Enhancing the Acetylene Yield from Methane by Decoupling Oxidation

Jul 12, 2016 - ... meshes, and these meshes are transformed to polyhedral zone using the function provided by FLUENT. ..... Bekdemir , C.; Somers , B...
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Enhancing the Acetylene Yield from Methane by Decoupling Oxidation and Pyrolysis Reactions: A Comparison with the Partial Oxidation Process Qi Zhang, Jinfu Wang, and Tiefeng Wang* Beijing Key Laboratory of Green Reaction Engineering and Technology Department of Chemical Engineering, Tsinghua University, Beijing 100084, China ABSTRACT: The partial oxidation (POX) of methane is one of the most important processes to produce acetylene and syngas. The reaction pathway analysis using a detailed chemical mechanism (modified GRI 3.0) showed that the exothermal oxidation and endothermic pyrolysis reactions were highly coupled in the original POX process, which limited the yield of acetylene. A new process that physically separated the heat supply and pyrolysis reactions was proposed to increase the acetylene yield. The maximum yield of acetylene was enhanced from 33% to 52% in the theoretical calculations assuming inert and instantaneous mixing. A jet-incross-flow (JICF) reactor was designed to realize this new process. The computational fluid dynamics (CFD) method coupled with the modified GRI 3.0 was applied to simulate the complex interaction between turbulent mixing and reactions. The results showed that a high acetylene yield of 41% could be obtained in the JICF reactor. The optimization of the reactor indicated that the optimum number of jets was 8, and the optimal mixing ratio was 0.566 for maximum acetylene yield. The maximum acetylene yield significantly decreased in a larger reactor, and mixing enhancement was the main way to further improve the acetylene yield. at a high temperature of 2100 K.4 This value is even higher than 90% in the experiments of plasma thermal conversion of methane.5 Nevertheless, the yield of acetylene in the POX process could not be further enhanced by adjusting the operating parameters. This conclusion has been confirmed by the industrial practice. The significantly lower acetylene yield in the POX process is due to the remaining oxidizing species like OH, O, and HO2 in the system, although the oxygen molecules are soon exhausted. In order to get a higher acetylene yield, a new method named as partially decoupled process (PDP) was adopted. In this process, fuel and oxygen first combust in the combustor and generate a heat carrier flow. Methane is jetted into the mixer and mixes with the combustion products in a very short time to achieve the target temperature. Then the mixture continues to react and produce acetylene. The PDP has the following advantages: (i) the oxidation reactions and pyrolysis reactions are physically decoupled in the reactor, and thus the concentrations of strongly oxidizing species are low when the pyrolysis reactions occur; (ii) the methane that takes part in the oxidation reactions of the original POX process can be replaced with cheaper fuel, such as coke oven gas; (iii) some oxidizing species remain in the system to prevent heavy soot.

1. INTRODUCTION With the increasing production of shale gas, chemical processes using natural gas as raw material are attracting more attentions in recent years.1 Acetylene is one of the most important products of natural gas chemical industry. The partial oxidation (POX) process developed in the 1950s by BASF is the main technology to produce acetylene.2 In the POX process, the high-speed premixed fuel-rich feedstock is ignited near the burner block and combusts for milliseconds before quenching to give a maximum acetylene yield of 30−33%. The POX process was developed based on the assumption that the speed of oxidation reactions is much faster than that of pyrolysis reactions. According to this assumption, the macrokinetics that only contains the reactants and several major products was used extensively in the past.3 For a simple description of this process, part of methane takes part in the exothermic oxidation reactions first to supply heat for the subsequent pyrolysis reactions of the excess methane. Oxygen is absent in the pyrolysis reactions because it is soon exhausted in the oxidation reactions. With more advanced measurement technology, many radical reactions have been detected and reliable detailed chemical mechanisms are developed. These mechanisms show that the oxidation and pyrolysis reactions are actually highly coupled and the simple empirical kinetics mentioned above is not appropriate to describe the complex reaction network. Research shows that the maximum yield of acetylene can be higher than 80% in the methane pyrolysis system without oxygen © XXXX American Chemical Society

Received: February 29, 2016 Revised: June 5, 2016 Accepted: July 12, 2016

A

DOI: 10.1021/acs.iecr.6b00817 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research Table 1. Specific Settings of the CFD Simulations item

settings

Domain Solver Turbulence model Radiation Turbulence−chemistry interaction Wall treatment Mixture material property Discretization schemes Under relaxation factors

