Lab scale biogas reformer D5.5 Final model of novel ... · WP5 – Lab scale biogas reformer ... This report presents the further development of the model presented in D5.4 and the

BIONICO

BIOGAS MEMBRANE REFORMER FOR DECENTRALIZED HYDROGEN PRODUCTION

FCH JU GRANT AGREEMENT NUMBER: 671459

Start date of project: 01/09/2015 Duration: 3 years

WP5 – Lab scale biogas reformer

D5.5 Final model of novel reforming reactor system

Topic: FCH-02.2-2014 - Decentralized hydrogen production from clean CO2-containing biogas Type of Action: FCH2-RIA Research and Innovation action Call identifier: H2020-JTI-FCH-2014-1

Due date of deliverable: 2017-04-30

Actual submission date:

Reference period: M20

Document name: BIONICO-WP5-D55-DLR-TuE-20170518-v1 Prepared by (*): TUE

Version DATE Changes CHECKED APPROVED

V1 2017-05-18 First release TUE Niek de Nooijer

Dissemination Level

PU Public X

PP Restricted to other programme participants (including the Commission Services)

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CON Confidential, only for members of the Consortium

___________________________________________________________________________________ (*) indicate the acronym of the partner that prepared the document

D5.5 Final model of novel reforming

membrane reactor system

Proj. Ref.: BIONICO - 671459 Doc. Ref.: BIONICO-WP5-D55-DLR-TUE-20170518-v01 Date: 2017/05/18 Page Nº: 2 of 23

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PUBLISHABLE SUMMARY

In this deliverable the model of the novel membrane reactor developed in the BIONICO project is presented. The developed model is validated with steam reforming experiments in a lab scale fluidized bed membrane reactor. The experiments and results are already presented in deliverable D5.3. The first model developed in D5.4 is reviewed and updated to account of the mass transport from the bulk of the system to the membrane, also known as concentration polarization.

The 1D fluidized bed membrane model is extended with a film layer description of concentration polarization. Permeation experiments show that the thickness δ which describes the mass transfer

resistance can be fitted. The results also show that the flow conditions significantly affect the mass transfer resistance. The delta used to validate the model is obtained from a fitting to one base case experiment and shows to predict the other experiments accurately. The model is then used to optimize and scale up the system. An important design parameter is introduced, the load to surface ratio. Showing that higher temperatures and pressures are beneficial. The scale up is dependent on the thickness of δ if delta changes significantly with scale up this can have significant effects

on the predictability of the model. Scale up experiments can give a more accurate prediction of the behaviour of δ at higher pressures and different flow conditions. Autothermal conditions increase the conversion, however give lower hydrogen recovery.




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Content

PUBLISHABLE SUMMARY .................................................................................................................. 2

EXECUTIVE SUMMARY ....................................................................................................................... 4

1.1. Description of the deliverable content and purpose .............................................................. 4

1.2. Brief description of the state of the art and the innovation brought ....................................... 4

1.3. Deviation from objectives ..................................................................................................... 4

1.4. If relevant: corrective actions ............................................................................................... 4

1.5. If relevant: Intellectual property rights .................................................................................. 4

2. INTRODUCTION ............................................................................................................................ 5

2.1. Biogas steam reforming in a fluidized bed membrane reactor. ............................................ 5

3. MODEL .......................................................................................................................................... 6

3.1. Model description ................................................................................................................. 6

3.2. Membrane permeation ......................................................................................................... 9

4. RESULTS ...................................................................................................................................... 11

4.1. Concentration polarization ....................................................................................................... 11

4.2. Model validation ...................................................................................................................... 13

4.3. System optimization ................................................................................................................ 15

CONCLUSIONS .................................................................................................................................... 22

REFERENCES ...................................................................................................................................... 23




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EXECUTIVE SUMMARY 1.1. Description of the deliverable content and purpose In this deliverable the model of the novel membrane reactor developed in the BIONICO project is presented. The developed model is validated with steam reforming experiments in a lab scale fluidized bed membrane reactor. The experiments and results are already presented in deliverable D5.3. The first model developed in D5.4 is reviewed and updated to account of the mass transport from the bulk of the system to the membrane, also known as concentration polarization. 1.2. Brief description of the state of the art and the innovation brought Extension of a 1D fluidized bed model with a film layer description of the concentration polarization. 1.3. Deviation from objectives N/A 1.4. If relevant: corrective actions N/A 1.5. If relevant: Intellectual property rights IP by TUE




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2. INTRODUCTION 2.1. Biogas steam reforming in a fluidized bed membrane reactor. Biogas is produced from biomass mostly by anaerobic digestion. Just like natural gas biogas is rich in CH4

and therefore a potential source for hydrogen production. However, biogas, compared to natural gas, has a relatively high amount of CO2 making the reforming of biogas for the production of hydrogen difficult. The reforming of natural gas proceeds mainly through two reactions: Steam methane reforming (SMR eq. 1) and Water gas shift (WGS eq. 2), reaction 1 and 2, respectively. In the case of biogas reforming the dry reforming reaction (DR, eq. 3) should also be considered, due to the high CO2 fraction in the feed.

