Oxy-Fuel Combustion Modeling: Performance of Global Reaction

Article pubs.acs.org/IECR

Oxy-Fuel Combustion Modeling: Performance of Global Reaction Mechanisms Stefan Hjar̈ tstam,* Fredrik Normann, Klas Andersson, and Filip Johnsson Department of Energy and Environment, Division of Energy Technology, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden ABSTRACT: Three global reaction mechanisms derived for oxy-fuel combustion and one global reference mechanism are investigated and compared under gaseous oxy-fuel combustion conditions. The aim is to evaluate their prediction of major inflame species and temperature by comparison with a detailed reaction mechanism (validated for oxy-fuel conditions) and experimental data. The evaluation is performed using a 1D plug flow reactor (PFR) method and 3D CFD calculations. Through the PFR calculations, it is found that the global mechanisms all predict a too early onset of fuel oxidation compared to the detailed mechanism. Furthermore, the global reference mechanism predicts gas concentrations more in line with the detailed mechanism than the oxy-fuel mechanisms, which yield incorrect reaction sequences. In the CFD analysis, significant differences in the predicted gas concentrations and temperature fields between the global mechanisms show that the choice of reaction mechanism strongly influences the results. In summary, the global reference mechanism is a preferable alternative to represent the combustion chemistry when modeling oxy-fuel combustion using CFD, if the use of a detailed reaction mechanism is prohibited due to computational limitations.

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INTRODUCTION Today, there is intense work, in both academia and industry, to find and develop efficient methods for reducing the emission of CO2 from fossil fuel combustion through carbon capture and storage (CCS). The oxy-fuel process is a promising capture technology, in which the fuel is burnt in oxygen (O2) and recycled flue gas instead of air as in conventional combustion. In this way, the flue gas is in principle free from nitrogen (N2), and it will instead consist mainly of CO2 and water vapor (H2O). The latter can easily be separated from the flue gas, to produce a CO2 rich flue gas that can be transported and stored cost-effectively. The replacement of N2 with CO2 and H2O affects the combustion characteristics, including the aerodynamics, reaction chemistry, and heat transfer. Understanding of the combustion is necessary to design oxy-fuel power plants, and the development of chemistry and heat transfer models is essential to this understanding. The gas-phase chemistry is crucial for all combustion modeling and is the focus of this paper. Modeling of heterogeneous reactions is beyond the scope of this work, although important in oxy-coal combustion. Flames burning low hydrocarbons can be modeled using computational fluid dynamics (CFD) with an applied detailed reaction mechanism, which yields valuable information on the combustion chemistry.1 However, such a mechanism is computationally demanding and therefore primarily suitable for simple combustion applications. Modeling of complex turbulent flames demands advanced turbulence and turbulence− chemistry interaction models, and achieving a converged solution in combination with a detailed reaction mechanism is not self-evident. When modeling large-scale combustion or complex flames using CFD it is instead common to apply a simplified reaction mechanism (global mechanism/scheme) to represent the combustion chemistry and thereby reduce the computational effort. Although these mechanisms strongly simplify the chemistry, since only a small number of reactants and reactions are © 2012 American Chemical Society

used, their prediction of major in-flame species can be satisfying. Global schemes are, however, limited to the specific conditions in order to be applicable. Typically, this means air-fired conditions for which most schemes have been developed. Leiser et al.2 identified the need for a gas phase chemistry model applicable to oxy-fuel conditions and proposed a new global reaction mechanism. CFD calculations including the proposed mechanism showed good agreement with measured gas concentrations, but flame temperatures were slightly underestimated and the predicted burnout of CO was too slow. In addition to this mechanism there are, according to the knowledge of the authors of the present paper, three global schemes available in the literature, which were derived for oxy-fuel conditions.3,4 Andersen et al.3 modified two global reaction mechanisms derived for air-firing, in order to better describe oxyfuel combustion conditions. The aim of their study was to improve predictions of major in-flame species and postflame equilibrium concentrations in oxy-fuel combustion. When evaluated in 2D CFD calculations, the modified mechanisms gave slightly improved predictions of the in-flame CO concentration, compared to the original schemes. Frassoldati et al.4 created a global scheme for high temperature oxy-fuel flames (T > 2500 K), since available air-derived global mechanisms tend to overestimate the temperature in such flames. The oxy-fuel scheme was developed by modifying an air-derived scheme and by adding two dissociation reactions to control the combustion temperature. Calculations of counter flow diffusion flames showed that the oxy-fuel scheme gave improved predictions of temperature and species composition, compared to the original air mechanism. Received: Revised: Accepted: Published: 10327

January 7, 2012 June 6, 2012 July 5, 2012 July 5, 2012 dx.doi.org/10.1021/ie300053t | Ind. Eng. Chem. Res. 2012, 51, 10327−10337

Industrial & Engineering Chemistry Research

Article

Figure 1. Schematic flame structure and principle mole fractions of major gaseous species along the centerline of a propane-fired nonpremixed oxy-fuel flame with 27 vol % O2 in the feed gas (dry recycling, stoichiometry 1.15). The figure is based on the results of the 1D plug flow reactor (PFR) modeling carried out in this paper.

include a detailed mechanism, which is not possible in the CFD calculations because of the required computational effort.