Three-dimensional Steady, segregated with implicit formulation Realizable k−ε with default setting Discrete ordinates (DO) with θ divisions = 5, φ divisions = 5, θ pixels = 3, φ pixels = 3 Eddy dissipation concept (EDC) model with default parameters Scalable wall functions Density: ideal-gas. Absorption coefficient: wsggm-cell-based PRESTO! for pressure, second order upwind for other equations, and SIMPLE for pressure-velocity coupling Pressure: 0.3. Density: 1.0. Body forces: 1.0. Momentum: 0.7. Turbulent kinetic energy: 0.8. Turbulent dissipation rate: 0.8. Turbulent viscosity: 1. Species: 1. Discrete ordinates: 1. Equations of continuity, velocity, k, ε, and species: 10−5. Equations of energy and Do intensity: 10−6. Full multicomponent diffusion, thermal diffusion.

Convergence criteria Other options

original POX process, the methane and oxygen are premixed as the input condition. In the simulation of PDP, the condition of the heat carrier is first calculated by this 0-D reactor, and then the composition and temperature of the mixture of heat carrier and methane is calculated with the assumption of instantaneously complete mixing. The isobaric heat capacity of the species used in the mixture calculation is chosen from the National Institute of Standards and Technology (NIST) chemistry database.20 The mixing result is then set as the input condition of another 0-D reactor to simulate the subsequent cracking reactions. Detailed reaction rates extracted from the calculation results are used to analyze the reaction pathway. The influence of turbulence is not considered in this model, and the results only reflect the intrinsic nature of chemical mechanism. 2.2. CFD Simulations. In a real reactor, the reactions and mixing process occur simultaneously; therefore it is impossible to realize instantaneous mixing of the heat carrier and methane. Thus, the results of CHEMKIN simulations only provide the theoretical verification of the new process. The three-dimensional CFD simulations are carried out using the commercial software FLUENT to further study the complex interaction between the turbulent mixing and reactions. The steady-state solver are chosen to solve the governing equations. The turbulence is modeled by the realizable k−ε model, which has been used in the literature to model the JICF21 reactor and the POX process.22 Compared with the standard k−ε model, the realizable k−ε model is more accurate in predicting flows with strong streamline curvature.23 The radiation effect is described by the discrete ordinates (DO) model. The compressibility of the fluids is considered because fluids are jetted into the reactor at a high velocity. The turbulence−chemistry interaction is described by the EDC model. This model is based on energy cascade model, and it divides the flow field into two parts, the “fine structures” and the surrounding flow. Reactions only happen in the “fine structures” where the reactants are mixed at molecular level. The ratio between the fine structures and the total mass is ξ3 where ξ is defined as

The jet-in-cross-flow (JICF) reactor is adopted to realize the PDP in this work. This type of reactor has been successfully applied in the pyrolysis of propane,6,7 liquefied petroleum gas (LPG),8 and naphtha9 to produce ethylene. The maximum yields of ethylene in these experiments are significantly higher than that in the conventional steam cracking. Compared with the above research, a much higher temperature is needed in the pyrolysis of methane to produce acetylene. Therefore, the feasibility of the JICF reactor for the PDP should be verified. CFD simulations of a reacting flow are developing quickly in recent years. Some expensive and dangerous experiments can be replaced by the CFD simulations. The detailed quantitative data that are difficult to measure can be easily obtained from CFD simulations to guide the reactor design and operation optimization. Compared with the expensive direct numerical simulation (DNS)10 and large eddy simulation (LES),11 the Reynolds average Navier−Stokes (RANS) simulation12 is effective to predict the mean velocity, temperature, and concentration fields; therefore it has been widely applied in the industrial design. The complex finite-rate chemical network cannot be well described by the conventional methods. The eddy dissipation concept (EDC) model13 coupled with detailed chemical mechanism well balances the accuracy and the computational cost in combustion simulations.14 It has been successfully applied in many studies, including the simulations of moderate or intense low-oxygen dilution (MILD) flames,15 bluff-body stabilized burner,16 gas turbine,17 and some other furnaces.18,19 The present work aims to develop a reliable simulation method to study the PDP and evaluate the performance of the JICF reactor in the acetylene production. The original POX process is first simulated, and the reaction pathway analysis is applied to explain the acetylene yield limitation. Theoretical calculations with the assumption of instantaneous mixing and adiabatic condition show that a higher acetylene yield can be obtained in the PDP. CFD simulations of the JICF reactor are then conducted to consider the influence of the complex turbulent-chemistry interaction on the acetylene yield. The simulation results further confirm the advantages of the new PDP. Last, the reactor configuration is optimized based on CFD simulations to get the highest acetylene yield.

