6 m/s, and the secondary air inlets are

experiment

simulation

1.8 0.125 3.6 6−7.7 0.03−0.9 0.71

1.8 0.125 3.6 7.28 0.65 0.71

m m m/s kg/h mm mm

unit

1374 1730

1374 1730

kg/m3 kg/m3

1.2 2.0 1133−1173

1.2 2.0 1150 0.97

K

0.9 80 × 0.005 140 × 0.01 25 × 0.005

m m m

The simulations are performed using a revised CFD code LES-SOM-FIX, which is on the basis of the K-FIX CFD code.39 The numerical scheme of implicit continuous approach is used in the LES-SOM-FIX code. It is important for LES to investigate the influence of grid size on simulation results, and three different grid sizes are tested preliminarily. The concentrations of particles along height of the CFB combustor with three different grid sizes are shown in Figure 2. Detailed grid size can be found in Table 2. The result indicates the coarse grid size has a serious discrepancy, while the difference between the medium and fine grid size is not obvious. Considering the effects of computation time and accuracy requirements, the medium grid size is selected in this simulation. The time step is adaptive in the range of 1 × 10−5 to 1 × 10−4 automatically. The simulation in this study is performed for 50 s, and variables are time-averaged for the final 20 s. 4.2. Model Validation. Figure 3 shows the time-averaged radial distribution of concentration and axial velocity of particles at the superficial gas velocity and solid mass flux of 7.76 m/s and 151.6 kg/m2 s from the riser by Herbert et al.40 Both the simulations by means of laminar flow for gas and experimental data from Herbert et al. are also given. For

Figure 1. Structure scheme of CFB. 2230


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Figure 2. Predicted axial concentration at three different grid sizes. Figure 3. Comparison of simulated concentration and velocity of particles with Herbert et al. experiments.

profiles of concentration of particles, both simulation and experiment show high concentrations of particles near the wall and low values in the center. The predictions by simulation agree with experimental data in the center, but the LES-SOM model gives a higher prediction than laminar flow of the gassecond order moment of particles model (LAM-SOM model) and agrees with experiments better near the wall. For profiles velocity of particles, the simulations with the LES-SOM model agree with experiments well, while the simulations with the LAM-SOM model appear lower in the center and higher near the wall due to no consideration of turbulence influence. Figure 4 shows the instantaneous molar fraction of CO, CO2, and O2 outlet during coal combustion. As can be seen from the figure, the changes of gas molar fraction fluctuate significantly at the beginning, while they tend to be stabilized after 20 s, which indicated that the quasi-steady state has been reached and timeaveraged variables from 30 s to 50 s are reasonable for the simulated cases. Figure 5 displays a comparison of simulated molar fraction of SO2 gas and NOx gas to experimental data along the riser. The peak values of SO2 and NOx occur near the coal feeding inlet due to coal devolatilization. The molar fraction of SO2 is decreased upward for desulfurization. The molar fraction of NOx gradually decreases along the riser with producing and reducing dynamically. The simulations are in good agreement with experimental data. Figure 6 shows a comparison of the simulated molar fraction of gas species to experimental data from the outlet of the riser reactor. The simulations without the EDC submodel are also given in Figure 6. For SO2 gas species, the simulations are higher than experimental data. The error of present simulation is about 4.14%. The simulation of the molar fraction of SO2 gas using the EDC submodel is lower and in better agreement with experimental data. Homogeneous reactions of gas consist of volatile combustion and NOx emissions, which make the volume of gas increased, and the total number of product moles is larger than reactants. The subgrid reaction model considers the effect of the reaction in SGS reasonably, which makes the reaction process accelerated and the gas volume in the furnace

Figure 4. Changes of the gas CO, CO2, and O2 molar fraction at the furnace outlet with time.

Figure 5. Comparison of simulated SO2 and NOx molar fraction along the furnace with Topal et al. experimental data.

Table 2. Grid Sizes Tested in the Simulations height of bed

0−0.4m

0.4−1.8m

coarse grid size medium grid size fine grid size

12.5 mm (radial) × 10 mm (axial) 5 mm (radial) × 5 mm (axial) 2.5 mm (radial) × 2.5 mm (axial)

12.5 mm (radial) × 20 mm (axial) 5 mm (radial) × 10 mm (axial) 2.5 mm (radial) × 5 mm (axial)

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the reactor, then fall back into the riser through recycle inlet, and complete a cycle of coal particles. The main source of desulfurizer particles consists of two parts, initially stacked in the bed and added to coal particles during the recycle process. However, the amount of desulfurizer particles is much smaller than that of coal particles. The instantaneous concentration of desulfurizer particles has the same distribution as coal particles, which illustrates that two kinds of particles are mixed sufficiently. Figure 8 shows the typical core-annular flow structure that the solid concentration is high near the wall and low in the

Figure 6. Comparison of simulated SO2 and NOx molar fraction at the furnace outlet with Topal et al. experimental data.