𝐶𝐻4 + 𝐻2𝑂

↔ 𝐶𝑂 + 3 𝐻2 ∆H𝑟⊖ = +206 𝑘𝐽 𝑚𝑜𝑙−1

Eq. (1)

𝐶𝑂 + 𝐻2𝑂

↔ 𝐶𝑂2 + 𝐻2 ∆H𝑟⊖ = −41 𝑘𝐽 𝑚𝑜𝑙−1

Eq. (2)

𝐶𝐻4 + 𝐶𝑂2

↔ 2𝐶𝑂 + 2 𝐻2 ∆H𝑟

⊖ = +247 𝑘𝐽 𝑚𝑜𝑙−1 Eq. (3)

Besides promoting the dry reforming reaction, the CO2 in the feed imposes also a thermodynamic equilibrium limitation on the yield and selectivity of hydrogen, when using the conventional reforming process. Moreover, the biogas mixture is sensitive for carbon formation in the operation regime used in the conventional process. In the project BIONICO a novel reaction concept is proposed to overcome these challenges and to produce pure hydrogen from Biogas. The reaction concept integrated high flux Pd-based membranes in a fluidized bed membrane reactor allowing for the selective extraction of hydrogen from the reaction system. The in-situ extraction of hydrogen results in: low temperature operation regime, higher energy efficiency and production of pure hydrogen without the requirement of downstream separation. Figure 1 one shows a schematic representation of the reactor concept.

Figure 1. Schematic representation of a fluidized bed membrane reactor.

In the project BIONICO the membranes produced by TECNALIA are thin film PdAg membranes supported on an Al2O3 porous support. The membranes are integrated in a fluidized bed reactor with a Rh/Al2O3 based catalyst supplied by JM. This report presents the further development of the model presented in D5.4 and the validation of a fluidized bed membrane reactor model. For the validation experimental results obtained in D5.3 are used. First the model is described, both the equation and closure correlation used are commented on. The newly implemented description of mass transport form the bulk to the surface of the membrane, also known as




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concentration polarization is then validated using experimental results in an empty tube and fluidized bed reactor. The validation is then extended to the steam reforming experiments. Following this, the model is used to describe the system with lower dilutions. Finally, the model is scaled up to the required size to produce 100 kg of hydrogen per day and results are presented for both steam reforming and auto thermal conditions. 3. MODEL 3.1. Model description The reactor model used in this work describes a membrane fluidized bed section in which a dead-end and perm-selective membrane can be integrated. The model used is a further development of the model used by Gallucci et al. [1]. The model is developed by Deshmukh et al. and based on the frequently used bubble assemblage model proposed by Kato and Wen [2][3]. In this model both bubble and emulsion phase are divided in a number of CSTRs (Continuous-flow Stirred-Tank Reactor) along the fluidized bed. In the work of Kato and Wen the volume of the CSTR is related to the local bubble size. However in the work of Deshmukh et al. this is not the case, the CSTRs are of equal volume and their number describes the amount of back mixing in the system [2][4]. The assumptions used in the model are summarized below:

The fluidized bed consists of two phases, the bubble and the emulsion phases

The gas flowing though the emulsion phase is considered to be completely mixed and at

incipient fluidization conditions.

The Bubble is assumed to be free of catalyst particles and homogeneous gas phase reactions

are neglected, hence no reaction is taking place in the bubble phase.

The bubble phase gas is assumed to be in plug flow (i.e. large number of CSTRs), where the

bubble size and the bubble rise velocity changes for each section.

The gas is extracted through the membrane from both the emulsion and the bubble phase,

distributed according to the local phase fraction. To maintain the emulsion phase at minimum

fluidization conditions the extracted gas is replenished from the bubble phase.

The bubble-to-emulsion phase mass transfer coefficients are assumed to be constant along

the bed height.

A uniform temperature is assumed throughout the adiabatic fluidized bed, thus assuming no

heat transfer limitations between the bubble and emulsion phases.