⎛ νε ⎞1/4 ξ = Cξ⎜ 2 ⎟ ⎝k ⎠

(1)

The fine structure is treated as a plug flow reactor (PFR) in FLUENT,24 and the residence time τ is expressed by the kinematic viscosity and turbulent property as

2. COMPUTATIONAL METHOD 2.1. 0-D Simulation. The “closed homogeneous batch reactor” model in the CHEMKIN software is used in this work. The pressure is set fixed, and all of the reactants and products are considered perfectly mixed all the time. In the simulations of the

⎛ ν ⎞1/2 τ = Cτ ⎜ ⎟ ⎝ε⎠ B

(2) DOI: 10.1021/acs.iecr.6b00817 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Figure 1. Comparison of experimental data and simulation results by modified GRI 3.0 for flat flames: (a) CH4/O2/Ar flame (p = 1 atm, ⌀ = 2.5), (b) C2H6/O2/Ar flame (p = 1 atm, ⌀ = 2.5), (c) CH4/O2/Ar flame (p = 30 Torr, ⌀ = 1.42), (d) CH4/O2 flame (p = 1 atm, ⌀ = 3.08).

been proposed by changing the expression of rate constant for the acetylene consumption reaction C2H2 + OH = CH2CO + H with

The turbulence and reactions are linked together by the kinetic energy k and the energy dissipation rate ε. The default model constants, Cξ = 2.1377 and Cτ = 0.4082, are used. The species concentrations in the computing cell is calculated by interpolation as Yĩ = ξ 3χY i* + (1 − ξ 3χ )Y i0

⎛ −11059 cal ⎞ 3 −1 −1 ⎟ cm mol kR1 = (1.326 × 1013)T 0.11 exp⎜ s ⎝ ⎠ RT

(3)

(5)

where Y*i and are the mass fractions of species i in the fine structure after the residence time τ and in the surrounding flow, respectively, Ỹ i is the average fraction of species i in a computational cell, and χ is the proportion of fine structures where reactions occur.16 When a detailed chemistry is used, χ = 1 is recommended.24 The source term in the conservation equation is expressed as Y0i

Ri =

ρ̅ ξ2 (Y i* − Yĩ ) τ(1 − ξ 3)

In order to verify this modified GRI 3.0 mechanism, the experimental data of fuel-rich flat flames are collected from the literature for comparison. Figure 1 shows good agreement between the experimental data and simulation results under different conditions. Thus, the modified GRI 3.0 mechanism is used to simulate the POX process and the PDP in the present work. 2.4. Verification of the EDC Model. Before simulation of the partially decoupled process, the EDC model is first verified by simulating the original POX process. The results in Figure 2 show good agreement between the industrial data and the simulation predictions. The calculated C2H2, CO and CO2 mole fractions are almost the same as the experimental results. The concentration of H2 is underpredicted by about 10%. In general, the accuracy of this model can satisfy our requirements and this model is used in the following simulations.

(4)

The calculated average temperature, species concentrations, and turbulent properties of the last iteration are used as the input parameters of the EDC model. The simulations are accelerated by the in situ adaptive tabulation (ISAT) algorithm developed by Pope.25 Considering that the diffusion of the species is very important in this process, the thermal diffusion is considered and the full multicomponent diffusion model is used to replace the mixture-averaged transport, although more computational time is needed. All of the specific settings are summarized and listed in Table 1. 2.3. Verification of the Detailed Reaction Mechanisms. The detailed reaction mechanism GRI 3.026 has been widely used to simulate the combustion of natural gas. However, this reaction mechanism overpredicts the concentration of acetylene at the fuel-rich conditions, and a modified GRI 3.0 mechanism22 has

