Numerical Simulation of CO Methanation for the Production of

Subscriber access provided by UNIVERSITY OF ADELAIDE LIBRARIES

Article

Numerical simulation of CO methanation for the production of synthetic natural gas in fluidized bed reactor Liyan Sun, Kun Luo, and Jianren Fan Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b01781 • Publication Date (Web): 10 Aug 2017 Downloaded from http://pubs.acs.org on August 17, 2017

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Energy & Fuels is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 24

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Numerical simulation of CO methanation for the production of synthetic natural gas in fluidized bed reactor Liyan Sun, Kun Luo*, Jianren Fan State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou, 310027, PR China

* Corresponding author. fax: +86 057187991863 E-mail address: [email protected]

Abstract: In order to obtain the characteristics of CO methanation process, the numerical simulations are carried out in fluidized bed reactor. The model is validated by comparing the simulation results of gas composition with experimental data. The influences of operational parameters on H2 conversation and CH4 yield are evaluated. The CO conversion and selectivity of CH4 increase with raising pressure, but decrease with the growing of temperature. The increase of catalyst inventory leads to difficulty in removal of reaction heat and reducing the production of CH4. The superficial gas velocity influences the production of methane slightly, but the reaction rates. Moreover, the CH4 production and CO conversion decrease with the decrease of ratio of H2/CO of feed composition. Meanwhile, the performance of water-gas shift reaction on CH4 yield is also analyzed. The addition of water into feed composition benefits the production of methane and the CO conversion. Key word: fluidized bed, methanation, simulation, catalytic reaction

ACS Paragon Plus Environment

Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 2 of 24

1. Introduction: The demand of energy is increasing sharply due to the fast development of industries and human activities 1 . The consequent pollution, global warming and supply shortage of fuel have drawn enough attention2,3. More and more researchers are considering the utilization of nature gas which is a clean energy 4 . The conversations of coal and biomass to substituted natural gas by methanation process are feasible way to reduce the pollution and overcome the shortage of energy. Substituted natural gas (SNG) production processes by gasification and methanation reaction have been developed since the 1960s. The gasification has been well developed and we focus on methanation reaction in this work. The process can be expressed mainly as a competition or combination of carbon monoxide methanation and watergas shift reaction: catalyst CO + 3H2 ←→ CH 4 + H 2O

catalyst CO + H2O ←→ CO2 + H2

∆H 298K = -206.28 kJ / mol

(1)

∆H 298K = -41.16 kJ / mol

(2)

The main issue is the strongly exothermic process during reaction which leads to carbon particle formation on the surface of catalysts5. And the catalytic activity and stability will be significantly affected due to the increasing of temperature6. Hence, the removal of reaction heat is the key point of methanation reactor. Hanaa et al.7 pointed out that the increase of


Page 3 of 24

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

temperature can be controlled by fluidized bed reactor. Liu et al.8 found that fluidized bed reactor gave a higher CH4 production and lower bed temperature than fixed bed reactor due to the massive heat transfer coefficient. Xu et al.9 found that the good performance of fluidized bed reactor was attributed to the large effective catalytic surface and effective heat and mass transfer. Gao et al. 10 found that the performances of catalyst are different under different state. Robert et al.11 presented the effects of catalyst size on production of methanation that the performance was greatly affected by crystallite size and smaller catalysts were more effective for CO methanation reaction12. For fluidized bed reactor, the fluidization behavior of catalysts is very complex due to the mixing of particles and interaction between solid phase and gas phase. Gas-particle flows are unstable and they manifest fluctuations of particle concentration. The formation of cluster, dense area of particle, will affect the interactions significantly 13 . Syamlal 14 concluded that clusters, ten times of particle diameter, existed in the fluidized bed and affected the flow behavior. Wang et al. 15 found that clusters formed during fluidization in fluidized bed ranging from small length at initial time to a large scale. For methanation process, reaction occurs in emulsion phase and the formation of cluster will cause the fluctuation of reaction rate between the cluster and single catalyst particle. Liu et al.16 pointed out the reaction rate on the scale of single particle was


Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

actually an oversimplification, the cluster structure should be considered. Boronat et al.17 showed that the catalytic activity of Au catalyst decreases with the raising cluster size. Rosch et al.18 found that the cluster size of catalyst had significant effect on CO adsorption properties. Accurate and fast simulation of particle system is hindered by their inherent heterogeneity at the meso-scale 19 . Unfortunately, we found very few researches published about the kinetic of reaction considering the effect of cluster and the numerical investigation of fluidized bed reactor recently. In this paper, the methanation process in fluidized bed reactor is numerical studied and the reaction rate is redefined considering the cluster structure. MFIX software is adopted and simulations are carried out by Euler-Euler model coupled with methanation reaction for better understanding the characteristics of reaction process. Results are compared with experimental data from a bench-scale reactor for validation of the model. Influence of operating parameters, including feeding ratio, gas velocity, catalyst inventory, are investigated numerically under different conditions. 2 Mathematical models 2.1 Governing equations In fluidized bed reactor, the mass conservation equations for each phase are given as:


Page 4 of 24

Page 5 of 24

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

∂(α g ρ g ) ∂t

+ ∇ ⋅ (α g ρ g u g ) = Rg

(3)

∂ (α s ρ s ) + ∇ ⋅ (α s ρ s u s ) = 0 ∂t

(4)

where u, ρ, and α represent velocity, density, volume fraction, respectively. Rg is the source term of mass transfer due to methanation reaction for gas phase20. For catalyst particles, the mass keep constant and the source term is set as 0. The momentum conservation equations for each phase are given as: ∂(α g ρ g u g )

+ ∇ ⋅ (α g ρ g u g u g ) = −α g ∇p + ∇ ⋅ (α gτ g ) + α g ρ g g + β (u s − u g )

(5)

∂ (α s ρ s u s ) + ∇ ⋅ (α s ρ s u s u s ) = −α s ∇p − ∇p s + ∇ ⋅ (α sτ s ) + α s ρ s g + β (u g − u s ) ∂t

(6)

∂t

β is the momentum transfer coefficient between phases, and Gidaspow model is adopted:  3  CDα gα s ρ g u g − u s     α g−2.65  dp  4   β =  µ gα s2   αs ρg   150 + 1.75  u − us   2    d  g   αgd p   p 

 24  CD =  Re α g  

Re =

α s < 0.2

(7) α s ≥ 0.2

1 + 0.15 ( Re α )0.687  g  

Re < 1000

0.44

Re ≥ 1000

ρg d p u g − us µg

τ is stress tensor and given as:


(8)

(9)

Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

[

]

Page 6 of 24

τ g = µ g ∇u g + (∇u g ) − µ g (∇ ⋅ u g )I

[

T

]

 

2 3

2 3

 

τ s = µ s ∇u s + (∇u s )T −  λs − µ s (∇ ⋅ u s )I

(10)

(11)

µ s and λs represent the solid shear viscosity and bulk viscosity,

respectively. For two-fluid model, the shear stress and solid pressure are calculated according to kinetic theory of granular flow. The basic variable of KTGF is the granular temperature and the transport equation can be expressed as: 3∂ (α g ρ g Θ) + ∇ ⋅ (α s ρ su s Θ) = (− ps I + τ s ) : ∇u s + ∇ ⋅ (κ s∇Θ) − γ s − J s  2  ∂t 

(12)

Θ is the granular temperature, κ s is the conductivity of granular

temperature, γ s and J s are dissipation rate from collision and fluctuating velocity of particle. The gas species transport equation is solved for methanation reaction and it can be written as follow: ∂(α g ρ gYg ,i ) ∂t

+ ∇ ⋅ (α g ρ g u g Yg ,i ) = ∇ ⋅ (α g J g ,i ) + Rg ,i

(13)

where Yg,i represents the mass fraction gas species i. Jg,i is the species diffusion flux of species i, Rg,i represents the reaction rate of species i. Methanation reaction is an exothermic progress and energy conservation equation is solved: ∂(α g ρg c pgTg ) ∂t

  µ   6 + ∇ ⋅ (α g ρg u g c pgTg ) = ∇α g  λg + c pg st ∇Tg  + α g hgs (Ts − Tg ) + ∑ Sg ,i c pg ,iTg (14) Prt     ds


Page 7 of 24

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

∂(α s ρs c psTs ) ∂t

  µ   6 + ∇ ⋅ (α s ρsus c psTs ) = ∇α s  λs + c ps st ∇Ts  + α s hgs (Tg − Ts ) + ∑ Ss ,i c ps,iTs (15) Prt   ds  

λ is the thermal conductivity. Pr is the Prandtl number. c is the specific

heat capacity which is a function of temperature. H is the heat transfer coefficient between phases. 2.2 Cluster structure dependent reaction rate The reaction rate for CO methanation and water-gas shift reaction are calculated as following: rm =

rw =

(1 + K

0.5 0.5 k1 K C pCO pH 2 C

0.5 pCO + K OH pH 2O pH−0.5 2

)