The steady state overall (bubble and emulsion phases) component mass conservation equations, the total volume balance and the overall balances for each component used in the model are formulated in Table 1. These equations take into account the chemical transformations in the emulsion phase and a net gas production due to the chemical reactions and gas extraction via the membrane. The equations are solved for each section in the fluidized bed reactor. Since the introduction of membrane reduces the extent of back mixing, the amount of CSTRs is selected to represent plug flow behavior. The empirical correlations for the description of the system hydrodynamics and mass transfer are obtained from literature and described in Table 2. Although these equations are developed for fluidized beds without membranes, it is shown in prior work that they give a reasonable description of the system [5]. The chemical transformations




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are described using the kinetic rate expressions of Numaguchi and Kikuci for steam reforming and water gas shift [6]. The dry reforming of methane is assumed not to take place in the reactor. Due to the large amount of steam used in the experiments the steam reforming is assumed to be dominant over the dry reforming. Research is still ongoing with in the project BIONICO to validate this assumption. The kinetic rate equations used are summarized in Table 3. The kinetic parameters of rhodium are obtained from Marra et al. and used in the Arrhenius expression shown in equation 4, the kinetic parameters are shown in Table 4 [7].

Table 1. Mass balance equations for each CSTR in each section of the fluidized bed membrane reactor.

Total mass balance

, 1 , 1 , , , 1 , 1 , ,

, , , , , ,

1

(1 ) 0c

s s s s

b n T b n b n T b n e n T e n e n T e n

nmembrane membrane

i mol w i membrane b n i mol w i membrane b n

i

u A u A u A u A

N M A N M A

Bubble phase component mass balance

, 1 , 1 , , , , , , , , , ,

1

, , , , , , ,

1

0

c

c

ns s

b n T b n b n T b n be i n b n b n b i n e i n

i

nmembrane

i mol w i membrane b n e i n b i n

i

u A u A K V w w

N M A w SF Q w SF Q

Emulsion phase component mass balance

, 1 , 1 , , , , , , , , , ,

1

, , , , , ,

1 1

, , , ,

1 (1 )

0

c

c rxn

ns s

e n T e n e n T e n be i n b n b n b i n e i n

i

n nmembrane

i mol w i membrane b n j i j e n p n e

i j

e i n b i n

u A u A K V w w

N M A r V

w SF Q w SF Q

Transfer term

, 1 , 1 , , , , , , , , , ,

1

, , ,

1

1

c

c

ns s

e n T e n e n T e n be i n b n b n b i n e i n

i

nmembrane

i mol w i membrane b n

i

Q u A u A K V w w

N M A

Where

, , ,

,0 ,

,0 ,

1

1

s

e n T e n T b n

s

b T tot T b n

s

b T tot T b n

u A u A

u A u A

u A u A




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Table 2. Empirical correlations used in the model for the description of the system hydrodynamics and mass transfer.

Parameter Equation

Archimedes number [8] 𝐴𝑟 =

𝑑𝑝3𝜌𝑔(𝜌𝑝 − 𝜌𝑔)𝑔

𝜇𝑔2

Minimum fluidization velocity [9] 𝑢𝑚𝑓 = (𝜇𝑔

𝜌𝑔𝑑𝑝)(√(27.2)2 + 0.0408𝐴𝑟 − 27.2)

Bed voidage at minimum fluidization velocity

[32] 휀𝑚𝑓 = 0.586𝐴𝑟−0.29(

𝜌𝑔

𝜌𝑝)0.021

Projected reactor area 𝐴𝑇 =𝜋

4𝐷𝑇

2

Bubble diameter [10] 𝑑𝑏 = 𝑑𝑏,𝑚𝑎𝑥 − (𝑑𝑏,𝑚𝑎𝑥 − 𝑑𝑏,0)𝑒

(0.3𝑧𝐷𝑇

)

Initial bubble diameter [8] 𝑑𝑏,0 = 0.376(𝑢0 − 𝑢𝑚𝑓)2

Maximum bubble diameter [8] 𝑑𝑏,𝑚𝑎𝑥 = min(1.6374𝐴𝑇(𝑢0 − 𝑢𝑚𝑓)0.4; 𝐷𝑇)

Average bubble diameter [8]

𝑑𝑏,𝑎𝑣𝑔 =𝑑𝑏,𝑚𝑎𝑥 + (𝑑𝑏,𝑚𝑎𝑥 − 𝑑𝑏0)

𝐷𝑇0.3

𝐻2 − 𝐻1(𝑒

−0.3𝐻2𝐷𝑇

− 𝑒−0.3

𝐻1𝐷𝑇 )