3. NUMERICAL SETTINGS 3.1. 0-D Simulations. The condition of the heat carrier flow is calculated by CHEMKIN software. The coke oven gas, which is a byproduct of the coking plant and much cheaper than natural gas, is used as the fuel to provide the high temperature flow. The typical composition of the coke oven gas is used in the calculations: O2 0.5%, H2 57.5%, CO 6.5%, CO2 2.5%, CH4 25%, N2 5%, and C2H4 3%. Stoichiometric oxygen is mixed with the C

DOI: 10.1021/acs.iecr.6b00817 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research Table 2. Detailed Setting of Boundary Conditions stream Mainstream as heat carrier

condition

Velocity/m·s−1 Temperature/K Turbulence intensity/% Hydraulic diameter D/m Species composition Nozzle inlet

Figure 2. Mole fractions of the main products getting from the industrial data and the CFD simulation of the original POX process.

coke oven gas for complete combustion. The coke oven gas and oxygen are preheated to 873 K. Methane, which is also preheated to 873 K, is then mixed with the heat carrier flow in the subsequent calculations. To determine the appropriate mixing ratio between methane and the heat carrier, numerical tests are carried out with different amount of methane. 3.2. CFD Simulations. 3.2.1. Computational Domain. Figure 3 shows the computational domain of the JICF reactor

Wall treatment Outlet

value

Velocity inlet

Velocity inlet Velocity/m·s−1 Temperature/K Turbulence intensity/% Hydraulic diameter D/m CH4 mass fraction Nonslip wall with zero heat flux Pressure outlet

86.4 3103 10 0.03 Adiabatic combustion results of coke oven gas from CHEMKIN simulation 120 873 10 0.004 1

formed to polyhedral zone using the function provided by FLUENT. This conversion reduces the overall cell number and improves the mesh quality. As a result, the computational cost is significantly reduced while the accuracy is maintained. Other parts of the reactor are meshed by structured meshes. Four cases with different grid number (11750, 31011, 81545, and 168040) are tested in this section. The axial profiles of the temperature, acetylene concentration, and turbulent properties along the reactor centerline are shown in Figure 4. The profiles indicate that when the grid number reaches 81545, the temperature, species concentration, and turbulent fields become almost independent of the grid number. Therefore, this mesh density is adopted in the following simulations. 3.2.4. ISAT Tolerance Test. When the ISAT algorithm is used to accelerate the calculations of the chemistry source term, the accuracy and computational cost depend on the ISAT error tolerance, εtol. The computational cost increases dramatically with the decrease of εtol. So it is necessary to find the appropriate value of εtol. Four different values of εtol (10−1, 10−2, 10−3, and 10−4) are tested. The results become independent of εtol when εtol ≤ 0.001; therefore, εtol = 0.001 is used in the following simulations.

Figure 3. Schematic of the computational domain of the JICF reactor.

used in this work. The structure and dimensions were designed based on our previous simulation results and understanding of this process. As a simplification, the combustion of coke oven gas is not present in the CFD simulations. The heat carrier (the mainstream) flows into the reactor from the top, and methane is jetted through the nozzles on the sidewall. The diameter of the reactor is fixed at 30 mm, and the total length of reactor is 800 mm. All of the nozzles are perpendicular to the reactor, and the diameter of the nozzles can be changed according to design requirements. The number of nozzles should be optimized for maximum yield of acetylene. 3.2.2. Boundary Conditions. The detailed boundary settings are listed in Table 2. The result of coke oven gas combustion from the CHEMKIN simulation is directly used as the input condition of the mainstream. For simplification, heat loss is not considered in the CFD simulations. 3.2.3. Grid Independence Test. The simulation results no longer change with the increase of mesh number after reaching a certain mesh density. In order to minimize the computational cost, a grid independence test is conducted to get the optimal mesh setting. The small regions near the nozzles are meshed by unstructured tetrahedral meshes, and these meshes are trans-

4. RESULTS AND DISCUSSION 4.1. Analysis of Original POX Process. The schematic of the BASF POX reactor has been reported in our previous work.22 In this POX reactor, the preheated methane and oxygen streams are rapidly mixed in the mixer and then jetted into the furnace at a high velocity of 100 m/s through the burner block. The premixed mixture with an equivalence ratio of 3.33−3.64 combusts in the furnace for several milliseconds and is then quickly quenched to give a maximum acetylene yield of about 30−33%. In this part, the original POX process is simulated by the 0-D reactor for analysis. Figure 5 shows the maximum yield of acetylene at different preheating temperatures and equivalence ratios. The results indicate that increasing the preheating temperature is beneficial to improve the acetylene yield. The preheating temperature of 873 K is adopted in the POX industrial process to avoid uncontrolled ignition in the mixing chamber. There exists an optimal equivalence ratio at a fixed preheating temperature, and this optimum equivalence ratio increases with an increase in the preheating temperature. The D

