Pulgarin_Leon Innovaquimica

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ANLISIS DE SENSIBILIDAD EN UN REACTOR DE CRAQUEO CATALTI-CO DE METANO PARA LA PRODUCCIN DE HIDRGENO

J. Pulgarn-Len1, J. Saavedra-Rueda2, A. Molina1,*1 Bioprocesos y Flujos Reactivos, Facultad de Minas, Universidad Nacional de Colombia, Sede Medelln

2 Instituto Colombiano del Petrleo, Ecopetrol, Bucaramanga

Resumen:Se desarroll un modelo de un reactor de craqueo cataltico de metanopara la produccin de hidrgeno utilizando un mecanismo que simplifica las

mltiples reacciones heterogneas que suceden en el reformado cataltico con tresreacciones que incluyen la adsorcin en sitios activos y el equilibrio qumico. El

modelo considera al reactor como un lecho empacado y simplifica la transferencia

de masa en el catalizador considerando las reacciones como pseudohomogneas.

Para el desarrollo del modelo se utiliz el software comercial ASPEN Plus y se es-

cribi un mdulo de usuario que utiliza una rutina en FORTRAN escrita especfi-camente para representar la cintica qumica. Las predicciones del modelo son si-

milares a las tendencias reportadas en la literatura y en un reformador industrial. El

artculo concluye utilizando el modelo para entender el efecto de la variacin de latemperatura, relacin vapor/carbono y tiempo de residencia sobre la conversin y

el rendimiento fraccional global para el hidrgeno.

Palabras Clave:Reformado de metano, Gas natural, Hidrgeno, ASPEN PLUS.

SENSITIVITY ANALYSIS OF A METHANE STEAM REFORMER

J. Pulgarn-Len1, J. Saavedra-Rueda2, A. Molina1,*1 Bioprocesos y Flujos Reactivos, Facultad de Minas, Universidad Nacional de Colombia, Sede Medelln

2 Instituto Colombiano del Petrleo, Ecopetrol, Bucaramanga

Abstract:A model that predicts the conversion in a methane steam reformer for

hydrogen production was developed. The model makes use of a three-reactionmechanism that simplifies the multiple heterogeneous reactions involved in re-

forming that include adsorption on catalyst active sites and chemical equilibrium.

The model considers the reformer as a packed bed and simplifies mass transfer in

the catalyst by considering reactions as pseudohomogeneous. The model was de-

veloped using a FORTRAN subroutine specially written for the former that waslinked to the commercial software ASPEN Plus. Model predictions are similar to

those found in the literature and with results from an industrial reformer. The pa-

per ends with a sensitivity analysis that uses the model to understand the effect that

the variation of temperature, steam to carbon ratio and residence time have on me-

thane conversion and on fractional conversion of hydrogen.

Keywords:Methane steam reforming, Natural Gas, Hydrogen, ASPEN PLUS.

*Corresponding author: [email protected]

1. IntroductionDespite the recent interest in different

technologies for hydrogen production,

such as biomass and coal gasification,

fluidized bed membrane reactors, fermen-

tative routes and water electrolysis; me-

thane steam reforming remains the major

production route of hydrogen. Although

this interest is mainly motivated by the

role that hydrogen can play as an energy

resource, hydrogen production for the

petrochemical, chemical and food industry

will remain a major activity of chemical

engineers.

In methane steam reforming, hydrogen is

produced in a furnace in which a mixture

of methane and water reacts in tubes iso-

lated from the combustion gases. With thehelp of a catalyst (typically with Ni as

major component) a highly endothermic


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Pulgarn et al., Innovaqumica, 2009

2

reaction converts methane and water into

a mixture of hydrogen and other com-

pounds, with carbon monoxide as major

component.

There is a vast literature on modeling

steam reformers. [1-22]. Most studies

date to the late 80s. In the 90s and early

21st century the number of papers in the

open literature on modeling methane

steam reformers decreased, probably be-

cause of licensing agreements between

production companies and research insti-

tutions as well as an increased interest in

alternative technologies for reforming

such as Fluidized Bed Membrane Reac-tors [10, 13, 16-19], optimized control

strategies [12, 14, 15] and novel catalysts

formulations [11, 21].

One of the most refereed studies on me-

thane reformers was the work by Xu and

Froment [5, 7] that describes a model for

these reactors and carefully compares

experimental data with predictions. In

Colombia, as early as in 1981, Ros de-

veloped a model that predicted hydrogen

production and methane conversion in anindustrial methane steam reformer [1].