Average bubble rise [8] 𝑢𝑏,𝑎𝑣𝑔 = 𝑢0 − 𝑢𝑚𝑓 + 0.711(𝑔𝑑𝑏,𝑎𝑣𝑔)1/2

Emulsion velocity [8] 𝑢𝑒 =

𝑢0 − 𝛿𝑢𝑏

1 − 𝛿

Bubble phase fraction [3] 𝛿𝑏 =𝑢0 − 𝑢𝑚𝑓

𝑢𝑏,𝑎𝑣𝑔

Emulsion phase fraction [3] 𝛿𝑒 = 1 − 𝛿𝑏

Initial superficial bubble gas velocity 𝑢𝑏,0𝑠 = 𝑢𝑏𝑟,0𝛿𝑏,0 where 𝛿𝑏,0 = (1 − 𝐻𝑚𝑓/𝐻𝑓)

Height of the bed at min. fluid. Velocity [10] 𝐻𝑚𝑓 = 𝐻𝑠

1 − 휀𝑠

1 − 휀𝑚𝑓

Height of bed expansion 𝐻𝑓 = 𝐻𝑚𝑓

𝐶1

𝐶1 − 𝐶2

𝐶1 = 1 −

𝑢𝑏,0

𝑢𝑏,𝑎𝑣𝑔𝑒𝑥𝑝(−

0.275

𝐷𝑇)

𝐶2 =

𝑢𝑏,0𝑠

𝑢𝑏,𝑎𝑣𝑔[1 − 𝑒𝑥𝑝(−

0.275

𝐷𝑇)]

Gas exchange coefficient [8]

𝐾𝑏𝑐 = 4.5(𝑢𝑚𝑓

𝑑𝑏,𝑎𝑣𝑔) + 5.85(

𝐷𝑔

12𝑔

14

𝑑𝑏,𝑎𝑣𝑔

54

)

𝐾𝑐𝑒 = 6.77(

𝐷𝑔휀𝑚𝑓𝑢𝑏,𝑎𝑣𝑔

𝑑𝑏,𝑎𝑣𝑔3 )

12

1

𝐾𝑏𝑒=

1

𝐾𝑏𝑐+

1

𝐾𝑐𝑒




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Table 3. Reaction rate expressions for SMR and WGS used in the model.

Reaction Stoichiometry and reaction rate equation

Methane steam reforming 𝐶𝐻4 + 𝐻2𝑂 ⇌ 𝐶𝑂 + 3𝐻2

[6] 𝑟2 =

𝑘2(𝑝𝐶𝑂𝑝𝐻2𝑂 − 𝑝𝐻2𝑝𝐶𝑂2

/𝐾𝑒𝑞,2)

𝑝𝐻2𝑂1.596

Water gas shift 𝐶𝑂2 + 𝐻2𝑂 ⇌ 𝐶𝑂2 + 𝐻2

[6] 𝑟3 =

𝑘32(𝑝𝐶𝑂𝑝𝐻2𝑂 − 𝑝𝐻2𝑝𝐶𝑂2

/𝐾𝑒𝑞,3)

𝑝𝐻2𝑂

𝑘𝑖 = 𝐴𝑖exp (−𝐸𝑎𝑐𝑡,𝑖

𝑅𝑇) Eq. (4)

Table 4. Kinetic parameters obtained from Marra et al.

Constant Value Unit

A2 9.74 × 104 mol · bar−0.404 · kgcat−1 · s−1

A3 17.2 × 102 mol · bar−1 · kgcat−1 · s−1

Eact,2 83.6 × 103 J · mol−1

Eact,3 54.531 × 103 J · mol−1

3.2. Membrane permeation The selective extraction of hydrogen in the model is described by the Sieverts law, using obtained parameters of the membrane. The parameters obtained in D5.3 and used in this work for the membrane are shown in Table 5.

2 2

0, ,

aEn nRT

i H Ret H Perm

pN e P P

t

Table 5. Experimental parameters from the membrane characterization used in the FBMR model.

Membrane code Activation energy

(kJ/mol)

Pre exponential factor

(mol m-2 s-1 pa-0.5)

Ideal perm

selectivity at 384 °C

∆P 1 bar

Ideal perm

selectivity at 545 °C

∆P 1 bar

E619 (c) 9.26 8.74 ∙ 10-3 4576 18000

In the case hydrogen extraction from a mixture through a high selective and permeable membrane using only Sieverts law is found to be insufficient to predict the flux. Due to a depletion of the permeable species near the membrane and accumulation of the non-permeable ones a boundary layer is formed adjacent to the membrane. The lower concentration of the permeable species results in a decreased driving force hence, a reduction of the permeated flux. To account for the mass transfer limitation induced by this effect,




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also known as concentration polarization, a stagnant film model is applied in the model. In the stagnant film model the following assumptions are applied:

Steady state conditions are present;

The concentration of the bulk in the radial direction is constant;

No axial convection in the film layer;

No axial dispersion, only radial dispersion.

