Numerical Analysis on Microscopic Characteristics of Pulverized Coal

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Numerical Analysis on Microscopic Characteristics of Pulverized Coal Moderate and Intense Low-Oxygen Dilution Combustion Xudong Jin and Yuegui Zhou* Institute of Thermal Energy Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China ABSTRACT: Moderate and intense low-oxygen dilution (MILD) combustion is regarded as a new clean combustion mode, which can simultaneously improve combustion efficiency and decease NOx emission. The computational fluid dynamics (CFD) modeling on pulverized coal MILD combustion was conducted to simulate the flue gas velocity, temperature and species concentration fields with two turbulence−chemistry interaction models, which were well-validated by the experimental data of International Flame Research Foundation (IFRF) furnace no. 1. Then, macro- and microscopic characteristics of pulverized coal MILD combustion were quantitatively analyzed to emphasize the unique MILD combustion regime compared to the conventional flame combustion. The eddy dissipation concept (EDC) model with a four-step global reaction can well reproduce turbulence−chemistry interaction behavior of pulverized coal MILD combustion. Strong turbulent mixing and entrainment of hot flue gases is found in the furnace because of high momentum secondary air jets. The internal flue gas recirculation ratio in the furnace is over 5, which makes local oxygen concentrations lower than 5% before the coal devolatilization proceeds and makes the fuel temperature higher than its autoignition temperature. Furthermore, the pulverized coal MILD combustion regime is first depicted with the calculated Damköhler number and Karlovitz number on the basis of different regimes of turbulent nonpremixed flames. The numerical results confirm that pulverized coal MILD combustion is in a slow chemistry regime (DaI < 10 and Ka ≫ 1) and disperses throughout the whole furnace volume. Pulverized coal MILD combustion is a unique combustion mode with strong turbulent mixing and entrainment, high internal flue gas recirculation ratio, and slow reaction rate under a low local oxygen concentration with respect to the traditional flame combustion mode.

1. INTRODUCTION Moderate and intense low-oxygen dilution (MILD) combustion1 is regarded as a new combustion technology, which can simultaneously improve combustion efficiency and decease NOx emission. According to the definition of MILD combustion by Cavaliere and de Joannon,1 two prerequisites are required: (1) the initial temperature of the fuel mixture is higher than its autoignition temperature, and (2) the maximum allowable temperature increase with respect to the initial temperature is lower than the fuel autoignition temperature during the combustion process. Many experimental and numerical investigations2−6 have shown that the MILD combustion characteristics were obviously different from the traditional combustion regime with a small temperature gradient, low oxygen concentration, slow reaction rate, and large reaction volume in the past few decades. MILD combustion of different fuels was experimentally performed in a 0.58 MW furnace facility by the International Flame Research Foundation (IFRF).7,8 The results indicated that MILD combustion took place throughout the whole furnace volume and the flue gas temperature, heat flux, and gas component fields were uniform because of strong turbulent mixing and entrainment of internally recirculated high-temperature flue gas. Suda et al.9 experimentally investigated pulverized coal MILD combustion characteristics in a 250 kW furnace and demonstrated that ignition delay decreased with the increasing air temperature because of higher particle heating rates and more rapid devolatilization. Mi et al.10,11 carried out some experiments on MILD combustion of different gas fuels at a laboratory-scale MILD combustion furnace, and the premixed MILD combustion © 2015 American Chemical Society

was realized without air preheating, which was dominated by the internal flue gas recirculation. Pulverized coal MILD combustion was performed in a self-recuperative furnace by Saha et al.,12 and the results indicated that the temperature distribution was uniform and no visible flame could be observed throughout the furnace. Kim et al.13 numerically simulated pulverized coal MILD combustion for the IFRF experiments7,8 with the eddy dissipation concept (EDC), and the predicted results gave good agreement with the measured temperatures and species concentrations. Schaffel et al.14 simulated pulverized coal MILD combustion for the same experiments with the eddy dissipation model (EDM) for volatile combustion and char combustion intrinsic reactivity model. The results showed that the uniform temperature distribution and chemistry fields could be observed and slow combustion could occur throughout the whole furnace. Many investigations indicated that the EDC model provided a relatively accurate and practical tool to predict the turbulent and chemical characteristics of pulverized coal MILD combustion.15−18 Aminian et al.19 used different kinetic schemes of the EDC model to investigate the turbulence−chemistry interaction of MILD combustion at jet-in-hot co-flow burner. The results indicated that the reaction rate was slower because of more uniform species and temperature in MILD combustion with respect to the conventional diffused or premixed flames. Galletti Received: January 14, 2015 Revised: April 9, 2015 Published: April 9, 2015 3456