(16)

2

(

) )

k 2  K α pCO pH 2O − pCO2 p H 2 / K eq    p

0.5 H2

(1 + K

C

0.5 CO

p

+ K OH p H 2O p

−0.5 H2

2

(17)

The catalysts form cluster during fluidization under the interaction between gas and solid. The stream can not flow through the cluster and the effect area of catalyst for cluster is just the interaction surface. Hence, the catalytic reaction rate must be redefined by taking the cluster structure into consideration. Wang et al.21 developed a cluster structure dependent model to take the effect of cluster into consideration. In this research, we use the reaction model based on the cluster. To characterize multi-scale structures in fluidized reactor, we consider the cluster as a new particle calculated by method of identical volume. For accurate calculation, the


Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 8 of 24

reaction rate needs to consider the cluster structure during the fluidization. So the new rate, rcsd , is redefined. rcsd = frden + (1 − f )rdil

(18)

rden represents the reaction rate in dense phase and rdil for dilute phase. f is the volume fraction of dense phase. Since the reaction rate for fluidized bed has not been measured until now. The feasible method is to calculate rate according to the ratio between the cluster diameter and initial single particle diameter. rcsd = [1 + ( n −1/ 3 − 1) f ] ⋅ r

(19)

3. Setup of simulations A laboratory-scale methanation fluidized bed reactor is adopted in this simulation. Experimental data of species concentration from Kopyscinski et al.22 are employed for validation. The diameter and length of fluidized bed reactor are set as 0.052m and 0.2m respectively according to the experiment setup. The superficial gas velocity is range from 0.063 to 0.25 m/s. Diameter and density of catalyst powder are 0.1mm and 2000 kg/m3, respectively. No-slip boundary conditions are set for the wall. Detail information are list in the Table 1. The composition of feeding gas is H2, CO, N2 and H2O. And all the simulation conditions are list in Table 2.


Page 9 of 24

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Table 1 Parameters used in simulation Parameter

value

Unit

Bed diameter

0.052

m

0.2

m

0.033~0.094

m

0.5

--

0.063~0.25

m/s

0.0001

m

2000

kg/m3

Bed height Initial bed height Initial solid packing Superficial gas velocity Diameter of catalyst Density of catalyst

Table 2 Simulation setup Mass of catalyst

Velocity

H2

CO

H2O

(g)

(m/s)

(Vol%)

(Vol%)

(Vol%)

1

70

0.078

60

20

0

2

70

0.063

60

20

0

3

70

0.11

60

20

0

4

70

0.15

60

20

0

5

70

0.20

60

20

0

6

100

0.078

60

20

0

7

100

0.11

60

20

0

8

100

0.11

50

20

0

9

100

0.11

40

20

0

10

100

0.11

40

20

10

11

100

0.11

40

20

20

12

100

0.11

30

20

0

13

100

0.11

20

20

0

14

140

0.11

60

20

0

15

200

0.11

60

20

0

No.


Energy & Fuels

4. Thermal analysis of methanation reaction Thermal analysis is carried out first based on the minimization of Gibbs Energy of chemical system. As the shown in Fig. 1, the methanation reaction is affected significantly by the pressure and temperature. The conversion of carbon monoxide decreases with the temperature and the value reduces sharply in high temperature conditions. The methanation is an exothermic process and low temperature is advantageous for the forward reaction. Hence, removal of reaction heat is an effective way to accelerate the reaction. Fig. 1 also shows the effect of pressure on the methanation reaction. The conversion of carbon monoxide increases with the increase of pressure. That is because the methanation reaction is a subtraction process and high pressure will promote the reaction.

1.0 0.9 0.8

CO : H2=1 : 3

0.7

XCO (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 10 of 24

0.12 MPa 0.20 MPa 0.25 MPa 0.30 MPa 0.40 MPa 0.50 MPa 0.60 MPa

0.6 0.5 0.4 0.3 300

350

400

450

500

550

600

650

700

o

Temperature ( C)

Fig. 1 The conversation of reactant under different operating condition


Page 11 of 24

To characterize the performance of each process, the selectivity of CH4 is calculated for each simulation and it is defined as following: S ch 4 =

nch 4,out nco ,in − nco ,out

× 100%

(20)

where n is the molar flow of CH4 or CO. Fig. 2 demonstrates the selectivity of methane under different operating conditions. The selectivity of methane reduces with the increase of temperature, and increases with the growing of pressure of reactor. The tendencies of curves are similar with Fig. 1, but it becomes smooth at high temperature. So we can conclude the ideal condition for the methanation reaction is under the high pressure and low temperature. 1.00