The expression for the flux through the stagnant film layer is derived for a cylindrical membrane. A schematic representation of the membrane and the mass transfer layer is given in Figure 2.

Figure 2. Schematic representation of the mass transfer layer around the membrane.

The derivation yields the following equation for the flux through the mass transfer layer:

,

,

,

1ln

1ln 1

m

i mi toti r

i b

m

m

xDCN

xr

r

Where rm is the outer radius of the membrane, Ni,rm is the flux at the surface of the membrane, Ctot the total concentration, δ the thickness of the film and Xi,m and Xi,b the concentration of species i at the membrane

and in the bulk respectively. Di is the diffusion coefficient which in an empty tube can be taken as the gas phase diffusivity and in a fluidized bed as the radial dispersion. However no correlation to describe the radial dispersion is available in literature, therefore in this work the radial dispersion is set at 1x10-4 obtained from CFD simulations. The above given equation can be set equal to the flux trough the membrane to obtain the partial pressure. However the layer thickness δ is missing, also for this parameter no correlation is available. In this work δ

is fitted from gas mixture permeation experiments in an empty tube, fluidized bed and reaction conditions. The results of the estimation of δ are presented in the results section of this work.




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4. RESULTS 4.1. Concentration polarization Simple gas mixture permeation tests are performed in order to validate the implemented concentration polarization in the model. First permeation test of hydrogen nitrogen mixtures in an empty shell and tube configuration are performed. Four sets are performed, three at different total flow rates with a fixed total pressure and a feed composition of hydrogen nitrogen mixtures between 40% and 90% of hydrogen. The fourth set is performed at different pressures keeping the total velocity constant, in this case hydrogen and nitrogen were fed 1:1. To obtain the thickness δ in the model it is set to match the outlet flow of hydrogen from the experiments. In this way different δ and corresponding mass transfer resistances are obtained for the different conditions.

Figure 3. Mass transfer resistance vs. the Average partial pressure of H2 in the module, the error bars indicate the maximum and minimum hydrogen partial pressure in the experiment.

The results of the first three sets are show in Figure 3. In these experiments the total pressure is kept constant while the partial pressure of hydrogen is changed by different compositions of feed gas. The average partial pressure in the reactor is shown, the error bars indicate the feed and outlet partial pressure of hydrogen. The experiments have been performed at three different total feed flow rates. The thickness δ obtained for these experiments ranged between 1.13 cm and 0.4 cm.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0 0.5 1 1.5 2 2.5 3

1/k

Average Pressure of H2 [bar]

3.6 Nl/min

4.8 Nl/min

6 Nl/min




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Figure 4. Mass transfer resistance vs. the average partial pressure of H2 in the module at, 400 °C and a 50% H2 50% N2 feed and different total pressures, the error bars indicate the maximum and minimum H2 partial pressure in the experiment.

In Figure 4 the results are presented in the same way as for Figure 3. In this case the total velocity is kept constant, by changing the total feed flow rate with increasing pressure. However, the mass transfer resistance is decreased instead of increased with the partial pressure of hydrogen. The experiment should be at a more or less constant velocity. Closer inspection of all the results by calculation of the average Reynolds number in the model shows that the conditions are not constant, and the Reynolds number is actually different for each experiment. The Reynolds number is calculated as following

Red

Where the characteristic length d is the distance between the membrane surface and the reactor wall.

Figure 5. Mass transfer resistance vs. average Reynolds number in the module.

From the results of Figure 5 a clear decrease of mass transfer resistance with increasing Reynolds number can be found for all the experiments.

0

0.5

1

1.5

2

2.5

3

3.5

0 0.5 1 1.5 2 2.5

1/k

Average Pressure of H₂ [bar]

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

0 5 10 15 20 25 30 35

1/k

Reynolds number [-]

3.6 Nl/min

4.8 Nl/min

6 Nl/min

Serie4




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After the experiments in the empty system, it was filled with the catalyst particles and studied under fluidized conditions. Similar experiments where performed in the fluidized bed membrane reactor as for the empty system. The radial dispersion of the fluidized bed was estimated from 2D two fluid model simulations, and found to be equal to 1*10-4 by Helmi et al., this radial dispersion was used in the calculation of the mass transfer coefficient. An average thickness δ was fitted to make the model

correspond the experiments. A δ of 0.975 cm was found to describe the fluidized bed system reasonably

well, the mass transfer resistance (1/k) was found to be 1.97, much lower compared to the 3.49 found in the empty system with a δ of 1.125 cm. Figure 6 shows the experimental and corresponding model results

of permeation test with equal conditions in both empty tube and fluidized bed, also the case without concentration polarization is shown.