DOI: 10.1021/acs.energyfuels.5b00088 Energy Fuels 2015, 29, 3456−3466

Article

Energy & Fuels et al.20 performed the computational fluid dynamics (CFD) modeling on a methane MILD combustion burner with internal recirculation of exhaust gases. The turbulence and chemical time scales were analyzed to confirm that the high-temperature region in the methane MILD combustion regime was characterized by Damköhler number, which was low and increased with the enhancement of internal flue gas recirculation. As mentioned above, many researchers have experimentally and numerically investigated the macroscopic characteristics of MILD combustion, such as the flue gas velocity, temperature and species concentration distributions, and internal flue gas recirculation ratio.7−9,12−16 However, the microscopic characteristics of MILD combustion were scarcely elucidated, especially for pulverized coal MILD combustion, such as the turbulence and chemical time scales, Damköhler number, Karlovitz number, and combustion regime. The objective of this work is to simulate the pulverized coal MILD combustion process with EDC model and EDM for the IFRF experimental facility and to emphasize on analyzing the microscopic characteristics of pulverized coal MILD combustion. The pulverized coal MILD combustion regime is first depicted with the calculated Damköhler number and Karlovitz number on the basis of different regimes of turbulent non-premixed flames, and pulverized coal MILD combustion is characterized as a unique combustion mode with strong turbulent mixing and entrainment, high internal flue gas recirculation ratio, and slow reaction rate under a low local oxygen concentration compared to the traditional flame combustion mode.

Table 1. Experimental Conditions of the IFRF Furnace No. 114

coal primary air secondary air

mass flow (kg/h)

velocity (m/s)

temperature (K)

66 130 675

26 26 65

313 313 1623

composition (wt %, wet) O2, 23%; N2, 77% O2, 23%; H2O, 9.5%; CO2, 12.5%; N2, 56%

the oxygen concentration of 21 vol %. The secondary air inlet velocity in the burner is 65 m/s, and the primary air inlet velocity is 26 m/s. The experiments were conducted at the furnace wall temperature of 1273 K, and the flue gas velocities, temperatures, and species distributions were measured at seven traverses, which were located 0.15, 0.44, 0.735, 1.32, 2.05, 3.22, and 4.97 m away from the burner tip.8 Table 2 lists the proximate and ultimate analyses of bituminous coal “Guasare” used in the experiments.16

Table 2. Proximate and Ultimate Analyses of Guasare Coal16 proximate analysis

(wt %)

ultimate analysis

(wt %, daf)

volatile matter fixed carbon moisture ash LHV (MJ/kg)

37.1 56.7 2.9 3.3 31.74

C H O N S

78.41 5.22 10.9 1.49 0.82

3. MATHEMATICAL MODELS The pulverized coal MILD combustion model was adopted to simulate the IFRF furnace no. 1 with the commercial Fluent 6.3 software, including gas−solid two-phase turbulent flow, coal pyrolysis, and homo- and heterogeneous chemical reaction submodels, which are briefly described as follows. 3.1. Coal Pyrolysis. The chemical percolation devolatilization (CPD) model is adopted to represent the devolatilization process of rapidly heated coal, which assumes the coal structure as a simplified lattice of chemical bridges that link the aromatic clusters.14 Figure 2 gives the chemical reaction scheme of the coal

2. DESCRIPTION OF THE IFRF FURNACE NO. 1 The schematic geometry of IFRF furnace no. 1 simulated in this paper has a cross-section of 2 × 2 m with a length of 6.25 m, as shown in Figure 1.7,8 The burner has a high-speed secondary air nozzle and two primary

Figure 2. Scheme of the coal devolatilization process.

devolatilization process, including the abruption of bridges and the generation of pyrolysis products.14 £ is the labile bridge, which detaches to form the reactive bridge £*. It can be cleaved by two competing pathways for £*, which forms char bridge c and light gas g2 in one pathway or forms side chains δ in another pathway. The side chains eventually decompose and form light gas g1. The CPD model can accurately predict the devolatilization rate and composition, including heavy hydrocarbons (tar) and light gases and hydrocarbons (CH4, CO, H2, CO2, H2O, etc.).14 Tar further decomposes to generate soot and some light gases (CO and H2). The parameters of the CPD model for Guasare coal are obtained from ref 16. 3.2. Turbulence Flow and Turbulence−Chemistry Interaction. The realizable k−ε model21 is used to predict the