Air-derived global schemes have also been used to model the gas phase in oxy-fuel combustion.8,9 The global scheme of Jones and Lindstedt10 is of interest for oxy-fuel combustion, since it is the basis for all the above-mentioned oxy-fuel mechanisms. This paper aims to perform a thorough evaluation of three of the above-mentioned oxy-fuel mechanisms2−4 and to investigate their differences by • Comparing the global oxy-fuel mechanisms to a detailed reaction scheme, validated for oxy-fuel conditions, using a 1D plug flow reactor method. • Comparing the global oxy-fuel mechanisms with a global reference mechanism (valid under conventional air-fired conditions), to investigate if the oxy-fuel mechanisms are superior to the reference mechanism or if the reference mechanism is sufficiently accurate also in oxy-fuel environments. • Investigating the behavior of the global mechanisms when applied in detailed CFD simulations and comparing the results with experimental data. A gas-fired oxy-fuel flame (similar to the flame modeled in this work) may be divided into four main zones, as shown in Figure 1. The present work investigates how the global schemes describe the combustion process according to this zone approach. Each zone is dominated by different phenomena,and the four zones are characterized as I. Preflame zone. The fuel is mixed with O2 and CO2 and heated up by radiation from the downstream flame. For simplicity, perfect mixing is assumed at the end of Zone I in Figure 1. In a real flame, however, all zones can be affected by mixing. II. Fuel oxidation zone. The hydrocarbon fuel is ignited and completely oxidized into intermediate combustion products. III. Burnout zone. The intermediate products are completely oxidized into CO2 and H2O. IV. Postflame zone. The gas concentrations now remain unchanged, since the combustion process is completed. In this work, the zone approach is applied in a 1D plug flow reactor (PFR) model using a detailed mechanism6,7 to validate the performance of the global oxy-fuel2−4 and air10 schemes. The global mechanisms are then implemented in CFD calculations, and the computational results are compared with experimental data. A benefit with the 1D PFR calculations is the opportunity to

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REACTION MECHANISMS Three global reaction mechanisms2−4 (termed three-step, fourstep, and six-step) derived for oxy-fuel combustion and a global reference mechanism10 (termed the JL mechanism) are investigated and compared with a detailed reaction scheme6,7 and experimental data. Table 1 presents the reaction rate constants and the reaction orders of the global schemes for propane combustion. The rate constants (k) are expressed in the form of an Arrhenius expression as k r = AT be−E /(R gT )

(1)

where A is the pre-exponential factor, T the temperature, b the temperature exponent, E the activation energy, and Rg the universal gas constant. The molar rate of formation (R̂ ) of a species i in a reaction r is given in eq 2, where Cj,r is the molar concentration of each reactant and product species j, N the number of species in the system, ν′i,r the stoichiometric coefficient for reactant species i, and νi,r″ the stoichiometric coefficient for product species i. Furthermore, η′j,r and η″j,r are the forward and reverse rate exponents for each reactant and product species j. ∧

N

′

N

″

R̂ i , r = (νi″, r − νi′, r )(k f , r ∏ [Cj , r ]ηj ,r − kb , r ∏ [Cj , r ]ηj ,r ) j=1

j=1

(2)

All the investigated global mechanisms include reversible reactions, but the reverse rate constants are not presented in the work of Jones and Lindstedt,10 Leiser et al.,2 and Frassoldati et al.4 In a reversible reaction, the reverse rate constant kb,r is equal to the forward rate constant kf,r divided by the equilibrium constant Kr. The latter can be calculated from the change in Gibbs free energy, a calculation that some commercial CFD software are able to perform. For all the reversible reactions in this work, Kr as function of temperature was computed from the JANAF tables16 and used to derive the reverse rate constants. The JL mechanism is reported to work well for both fuel-lean and fairly fuel-rich conditions during air firing.10 Furthermore, the mechanism has predicted measured temperature and gas composition in numerous publications on conventional combustion.11−15 In the JL mechanism, R1_JL and R2_JL (Table 1) express the initial breakdown of propane. Oxidation 10328

dx.doi.org/10.1021/ie300053t | Ind. Eng. Chem. Res. 2012, 51, 10327−10337


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Table 1. Reaction Orders and Global Arrhenius Type Rate Constants (as A, Tb, e−E/RT) in units kg, m, s, kcal, mol, and Ka mech. JL

three-step

four-step

reaction

C3H8 + 1.5O2 → 3CO + 4H 2

[C3H8]0.5[O2]1.25

4 × 1011

R2_JL:

C3H8 + 3H 2O → 3CO + 7H 2

[C3H8][H2O]

3 × 108 2.52 × 1019

−1.5

99.2

2.75 × 109

0

20.0

10

0

28.1

4 × 1011

0

30.0

[O2]

8.5 × 1015

−R3_JL:

H 2O → H 2 + 0.5O2

[H2]−0.75[O2][H2O]

+R4_JL:

CO + H 2O → CO2 + H 2

[CO][H2O]

−R4_JL:

CO2 + H 2 → CO + H 2O

[CO2][H2]

R1_3S:

C3H8 + 1.5O2 → 3CO + 4H 2

[C3H8]0.5[O2]1.25

9.268 × 10

0.5

1.8 × 10

0

35.1

5.337 × 1016

−0.5

94.3

0

30.0

−0.5

97.1

0

30.0

13

+R2_3S:

H 2 + 0.5O2 → H 2O

[H2][O2]

−R2_3S:

H 2O → H 2 + 0.5O2

[H2O]

+R3_3S:

CO + 0.5O2 → CO2

[CO][O2]0.5[H2O]0.5

1.3 × 1011

−R3_3S:

CO2 → CO + 0.5O2

[CO2][H2O]

R1_4S:

C3H8 + 1.5O2 → 3CO + 4H 2

[C3H8]0.5[O2]1.25

4 × 1011 3 × 10

1.213 × 10

0.5

16

8

C3H8 + 3H 2O → 3CO + 7H 2

[C3H8][H2O]

0

30.0

+R3_4S:

H 2 + 0.5O2 → H 2O

[H2]0.25[O2]1.5

2.812 × 1018

−1

30.0

−R3_4S:

H 2O → H 2 + 0.5O2

[H2]−0.75[O2][H2O]

8.337 × 1021

−1.5

89.2

CO + H 2O → CO2 + H 2

[CO][H2O]

2.75 × 109

0

20.0

10

+R4_4S: −R4_4S:

CO2 + H 2 → CO + H 2O

[CO2][H2]

9.268 × 10

0

28.1

R1_6S:

C3H8 + 1.5O2 → 3CO + 4H 2

[C3H8]0.5[O2]1.3

2.782 × 1010

0

30.0

C3H8 + 3H 2O → 3CO + 7H 2

[C3H8][H2O]

3.84 × 10

0

30.0

+R3_6S:

H 2 + 0.5O2 → H 2O

[H2]0.3[O2]1.55

1.004 × 1017

−1

40.0

−R3_6S:

H 2O → H 2 + 0.5O2

[H2]−0.7[O2]1.05[H2O]

2.977 × 1020

−1.5

99.2

+R4_6S:

CO + H 2O → CO2 + H 2

[CO][H2O]

2.01 × 109

0

20.0

R2_6S:

a

30.0 40.0

[H2]

1.5

E 30.0

0

H 2 + 0.5O2 → H 2O

0.25

b 0 −1

+R3_JL:

R2_4S:

six-step

A

reaction order

R1_JL:

9

−R4_6S:

CO2 + H 2 → CO + H 2O

[CO2][H2]

+R5_6S:

O2 → 2O

[O2]

1.5 × 109

−R5_6S:

2O → O2

[O]2

1.312 × 101

+R6_6S:

H 2O → H + OH

[H2O]

−R6_6S:

H + OH → H 2O

[H][OH]

6.774 × 10

10

0 0 1

2.3 × 1022

−3

2.74 × 1014

−2

28.1 113 −7.2 120 1.2

“Mech.” and “Reaction” denote the name of the mechanism and the individual reactions used throughout the paper.

of H2 and CO is described by the H2−O2 recombination reaction R3_JL and the water-gas shift reaction R4_JL, which are both reversible. The latter reaction is dependent on the concentrations of CO2 and H2O and are, thus, affected by oxy-fuel operation. Two sets of rate parameters for reaction +R3_JL were proposed by Jones and Lindstedt.10 Due to possible numerical issues with the first set of parameters, as pointed out by Jones and Lindstedt, the second set was used in the present work. The three-step mechanism by Leiser et al.2 describes the fuel breakdown by the single irreversible reaction R1_3S which is identical to reaction R1_JL. Oxidation of H2 by O2 is governed by the reversible reaction R2_3S, with rate constant and reaction order taken from Marinov et al.17 for the forward reaction +R2_3S. The reversible reaction R3_3S describes the oxidation of CO by O2, and the rate constant and reaction order for the forward reaction +R3_3S are from the work of Howard et al.18 The four-step mechanism of Andersen et al.3 includes the same reactions as the JL mechanism. Andersen et al.3 developed their mechanism primarily for combustion of methane, but they evaluated the mechanism for combustion of both methane and propane. The rate constants and reaction orders of the fuel breakdown reactions R1_4S and R2_4S as well as the water−gas shift reaction R4_4S are identical to those of the JL scheme. The difference between the two mechanisms is a faster oxidation of

H2 (reaction R3_4S) in the four-step mechanism. The reverse rate constant of reaction R3_4S derived in the present study differs slightly from the one presented in the original reference. To test the sensitivity for this noticed difference, the original reverse rate constant was investigated as well. The choice between the reverse rate constant used in the present study and the original reverse rate constant is showed to have insignificant effect on the results and conclusions drawn in this paper. The four reactions of the JL mechanism are also included in the six-step mechanism by Frassoldati et al.4 The rate constants are, however, modified for all four reactions, and the reaction orders of reaction R1_6S and R3_6S are different from those in the JL scheme. Two reversible dissociation reactions R5_6S and R6_6S are included in the six-step mechanism to make the mechanism applicable to high temperature (>2500 K) oxy-fuel combustion. Furthermore, Frassoldati and co-workers developed their mechanism for methane combustion, but in this work propane is used as fuel. Therefore, the reaction rates of the two fuel breakdown reactions R1_6S and R2_6S were modified here using the same scaling between methane and propane as in the work of Jones and Lindstedt.10 In the 1D PFR modeling, a detailed reaction scheme is used for validation of the investigated global mechanisms. The detailed mechanism is based on the work of Mendiara and Glarborg6 on 10329



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Figure 2. Calculated temperature as a function of time along a path line in the Chalmers 100 kW OF 27 flame as obtained from the CFD simulations with the global mechanisms investigated. The temperature profile used in the 1D PFR model is also shown (termed 1D profile).

Figure 3. Concentration of O2 as a function of time along a path line in the Chalmers 100 kW OF 27 flame as obtained from the CFD simulations with the global mechanisms investigated. The plot also includes the O2 profile of the detailed model (termed 1D profile) used in the 1D model and the injection rate of O2 (termed O2 injected) to the fuel stream in the 1D model as the accumulated percentage of O2 injected through time.

calculations. Conventional PFR calculations (premixed conditions, fixed stoichiometry, and isothermal conditions) can be used to evaluate reaction mechanisms. However, the drawback of this type of PFR modeling is the difficulty to capture the effects that a real flame, with varying temperature and local stoichiometric conditions, has on the reaction mechanism. As mentioned, an important difference between the CFD and the PFR calculations is in the treatment of the flow. Apparent recirculation zones are present in the flame, which are not captured by a conventional plug-flow assumption. Therefore, a different approach to PFR modeling is adopted in this work. Instead of using a fixed temperature and stoichiometry in the PFR calculations, a temperature profile and a continuous introduction of O2 are applied throughout the reactor to resemble the conditions in the real 3D flame, as described below. PFR Model. The 1D PFR modeling is carried out in the Chemkin-Pro software.19 The calculations are based on the temperature (Figure 2) and O2 concentration profiles (Figure 3) along path lines from the 3D CFD calculations. The path lines start from the fuel inlet, follow the flow toward the outlet of the furnace, and are generated by tracking the trajectory of a single mass-less particle. Path-line data was calculated for each of the global mechanisms. On the basis of the path-line data a

C1, C2 chemistry under oxy-fuel conditions and of Frassoldati et al.7 on C3 chemistry. This approach has been used previously by Kühnemuth and co-workers.37 Since the global schemes are to be evaluated against the detailed mechanism, an additional detailed mechanism38 was initially compared with the original detailed scheme, and the agreement in the predicted species concentration profiles was satisfactory (an example showing the agreement is given in the Results and Discussion section of this work). The additional detailed mechanism was developed for describing air combustion of up to C4 hydrocarbons.