Figure 6. Permeance plot of both experiments with and without fluidized and the corresponding modeling results.

The thickness δ is changing with the conditions in the reactor, the diffusion in the system plays an important

role in the extent of the concentration polarization. In the case of the fluidized bed the radial dispersion accounts for the diffusion term in the mass transfer coefficient. However the radial dispersion also effects the thickness of the boundary layer. The results show that the mass transfer resistance from bulk to membrane is decreased in a fluidized bed by both an increase of the diffusion term and a decrease in the boundary layer thickness. The thickness of δ for the simulations of the reforming experiments is selected and fitted by the base case

experiment, the value for δ was 0.5402 cm. This value is lower than what was obtained for the H2/N2

permeation mixtures. However the mass transfer resistance was found to be 1.47, a bit lower as for the gas mixtures. The average velocity, density and viscosity of the reforming mixture was also higher. The obtained δ of 0.5402 cm together with the radial dispersion coefficient of 1*10-4 was used for the calculation

of k in the model validation. 4.2. Model validation The model is validated with the use of the experimental results of D5.3. The outlet composition of the model has been compared with the outlet composition of the experiments. Figure 7 shows the outlet composition of the retentate.

0

0.05

0.1

0.15

0.2

0.25

0.3

0 50 100 150 200 250 300 350

Flu

x [m

ol s

-1 m

-2]

∆PH₂ [Pa0.5]

Empty tube, Exp.

Fluidized bed, Exp.

Without CP

Empty tube, Model

Fluidized bed, Model




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Figure 7. Parity plot of retentate outlet fractions.

The permeate flow obtained by the model and from the experiments shows fairly good agreement, Figure 8. The predictability of the model is significantly increased with the implementation of concentration polarization. However the results still shows discrepancy with increasing hydrogen flux, this can be explained by the fact that the thickness δ is fitted at bit different conditions.

Figure 8. Parity plot of the permeate flow rate in Nml/min of hydrogen.

To further validate the model and to study the system a set of experiments with low dilution is performed. This set of experiments approaches the actually feed of biogas to the BIONICO system. The base case representing a biogas composition with CO2/CH4 ratio of 0.7 is presented in Table 6.

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 0.1 0.2 0.3 0.4

Mo

del

Experiments

±5%

CH4

CO2

CO

H2

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200

Mo

del

Experiments

H2 [Nml/min]

±5%




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Table 6. Results of base case experiment with low dilution.

Feed composition (v/v) T (°C) P (bar) Conversion Hydrogen recovery

Exp. Model Exp. Model

CH4 16%

486 3 48% 46% 25% 23% CO2 11%

H2O 48%

N2 25%

4.3. System optimization In this part the model is used to calculate the required system configuration and dimensions to reach the target of 100 kg of hydrogen per day. This optimization is performed for different system parameters: pressure, temperature and CO2/CH4 ratio in the feed, furthermore the sensitivity of the model parameter δ

is studied. The system optimization is done in terms of methane conversion and separation factor vs load to surface ratio. The load to surface ratio is the volumetric feed flow rate of methane over the membrane surface.

𝑋𝐶𝐻4=

(𝐹𝐶𝐻4,𝑖𝑛 − 𝐹𝐶𝐻4,𝑜𝑢𝑡)

𝐹𝐶𝐻4,𝑖𝑛 Eq. (5)

𝑌𝑖𝑒𝑙𝑑𝐻2 =

(𝐹𝐻2,𝑃𝑒𝑟𝑚. + 𝐹𝐻2,𝑅𝑒𝑡.)

4 ∙ 𝐹𝐶𝐻4,𝑖𝑛 Eq. (6)

𝑆𝑒𝑝𝑒𝑟𝑎𝑡𝑖𝑜𝑛 𝑓𝑎𝑐𝑡𝑜𝑟𝐻2 =

𝐹𝐻2,𝑃𝑒𝑟𝑚.

(𝐹𝐻2,𝑃𝑒𝑟𝑚. + 𝐹𝐻2,𝑟𝑒𝑡.) Eq. (7)

𝐻𝑦𝑑𝑟𝑜𝑔𝑒𝑛 𝑟𝑒𝑐𝑜𝑣𝑒𝑟𝑦 𝑓𝑎𝑐𝑡𝑜𝑟 = 𝑌𝑖𝑒𝑙𝑑𝐻2∙ 𝑆𝑒𝑝𝑒𝑟𝑎𝑡𝑖𝑜𝑛 𝑓𝑎𝑐𝑡𝑜𝑟𝐻2

Eq. (8)

The selected conditions are taken of which the optimization is performed are taken from WP5 MS6. The conditions and feed gas composition used are summarized in Table 7.