DOI: 10.1021/acs.iecr.6b00817 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Figure 4. Effect of mesh size on the simulation results along the centerline: (a) static temperature; (b) mass fraction of acetylene; (c) turbulent kinetic energy k; (d) energy dissipation rate ε.

increases and the reactions starting from methane can be divided into two competing pathways. In the POX process, methane first reacts with the active radicals of H, OH, and O to generate CH3 radical. Two CH3 radicals combine to form C2H6, which is the initial substance of acetylene formation pathway. The H atom is continuously removed from C2 species to generate C2H2. The CO formation pathway is propelled by O2 molecule and O, OH radicals. Part of the generated C2H2 continues to react with O and OH radicals and finally forms CO. It is clear that in this process a considerable amount of methane and generated acetylene is converted to CO, which decreases the yield of acetylene. For comparison, Figure 6b shows the reaction pathways of the PDP. In order to show the advantage of the new PDP over POX process, the hydrogen is used as the fuel in the combustor so that there is no carbonaceous species in the heat carrier flow. The CO formation pathway is significantly diminished in the new process. At the very beginning of the pyrolysis process, the formation rate of C2H2 is even 2 orders of magnitude higher than the formation rate of CO. When H2 is replaced by coke oven gas, the selectivity and yield of C2H2 are still much higher than that in the original POX process. A high concentration of H radical is beneficial to reduce the formation of CO, so H2 is theoretically better to generate the heat carrier flow. However, coke oven gas is much cheaper than hydrogen, so it is used as the fuel in the following parts. The reaction kinetic parameters of the most important reactions are listed in Table 3. 4.2. Simulations of Process with Ideal Mixing. The analysis in section 4.1 indicates that the oxidation and pyrolysis reactions are actually highly coupled in the original POX process, which limits the further enhancement of acetylene yield. In this section, the partially decoupled process is analyzed in detail.

Figure 5. Maximum yield of acetylene of the POX process at different preheating temperatures and equivalence ratios.

simulation results show that the maximum acetylene yield cannot be further enhanced by just optimizing the operating conditions. This conclusion has also been confirmed by industrial practice. When there is no oxygen in the system, the yield of acetylene is as high as 0.7 in the methane pyrolysis process at 1900 K.4 However, acetylene is also the main precursor for formation of polycyclic aromatic hydrocarbons (PAHs)30 and the serious sooting problem limits the industrial application of this process. The introduction of oxygen into the system has the following two advantages: (i) the heat needed in the pyrolysis process is produced by the system itself, and thus the equipment can be simplified; (ii) soot can be oxidized by the oxidizing radicals. The disadvantage is that some of the generated acetylene is further oxidized to CO; thus the maximum acetylene yield is reduced. Figure 6a shows the reaction pathway of the original POX process before oxygen is exhausted. In this stage, the temperature E

DOI: 10.1021/acs.iecr.6b00817 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Figure 6. Simplified reaction pathways for (a) original POX process before oxygen is exhausted and (b) partially decoupled process, with the line thickness approximately proportional to the reaction rate.

Table 3. Parameters of the Arrhenius Rate Expression of Some Important Reactions reaction

A

β

E/cal

H + CH4 ↔ CH3 + H2 OH + CH4 ↔ CH3 + H2O O + CH4 ↔ CH3 + OH 2CH3 (+M) ↔ C2H6 (+M) C2H6 (+M) ↔ H + C2H5 H + C2H6 ↔ C2H5 + H2 2CH3 ↔ H + C2H5 H + C2H5 ↔ H2 + C2H4 H + C2H4 ↔ C2H3 + H2 H + C2H3 ↔ H2 + C2H2 HO2 + CH3 ↔ OH + CH3O CH3 + CH2O ↔ HCO + CH4 HCO + H2O ↔ CO + H + H2O HCO + M ↔ H + CO + M HCO + O2 ↔ HO2 + CO CH2CO(+M) ↔ CH2 + CO H + CH2CO ↔ CH3 + CO OH + C2H2 ↔ H + CH2CO