0.12 MPa 0.20 MPa 0.25 MPa 0.30 MPa 0.40 MPa 0.50 MPa 0.60 MPa

0.95

CO : H2=1 : 3 0.90

SCH4 (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

0.85

0.80

0.75 300

350

400

450

500

550

600

650

700

o

Temperature ( C)

Fig. 2 Selectivity of methane under different operating conditions 5. Results and discussion The contours of time-averaged volume fractions of each species are presented in Fig. 3. The ratio of H2/CO is 3:1 and gas velocity is 0.11 m/s.


Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

CO is consumed rapidly near the distributor of bed due to the high reaction rate according to the reaction kinetic, also the high interaction with catalyst. At top field, CO concentration is nearly zero. The distribution of H2 is similar to the CO, but H2 is not completely consumed and residual is observed. The reason maybe is the water-gas shift reaction which consumes CO and produces H2. The production of CH4 is very fast and concentration of CH4 distributes uniformly along the height.

Fig. 3 Time-averaged distribution of mass fractions of CO, H2 and CH4 To validate current model, the simulated results are compared with the experimental data. Fig. 4 shows the volume-averaged gas species concentration in vol% along the height of bed with 100g catalysts. The concentration of H2 decreases rapidly in first 15mm after distributor and


Page 12 of 24

Page 13 of 24

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

then keeps nearly constant to the end of bed. In accordance with Fig. 3, CH4 concentration increases at the same time to maximum value of approximately 45%. The CO concentration diminishes very quickly to zero in the first 10 mm. The N2 concentration increases rapidly and reaches maximum due to the volume contraction reaction. CO2 is formed in first 5 mm by water-gas shift reaction. From 10mm, the rates of H2 consumption and CH4 production keep constant due to the end of catalyst bed and exhaustion of reactants. The simulated concentrations of CO, H2, CH4, and N2 are in reasonable agreement with data from reference. However the large discrepancy is observed at bottom. The deviation is caused by the complex interaction between phases. Meanwhile, the distribution of CO2 shows an opposite tendency against the experimental data near the distributor. This is caused by the complex reactions in the dense region. We only consider the main processes and the CO2 methanation process is neglected, which is a reversible reaction. Also, some other reactions generate CO2 are not taken into consideration due to the complex reaction kinetic. These are the main reasons for the tendency of CO2 distribution.


Energy & Fuels

30

Experimental data H2 25

CO CH4 N2

20

Height (mm)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 14 of 24

CO2

Simulation results 15

H2 CO CH4

10

N2 CO2

5

0 0

5

10

15

20

25

30

35

40

45

50

Vol %

Fig. 4 Comparison of the simulated species composition with experimental data Usually, the ratio between H2 and CO of the syngas from gasification of biomass or coal is unstable and ranges from 0.3 to 2.0. The production is quite different under different feed components. Figure 5 represents the production of methane at different ratio of H2/CO. Five simulations are carried out for analyzing the effect of feed component ratio. The volume fraction of methane increases near the distributor and then keeps nearly constant to the end of bed. Comparing the results under different operating conditions, it is easy to be observed that the decrease of feeding ratio produces less methane. For the CO concentration, it is consumed completely at ratio 3 due to methanation and water-gas shift reaction as an ideal condition. When the ratio is less than 3, the concentration of carbon monoxide excesses the amount, and it increases at the outlet with


Page 15 of 24

the decrease of feed ratio between H2 and CO. Moreover, when the ratio is very small, such as 1.5 and 1.0, the difference becomes small between different curves.

60

100g catalyst

55

Vg=0.11 m/s

50

H2:CO=3.0 : 1.0

CH4 vomlume fraction

45 40

H2:CO=2.5 : 1.0

35 30

H2:CO=2.0 : 1.0

25 20

H2:CO=1.5 : 1.0

15 10

H2:CO=1.0 : 1.0

5 0 0

10

20

30

40

50

60

70

80

90

100

80

90

100

Height of bed (mm)

25

100g catalyst 20

CO vomlume fraction

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Vg=0.11 m/s

H2:CO=1.0 : 1.0 H2:CO=1.5 : 1.0

15

H2:CO=2.0 : 1.0

10

H2:CO=2.5 : 1.0

5

H2:CO=3.0 : 1.0

0 0

10

20

30

40

50

60

70

Height of bed (mm)