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EVALUATION METHODOLOGY AND MODELING The Chalmers 100 kW OF 27 flame (described in the Experimental Data section) is modeled using both 1D PFR and 3D CFD calculations. The result of the CFD calculations, in terms of the temperature profiles and the gas compositions generated by the four global mechanisms, are evaluated and compared to experimental data. It is, however, not possible to isolate the importance of the reaction mechanism from other models describing turbulence, interaction between turbulence and chemistry, and heat transfer phenomena. The 1D modeling offers the possibility to focus on the combustion chemistry, since neither fluid dynamics nor heat transfer is included in the 10330



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representative temperature profile, included in Figure 2 (termed 1D profile), is predefined in the 1D model. Mixing in the 1D model is by definition avoided by the plugflow assumption; however, to simulate imperfect mixing in the combustion process a continuous introduction of the oxidizer (27 vol % O2 and 73 vol % CO2) to the reactor is applied, according to Figure 3. The fuel is introduced from the beginning, and the oxidizer is thereafter gradually mixed into the fuel stream. After the initiation of combustion, O2 is rapidly consumed in the flame and its concentration profile may, therefore, be used as an indication of the mixing rate between fuel and oxidizer stream. An additional reason for choosing the concentration of O2 as input for the PFR calculations is that O2 is the main oxidizer in the combustion, regardless of which reaction mechanism that is applied, and the consumption of O2 should therefore give a representative description of the combustion process in general. The resulting O2 injection profile used in the 1D model is included in Figure 3. The O2 concentration of the detailed mechanism in the 1D model is, thus, fitted to the 3D modeling result, while the CO, C3H8, H2O, and H2 concentration profiles are calculated. The sensitivity of the results to the assumed temperature (peak temperature from 1600 to 2000 K), mixing profile (90% injected O2 at residence times between 0.1 and 0.6 s), fuel (methane or propane), and water content (dry or wet recycle) has been analyzed. The sensitivity analysis shows that the results achieved with the chosen path line are representative to the investigated area; that is, the conclusions drawn are valid at least for the span of parameters given above. CFD Model. The oxy-fuel flame (described in detail in the Experimental Data section of this work) is modeled using the CFD software ANSYS FLUENT 12.1.4.20 One quarter of the combustion chamber, including one of the four symmetrically placed cooling tubes, is modeled in 3D using periodic boundary conditions. For simplicity, the outlet of the flow is located in the center of the bottom of the reactor instead of the actual position at one of the sides, close to the bottom. This positioning does not affect the flame chemistry or distribution in the simulations. The grid consists of hexahedral cells and is dense in the near burner region where the actual flame is present and coarsened toward the outlet of the furnace where no major reactions occur. Care was taken in achieving grid independent solutions, and this resulted in the use of a grid including 340 000 cells. In this study, the Realizable k−ε model21 is used to account for turbulence, since it is a reasonable compromise between accuracy and computational effort. This model has been used successfully in numerous turbulent combustion modeling studies.22−24 A “mixed-is-burned” approach is a simple way to model the combustion chemistry, but the method has limitations when reversible reactions are important.25 In oxy-fuel combustion, where CO2 decomposition can be of major importance, the use of a kinetically controlled chemistry model is therefore necessary.3,26 In this work, a variant of the Eddy Dissipation Concept (EDC)27 as implemented in ANSYS FLUENT 12.1.420 describes the chemistry and the interaction between turbulence and chemistry. Both premixed and nonpremixed flames can be treated by the EDC approach, including flames with local extinction and complex chemistry. The approach is well established within the research community, and it has been used to model various combustion devices.11,13,28,29 Breussin et al.29 modeled oxy-natural gas flames using both the mixedis-burned and an EDC approach, where the latter gave superior predictions of temperature and main species concentrations in the flames investigated. Both Leiser et al.2 and Andersen et al.3

evaluated their oxy-fuel schemes by CFD calculations of propane-fired oxy-fuel flames, using k−ε models for turbulence and the EDC approach for turbulence−chemistry interactions. A direct use of a global mechanism with rate exponents other than the stoichiometric exponents may lead to numerical difficulties, since the reaction rates may approach infinity when the species concentrations are close to zero. To avoid this problem, a method10 which implies a switch to a linear dependence when the species concentration is below a certain value is used in the present work. Here, a linear dependence for the afflicted reactions is applied when the molar concentration (mol/m3) of the problematic species is below 10−9. This work applies a conservative variant of the Discrete Ordinates Method (DOM)30,31 to solve the radiative transfer equation (RTE) and a weighted-sum-of-gray-gases (WSGG) model,32 derived for oxy-fuel conditions, to describe the gaseous radiative properties. Soot radiation and turbulence−radiation interactions (TRI) are not included in the present investigation, since this would add further uncertainties to the model. The use of a gas property model that is valid under oxy-fuel conditions is important, as shown in a recent CFD based evaluation33 of the WSGG model applied here. The common gray gas approximation for the WSGG model is used in the present study to calculate total radiative properties, and to estimate the absorption coefficient a characteristic length is needed. This is either the length of a computational cell or a characteristic length of the domain. Here, the domain-based approach is used since the cellbased approach results in grid-dependent solutions.34,35 Both the WSGG model and the reaction rates were implemented as user defined functions (UDF). For all simulations the segregated steady state solver is used. The pressure−velocity coupling is solved by the SIMPLE algorithm, and transport scalars are discretized using a second order upwind scheme. Piecewise polynomial specific heat capacities are used for the gases in the CFD calculations, and the in situ adaptive tabulation (ISAT) algorithm36 is used in combination with the EDC model to speed up the calculations. The default values of ANSYS FLUENT 12.1.420 were applied for the model specific constants of the Realizable k−ε model, the EDC, and the specific heat capacities of the species. The modeling approach of the present investigation only considers time-averaged values of the scalars. Information of turbulent fluctuations, which may play a crucial role for the combustion, is, thereby, lost. However, as Reynolds-Averaged Navier−Stokes (RANS) models, such as the Realizable k−ε model, are of large practical interest for the industrial CFD community and as the evaluation of global mechanisms are complemented by the 1D PFR modeling, the simplifications made in the CFD calculations are motivated. Information regarding boundary conditions used in the CFD modeling is given in the following section.

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EXPERIMENTAL DATA Experimental data from Andersson et al.,5 measured in a Chalmers 100 kW oxy-fuel unit, is used for comparison with the CFD results in this work. The top-fired furnace, schematically shown in Figure 4, is cylindrical and refractory lined. Four cooling tubes, symmetrically positioned close to the furnace walls, cool the flame. The burner, highlighted in Figure 4, consists of two swirled feed gas registers and a central gas lance, equipped with a small bluff-body. The oxy-fuel flame investigated in this work (termed the OF 27 flame) has 27 vol % O2 in the feed gas, and the remaining part 10331



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Table 2. Test Conditions for the OF 27 Case test case Fuel Properties fuel heat input [kW] fuel flow [g/s] Furnace Cooling cooling water flow [m3/h] total heat absorption [kW] Feed Gas Properties feed gas temperature [°C] feed gas composition O2 [vol %, dry] N2 [vol %, dry] CO2 [vol %, dry] primary feed gas flow [mn3/h] secondary feed gas flow [mn3/h] stoichiometric ratio Flue Gas Properties CO2 concn at stack [vol %, dry] flue gas excess O2 [vol %, dry] Swirl Settings primary register fin angle secondary register fin angle

OF 27 C3H8 80 1.74 3.75 52 25−30 27 71 29.5 42 1.15 94 3.8 45° 15°

and the fate of CO throughout the reactor is discussed, whereas the CFD results compare temperature and CO concentration profiles. PFR Analysis. As mentioned, the O2 profile of the detailed mechanism in the 1D PFR calculations was set to resemble the O2 profile of the 3D simulations by adjusting the feed of O2. For the global mechanisms, the temperature and the feed of O2 over time were the same as for the detailed mechanism. Besides this case, different temperature and mixing profiles, fuels, and water content have been simulated. The qualitative comparison between mechanisms in the cases tested is similar, and only the base case is further discussed in this paper. Calculated concentrations of O2 from the 1D PFR modeling are presented in Figure 5a. The predicted O2 peak, when t < 0.1 s, is similar with the JL, threestep, and four-step mechanisms. In these mechanisms fuel and O2 react through reactions R1_JL, R1_3S, and R1_4S (Table 1), respectively. These reactions all have identical reaction rate constants, which explain the similarities in the early part of the flame. The six-step mechanism includes the same reaction between fuel and O2 (R1_6S), but the lower pre-exponential factor and the higher rate exponent for O2 compared to the other global mechanisms contribute to a slower consumption of O2. Hence, the early O2 peak of the six-step mechanisms is higher than for the other global mechanisms, a trend more in line with the detailed mechanism. Figure 5b shows the concentration of C3H8 as a function of time. The oxy-fuel derived mechanisms give quite similar profiles, but in comparison to the detailed mechanism they all predict a more time-consuming breakdown of the fuel. The JL mechanism, on the other hand, predicts a breakdown of the fuel that is initially faster than the detailed mechanism, even though the time of complete fuel oxidation is similar for both mechanisms. The faster fuel breakdown of the JL mechanism is in agreement with the predicted concentration of CO, where the peak is reached sooner than with the detailed mechanism, as will be shown below. There are significant differences between the global mechanisms in the predicted concentration of H2, as can be

Figure 4. Combustion chamber of the Chalmers 100 kW oxy-fuel unit with highlighted details of the burner.

is mostly CO2, since dry recycling is applied. Test conditions for the OF 27 flame, including gas flows and swirl settings, are given in Table 2. Propane (98.3 mol % C3H8, 1.1 mol % C4H10) and oxygen (99.5 vol % O2) are fed from bottles. A suction pyrometer (type B thermocouple) was used to measure radial profiles of flame temperature, whereas gas composition was measured with a suction probe, connected to online gas analysis. Wall temperatures were recorded by wall-mounted thermocouples along the side of the reactor, where the average wall temperature of the OF 27 case was ∼585 ± 50 °C over the axial distance of 0−1.4 m from the burner. The measured average temperature of the gas close to the wall (0−1.4 m from the burner) was ∼730 °C. During operation of the OF 27 case, the temperature of the cooling water is raised from ∼10 °C to ∼20 °C in the cooling tubes. In the CFD calculations, adiabatic wall temperatures are used for the furnace walls. The surface temperature of the cooling tubes is set to a fixed temperature of 10 °C. The walls and the cooling tubes are treated as opaque with a surface emissivity equal to unity. Feed gas and fuel inlet boundary conditions used in the CFD calculations are based on experimental flow rates. It is, however, assumed that the feed gas consists only of O2 (27 vol %) and CO2 (73 vol %). The directions of the two feed gas streams are set to match the fin angles of the swirl registers, as given in Table 2. For simplicity, the fuel is assumed to contain pure C3H8, which is injected parallel to the angled side of the bluff-body as shown in Figure 4 (∼45° to the centerline axis).

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RESULTS AND DISCUSSION This section presents and compares the results of the 1D PFR and the 3D CFD calculations. The PFR results compare gas concentrations of O2, C3H8, H2, and CO as a function of time, 10332



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Figure 5. Calculated concentration of O2 (a) and C3H8 (b) as a function of time. Results from the 1D PFR calculations of the Chalmers OF 27 flame, using an O2 injection and temperature profile based on the CFD analysis.

Figure 6. Calculated concentration of H2 (a) and CO (b) as a function of time. Results from the 1D PFR calculations of the Chalmers OF 27 flame, using an O2 injection and temperature profile based on the CFD analysis.

neither of the global mechanisms can describe this process accurately. The principle shape of the CO profile of the detailed scheme is, however, captured by the JL mechanism and the sixstep mechanism, even though the latter strongly underestimates the peak concentration of CO. The JL and the three-step mechanisms yield peak concentrations of CO in line with the detailed mechanism. Furthermore, the JL and the three-step mechanisms predict a burnout of CO in agreement with the detailed mechanism. However, the three-step mechanism predicts a negative peak in the CO concentration after 0.06 s, which is not seen with the detailed scheme. All global mechanisms as well as the detailed mechanism predict a complete burnout of CO after ∼0.4 s. At this time O2 is still being fed to the reactor, which results in an increased O2 concentration as shown in Figure 5a. In the detailed mechanism the dominant reactions, through which CO is formed from fuel-radicals in flame Zone II, are HCO = H + CO and HCO + O2 = CO + HO2 (the differentiation between flame zones was discussed in the Introduction of this paper). Decomposition of CO2 in flame Zone III through the reaction CO2+ H = CO + OH also contributes to the formation of CO. In the global mechanisms, CO is formed from the fuel by the irreversible reactions C3H8 + 1.5O2 = 3CO + 4H2 (R1) and C3H8 + 3H2O = 3CO+7H2 (R2). CO is also formed by decomposition of CO2 through the reversible reactions R4_JL, R3_3S, R4_4S, and R4_6S. To study the CO formation, the

seen from Figure 6a. The JL mechanism overestimates the production rate of H2 leading to an early H2 peak compared to the detailed mechanism. The three-step mechanism also predicts an early H2 production, but the peak concentration is predicted too low. An even lower peak concentration is given by the sixstep mechanism that, however, predicts a slower burnout compared to the three-step mechanism. The largest deviation from the detailed mechanism is achieved with the four-step mechanism that hardly predicts any H2 at all. In Figure 6b the calculated concentration of CO as a function of time is given. CO is an indicator for the progress of combustion, and Figure 6b therefore includes the prediction of an additional detailed mechanism (Detailed 2)38 in order to rule out any major differences between detailed mechanisms. As mentioned previously, the Detailed 2 mechanism was developed for air-fired conditions, and due to that fact, some minor deviations between the two detailed mechanisms could be expected. However, as seen in Figure 6b, the Detailed 2 mechanism more or less reproduces the predictions of the original detailed mechanism. This result gives confidence to the use of the original detailed model as a reference, when evaluating the global schemes in the present work. All the global schemes predict an earlier formation of CO than the detailed mechanism. In contrast to the global mechanisms, the detailed mechanism includes several reactions steps for the fuel oxidation before CO is formed, and the results show that 10333



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Figure 7. Reaction rates of fuel−CO reactions (a) and CO2−CO reactions (b) as function of time for the detailed and the global mechanisms. Results from the 1D PFR calculations of the Chalmers OF 27 flame, using an O2 injection and temperature profile based on the CFD analysis.

Figure 8. Measured and modeled temperature along the centerline (a) and a radial profile 0.384 m downstream of the burner (b) in the Chalmers 100 kW OF 27 flame. Results of the CFD calculations using the global reaction mechanisms.

of CO2 but clearly overestimates the reduction compared to the detailed mechanism, while the four-step mechanism predicts a completely different behavior with CO being oxidized to a large extent through the water gas-shift reaction. Considering the flame zone discussion earlier in this work, the behavior of the four-step mechanism is not expected. This is because C3H8 is still present in Zone II and should primarily consume the available O2. CO is primarily oxidized after C3H8, in Zone III. Andersen et al.3 partly developed their four-step mechanism in order to lower the CO concentration compared to the JL scheme, an effect that clearly can be seen in Figure 7b, but compared to the detailed mechanism there are large differences. The behavior of the threestep mechanism is also in contradiction with the flame zone concept. As in the four-step mechanisms, CO is oxidized already in Zone II. After ∼0.07 s, the three-step mechanism predicts a strong decomposition of CO2 into CO and O2 (R3_3S). Since C3H8 is not fully consumed at this stage, the regeneration of O2 results in an increased reaction rate of reaction R1_3S, as seen in Figure 7a. This behavior is not in line with the detailed mechanism. The six-step mechanism suffers from the same problem as the three-step and the four-step mechanisms, with CO2 formation in the presence of fuel and O2. CFD Analysis. Obviously, the comparison between the CFD modeling results and the experimental data will depend not only on the applied reaction mechanism but also on other submodels, such as turbulence, turbulence−chemistry interaction, and radiation models. The results from the 3D CFD calculations are

reaction rates of the global mechanisms are compared with those of the detailed scheme. Reaction rates are presented for fuel−CO reactions in Figure 7a and for CO2−CO reactions in Figure 7b. The reaction rates of reaction R2 are surprisingly slow compared to the other fuel-CO reactions and are therefore not included here. In general, none of the global mechanisms have the same timing in the CO peaks as the detailed mechanism. The reaction rate expressions of reactions R1_JL, R1_3S, and R1_4S are identical so the deviations in the global reaction rates in Figure 7a are due to differences in other reaction rates. Fuelrelated formation of CO in the global mechanisms starts earlier and lasts longer than in the detailed scheme, as shown in Figure 7a. The early start is expected since there are several fuel-related reactions in the detailed scheme that must be completed before CO is formed, whereas CO is formed directly from the fuel in the global mechanisms. The JL mechanism predicts a fast and strong CO formation, while the three-step and the four-step mechanisms predict lower reaction rates which span over a longer time. The different rate expression for reaction R1 in the six-step mechanism results in a delayed CO formation compared to the other global mechanism, a result more in line with the detailed scheme. The reaction rate peak of reaction R1_6S is, however, too low and the time span too long, compared to the detailed mechanism. An interesting difference between the global mechanisms and the detailed scheme is in the decomposition of CO2, shown in Figure 7b. The JL mechanism captures the trend of the reduction 10334



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Figure 9. Measured and modeled concentration of CO along the centerline (a) and a radial profile 0.384 m downstream of the burner (b) in the Chalmers 100 kW OF 27 flame. Results of the CFD calculations using the global reaction mechanisms.

Andersen et al.3 performed 2D CFD calculations of the present OF 27 flame using their four-step mechanism and the JL mechanism. Their temperature profiles show similar trends as the profiles in the present work, but calculated temperatures here are significantly higher than in the work of Andersen and coworkers. The discrepancies in the results are likely because of the different radiation models applied in the calculations. Andersen et al. used the P1 model to solve the RTE and a WSGG model derived for air-like conditions for the gaseous radiative properties. In the present work the more advanced DOM was applied to solve the RTE, and a WSGG model32 applicable to oxy-fuel conditions was used for the radiative properties. As a result of the lower temperatures, the predicted concentrations of CO by Andersen et al. differ from the concentrations achieved in the present study. Leiser et al.2 also evaluated their three-step mechanisms against the Chalmers OF 27 flame and obtained temperatures lower than in the present study. Compared to the present study, Leiser and co-workers used different models to describe turbulence and the absorption coefficient of the gas, which might explain the discrepancies between the modeled temperature profiles. As in the present work, the predicted burnout of CO by Leiser et al. was too slow.

shown as axial profiles along the reactor centerline and radial profiles 0.384 m downstream of the burner. Figure 8a shows the temperature along the centerline of the Chalmers 100 kW OF 27 flame. There is a large difference in the predicted peak temperature between the mechanisms, where the JL mechanism predicts the highest centerline temperature and the four-step mechanisms the lowest. The choice of reaction mechanism is, thus, important for the temperature prediction since the turbulence, turbulence−chemistry interactions and radiation models were the same for all cases. Furthermore, the JL mechanism predicts the most intense combustion, with a short flame characterized by a high peak temperature. The three oxy-fuel mechanisms give flames with smoother axial temperature gradients. Approximately one meter downstream of the burner, the combustion is completed and all models give similar predictions of temperature. A low temperature zone is predicted in the center of the flame by the four-step mechanism, as shown in the radial temperature profile in Figure 8b, whereas the JL mechanism predicts a wider radial temperature profile than the oxy-fuel derived mechanisms. The difference in peak temperature between the models is not as pronounced as for the centerline profile, indicating that the oxyfuel derived mechanisms do not necessarily yield lower temperatures compared to the JL scheme. The general overprediction of temperature with the global mechanisms is to a large extent a consequence of the global nature and the absence of product dissociation. Furthermore, the exclusion of soot radiation in the calculation may also partly explain the overpredicted temperatures. Soot radiation enhances the radiative heat exchange and has been shown to be of great importance for the temperature field of the flame studied in this work.33 Figure 9 gives calculated concentrations of CO along the centerline (Figure 9a) and a radial profile 0.384 m downstream of the burner (Figure 9b). Both the JL mechanism and the six-step mechanism have clear peaks in the concentration of CO along the centerline, whereas the three-step and the four-step mechanisms give smoother profiles. The three-step mechanism predicts considerably lower peak concentrations than the other models. Compared with the JL scheme, the oxy-fuel mechanisms predict a longer CO rich zone along the centerline. This behavior is also seen in the radial profile, Figure 9b, where the oxy-fuel derived mechanisms yield higher concentrations of CO than the JL mechanism.

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CONCLUSIONS Three global reaction mechanisms (three-step, four-step, and sixstep) derived for oxy-fuel combustion and a global reference mechanism (JL) have been investigated and compared in 3D CFD calculations of an oxy-fuel flame. In addition, 1D plug flow reactor (PFR) modeling based on the CFD results is undertaken. In the PFR modeling, where fluid dynamics and heat transfer models are excluded, the global mechanisms are evaluated by a comparison with a detailed mechanism. The PFR calculations show that the onset of fuel oxidation with the global mechanisms is early compared with the detailed mechanism. The JL mechanism and the three-step mechanism, however, yield predictions of major gaseous species that are comparable with those of the detailed scheme, whereas the fourstep and the six-step mechanism underestimate the in-flame concentrations of CO and H2. The JL mechanism is the only scheme that captures a rational reaction history of CO that is in line with the detailed mechanism, with an initial formation of CO from the fuel followed by an oxidation of CO to CO2. The global oxy-fuel mechanisms all predict simultaneous oxidation of fuel and CO, a behavior in contradiction with the detailed scheme. 10335



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(9) Toporov, D.; Bocian, P.; Heil, P.; Kellermann, A.; Stadler, H.; Tschunko, S.; Förster, M.; Kneer, R. Detailed investigation of a pulverized fuel swirl flame in CO2/O2 atmosphere. Combust. Flame 2008, 155, 605. (10) Jones, W. P.; Lindstedt, R. P. Global reaction schemes for hydrocarbon combustion. Combust. Flame 1988, 73, 233. (11) Brink, A.; Kilpinen, P.; Hupa, M.; Kjäldman, L. Study of alternative descriptions of methane oxidation for CFD modeling of turbulent combustors. Combust. Sci. Technol. 1999, 141, 59. (12) Jones, W. P.; Kakhi, M. Pdf Modeling of Finite-rate Chemistry Effects in Turbulent Nonpremixed Jet Flames. Combust. Flame 1998, 115 (1−2), 210. (13) Cuoci, A.; Frassoldati, A.; Faravelli, T.; Ranzi, E. Accuracy and Flexibility of Simplified Kinetic Models for CFD Applications. Presented at Combustion Colloquia - 32nd Combustion meeting, II-6; Italian section of the Combustion Institute, Napoli, Italy, April 26−28, 2009. (14) Marklund, M.; Tegman, R.; Gebart, R. A Self-Consistent CFDmodel for Pressurised High Temperature Black Liquor Gasification. IFRF Combust. J. 2008, 200801. (15) Zucca, A.; Marchisio, D. L.; Barresi, A. A. Modeling of Moderately Swirling Turbulent Non-premixed Flames. Presented at Combustion Colloquia - 32nd Combustion meeting, II-9, Italian section of the Combustion Institute, Napoli, Italy, April 26−28, 2009. (16) Chase, M. W. NIST-JANAF Thermochemical Tables. J. Phys. Chem. Ref. Data, Monogr. 1998, 9, 1 (4th ed.). (17) Marinov, N. M.; Westbrook, C. K.; Pitz, W. J. Detailed and Global Chemical Kinetics Model for Hydrogen. Presented at the 8th International Symposium on Transport Properties, San Francisco, CA (U.S.), 1995. (18) Howard, J. B.; Williams, G. C.; Fine, D. H. Kinetics of Carbon Monoxide Oxidation in Postflame Gases. Presented at the 14th Symposium (Int.) on Combustion; The Combustion Institute, 1972. (19) Chemkin-Pro; Reaction-Design: San Diego, CA, 2008. (20) ANSYS FLUENT 12.1.4; ANSYS, Inc: Canonsburg, PA, USA, 2011. (21) Shih, T.-H.; Liou, W. W.; Shabbir, A.; Yang, Z.; Zhu, J. A new k-ε eddy viscosity model for high Reynolds number turbulent flows. Comput. Fluids 1995, 24 (3), 227. (22) Lopez-Parra, F.; Turan, A. Computational study on the effects of the non-periodic flow perturbations on the emission of soot and NOx in a confined turbulent methane/air diffusion flame. Combust. Sci. Technol. 2007, 179, 1361. (23) Saario, A.; Oksanen, A. Comparison of global ammonia chemistry mechanisms in biomass combustion and selective noncatalytic reduction process conditions. Energy Fuels 2008, 22 (1), 297. (24) Bäckström, D.; Jilvero, H. CFD-modelling of Chalmers 100 kW oxyfuel unit: Investigation of swirling air and oxy-fuel flames; Technical report No. 2009-324; Chalmers University of Technology: Gothenburg, Sweden, 2009. (25) Brink, A.; Mueller, C.; Kilpinen, P.; Hupa, M. Possibilities and limitations of the Eddy Break-Up Model. Combust. Flame 2000, 123, 275. (26) Glarborg, P.; Bentzen, L. Chemical effects of a high CO2 concentration in oxy-fuel combustion of methane. Energy Fuels 2008, 22, 291. (27) Magnussen, B. F. On the structure of turbulence and a generalized eddy dissipation concept for chemical reaction in turbulent flow. Presented at the 19th AIAA Aerospace meeting, St. Louis, MO, January 12−15, 1981. (28) Castineira, D.; Edgar, T. E. CFD for Simulation of Steam-Assisted and Air-Assisted Flare Combustion Systems. Energy Fuels 2006, 20, 1044. (29) Breussin, F.; Lallemant, N.; Weber, R. Computing of oxy-natural gas flames using a global combustion scheme and a chemical equilibrium procedure. Combust. Sci. Technol. 2000, 160, 369. (30) Chui, E. H.; Raithby, G. D. Computation of radiant heat transfer on a nonorthogonal mesh using the finite-volume method. Numer. Heat Transfer, Part B 1993, 23, 269.

Hence, to compensate for quantitative errors, such as overpredicted CO concentration or combustion temperature, by simply adjusting the reaction parameters may lead to errors in the reaction dynamics. The CO2/CO reactions of the global oxy-fuel mechanisms evaluated in the present investigation, for instance, have a qualitatively incorrect behavior. In turn, this reduces the generalizability of the mechanism. The PFR method shows that there is a significant improvement potential for global oxy-fuel reaction mechanisms and the development of a refined global reaction mechanism is a task suitable for future research. In CFD calculations, effects on the results caused by different reaction mechanisms could possibly be smoothed out by heat transfer and turbulence−chemistry interaction descriptions. Still, the temperature profiles of the CFD calculations performed in the present work clearly point out that the choice of global mechanism is critical to the results. The JL mechanism overestimates peak temperatures, whereas the four-step mechanism underestimates the centerline temperature. As in the PFR calculations, the JL mechanism gives a CO prediction that is satisfactory, even though more measurement data from the near burner region would have been beneficial. The threestep mechanism predicts low concentrations of CO compared to the other schemes, and the four-step mechanism predicts a slow CO formation and burnout compared to measured data. The differences in the results between the 1D PFR and the 3D CFD modeling shows the large impact that the turbulence, turbulence−chemistry interaction, and radiation model have on the results.

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AUTHOR INFORMATION

Corresponding Author

*Telephone: + 46 31 772 1442. Fax: +46 31 722 3592. E-mail: [email protected], [email protected]. Notes

The authors declare no competing financial interest.

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REFERENCES

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Oxy-Fuel Combustion Modeling: Performance of Global Reaction

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