6.600 × 1008 1.000 × 1008 1.020 × 1009 6.770 × 1016 5.210 × 1017 1.150 × 1008 6.840 × 1012 2.000 × 1012 1.325 × 1006 3.000 × 1013 3.780 × 1013 3.320 × 1003 1.500 × 1018 1.870 × 1017 13.45 × 1012 8.100 × 1011 1.130 × 1013 1.326 × 1013

1.620 1.600 1.500 −1.180 −0.990 1.900 0.100 0.000 2.530 0.000 0.000 2.810 −1.000 −1.000 0.000 0.500 0.000 0.110

10840.00 3120.00 8600.00 654.00 1580.00 7530.00 10600.00 0.00 12240.00 0.00 0.00 5860.00 17000.00 17000.00 400.00 4510.00 3428.00 11059.00

Figure 7. Flowcharts of (a) original POX process and (b) partially decoupled process.

Compared with the original POX process, the PDP physically decouples the exothermic oxidation and endothermic pyrolysis reactions, as shown in Figure 7. Oxygen is actually not completely removed from the system; therefore this process is called “partially decoupling”. It prevents methane from directly

contacting with oxygen or other strongly oxidizing radicals, so the acetylene consumption reactions are significantly reduced. Meanwhile, the production cost decreases because part of the methane used as “fuel” in the original POX process is replaced by much cheaper gases. F

DOI: 10.1021/acs.iecr.6b00817 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Figure 8. Simulation results of PDP with the assumption of ideal mixing: (a) maximum acetylene yield and corresponding methane conversion and acetylene selectivity at different mixing ratios; (b) net acetylene production rate of the main acetylene formation reactions.

Figure 9. Contours of (a) static temperature, (b) mass fraction of C2H2, and (c) mass fraction of CH4 on a plane through reactor centerline (D = 30 mm, d = 4 mm, vm = 86.4 m/s, vj = 120 m/s).

Figure 8 shows the 0-D simulation results of the PDP. A series of methane mixing ratios are investigated to determine the optimal target mixing temperature. The effect of the mixing temperature on the maximum acetylene yield and corresponding acetylene selectivity and methane conversion are shown in Figure 8a. As expected, the maximum yield of acetylene obtained from the new partially decoupled process is 52%, which is much higher than that from the original POX process. However, this value is lower than the acetylene yield in the methane pyrolysis process because some of the acetylene is still oxidized by the oxidizing radicals remaining in the system. The methane conversion is lower in this new process than in the POX process, but the unreacted methane can be mixed with the coke oven gas and reused as fuel. In terms of the acetylene yield, the optimal mixing temperature is 1850 K. However, the selectivity to acetylene monotonically decreases with the mixture temperature in the range 1700−2000 K. For a lower mixing temperature, less coke oven gas is needed for pyrolysis of the same amount of methane. As a comprehensive consideration, the mixing temperature of 1700−1850 K is optimum.

Two important simplifications in the above simulations need to be discussed. First, the heat loss is neglected; thus more coke oven gas is needed in the real situation to deal with the same amount of methane. Second, the complex mixing process is not considered, and the mixing is simplified to be instantaneous and inert. Figure 8b shows the main acetylene formation reactions in the 0-D simulations of PDP. It is seen that these reactions are accomplished in a very short time. Therefore, the feasibility of the PDP in a real reactor needs further discussion 4.3. CFD Simulation Results. 4.3.1. Comparison with the 0-D Simulation. Compared with the ideal 0-D simulations that only reflect the effect of chemical kinetics, the CFD simulations include the effects of both the complex mixing and the detailed chemical reactions. Figure 9 presents the contours of the temperature and major species concentrations on the longitudinal cross section of the reactor. Methane contacts with the high temperature heat carrier gas, and a sharp temperature gradient is formed near the interface of these two streams. Methane is consumed so quickly under a high temperature that no methane remains in the regions with a temperature above 2200 K. In the region where temperature is G