Fig. 5 Effect of feed composition on concentration of gases Fig. 6 demonstrates the comparison between simulation results and experimental data with different catalyst inventories. The feeding ration


Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

of H2 and CO is 3.0 and superficial gas velocity is 0.11 m/s. The simulation results are collected at outlet under the steady state. The left column in solid is the experimental data from the literature. For each case, the CO is not placed since it is vanishes very soon during reaction. The volume fraction of CO2 is less than 5% which is the product of water-gas reaction. The concentration of H2 is nearly 10 % which do not react completely in the reactor. The simulation results are in reasonable agreement with data from reference. Comparing the results with different inventories, the productions of methane decrease slightly with the increase of mass of catalysts. The possible reason for this phenomenon is the increasing of temperature of the bed. As we mentioned before, the main challenge of methanation reactor is the removal of reaction heat. And a region with high temperature occurs for the bed with more catalysts which leads to decrease of methanation rate.


Page 16 of 24

Page 17 of 24

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Fig. 6 Effect of catalyst inventory for the concentration of gas components Fig. 7 shows the distribution of gas component concentrations for cases with different inventories (200g, 70g). Reactions complete rapidly at first a few millimeters, so only 35 millimeters height is plotted in the figure. In the simulation of 200g catalyst, the H2 concentration decreases rapidly from initial value, 60 vol% to 10 vol%. The CO concentration diminishes very quickly in first 10 mm. The CH4 concentration increases at the same time to approximately 45 vol%. The trend of distribution of gas concentration with 70g catalyst is similar. But there are some differences need to be noticed. The locations of maximum value of concentration are shifted by a few millimeters downwards compared with simulation results


Energy & Fuels

with 200g catalysts. The rate of conversion of H2 in simulation (70g) is faster than that in simulation (200g), as shown in the figure by angle θ1 and θ2. Also the production rate of CH4 is higher for simulation with 70g catalysts. The appropriate explanation is the influence of temperature. It is hard to remove the reaction heat for the case with more catalyst inventory. According to the reaction kinetic theory, increase of temperature will accelerate the reaction rate, but the water-gas shift reaction and reverse reactions play an important role in this temperature range according to the experiment. One would expect a high rate of H2 conversion and CH4 production, but the opposite is observed due to the high temperature. 35

35

30

Height of bed (mm)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 18 of 24

30

200g catalyst

70g catalyst

CO H2

25

CH4

20 15

25

CO H2

20

CH4

H2O

H2O

CO2

15

CO2

10

10

θ1 5

θ2

0

5 0

0

10 20 30 40 Volume fraction (%)

50

0

10 20 30 40 Volume fraction (%)

50

Fig. 7 Profile of simulated gas species concentration and bed temperature To achieve high yield of methane and high conversion of carbon monoxide, WGS reaction plays a significant role for adjusting the ratio


Page 19 of 24

between H2 and CO. Fig. 8 demonstrates the influence of additional water in feeding gases on the yield of methane and carbon monoxide conversion. The ratio of H2/CO of syngas is usually not enough for reaction. The WGS reaction will produce additional H2 for methanation reaction. Compared the CH4 yield, the increase of addition water is helpful for production of methane under current situation. The volume fraction of methane increases from 22% (no water) to 32.5% (with water). The concentration of carbon monoxide also decreases with the addition of water in feeding gases.

36 32 28

Volume fraction

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

24 20

40% H2

CH4

40% H2

20% CO

CO

20% CO 10% H2O

16

CH4 CO

40% H2

CH4

20% CO 20% H2O

CO

12 8 0

10

20

30

40

50

60

70

80

Height of bed (mm)

Fig. 8 Effect of feed composition on CH4 and CO concentration Fig. 9 displays the instantaneous solid volume fraction under different superficial gas velocity. The different color represents the solid volume fraction as shown in the label. It is easy to be observed that the expansion height of bed increases continuously with the fluidizing gas velocity.


Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Also, the area of dense region decreases with increase of gas velocity. These will influence the reaction rate and the reaction process. Also, the mass and heat transfer of the bed material that will significantly influence the particle mixing and removal of reaction heat.