Table 7. Compositions used for system optimization.

Parameter value Unit

Pressure 8 – 12 bar

Temperature 500 – 600 °C

Permeate pressure 0.1 bar H2O/CH4 2.4 - CO2/CH4 0.76 - N2/CH4 0.37 -

4.3.1. Pressure Increasing the pressure shows to increase both conversion and hydrogen recovery. Only when the load to surface ratio becomes very high the negative effect of the pressure on the thermodynamic equilibrium is not compensated by the membrane. The pressure of 12 bar is selected for the other analysis.




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Figure 9. CH4 conversion and Hydrogen recovery factor vs load to surface ratio at different pressures with a temperature of 550 °C.

4.3.2. Temperature The temperature increases the surface to volume ratio at which a full conversion and full hydrogen recovery can be obtained, due to the increase in hydrogen permeability of the membrane. For further analysis the case of 550 °C is selected because of the increase system performance, 600 °C would be

more favorable however the membranes would not be stable at this temperature.

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Load to surface [m3 h-1 m-2]

XCH₄ 8 bar

XCH₄ 10 bar

XCH₄ 12 bar

SepF 8 bar

SepF 10 bar

SepF 12 bar




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Figure 10. CH4 conversion and Hydrogen recovery factor vs load to surface ratio at different Temperatures with a Pressure of 12 bar.

4.3.3. Biogas The reforming of pure methane is compared with the reforming of biogas, the biogas. The volume to surface ratio of the system should be decreased to obtain the same conversion and separation factor. This means either the load of the system should be decreased or the number of membranes.

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XCH₄ 500 °C

XCH₄ 550 °C

XCH₄ 600 °C

SepF 500 °C

SepF 550 °C

SepF 600 °C




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Figure 11. CH4 conversion and Hydrogen recovery factor vs load to surface ratio at 550 °C and 12 bar of Natural gas and Biogas.

4.3.4. Influence of concentration polarization As described before the concentration polarization in the system is accounted for via a mass transfer term between bulk and membrane. The mass transfer resistance between bulk and membrane is strongly dependent on the parameter δ, representing the thickness of the stagnant film layer. From the experiments

δ is fitted, however it is not clear if δ will change when scaling up the system, to one with higher pressures

and conversions. In Figure 12 the conversion and separation are shown for the base case and two cases where the thickness of δ is increased and decreased. The decrease of δ results in and a significant

increase, on the other hand the increase of δ would decrease the system performance significantly.

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SepF Biogas




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Figure 12. CH4 conversion and Hydrogen recovery factor vs load to surface ratio at 550 °C and 12 bar for different thicknesses of δ in the model.

4.3.5. Autothermal conditions In autothermal conditions oxygen is co-fed into the system to combust a part of the feed stock to provide the required heat in the process. In the case of Bionico, the oxygen is supplied by co-feeding air into the reactor system. To simulate the autothermal conditions the reaction kinetics of Trimm et al. are implemented in the model with the rate parameters obtained by Marra et al. for rhodium [11]. The reaction rate equation of methane combustion is reported in Table 8.

Table 8. Reaction rate equation of methane combustion used for autothermal conditions.

Reaction Stoichiometry and reaction rate equation

Methane combustion on Pt catalyst 𝐶𝐻4 + 2𝑂2 ⇌ 𝐶𝑂2 + 2𝐻2𝑂

[11] 𝑟3 =

𝑘1𝑎𝑝𝐶𝐻4𝑝𝑂2

(1 + 𝐾𝐶𝐻4

𝑂𝑋 𝑃𝐶𝐻4+ 𝐾𝑂2

𝑂𝑋𝑃𝑂2)

+𝑘1𝑏𝑝𝐶𝐻4

𝑝𝑂2

(1 + 𝐾𝐶𝐻4

𝑂𝑋 𝑃𝐶𝐻4+ 𝐾𝑂2

𝑂𝑋𝑃𝑂2)

In the simulations a normal steam reforming condition is compared to an autothermal reforming condition with Oxygen to carbon ratio (OCR) of 0.4, the results are shown in Figure 13. With the autothermal conditions the conversion of methane increases due to the combustion of methane. However the

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XCH₄ δ 0.54 cm

XCH₄ δ 0.75 cm

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SepF δ 0.54 cm

SepF δ 0.75 cm




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separation factor is decreased due to the diluting effect of air and lower production of hydrogen. It should be noted that these conditions are not validated with experiments.

