Reforming of liquid fuels to hydrogen is being considered to enable hydrogen-powered fuel cells
to be used to generate remote power. For example, the military is interested in using hydrogen
fuel cells to replace conventional batteries, which have a low power density and a short lifetime.
Reforming, then, could be used to transform military fuels to hydrogen to power fuel cells.
Autothermal reforming is one means for converting liquid fuels to hydrogen. In this process, the
liquid fuel is reacted with oxygen and water to produce hydrogen. The overall reaction involves
multiple reactions. Assuming that isooctane (2,2,4 trimethyl pentane) is the fuel, the overall
reaction scheme can be written:
C8H18 + 12.5 O2 8 CO2 + 9 H2O
C8H18 + 8 H2O 8 CO + 17 H2
C8H18 + 8 CO2 16 CO + 9 H2
C8H18 + 16 H2O 8 CO2 + 25 H2
CO + H2O CO2 + H2
Your assignment is to model the reforming of isooctane in a packed-bed reactor.
Reaction Kinetics
Pacheco, et. al. (Pacheco, 2003) fit experimental data for a proprietary Pt/CeO2 catalyst to obtain
reaction kinetics for each of these reactions. The reaction rate laws they used are shown in
Table 1, where the reaction order corresponds to that shown above, and the rate law constants
are given in Table 2.
2
Table 1. Reaction rate laws for all reactions involved in isooctane reforming
r1 = k1Pic8PO2
( )
++++
−
2
22 88 222
2
3
28 2
5.2
2
2
2
1 /
/
COCO HH i Ci C HOHOH
i C HOH CO
H PPKPKPKPK
KPPPP
P
k
r
= −
283
2
2
2
2833 1
iC CO
CO H
iC CO PPK
PP
PPkr
( )
++++
−
2
22 88 222
42
4
2
2
28
5.3
2
4
1 /
4 /
COCO HH i Ci C HOHOH
i C HOH CO
H PPKPKPKPK
KPPPP
P
k
r
( )
++++
−
2
22 88 222
2 522
2
5
5
1 /
/
COCO HH i Ci C HOHOH
CO HOH CO
H PPKPKPKPK
KPPPP
P
k
r
Table 2. Kinetic parameters for all reactions involved in isooctane reforming
Parameter Pre-exponential factor
or KTR
Activation energy and heat of
adsorption (kJ/mol)
k1 (mol/gcat/s/bar2
) 2.58E+08 166
k2 (mol bar0.5/gcat/s) 2.61E+09 240.1
k3 (mol/gcat/s/bar2
) 2.78E-05 23.7
k4 (mol bar0.5/gcat/s) 1.52E+07 243.9
k5 (mol/gcat/s/bar) 1.55E+01 67.1
KH2O (dimensionless) 1.57E+04 HH2O= 88.7
KH2 (dimensionless) 0.0296 (TR=648 K) HH2= -82.9
KCO (dimensionless) 40.91 (TR=648 K) HCO= -70.65
KiC8 (dimensionless) 0.1791 (TR=823 K) HiC8= -38.28
Note: For H2, CO, and iC8, K is found from:
−
−
R
R
T
TTR
H
KK
R
11
exp
For H2O, K is found from:
TRHKK )//exp(
o −= R
Note that the equilibrium constants are calculated assuming reaction stoichiometry for methane,
not iso-octane. For example, K2 is the equilibrium constant for the following reaction:
C8H18 + H2O CO + 3 H2
3
Reactor Model and Simulation – Base Case
The base case reactor design is to be based on the following reaction conditions:
Reactor temperature – 700oC
Reactor pressure – 5 psig
Catalyst size – 0.51 mm
H2O/C (mol/mol in the feed) – 1.43
O2/C (mol/mol in the feed) – 0.42
O2 is supplied as air
No pressure drop
Isooctane molar flow rate = 0.00269 kmol/hr
Assume that there are no internal pore diffusion limitations and no external heat or mass transfer
limitations.
The desired production rate of hydrogen is 0.033 kmol/hour. Report the mass of catalyst needed
to achieve this production rate and the concentration profile in the reactor. Discuss the trends
seen in the profiles.
Reactor Model – Adiabatic
Next you should consider the same reactor, but operating adiabatically rather than isothermally.
Assume the inlet temperature is 700oC. Other than the change in heat transfer mode, you may
make the same assumptions as you did for the base case. Report the mass of catalyst needed to
achieve the desired production rate and the concentration and temperature profiles in the reactor.
Reactor Model – Optimized
Finally, you should optimize the reactor to achieve the desired hydrogen production rate with a
minimum of carbon monoxide production. You should use your adiabatic reactor model. You
may change as many of the base case variables as you want, although you should keep in mind
the feasibility of those changes. You should report the same information you reported for the
base case and adiabatic models, and should also discuss the trends you noted while doing your
optimization study (i.e. how different parameters affected hydrogen production rate and CO
concentration).