Fig. 9 Profile of solid volume fraction under different gas velocity (from 6.3, 7.8, 11, 15 and 20 cm/s) Fig. 10 shows the effect of inlet gas velocity on the volume fraction and the angle of curve. To show the result clearly and visually, we use the angle θ of the curve for methane concentration to represent the yield rate as shown in the figure. The smaller the value θ represents the bigger production rate. The concentration of methane increases slightly with raising gas velocity. That indicates that the increase of inlet gas velocity has small effect on the terminal results of production under current


Page 20 of 24

Page 21 of 24

conditions. But it will affect the process of the methanation. The angle θ decreases with the increase of superficial gas velocity. Less time is needed for completing the reaction. The reason we think is the high gas velocity helps to remove the reaction heat fast which is advantageous for the exothermic reaction. Also the contact and mixing of gas and solid is enhanced.

30 28

Volume fraction (%) and angle (degree)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

26 24 22 20

CH4 volume fraction

18 16

Angle of CH4 curve

14 12 10 8 6 4 2 0 6

8

10

12

14

16

18

20

22

Gas velocity (cm/s)

Fig. 10 Effect of gas velocity on CH4 concentration and angle of curve

4. Conclusion: The simulations of methanation reaction in fluidized bed reactor are carried out using CFD open-source software. The results of species concentration are in reasonable agreement with experiment data. The CO is consumed rapidly and little H2 remains in the bed due to water-gas shift reaction. At current situation, with the increase of catalyst inventory, the


Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

production of methane reduces slightly. The high fluidizing gas velocity is beneficial for the removal of reaction heat and the increasing of production rate of CH4. By adding the water into the feedstock, the methane production increases since the additional hydrogen is produced by water-gas shift reaction.

Acknowledgement This work is supported by the Fundamental Research Funds for the Central Universities, China Postdoctoral Science Foundation funded project (509200-X91701). We are grateful to that.

Reference:

(1) Younas M, Kong L L, Bashir M, Nadeem H, Shehzad A, Sethupathi S. Energ. Fuel. 2016,30,8815-8831. (2) Chein R, Chen W, Yu C. J Nat Gas Sci Eng. 2016,29,243-251. (3) Michiaki Y, Hiroki H, Katsuhiko A, Kohichi I, Koji H. Catal.

Commun. 2006,7,24-28. (4) Razzaq R, Li C, Amin N, Zhang S, Suzuki K. Energ. Fuel. 2013,27, 6955-6961. (5) Neubert M, Widzgowski J, Ronsch S, Treiber P, Dillig M, Karl J.

Energ. Fuel. 2017,31, 2076-2086 (6) Cheng C, Shen D, Xiao R, Wu C. Fuel. 2017,189,419-427.


Page 22 of 24

Page 23 of 24

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

(7) Hanaa E, Chakib B. Energy. 2014,75,81-88. (8) Liu B, Li S. Journal of Energy Chemistry. 2013,22,740-746. (9) Liu J, Shen W, Cui D, Yu J, Su F, Xu G. Catal. Commun. 2013,38, 35-36. (10) Gao Z, Cui L, Ma H. Int. J. Hydrogen. Energ. 2016,41,5484-5493. (11) Robert D, Wang Y, Xia G, James S, Jamelyn H, Daniel P. Appl.

Catal. A-Gen. 2007,326,213-218. (12) Sakae T, Toru S, Kiyoshi Oa. Int. J Hydrogen. Energ. 2004,29,1065 -1073. (13) Wang S, Liu G, Lu H, Xu P, Yang Y, Dimitri G. Powder. Technol.

2012,225,176-189. (14) O’Brien T J, Syamlal. Circulating Fluidized Beds IV. 1993,345-350. (15) Wang S, Zhao G, Liu G, Lu H, Zhao F, Zhang T. Powder. Technol. 2014,254,214-227. (16) Liu C, Wang W, Zhang N, Li J. Chem. Eng. Sci. 2015,122,114-129. (17) Boronat M, Leyva A, Corma A. Accounts. of Chem. Res. 2014,47, 834-844. (18) Yudanov V, Metzner M, Genest A, Rosch N. J. of Phys. Chem. C.

2016,112,20269-20275. (19) Qiu X, Wang L, Yang N, Li J. Powder. Technol. 2017,314,299-314.


Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(20) Chen J, Yin W, Wang S, Meng C, Li J, Qin B, Yu G. Bioresource.

Technol. 2016,211,93-100. (21) Wang S, Wang Q, Chen J, Liu G, Lu H, Sun L. Advanced. Powder.

Technol. 2016,27,57-63. (22) Jan K, Tilman S, Serge B. Chem. Eng. Sci. 2011,66,924-934.


Page 24 of 24

Numerical Simulation of CO Methanation for the Production of

Recommend Documents