DOI: 10.1021/acs.iecr.6b00817 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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the generated acetylene is converted to CO in these high temperature regions. The maximum acetylene yield in the CFD simulations of the PDP is still much higher than that of the original POX process. Therefore, this new process is very promising to realize using a JICF reactor. Turbulence not only affects the macromixing, but also affects the micromixing and turbulent reaction rate, as reflected in the EDC model. Figure 11 shows the profiles of the two important parameters in the EDC model, namely the “fine structure” fraction in a cell and the time scale. These two parameters characterize the effect of turbulence on the reactions. As shown in Figure 11, the fine structure fraction is large near the wall and the time scale is large in the middle of the fluid. Both the fine structure fraction and time scale in the EDC model are small near the nozzles. The turbulent Reynolds number based on the Kolmogorov scale can be expressed by eq 6 in the k−ε model.

higher than 2500 K, C2H2 is oxidized immediately as it is produced. The concentration of C2H2 is sensitive to the temperature, and it can maintain a relatively high value when the temperature is below 1800 K. Figure 10 shows the mass-averaged temperature, CH 4 conversion, and the yield of C2H2 on a series of cross sections

Ret =

k2 vε

(6)

According to eqs 1 and 6, the fine structure fraction is correlated to the turbulent Reynolds number by ξ3 ∝ Ret−3/4. Therefore, high turbulence tends to decrease the reaction rate provided that other conditions are the same. Note that the chemical reaction rate depends on not only the turbulent parameters but also the region temperature and concentration of the reactants. In the region near the nozzles except the thin interface between the hot and cold fluids, the macromixing is far from complete and the temperature is low; thus the reaction rate is small. 4.3.2. Influence of Mixing Ratio. The mixing ratio defined as Gj/Gm is an important operating parameter, where Gj and Gm are the mass flow rates of the jets and mainstream. Different mixing ratios lead to different mixing temperature. The mixing temperature of 1850 K is considered the appropriate value in the 0-D simulations. To determine the optimum mixing temperature in the JICF reactor, a series of simulations with

Figure 10. Axial profiles of mass-averaged static temperature, CH4 conversion, and C2H2 yield in the partially decoupled process.

along the axial direction. It is seen that the temperature sharply decreases near the nozzles and then becomes flat until the temperature reaches 1750 K at the exit of the reactor. The temperature profile clearly reflects the significant deviation from the ideally instantaneous mixing. The methane conversion reaches 0.75 at the reactor exit, which is higher than that in the ideally mixing simulation for a mixing temperature of 1750 K (see Figure 8a). The maximum C2H2 yield is about 41%, which is lower than the results of the simulations with ideal mixing. The reason is that methane is consumed too quickly in the high temperature region before the temperature reduces to the target mixing temperature. Some of

Figure 11. Contours of (a) fine structure fraction and (b) time scale τ in s. H

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Figure 12. Simulation results with different mixing ratios along the axial direction: (a) mass-averaged static temperature, (b) methane conversion, (c) mass-averaged mass fraction of C2H2, and (d) maximum C2H2 yield.

Figure 13. Simulation results of nozzle numbers along the axial direction: (a) mass-averaged static temperature, (b) methane conversion, (c) massaveraged mass fraction of acetylene, and (d) yield of acetylene at the exit of reactors.

different mixing ratios (0.482, 0.527, 0.566, 0.605, and 0.651)

and the main flow are set the same by changing the diameter of

have been tested. In these simulations, the jet velocity of methane

nozzles to eliminate the influence of momentum ratio. I

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Figure 14. Simulation results along the axial direction with different reactor diameters: (a) mass-averaged static temperature, (b) methane conversion, (c) yield of acetylene, and (d) mass-averaged local mixedness.

The simulation results are shown in Figure 12. A negative correlation between the system temperature and the mixing ratio can be easily found in Figure 12a. Figure 12b shows that the methane conversion is significantly enhanced when the mixing ratio decreases. Figure 12c indicates that the mass fraction of C2H2 quickly reaches the peak value and then begins to decline when the mixing ratio is too small. But when the mixing ratio is higher than 0.527, the C2H2 concentration continues to grow along the axial direction, though the slope of the concentration profiles is already very small near the exit. Figure 13d shows the maximum yield of C2H2 in the reactor under different mixing ratios, indicating that Gj/Gm = 0.566 is the optimal value and the corresponding mixing temperature is about 1750 K. It is seen that the optimal mixing temperature in the CFD simulations is lower than the value from the 0-D simulations (1850 K). In the actual mixing condition, the system temperature cannot instantly fall to 1850 K and the generated acetylene is significantly consumed in the high-temperature area. This explains the decrease of the optimal mixing temperature in the real reactor. 4.3.3. Influence of Nozzle Setting. The number of nozzles n is one of the most important structure parameters. Five different settings with different number of nozzles are tested. The reactor diameter is fixed at 30 mm and the mixing ratio is 0.566. The total area of the nozzles remains unchanged; thus the nozzle diameter decreases with the increase of nozzle number. Figure 13 shows the simulation results. The temperature profiles at the reactor centerline in Figure 13a well describe the influence of nozzle numbers on the temperature field. The penetration distance of the jets decreases with increasing nozzle number; therefore the temperature profile declines slowly when the nozzle number is large. When n = 2, the methane jets