More recently Acua [14], in order to

improve the controllability of steam re-

formers, developed a detailed model of

the methane steam reforming process.

This paper presents preliminary results on

a model that predicts the conversion of

steam and methane in a reformer. Model

details, such as kinetic expressions and

input parameters are defined. The resultsfrom the model are validated against pre-

vious literature results, and data from an

industrial reformer. The paper ends with a

sensitivity analysis that allows an addi-

tional test to the model and further under-

standing of the methane steam reforming

reaction. The results show that the model

can correctly predict most of the trends

observed in an industrial reformer.

2. ModelTo simulate the conversion of methane to

hydrogen in a catalytic reactor it is neces-

sary to consider three elements: (1) the

kinetic expressions that describe the rateof methane and water reaction on the cata-

lyst surface to produce hydrogen and other

byproducts, (2) the mathematical expres-

sions that address the mole, momentum

and energy balances in the reactor and (3)

the process parameters (both operational

and geometrical) that characterize the

reactor.

2.1 Kinetic data

As mentioned in the introduction, bothRos [1] and Acua [14] modeled methane

steam reformers. While Ros fitted expe-

rimental data to obtain the kinetic parame-

ters for his model, Acua [14] used the

kinetic expressions described by Haldor

[23], as quoted by Acua [14], that date

from 1965. The present research aimed at

making use of more contemporary kinetic

data.

A review of previous literature showed

that the model proposed by Xu and Fro-ment [7] in 1989 is the one more quoted in

the literature. Although it is an old model,

it was recently successfully used by Za-

maniyan et al. [20] and Alberton et al.

[22] in the simulation of industrial me-

thane reformers.

Table 1shows the reactions considered by

Xu and Fromment [7].

These authors came to the conclusion that

reactions R 6 to R 11 are not important

because the ratios of forward to reverse

reaction rates are always higher than 1 at

typical steam reforming conditions. Reac-

tions R 4 to R 5 are also considered of

minor importance because they, although

thermodynamically favored at typical

reforming conditions, describe trends

(lower CO2concentration as the length in

the reactor increases) that do not agree

with normal reactor performance. Al-


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though these are rather weak assumptions

as local conditions inside the reformer

may have concentrations that will thermo-

dynamically favor forward reactions, as a

first approximation in this paper, we

adopted Xu and Fromment [7] recom-

mendations and simply considered R 1 to

R 3 as the most important reactions in the

process.

Table 1. Reactions involved in methane steam reforming as reportedby Xu and Fromment [7]

Reaction H298(kJ/mol)

R 1224 H3COOHCH 206.1

R 2222 HCOOHCO 41.15

R 3224 H4COOH2CH 165.0

R 4224 H2CO2COCH 247.3

R 5 OH2CO4CO3CH 224

330.0R 6

24 H2CCH 74.82R 7

2COCCO2 173.3

R 8 OHCHCO 22 131.3R 9 OH2CH2CO 222 90.13

R 10 OH2C3CO2CH 24 187.6R 11 OH2C2COCH 224 15.3

Xu and Fromment [7] carried out a bal-

ance of active sites on the catalysts for aheterogeneous mechanisms they devel-

oped to simulate R 1 to R 3. From this

balance these authors derived three rate

expressions shown in E 1 toE 3 that con-

sider the partial pressure of hydrogen,

methane, water and carbon monoxide, (Pi)

as well as kinetic (ki), equilibrium (Ki) and

adsorption constants (Kj, with j represents

CO, H2, CH4, H2O). E 5 toE 7present the

mathematical expressions used to

represent the variation of the constant withtemperature. Table 2 to Table 4 show the

kinetic constants finally used in the model.

Equilibrium constants were calculated

using the free-domain code for gaseous

equilibrium Gas-Eq [24].

2

1

CO

3

OHCH5.2

2H

1

1DEN

K

pppp

p

k3

r

2H

24

E 1

2

2

COH

OHCO2H

2

2DEN

K

pp

ppp

k

r

22

2

E 2

2

3

CO

4

4

4CH5.3

2H

3

3DEN

K

pppp

p

k4

r

22H

O2H

E 3

2

2

244

22

H

OH

OHCHCH

HHCOCO

p

pKpK

pKpK1

DEN E 4

ir

T,iiT

1

T

1

R

Eaexpkk

E 5

ir

j

T,iiT

1

T

1

R

HexpKK

E 6

i

ibi

ii,eqT

EaexpTAK

E 7


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Table 2. Kinetic constants used in the model(adapted from [7])

ki, 648K Eai

(kmol bar1/2

/ kg cat h) (kJ/mol)

k1 1.84 10-4 240.1

k2 7.558 67.13

k3 2.19 10-5

243.9

Table 3. Adsorption constants used in the model(adapted from [7])

Kj TrH

(bar-1

) (K) (kJ/mol)

CH4 0.1791 823 -38.28

H2O 0.4152* 823 88.68CO 40.91 648 -70.65

H2 0.02960 648 -82.90

*Dimensionless

Table 4. Equilibrium constants used in the mod-el (calculated from[24])

Ai (bar2) bi Eai (K

-1)

Keq1 4.94106 1.89 -25216

Keq2 1.2010-6

* 1.24 5425

Keq3 5.93 3.13 -19791

*Dimensionless

2.2 Balance equations in the reactorAs one of the objectives of the paper was

to perform a sensitivity analysis of the

methane steam reformer and given the

extended use of the commercial software

ASPEN in the Chemical Engineering in-

dustry, this research employed ASPEN

PLUS V 7.0, as simulation tool. Unfortu-

nately, as it happens with most commer-

cial software, the presence of non-conventional kinetic expressions, (e.g.E 1

to E 3), impose the use of user-defined

models in ASPEN.

There are typically two possibilities when

modeling non-conventional rate expres-

sions in ASPEN. The first one, as illu-

strated by Barrera et al. [25], consists in

linking ASPEN to Excel and developing

the kinetic expressions through Excel by a

spreadsheet. The second one, adopted in

this research, consist on defining FOR-

TRAN-based subroutines. We consider the

second approach more suited for our re-

search needs as FORTRAN allows more

complex calculations that Excel.

As this was the first time that FORTRAN

was linked with ASPEN in our research

group, we developed our own code to

model a PFR reactor using MATLAB to

validate the ASPEN/FORTRAN approach.

Both programs (MATLAB and AS-

PEN/FORTRAN) yielded identical results.

Although the methane steam reformer

simulations by Ros [1] and Acua [14]

considered energy and momentum bal-ances inside the reactor, this research used

predefined pressure and temperature pro-

files as inputs to the model. This was done

because emphasis was placed in the kinet-

ic approach and, as a first step; it was con-

sidered more important to address the

chemistry. Current work conducted in our

research group, is incorporating energy

and momentum expressions to the model.

In the treatment of the reactor in ASPENwe adopted a PFR formulation and consi-

dered did not consider heterogeneous limi-

tations (pseudo-homogeneous approach).

This is clearly an oversimplification, al-

though frequently adopted in the literature

(e.g. [1, 14]). Future developments of the

FORTRAN subroutine will include mass

transfer to the particle with approaches

similar to those described by Xu and

Fromment [5], Zamaniyan et al. [20] and

Alberton et al. [22]

2.3 Process and reactor parametersAlthough, as explained above, the AS-

PEN/FORTRAN reactor model was vali-

dated with an independent program de-

signed by our research group, additional

validation of the kinetic expressions was

mandatory before simulation of an indus-

trial furnace could be undertaken. This

kinetic validation was carried out using the

data presented by Zamaniyan et al. [20]. A


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5

comparison of our results with those of

Zamaniyan et al. [20] is presented in the

Results section.

In the simulations used to validate our

model against that of Zamaniyan et al.

[20], we employed the same input parame-

ters (temperature and pressure profile,

geometry, input stream gas composition,

temperature and pressure profiles) that

Zamaniyan describe in their paper [20].

For the simulation of the industrial me-

thane steam reformer a 15-m length, 12.6-

cm internal diameter reactor was consi-

dered. Table 5 shows the input-stream

composition as supplied by the reformeroperator. O2 and N2 were considered as

inert gases, given their low concentrations.

The concentrations of ethane, propane and

butane were added to that of methane fol-

lowing the equal-carbon concept described

by Zamaniyan et al. [20].

Table 5. Input-stream composition

Species CH4 H2O O2 N2Molar

fraction0.1384 0.8424 0.0003 0.0017

Species C2H6 C3H8 C4H10Molar

fraction0.0143 0.0027 0.0002

As only input and output data were availa-

ble for temperature and pressure, the tem-

perature and pressure profiles reported for

an industrial methane steam reformer in

the literature [20] were adjusted to obtain

the same input and output values as those

reported by the reformer operator. Figure1 compares the temperature and pressure

profiles used in this paper for the industri-

al reformer with those of Zaminiyan et al.

[20]. It is evident that the use of these

profiles is a rather crude simplification.

Nevertheless, as it will be shown below, it

turned out to be an acceptable approxima-

tion.

Because, mass-transfer limitations were

not modeled, no data on the catalyst is

given different from the fact that it was a

Ni/Al2O3 catalyst and the density was as-

sumed to be 2355.5 kg m-3, as reported in

[20].

3.Results and discussion3.1 Model validationFigure 2 compares the profiles of major

species (CH4, H2O, H2and CO) along the

reactor predicted by Zamaniyan et al. [20]

with those obtained using our model. Al-

though there are some clear differences in

trends, exit concentrations are very similar

for all species. Particularly the two more

important species, H2and CH4, show simi-

lar concentrations at the reactor exit. This

gives confidence on the model ability tocorrectly predict the final result for the

reactor.

600

800

1000

1200

0 2 4 6 8 10 12 14distance along reactor (m)

T(K)

Zamaniyan et al.

this paper

a.

11

12

13

14

15

16

17

0 2 4 6 8 10 12 14distance along reactor (m)

P(bar)

Zamaniyan et al.

this paper

b.

Figure 1. Comparison of (a) temperature and(b) pressure profiles along the reactor. Datafrom Zamaniyan et al. [20] and this paper

Contrary to the relative success in predict-

ing the final concentrations,Figure 2 a. to

d. show that our model tends to overesti-

mate methane conversion. This is evident

in Figure 2 because the predictions by

Zamaniyan et al. [20], show that methane

concentration is always higher and hydro-

gen concentration lower than our model


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6

0.0

0.1

0.2

0.3

0 2 4 6 8 10 12

distance along reactor (m)

CH4

(molfraction)

a.

Zamaniyan et al.

this paper

0.2

0.3

0.4

0.5

0 2 4 6 8 10 12


H2O

(molfraction)

b.

Zamaniyan et al.

this paper

0.0

0.1

0.2

0.3

0 2 4 6 8 10 12


H

2(molfraction)

Zamaniyan et al.

this paper

c.

0.0

0.1

0.2

0.3

0 2 4 6 8 10 12


CO(molfraction)

d.

Zamaniyan et al.

this paper

Figure 2. Comparison of concentration profiles as predicted by the model described by Zamaniyan et al. [20] and by this paper. (a)CH4, (b), H2O, (c) H2and (d) CO.


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7

results, at short distances inside the reac-

tor. This result is not surprising as Zama-

niyan et al. [20] considered mass-transfer

limitations inside the catalyst (using an

effectiveness factor) and our model consi-dered a pseudo-homogeneous approach.

Neglecting mass transfer limitations caus-

es the observed overestimation of methane

conversion at short distances in the reac-

tor. As stated above, future model ver-

sions should consider mass transfer limita-

tion in the catalyst.

3.2 Simulation of industrial methanesteam reformer.

Once the model was validated againstliterature data, the ability of the model to

predict the behavior in an industrial re-

former was addressed. Table 6 compares

the exit concentrations (in mole fractions)

as reported by the reformer operator with

model predictions. Although there are

some differences, particularly in CO, the

agreement between predictions and the

data for the industrial reformer is deemed

as excellent, considering some of the

crude approximations taken with the pres-sure and temperature profiles.

Table 6. Comparison of exit concentrations(mole fraction) in an industrial reformer with

model predictions

Industrial

reformer

Model

CH4 0.0110 0.0145

H2O 0.4536 0.4878

H2 0.4121 0.3885

CO 0.0600 0.0419

CO2 0.0620 0.0657

N2 0.0013 0.0015

3.3 Sensitivity analysisTo make an additional validation of the

model and get a better understanding of

the reforming reaction, a sensitivity analy-

sis of the model response to variations in

temperature profile, steam-to-carbon ratio

in

CS (in molar units) and residence

time was carried out. There are different

variables that can be used to evaluate the

performance of a methane steam reformer

(e.g. mass flow hydrogen produced, con-

version of different species, rate of coke

deposition, rate of H2to CO at the reactor

exit). Among those and for clarity of thediscussion we selected only two: conver-

sion of methane 4CHX defined as theratio of methane moles converted in the

reactor to those entering the reformer and

the fractional conversion of hydrogen

42 CHH defined inE 8.

(moles)convertedCH

molesreactor

theleavingH

CHH

4

2

42

E 8

Figure 3 shows the variation of methane

conversion 4CHX and hydrogen fraction-al conversion 42 CHH with changes innominal reactor temperature. Because

there is a temperature profile, the abscissa

inFigure 3 represents a nominal tempera-

ture that reflects the mean temperature in

the profile.

As expected, inFigure 3 methane conver-

sion increases with temperature. However,

42 CHH decreases, with temperature,as thermodynamic restrictions on the for-

ward reaction in R 3 augment with tem-

perature. Figure 3 suggests that a temper-

ature of the order of 1100 K guarantees

acceptable methane conversion, while the

fractional hydrogen conversion remains at

an acceptable value of 2.8. It is important

to note that accordingR 1 toR 3,the max-

imum possible value of 42 CHH is 4.A value of 2.8, such as that obtainedaround 1100 K, seems a good compromise

between methane conversion and hydro-

gen production.

As Figure 4 shows, a higher value in the

steam to carbon ratio in

CS favors both,

methane conversion and fractional con-

version to hydrogen. This happens be-

cause a higher steam concentration favors


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equilibrium toward hydrogen production

in E 3. Favoring hydrogen production

increases as well methane conversion.

0.0

0.2

0.4

0.6

0.8

1.0

700 900 1100 1300

temperature (K)

XCH4

2.4

2.6

2.8

3.0

3.2

(H2/CH4)

Figure 3. Predicted variation of methane con-

version 4CHX and fractional conversion ofhydrogen 42 CHH with changes in no-minal reactor temperature

0.0

0.2

0.4

0.6

0.8

1.0

4 5 6 7 8(S/C)in(mol/mol)

XCH4

2.4

2.6

2.8

3.0

3.2

(H2/CH4)


version 4CHX and hydrogen fractional con-version 42 CHH with steam-to-carbonratio

inCS

Figure 4 suggests that the use of a higher

value of in

CS would be advisable, as

higher methane conversion and fractional

conversion of hydrogen are desirable out-

comes. However, as Figure 5 shows, the

total mass flow of hydrogen2H

m de-

creases as the steam to carbon ratio in-

creases. Therefore, a balance between a

reduction on hydrogen production and an

increase in methane conversion and frac-

tional conversion of hydrogen needs to be

performed during reactor design. A final

sensitivity analysis was conducted for

residence time (Figure 6). The model

predicts a reduction on methane conver-

sion and fractional selectivity of hydrogen

as the residence time in the reactor de-

creases. This is an expected result. How-

ever, Figure 6 gives very important infor-mation for model validation as shows that

for typical conditions (residence time of

0.11 s) methane conversion and the frac-

tional conversion of hydrogen present a

plateau that favors stable operation.

900

1000

1100

1200

1300

3.5 4.5 5.5 6.5 7.5(S/C)in(mol/mol)

h/

kg

m

2

H

Figure 5. Predicted variation of hydrogen mass

flow2H

m with changes in the steam-to-carbon

ratio in

CS

0.0

0.2

0.4

0.6

0.8

1.0

0.00 0.02 0.04 0.06 0.08 0.10 0.12

residence time (s)

XCH4

2.4

2.6

2.8

3.0

3.2

(H2/CH4)


version 4CHX and hydrogen fractional con-version 42 CHH with residence time in thereactor

4. ConclusionsA model that integrates complex chemical

kinetics into ASPEN using a FORTRAN

subroutine correctly predicts the behavior

of an industrial methane steam reformer.

The model, validated against literature and

industrial data, was used to conduct a sen-


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9

sitivity analysis of methane conversion

and fractional conversion to hydrogen

with temperature, steam to carbon ratio

and residence time. Although the higher

the temperature, the higher the methaneconversion, thermodynamic restrictions

decrease methane and steam conversion to

hydrogen as temperature increases. A

nominal temperature of 1100 K seems to

give a reasonable balance between me-

thane conversion and factional conversion

of hydrogen. Higher steam to carbon ratio

favors both methane conversion and fac-

tional conversion of hydrogen, however it

decreases the mass flow of hydrogen. It is

necessary to establish a balance on prod-uctivity and conversion to assure optimal

reformer behavior. The model gives in-

formation on the variation of methane

conversion and fractional conversion of

hydrogen with residence time. The results

suggest that for the industrial reformer

analyzed, a residence time close to 0.12 s

is optimal because it guarantees that varia-

tions in residence time do not have a ma-

jor impact in conversion.

Acknowledgment

We acknowledge Aspen Technology for

having granted special permission for the

use of the ASPEN. PLUS under the condi-

tion of the academic licensing agreement.

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reactor for the steam methane reforming using

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