Figure 1. Schematic geometry of the IFRF furnace no. 1. air (coal and transport air) nozzles, which are located 0.28 m away from the burner center, and the nozzle diameters are 0.125 and 0.0273 m, respectively. The MILD combustion experiment was performed in a 0.58 MW furnace facility, and the experimental conditions are shown in Table 1.14 The secondary air jet was heated in advance to the temperature of 1623 K through a precombustor of natural gas combustion, and some amount of pure oxygen was added to maintain 3457


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Energy & Fuels gas-phase turbulent flow, which is different from the standard k−ε model in the fields of the ε equation and eddy viscosity constant Cμ. The modified source term of the ε equation is used to solve the spreading rate of round jets, and the constant Cμ can guarantee the realizability effect, which is relative to mean strains and rotation rates. The model has been widely adopted to predict turbulent flow performance for different kinds of flows, such as rotation flow and strong recirculation flow. Two turbulence−chemistry interaction models for volatile matter combustion are adopted in this work. One is the EDM, which assumes infinitely fast chemistry. The gas-phase reaction rate is determined by the characteristics of turbulent mixing and is positively related to the dissipation rate. Therefore, the model can handle only one- or two-step global kinetic mechanisms and cannot predict kinetically controlled components. Two-step global reactions are used to describe combustion of the volatiles.14

where C1 is the mass diffusion-limited rate constant, T∞ is the bulk temperature, dp is the particle diameter, ρp is the char apparent density, AG is the specific internal surface area, Ai is the pre-exponential factor, Ei is the activation energy, and η is the effectiveness factor, which can be calculated by eq 414 η = 3(Φ coth Φ − 1)/Φ2

(4)

where Φ is the Thiele modulus Φ = 0.5d p[S bρp A GAj exp(−Ei /RTp)pox /(Deρox )]0.5

(5)

where pox is the oxidant partial pressure in the bulk gas, ρox is the oxidant density, Sb is the stoichiometric coefficient of the char oxidation reaction, and De is the effective diffusion coefficient in the particle pores, which can be calculated by eq 6 in ref 14 and is relative to the char porosity θ, tortuosity τ, and the mean pore radius rp. The parameters for the char combustion intrinsic model of Guasare coal are shown in Table 3.14 The discrete

Cx HyOz + (x /2 + y/4 − z /2)O2 → xCO + y/2H 2O

Table 3. Parameters for the Intrinsic Char Combustion Model of Guasare Coal14

(R1)

CO + 1/2O2 → CO2

(R2) 22

Another model is the EDC model, which can consider more kinetic mechanisms and is appropriate to couple the turbulence and chemistry with respect to the EDM. The reactions take place in small turbulent structures assumed to be homogeneously mixed in Kolmogorov scale regions, which are responsible for turbulent dissipation into heat.19 Jones and Lindstedt et al.23 proposed a four-step global reaction mechanism for six species. CH4 + 1/2O2 → CO + 2H 2

(R3)

CH4 + H 2O → CO + 3H 2O

(R4)

CO + H 2O → CO2 + H 2

(R5)

H 2 + 1/2O2 → H 2O

(R6)

(1)

(2)

and R0 is the chemical reaction rate, which is controlled by the intrinsic chemical reaction and pore diffusion rates R 0 = ηd pρp A GAi exp( −Ei /RTp)/6

value

unit

C1 Ai Ei θ rp AG τ

5 × 10−12 1 × 10−3 5 × 107 0.74 1 × 10−7 2.5 × 104 1.414

m3/(K0.75s) kg/(m2s) J/kmol m m2/kg

4. RESULTS AND DISCUSSION One quarter of the IFRF furnace no. 1 was simulated as a result of the symmetry with 400 000 hexahedral cells, which was fine enough to obtain the calculated results independent of the cell sizes. The numerical results were well-verified by the IFRF experimental data,7,8 and the macro- and microscopic characteristics of pulverized coal MILD combustion were quantitatively analyzed to indicate the inherent MILD combustion features. 4.1. Flue Gas Velocity. The predicted flue gas velocity profiles at different traverses are compared to the experimental data, as shown in Figure 3. The predicted gas velocity profiles correspond well with the experimental data, expect for the central jet zone near the burner tip. The primary and secondary air jets keep high velocities near the burner region, and then the strong and weak jets begin to merge into a stream downstream of the third traverse, with their velocities gradually decreasing as a result of the strong mixing and entrainment of hot flue gases into the jets. The gas velocity profiles become flat in the fully development zone far away from the burner. 4.2. Flue Gas Temperature. Figure 4 illustrates the predicted flue gas temperature profiles at different traverses with EDC model and EDM compared to the experimental data. The temperature of the lateral primary air jet is rather low at the first and second traverses because of low initial temperature, which is not observed by the measurements. Then, the primary air jet is heated by the recirculated hot flue gas, and the coal particles ignite and combust after the second traverse when the particle temperature exceeds its ignition temperature. The flue

where D0 is the diffusion coefficient, which is expressed as follows: D0 = C1[(Tp + T∞)/2]0.75 /d p

symbol

ordinates (DO) radiation model is adopted to solve the radiation transfer equation throughout the furnace with a weighted sum of gray gas model (WSGGM), and the scattering has been omitted.

3.3. Coal Particle Tracking. The coal particles are injected into the combustion chamber and are tracked to calculate the particle trajectories by a discrete phase model, which can exchange mass, momentum, and energy with the fluid phase. In the stochastic tracking approach, the discrete phase particle trajectories are computed by integrating the trajectory equations for a single particle. The size distribution of coal particles ranges from 10 to 300 μm and 80% less than 90 μm and are classified into six size groups with the mean diameter of 42 μm and the spread parameter of 1.36.14 3.4. Heterogeneous Chemical Reactions. The char combustion intrinsic reactivity model based on the model by Smith assumes that the heterogeneous chemical reaction rate Rs is dominated by both the oxidant diffusion to the particle surface and the intrinsic chemical kinetics,14,24 which can be calculated by eq 1 R s = R 0D0 /(R 0 + D0)

parameter mass diffusion-limited rate constant pre-exponential factor activation energy char porosity mean pore radius specific internal surface area tortuosity

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Figure 3. Predicted flue gas velocity profiles at different traverses compared to the experimental data.8

Figure 4. Predicted flue gas temperature profiles at different traverses compared to the experimental data.8

gas temperature profiles are flat after the fifth traverse with the burnout of the coal particles. The flue gas temperature contours at the horizontal crosssection y = 0, and the axial temperature and temperature gradient distributions with EDC model and EDM at z = 0.18 m line can be seen in Figure 5. The peak gas temperature is located toward the central secondary jet because the primary air jet deflects toward it with the action of the high momentum secondary jet. The numerical results also show that the peak gas temperature of the

EDM is higher than that of the EDC model. At the same time, larger gas temperature gradients are observed in the volatile combustion zone because of the higher reaction rate of volatile species for the EDM, which assumes the infinitely fast chemistry. The maximum gas temperature in the furnace is 1918 K for the EDM and 1755 K for the EDC model, and the corresponding temperature rise in the furnace is 395 and 232 K, respectively. The results show that the calculated gas temperature for the EDC model in the furnace is more uniform than that for the EDM and 3459


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low gas temperature gradient in the furnace are predicted by the EDC model, which more accurately reflects the actual MILD combustion characteristics. 4.3. Flue Gas Components. The predicted oxygen concentration profiles at different traverses are compared to the experimental data, as shown in Figure 6. The predicted results give good agreements with experimental data, except for the results near the primary air jet. The oxygen concentrations of primary and secondary air near the burner are rather high, and they significantly decrease with the dilution of the recirculated flue gas and the oxygen consumption of coal particle combustion. The oxygen concentration is uniform and as low as 3% after the fifth traverse with the burnout of coal combustion. Figure 7 shows the oxygen concentration contours at the horizontal cross-section y = 0 and the oxygen concentration axial distributions at the z = 0.18 m line with EDC model and EDM. It is found that the actual oxygen concentration just near the MILD burner outlet is as low as 3%, although all initial oxygen concentrations of primary and secondary air streams are 21%, which reflects the diluted oxygen combustion feature of pulverized coal MILD combustion. This is because a large amount of the hot flue gas is intensively entrained by high momentum secondary air jet and the oxygen concentrations of primary and secondary air streams are significantly diluted before the ignition and combustion of coal volatile matter. The simulated results emphasize that pulverized coal MILD combustion is under the extremely diluted oxygen concentration and hot fuel−air mixture. Furthermore, the actual oxygen concentration sharply decreases with the coal volatile combustion and nearly reaches 1%. Then, the oxygen concentration increases a little with the complete combustion of the coal volatile matter and continues to decrease with the char combustion. The oxygen concentration returns with the burnout of the coal char particles. The minimum oxygen concentration for EDM is lower than that for the EDC model because the EDM

Figure 5. Flue gas temperature distributions: (a) temperature contours at the horizontal cross-section y = 0 and (b) axial temperature and temperature gradient distributions at z = 0.18 m line.

the gas temperature gradient for the EDC model is smaller than that for the EDM, especially for the early stage of volatile combustion. As a consequence, the uniform temperatures and

Figure 6. Predicted oxygen concentration profiles at different traverses compared to the experimental data.8 3460


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flue gas and a large recirculating flow region is formed outside of the jets. The flue gas cannot be entrained into the flame root because of the lateral primary air jets in the horizontal axial section in Figure 11a. However, the flue gas can be entrained into the flame root, and a larger recirculating flow region is formed outside of the central secondary air jets in the 45° sloped section, as shown in Figure 11b. The large amount of hot flue gas is recirculated to preheat the fuel−air mixture to its autoignition temperature and to dilute the primary and secondary air streams to a low oxygen concentration. The internal flue gas recirculation ratio is one of the most important parameters to characterize the macroscopic characteristics of MILD combustion. The value of the internal flue gas recirculation ratio KV is defined as follows by Wünning et al.:2 KV = Ṁ E /(Ṁ F + Ṁ A )

(6)

where Ṁ E is the mass flow rate of internally recirculated hot flue gas at each axial cross-section and Ṁ F and Ṁ A are the mass flow rates of initial fuel and initial combustion air, respectively. The value of Ṁ E at each x direction cross-section is calculated as follows:25 Ṁ E = −

∫ ∫A (y ,z) ρvx(x , y , z) dy dz x

(7)

where Ax(y, z) is the x cross-section area of the backflow region, vx(x, y, z) is the negative velocity in the x-coordinate direction in the backflow region, and ρ is the density of the gas mixture determined by the gas state equation. Figure 12 shows the variation of the internal flue gas recirculation ratio KV calculated with the EDC model. The result indicates that the recirculation ratio gradually increases with the expansion of the recirculation region and reaches the peak value at the maximum recirculation region. Then, it decreases until the chamber outlet with the attenuation of the jets. The maximum of the recirculation ratio KV is greater than 5, which is large enough to preheat the fuel−air mixture and to intensively dilute primary and secondary air streams. The result indicates that a large internal flue gas recirculation ratio because of a strong turbulent mixing and entrainment can be considered as an important macroscopic parameter to result in MILD combustion characteristics of a low oxygen concentration. 4.6. Pulverized Coal MILD Combustion Regime. MILD combustion is typically characterized by a particular kind of turbulence−chemistry interaction compared to conventional flames,20 in which higher turbulent mixing occurs in the reaction region because of the intensive jet entrainment and the strong flue gas recirculation, whereas a slower reaction rate happens because of large dilution of the reactants. Three characteristic time scales are important to characterize the turbulence−chemistry interaction in turbulent MILD combustion. The characteristic flow time τf is defined as the flow time based on the integral scale of large eddies in turbulent reacting flow,26,27 i.e.

Figure 7. Oxygen concentration distributions: (a) oxygen concentration contours at the horizontal cross-section y = 0 and (b) oxygen concentration axial distributions at the z = 0.18 m line.

is assumed as an infinitely fast combustion rate of the volatile matter. Figure 8 shows the carbon monoxide concentration contours at the horizontal cross-section y = 0 and the predicted carbon monoxide concentration profiles at different traverses compared to the experimental data. The results demonstrate that the carbon monoxide concentration peak values for the EDC model are obviously higher than those for EDM from the first traverse to the fourth traverse and correspond well with experimental data than those for EDM because the intermediate combustion products can be accurately simulated by the finite rate chemistry model. 4.4. Coal Particle Concentration and Char Burnout. Figure 9 illustrates coal particle concentration distribution at the central and horizontal sections and the trajectories of one stream of coal particles in mass. The results indicate that a portion of the coal particles can be entrained to the combustion region because of strong recirculation of high-temperature flue gas and disperse in a larger furnace volume. Figure 10 shows the numerical result of char burnout along the centerline of the fuel jet compared to the experimental data. The numerical result of the char burnout corresponds well with the experimental data. Coal char burns very quickly near the burner region, and the char burnout is about 90% when the char particles left about 2 m away from the burner tip. The residual char is completely burned out before the outlet of the furnace. 4.5. Internal Flue Gas Recirculation Ratio. Figure 11 illustrates the flue gas velocity field and the intense internal flue gas recirculation in the furnace, which influence the local oxygen concentration and gas temperature. The result shows that the secondary air jets with high velocities are injected into the confined chamber to induce and entrain a large amount of hot

τf = l0/u′(l0)

(8)

where l0 is the integral scale of large eddies in turbulent flow and u′(l0) is the turbulent velocity fluctuation. The Kolmogorov eddy time τk is defined as the flow time based on the smallest eddy length scale and represents the capacity of turbulent kinetic energy converted into fluid internal energy27

τk = (v /ε)1/2 3461

(9) DOI: 10.1021/acs.energyfuels.5b00088 Energy Fuels 2015, 29, 3456−3466

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Figure 8. Carbon monoxide concentration distributions: (a) carbon monoxide concentration contours at the horizontal cross-section y = 0 and (b) predicted carbon monoxide concentration profiles at different traverses compared to the experimental data.8

magnitude as the characteristic flow time. However, the Kolmogorov eddy time τk is 2 orders of magnitude smaller than the chemical reaction time, and the Kolmogorov eddies can penetrate into the reaction zone and, thereby, enhance heat- and mass-transfer rates, which produce more moderate temperatures in the furnace.28 Damköhler number and Karlovitz number are two important non-dimensional numbers to evaluate the turbulence−chemistry interactions in the combustion theory. The first Damköhler number DaI represents the ratio of characteristic flow time τf to chemical reaction time τc.29

where ν is the turbulent kinematic viscosity and ε is the turbulent dissipation rate. The chemical reaction time τc is a time scale based on the coal char combustion reaction rate,27 i.e. τc = mp /(A pR s)

(10)

where mp is the char particle mass, Ap is the particle surface area, and Rs is the char reaction rate calculated by the char combustion intrinsic reactivity model. Figure 13 shows different characteristic time distributions at the axial direction of z = 0.18 m line for pulverized coal MILD combustion. The result indicates that the characteristic flow time τf becomes short in the whole furnace because of strong mixing and entrainment of high momentum secondary jet. The internally recirculating hot flue gas also dilutes the oxygen concentration, which makes the chemical reaction time increase. On the whole, the chemical reaction time is the same order of

DaI = τf /τc

(11)

The second Damköhler number DaII describes the ratio of the reaction rate to the diffusion rate for the heterogeneous reaction30,31 DaII = k/αd 3462

(12) DOI: 10.1021/acs.energyfuels.5b00088 Energy Fuels 2015, 29, 3456−3466

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and widely considered as being the most accurate.34,35 According to the theory of pulverized coal combustion,33 the combustion system is kinetically controlled when the second Dahmköhler number is less than 0.11 and the system is a diffusion-controlled regime when the second Dahmköhler number is larger than 9. The combustion system is in the diffusion−kinetic-controlled region when the second Dahmköhler number is in the range from 0.11 to 9. Karlovitz number Ka is expressed as the ratio of chemical reaction time τc to Kolmogorov eddy time τk, which describes the relative chemical strength of the flame and the reaction zone thickness.28,36

Ka = τc/τk

Figure 14 shows Damköhler number Da and Karlovitz number Ka distributions for pulverized coal MILD combustion calculated with the EDC model. It is found that the value of the first Damköhler number DaI is lower than 10 and is near unity in the central reaction region, which proves that both chemical reaction and turbulent mixing control the finite reaction rate. Moreover, the value of the second Damköhler number DaII is around 0.15− 0.5 in the central reaction region, which demonstrates that the coal char reaction depends upon both the chemical reaction rate and oxygen diffusion rate, more closely approaching the kinetically controlled combustion regime. The characteristic reaction time significantly increases because of the dilution of the reactants, while the characteristic mixing time and diffusion time reduce because of the intensive hot flue gas recirculation. Therefore, the overall effect is to obtain a Damköhler number as small as possible. In addition, the Karlovitz number is much larger than 1 in the main reaction zone, which demonstrates that the Kolmogorov eddy length scale is smaller than the reaction zone thickness and the Kolmogorov eddies can penetrate into the reaction zone structure.28 This facilitates diffusion and heattransfer rate to the reaction zone, leading to the uniform combustion temperature. Thus, no reaction sheet is expected throughout the entire combustion process, and an invisible flame is formed. Therefore, it can be concluded that pulverized coal MILD combustion is more likely a well-stirred reactor, which is inherently different to traditional pulverized coal combustion. Figure 15 depicts the regime of pulverized coal MILD combustion mode according to the calculated values of Damköhler number and Karlovitz number based on different regimes of turbulent non-premixed flames.31 The turbulent Reynolds number Rel can be defined as28

Figure 9. Coal particle concentration of the MILD combustion: (a) coal particle concentration distributions at the central and horizontal sections and (b) particle trajectories of one stream of coal particles in mass.

Rel = u′(l0)l0/v

(15)

From the above calculated results, the first Damköhler number DaI is lower than 10 and near unity in the central reaction region and the Karlovitz number is much larger than 1 in the main reaction zone for pulverized coal MILD combustion. Therefore, numerical results confirm that pulverized coal MILD combustion is in a slow chemistry regime (DaI < 10 and Ka ≫ 1) and disperses in the whole furnace volume, which is significantly different from the conventional flame combustion.

Figure 10. Numerical results of char burnout along the centerline of the fuel jet compared to the experimental data.8

5. CONCLUSION Two different turbulence−chemical interaction models are adopted to simulate pulverized coal MILD combustion for the IFRF furnace no. 1. The numerical results with the EDC model and EDM are verified by the IFRF experimental data, and the inherent macro- and microscopic characteristics of pulverized coal MILD combustion are numerically analyzed, including the

where k is the reaction rate constant and αd is the mass-transfer coefficient, which is defined in eq 13 αd = NuDg /d

(14)

(13) 32

where d is the particle size, Dg is the diffusion coefficient. Nu is the Nusselt number, which is defined using that of Whitaker33 3463


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Figure 11. Flue gas velocity vector fields for the EDC model (a) at the axial section and (b) at the 45° inclined section.

Figure 13. Different characteristic time scale distributions at z = 0.18 m line for the EDC model.

Figure 12. Variation of internal flue gas recirculation ratio KV for the EDC model.

temperature by the recirculated hot flue gas. Third, pulverized coal MILD combustion regime is first depicted with the calculated Damköhler number and Karlovitz number on the basis of different regimes of turbulent non-premixed flames, and the numerical results confirm that pulverized coal MILD combustion is in a slow chemistry regime (DaI < 10 and Ka ≫ 1) and disperses in the whole furnace volume. Therefore, in comparison to the traditional combustion mode, pulverized coal MILD combustion is a unique combustion mode with strong turbulent mixing and entrainment, high internal flue gas recirculation ratio, and slow chemical reaction rate under low local oxygen concentrations.

internal flue gas recirculation ratio, the turbulence and chemical time scales, Damkö hler number, Karlovitz number, and pulverized coal MILD combustion regime. First, the numerical results show that the EDC model with a four-step global reaction can better reproduce turbulence−chemistry interaction behavior of pulverized coal MILD combustion. Second, the macroscopic characteristics of pulverized coal MILD combustion indicate that the strong entrainment and intensively turbulent mixing of hightemperature flue gas are found in the furnace because of high momentum secondary jets. The internal flue gas recirculation ratio is as high as over 5, which makes the low local oxygen concentration less than 5% before the coal devolatilization proceeds and makes the fuel heated higher than its autoignition 3464


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AUTHOR INFORMATION

Corresponding Author

*Telephone/Fax: +86-21-34207660. E-mail: [email protected]. cn. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS

This work was supported by the National Natural Science Foundation of China (51276110) and the Natural Science Foundation of Shanghai (12ZR1414600). The authors are grateful for the partial support of the projects sponsored by the Program for New Century Excellent Talents in University (NCET-10-0584) and the Chenxing Young Scholarship of Shanghai Jiao Tong University (12X100010102).

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NOMENCLATURE MILD = moderate and intense low-oxygen dilution CFD = computational fluid dynamics IFRF = International Flame Research Foundation EDM = eddy dissipation model EDC = eddy dissipation concept CPD = chemical percolation devolatilization DO = discrete ordinates WSGGM = weighted sum of gray gas model KV = internal flue gas recirculation ratio Da = Damköhler number Ka = Karlovitz number REFERENCES

(1) Cavaliere, A.; de Joannon, M. Prog. Energy Combust. Sci. 2004, 30 (4), 329−366. (2) Wünning, J. A.; Wünning, J. G. Prog. Energy Combust. Sci. 1997, 23 (1), 81−94. (3) Plessing, T.; Peters, N.; Wünning, J. G. Proc. Combust. Inst. 1998, 27 (2), 3197−3204. (4) Katsuki, M.; Hasegawa, T. Proc. Combust. Inst. 1998, 27 (2), 3135− 3146. (5) Mardani, A.; Tabejamaat, S.; Ghamari, M. Combust. Theory Modell. 2010, 14 (5), 747−774. (6) Mardani, A.; Tabejamaat, S.; Mohammadi, M. B. Combust. Theory Modell. 2011, 15 (6), 753−772. (7) Weber, R.; Smart, J. P.; Kamp, V. W. Proc. Combust. Inst. 2005, 30 (2), 2623−2629. (8) Orsino, S.; Tamura, M.; Stabat, P.; Constantini, S.; Prado, O.; Weber, R. Excess Enthalpy Combustion of Coal; International Flame Research Foundation (IFRF): IJmuiden, Netherlands, 2000; Technical Report IFRF f46/y/3. (9) Suda, T.; Takafuji, M.; Hirata, T.; Yoshino, M.; Sato, J. Proc. Combust. Inst. 2002, 29 (1), 503−509. (10) Li, P.; Mi, J.; Dally, B. B.; Craig, R. A.; Wang, F. Energy Fuels 2011, 25 (7), 2782−2793. (11) Li, P.; Dally, B. B.; Mi, J.; Wang, F. Combust. Flame 2013, 160 (5), 933−946. (12) Saha, M.; Dally, B. B.; Medwell, P. R.; Cleary, E. M. Energy Fuels 2014, 28 (9), 6046−6057. (13) Kim, J. P.; Schnell, U.; Scheffknecht, G.; Benim, A. C. Prog. Comput. Fluid Dyn. 2007, 7 (6), 337−346. (14) Schaffel, N.; Mancini, M.; Szlek, A.; Weber, R. Combust. Flame 2009, 156 (9), 1771−1784. (15) Li, P.; Wang, F.; Mi, J.; Dally, B. B.; Mei, Z. Energy Fuels 2014, 28 (3), 2211−2226. (16) Vascellari, M.; Cau, G. Fuel 2012, 101, 90−101.

Figure 14. Different dimensionless characteristic parameters for the EDC model: (a) the first Damköhler number DaI contour along the axial section, (b) the second Damköhler number DaII contour along the axial section, (c) Karlovitz number Ka contour along the axial section, and (d) Damköhler number and Karlovitz number distributions at the z = 0.18 m line.

Figure 15. Predicted pulverized coal MILD combustion regime. 3465


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Energy & Fuels (17) Vascellari, M.; Schulze, S.; Safronov, D.; Nikrytyuk, P.; Hasse, C. Proceedings of the 7th International Symposium on Turbulence, Heat and Mass Transfer; Palermo, Italy, Sept 24−27, 2012. (18) Vascellari, M.; Schulze, S.; Nikrityuk, P.; Dmitry, S.; Christian, H. Flow, Turbul. Combust. 2014, 92 (1−2), 319−345. (19) Aminian, J.; Galletti, C.; Shahhosseini, S.; Leonardo, T. Flow, Turbul. Combust. 2012, 88 (4), 597−623. (20) Galletti, C.; Parente, A.; Tognotti, L. Combust. Flame 2007, 151 (4), 649−664. (21) Shih, T. H.; Liou, W. W.; Shabbir, A.; Yang, Z.; Zhu, J. Comput. Fluids 1995, 24 (3), 227−238. (22) Magnussen, B. F. Proceedings of the 19th AIAA Meeting; St. Louis, MO, Jan 12−15, 1981. (23) Jones, W.; Lindstedt, R. Combust. Flame 1988, 73 (3), 233−250. (24) Smith, I. W. Fuel 1978, 57 (7), 409−414. (25) Cavigiolo, A.; Galbiati, M. A.; Effuggi, A.; Gelosa, D.; Rota, R. Combust. Sci. Technol. 2003, 175 (8), 1347−1367. (26) Pope, S. B. Turbulent Flows; Cambridge University Press: New York, 2000; pp 96−158. (27) Wu, Y.; Smith, P. J.; Zhang, J.; Thornock, J. N.; Yue, G. Energy Fuels 2010, 24 (2), 1170−1175. (28) Law, C. K. Combustion Physics; Cambridge University Press: New York, 2006; pp 481−512. (29) Turns, S. R. An Introduction to Combustion: Concepts and Applications, 2nd ed.; McGraw-Hill: London, 2000; pp 458−460. (30) Xu, X.; Lu, J.; Zhang, H. Combustion Theory and Combustion Equipment; Science Press: Beijing, China, 2012; pp 307−311. (31) Bird, R. B.; Stewart, W. E.; Lightfoot, E. N. Transport Phenomena, 2nd ed.; John Wiley & Sons, Inc.: New York, 2002; p 553. (32) Perry, R. H. Perry’s Chemical Engineers’ Handbook, 7th ed.; The McGraw-Hill Companies, Inc.: New York, 1997; pp 2−370. (33) Whitaker, S. Elementary Heat Transfer Analysis; Pergamon Press, Inc.: New York, 1976; p 227. (34) Sparrow, E.; Abraham, J.; Tong, J. Int. J. Heat Mass Transfer 2004, 47 (24), 5285−5296. (35) Nikrityuk, P. A.; Gräner, M.; Kestel, M.; Meyer, B. Fuel 2013, 114, 88−98. (36) Poinsot, T.; Veynante, D. Theoretical and Numerical Combustion, 2nd ed.; R.T. Edwards, Inc.: Philadelphia, PA, 2005; pp 197−203.

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Numerical Analysis on Microscopic Characteristics of Pulverized Coal

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