increased. When the formation and absorption of SO2 gas is constant, the molar fraction of SO2 gas is relatively lower. For NOx gas species, the simulation results are lower than the experimental data, which may be due to that the generation of NO2 gas during the NOx emission process is not considered. The error of present simulation is about 9.52%, while the error of simulation without EDC submodel is about 12.38%. Because the reaction rates of NOx gas generated by CNO or NH3 combustion are faster using the EDC submodel, the CNO and NH3 gas are transformed more completely, and the molar fraction of NOx is higher. 4.3. Flow Characteristics. Figure 7 shows instantaneous concentration of particles at 30 s and 35 s in the riser. The first

Figure 8. Distribution of time-averaged concentration and axial velocity of particles.

center, while the velocity of particles is low near the wall and high in the center. The concentration of coal particles is far higher than that of desulfurizer particles, which indicates that the coal particles are dominant in the combustion process. However, the velocity of coal particles is similar and only a little higher than desulfurizer particles, which indicates that the two kinds of particles are mixed sufficiently. Figure 9 shows the distribution of normal second-order moments Mxx and Mzz. The values of a normal second-order moment along the axial direction Mzz are larger than that of Mxx. Roughly, both Mzz and Mxx are large near the wall and low in the center. The peak of second-order moments appears close to the wall, which means an increase of the fluctuating of particles near the wall due to the entry of secondary air. The

Figure 7. Instantaneous concentration of particles in the riser.

component of particles represents fuel particles of coal, and the second component represents desulfurizer particles. In the bottom region, particles are easy to form clusters and attach near the wall. The clusters move upward and change continuously and are broken up into disperse particles gradually along the riser. The instantaneous concentration of coal particles has the same distribution as total particles, which illustrates that the movement of coal particles plays a dominant role in the riser. The concentration of coal particles is high and a part of clusters are stacked near the coal feeding inlet and recycle inlet. Most of coal particles are concentrated in the bottom, while only few particles are driven by gas and outflow

Figure 9. Distribution of time-averaged second-order moment of particles. 2232


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oxide generated by calcinations will absorb part of the SO2, which leads to the decrease of the SO2 molar fraction along the reactor. Figure 12 shows the radial distribution of the molar fraction of NO and N2O gas at different heights. The distribution of the

second-order moments of coal particles are similar with that of disulfurizer particles and a little less numerically. Because the coal particles are easier to form clusters, while the desulfurizer particles consist of dispersed particles mostly. The dispersed particles are easier to control and enhance fluctuating. 4.4. Reaction Characteristics. Figure 10 shows the instantaneous molar fraction of NO and N2O from 30 s to

Figure 12. Distribution of time-averaged molar fraction of NO and N2O gas at different heights.

molar fraction of N2O gas is similar with that of NO gas and 1 order of magnitude smaller. The molar fractions of NO and N2O decrease along the height, and there is a higher fraction on the left sides due to the effect of the coal feeding inlet. Figure 13 shows the distribution of reaction rates for reactions R9 and R15 with the concentration of total particles.

Figure 10. Instantaneous molar fraction of NOx gas.

50 s. From Figure 10, the distribution of NO and N2O is more similar, and the molar fraction of N2O is 1 order of magnitude lower than that of NO. The peak values of molar fraction of NOx appear near the coal feeding inlet owing to coal devolatilization. The volatile gas includes HCN and NH3. HCN is rapidly converted into CNO by an oxidation reaction. CNO and NH3 are consumed by oxygen and produce NO. Meanwhile, CNO can also react with NO into N2O. So, NOx (NO and N2O) is generated. Along the height of the reactor, generated NOx gas may react with reduced gas and produce N2, which makes a reduction of the molar fraction of NOx. Figure 11 shows the instantaneous molar fraction of SO2 from 30 s to 50 s. The SO2 is produced by coal devolatilization, so the molar fraction is high near the coal feeding inlet. With disulfurizer particles added, calcium carbonate and calcium

Figure 13. Chemical rates of reactions R9 and R15 as a function of particle concentrations.

The reaction R9 indicates the NO generation process, and the reaction R15 indicates the NO reduction process. Figure 14 shows the distribution of reaction rates of reactions R10 and R18 with the concentration of total particles. The reaction R10 indicates the N2O generation process, and the reaction R18 indicates the N2O reduction process. The total reaction rates, SGS reaction rates, and the reaction rates without the EDC submodel are all given. From Figures 13 and 14, we can observe that the three kinds of rates have the same tendency. The reaction rates without the EDC submodel are lower than the total reaction rates, and the SGS reaction rates account for 22% of the total reaction rates. For the NOx generation process, the reaction rates of reactions R9 and R10 increase with the

Figure 11. Instantaneous molar fraction of SO2 gas. 2233


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increasing concentration, which indicates that the reaction rates of the NOx generation process are fast when the content of carbon is increased. For the NOx reduction process, the reaction rates of reactions R15 and R18 first increase seriously, reach the peak when the concentration of particles is about 0.03, and then decrease with the concentration increased gradually. This is attributed to the molar fraction of NOx reaching a certain high level at the top of the reactor where the solid concentration is lower, and a high level of NOx enhances the NOx reduction reaction process. NOx is mainly generated at the bottom region where the solid concentration is high. Figure 15 shows the radial distribution of molar fraction of SO2 and mass fraction of CaSO4 at different heights. From the

reaction rates without the EDC submodel has the same tendency with that using the EDC submodel, but smaller than that using EDC submodel, and account for about 80% of the reaction rates with SGS reaction rates. The difference indicates that increasing homogeneous reaction rates of gas will also affect the heterogeneous reaction rates of gas−solid two-phase. The increasing volatile combustion reaction rates will promote the Volatile-S to convert into SO2. The increase of the generation of SO2 will accelerate the reaction rates of absorption of SO2. Hence, increasing homogeneous reaction rates will influence the heterogeneous reaction rates indirectly. The distribution of the reaction rate of reaction R20 shows the “parabolic” type with the concentration of particles increasing, which increases and reaches the peak and then decreases gradually. The reaction of calcination of the limestone process will be inhibited due to the effect of clusters when the concentration of particles is too high. The reaction rate of reaction R21 has the same distribution with the reaction rate of reaction R20, because the mass fraction of CaO is directly influenced by the reaction rate of reaction R20.

5. CONCLUSIONS The LES-SOM model on the basis of the two-fluid model is extended into the gas−solid reacting flow field. Considering the influence of particles, the EDC submodel is developed for the gas−solid reaction process in CFB. The present model is verified by experiments, and the simulations are in good agreement with experimental data. The flow characteristics including the concentration, velocity, and second-order moment of particles are studied. The typical “core-annular” flow structure in the riser can be captured. Both coal particles and desulfurizer particles are mixed sufficiently. The velocity fluctuation of particles is enhanced for the combustion process, and the velocity fluctuation in the axial direction Mzz is about 2 times higher than that in radial direction Mxx. The reaction characteristics including concentrations of gas species and the distribution of chemical reaction rates with concentration of particles are studied. The simulations with the EDC submodel are closer to experiments. The simulations with the EDC submodel not only improve the homogeneous reactions of gas but also influence the heterogeneous reactions of gas−solid two-phase reaction. NOx is mainly produced at the bottom of the riser, and along the riser height, reduction

Figure 15. Distribution of the time-averaged molar fraction of SO2 gas and mass fraction of CaSO4.

figure, the molar fraction of SO2 is high near the coal feeding inlet. The generated SO2 can be absorbed by CaO and CaCO3, and correspondingly the mass fraction of CaSO4 is increased. Both the molar fraction of SO2 and the mass fraction of CaSO4 are decreased along the riser height with the reaction in progress. Figure 16 shows the distribution of reaction rates of reactions R20 and R21 with the concentration of total particles. Reaction R20 is calcinations of limestone process, and the reaction R21 represents the SO2 absorbed process. Both the reaction rates with the EDC submodel and without the EDC submodel are given. From Figure 16, we can observe that the distribution of 2234


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reactions gradually dominate. The molar fraction of N2O gas is approximately 1 order of magnitude smaller than that of NO gas. The SO2 gas can be absorbed by desulfurizer particles in the reactor, but desulfurization effect will be weakened when the concentration of particles is higher.

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AUTHOR INFORMATION

Corresponding Author

*Phone: +0451-8639-0550. Fax: +0451-8639-0550. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was financially supported by Program for New Century Excellent Talents of Heilongjiang Grant No. 1252NCET-017, the Key Program of National Natural Science Foundation of Heilongjiang Grant No. ZD201309, and the project supported by the Major International Joint Research Program of China (Grant No. 2014DFA70400).

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NOMENCLATURE C = particle fluctuating velocity (m s−1) ds = particle diameter (m) D = diffusion coefficient (m2 s−1) e = restitution coefficient g = gravity (m s−2) G = mass flow rate (kg m−2 s−1) hsg = heat transfer coefficient (W m2− K−1) H = enthalpy (J kg−1) k = turbulent kinetic energy (kg m−1 s−1) m = mass (kg) M = second-order moment (m2 s−2) p = pressure (Pa) R = reaction rates (kmol m−3 s−1) S = mass transfer (kg m−3 s−1) T = temperature (K) u = velocity (m s−1) Y = mass fraction

Greek Letters

α = volume fraction β = drag coefficient (kg m−3 s−1) χ = source term for collisional rate (kg m−1 s−3) ε = turbulent dissipation (kg m−1 s−3) γ* = mass fraction in fine structure λ = thermal conductivity of mixture (W m1− K−1) μ = viscosity (Pa s) ρ = density (kg m−3) τ = stress tensor (Pa) τ* = residence time scale in fine structure υ = stoichiometric coefficient Ξ = transport of momentum by velocity fluctuations and collisions (kg m−1 s−2)

Subscripts

g = gas phase s = particles phase n = the nth species sgs = subgrid scales

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REFERENCES

(1) Shimizu, T.; Satoh, M.; Fujikawa, T.; Tonsho, M.; Inagaki, M. Energy Fuels 2000, 14, 862−868. 2235


Analysis of SO2 and NO x Emissions Using Two-Fluid Method

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