Figure 13. CH4 conversion and Hydrogen recovery factor vs load to surface ratio at 550 °C and 12 bar for Steam reforming and autothermal conditions.

4.3.6. Number of membranes From the prior presented plots, a desired conversion and separation factor can be selected and used to calculate the number of membranes required at the selected conditions. An example is shown below for the production of 100 kg/day of hydrogen. The conditions are 12 bar at 550 °C and Biogas the membranes

used for this optimization are 50 cm long and have a diameter of 1.4 cm and the properties from Table 5. From Figure 14 and with the use of the black lines in Figure 13 can be seen that with 110 membranes a load to surface ratio of 8.3 is required which would give a conversion of 63% with a separation factor of 87%. If at the same conditions a conversion of 95% would be desired +- 170 membranes would be required.

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Figure 14. Number of membranes vs load to surface ratio for 12 bar and 550 °C biogas reforming.

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Biogas SR




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CONCLUSIONS This report shows the validation and optimization of and with the fluidized bed reactor model developed in the Bionico project. The 1D fluidized bed membrane model is extended with a film layer description of concentration polarization. Permeation experiments show that the thickness δ which describes the mass

transfer resistance can be fitted. The results also show that the flow conditions significantly affect the mass transfer resistance. The delta used to validate the model is obtained from a fitting to a base case experiment and shows to predict the other experiments accurately. The model is then used to optimize and scale up the system. An important design parameter is introduced, the load to surface ratio. Showing that higher temperatures and pressures are beneficial. The scale up is dependent on the thickness of δ if delta changes significantly with scale up this can have significant effects

on the predictability of the model. Scale up experiments can give a more accurate prediction of the behaviour of δ. Autothermal conditions increase the conversion, however give lower hydrogen recovery.

From the system optimization an estimate is made of the amount of membranes required for the production of 100 kg/day of hydrogen at 12 bar and 550 °C from biogas. The membranes performance of the

membranes are shown in table 5, the length and diameter of the membranes was selected at 50cm and 1.4 cm respectively. With the current performance of the membranes the designed would require +-170 membranes to reach a methane conversion of 95%.




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REFERENCES [1] F. Gallucci, M. Annaland, J. Kuipers, Autothermal reforming of methane with integrated CO2

capture in a novel fluidized bed membrane reactor. Part 1: experimental demonstration, Top. Catal. 51 (2008) 133–145.

[2] S.A.R.K. Deshmukh, J.A. Laverman, A.H.G. Cents, M.V.S. Annaland, J.A.M. Kuipers, Development of a Membrane-Assisted Fluidized Bed Reactor . 1 . Gas Phase Back-Mixing and Bubble-to-Emulsion Phase Mass Transfer Using Tracer Injection and Ultrasound Experiments, (2005) 5955–5965.

[3] K. Kato, C.Y. Wen, Bubble assemblage model for fluidized bed catalytic reactors, Chem. Eng. Sci. 24 (1969) 1351–1369.

[4] S.A.R.K. Deshmukh, J.A. Laverman, M.V.S. Annaland, J.A.M. Kuipers, Development of a Membrane-Assisted Fluidized Bed Reactor . 2 . Experimental Demonstration and Modeling for the Partial Oxidation of Methanol, (2005) 5966–5976.

[5] F. Gallucci, M. van Sint Annaland, J. Kuipers, Autothermal reforming of methane with integrated CO2 capture in a novel fluidized bed membrane reactor. Part 2 comparison of reactor configurations, Top. Catal. 51 (2008) 146–157.

[6] T. Numaguchi, K. Kikuchi, Intrinsic kinetics and design simulation in a complex reaction network; steam-methane reforming, Chem. Eng. Sci. 43 (1988) 2295–2301.

[7] L. Marra, P.F. Wolbers, F. Gallucci, M.V.S. Annaland, Development of a RhZrO 2 catalyst for low temperature autothermal reforming of methane in membrane reactors, Catal. Today. 236 (2014) 23–33.

[8] D. Kunii, O. Levenspiel, Fluidization Engineering, Elsevier, 1991. doi:10.1016/B978-0-08-050664-7.50012-3.

[9] C.-Y. Shiau, C.-J. Lin, Equation for the superficial bubble-phase gas velocity in fluidized beds, AIChE J. 37 (1991) 953–954.

[10] S. Mori, C.Y. Wen, Estimation of bubble diameter in gaseous fluidized beds, AIChE J. 21 (1975) 109–115.

[11] D.L. Trimm, C.W. Lam, The combustion of methane on platinum-alumina fibre catalysts-I. Kinetics and mechanism, Chem. Eng. Sci. 35 (1980) 1405–1413.

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