penetrate so deeply that a low temperature region is produced near the reactor centerline. Figure 13b shows that the methane conversion is very close in these cases near the exit. But the concentration distributions of C2H2 are quite different in Figure 13c. The increase of nozzle number provides a larger contacting area between the methane and the high temperature mainstream, which leads to faster rates of both the C2H2 formation and consumption. So there exists an optimal nozzle number. Figure 13d indicates that n = 8 is the optimal value. 4.3.4. Influence of Reactor Diameter. Three different diameters (D = 30, 60, and 100 mm) are calculated to study the influence of the reactor scale-up. The mixing ratio and nozzle number are set as the optimal value obtained in the above sections. Figure 14a displays the mass-averaged temperature profiles along the axial direction. As expected, the temperature decreases more slowly in a larger reactor, and it continues to decline near the exit of the reactor. Figure 14b shows that methane is consumed faster in a smaller reactor. The yield of C2H2 significantly decreases with the increase of the reactor diameter, as shown in Figure 14c. This change in the performance of the JICF reactor is closely related to the dependence of the mixing behavior on the reactor size. To better characterize the mixing efficiency, a “local mixedness” is defined as ⎛ T* 1 − T* ⎞ , η = min⎜ ⎟ Tmix ⎠ ⎝ Tmix

(7)

where T* and Tmix are dimensionless numbers express as T* = J

T − Tj Tm − Tj

(8) DOI: 10.1021/acs.iecr.6b00817 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research Tmix =

Tc − Tj Tm − Tj

because the mixing efficiency is worse in a bigger reactor. The simulation results have provided important reactor design parameters and can be used to guide the experiments in subsequent research.

(9)

where Tm and Tj are the initial temperature of the mainstream and jet flow, respectively; Tc is the complete mixing temperature and it is fixed at 1750 K in these cases; T is the local temperature. The value of η is between 0 and 1. When the jet flow and mainstream are not mixed, η = 0; when the two fluids are completely mixed, η = 1. Figure 14d displays the mass-averaged local mixedness along the axial direction. The jets and mainstream reach “complete mixing” faster in the smaller reactor. The mixing efficiency is more intuitively described by the pseudo-color images of local mixedness, as shown in Figure 15. These results indicate that the yield of C2H2 is greatly affected by the mixing condition and the mixing enhancement is a key problem to further improve the PDP.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +86-10-6278-5464. Fax: +86-10-6277-2051. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors gratefully acknowledge the financial support by the National Natural Science Foundation of China (Grant 21276135) and by the Project of Chinese Ministry of Education (Grant 113004A).

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REFERENCES

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Figure 15. Contours of local mixedness with different diameters.

5. CONCLUSIONS A new process for acetylene production called partially decoupled process has been developed by simulations with a detailed chemical mechanism. The 0-D simulations with ideal mixing are conducted first to determine the possibly best performance of this new process. The maximum acetylene yield is 52%, and it is much higher than that in the original POX process (30−33%). A reaction pathway analysis shows that the CO formation pathway has been significantly inhibited in the new process. To further verify the new process, CFD simulations that consider the effect of velocity field, turbulence−chemistry interaction, and radiation are conducted for the jet-in-cross-flow (JICF) reactor. The maximum acetylene yield obtained from the CFD simulation results is 41%, which is also higher than that of the original process. The influence of the operating parameter (mixing ratio) and the structure parameters (nozzle number and reactor size) on the acetylene yield has been investigated. The mixing ratio of 0.566 and nozzle number of 8 are the optimal values to obtain the highest yield of acetylene. The acetylene yield significantly decreases when the reactor size increases K

DOI: 10.1021/acs.iecr.6b00817 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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DOI: 10.1021/acs.iecr.6b00817 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX