(684e) Modeling Chemical-Looping Combustion in Bubbling Fluidized Bed Reactors | AIChE

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(684e) Modeling Chemical-Looping Combustion in Bubbling Fluidized Bed Reactors

Authors 

Navarro, M., University of Connecticut
Bollas, G. M., University of Connecticut


Chemical-looping
combustion (CLC) is typically realized as a dual fluidized bed technology. Most
current CLC reactor designs for gaseous fuels processing comprise riser and bubbling
fluidized beds [1], two bubbling fluidized beds [2], or dual circulating fluidized beds [3]. Because of the higher space times required for complete
metal oxide reduction (or fuel oxidation), when compared with the metal
oxidation reactions, fuel reactor designs have focused on bubbling bed
technologies. The objective of this work is to analyze existing bubbling bed
reactors for chemical-looping reduction through dynamic modeling. Experimental
data from published bubbling bed chemical-looping reactors are used for model
development and validation. The reaction scheme and kinetics used in this study
have been developed and validated against published fixed bed chemical-looping
units operating with CH4 and NiO/support
(oxygen carrier) [4].  The proposed reaction scheme
includes heterogeneous reactions of NiO reduction by CH4, H2
and CO, gas phase reactions including reforming reactions (steam, dry and
overall steam), water gas shift reaction, methane decomposition and carbon
gasification by CO2 and H2O. The two-phase (emulsion and
bubble) flow model is used to predict bubbling bed hydrodynamics [5,6]. It considers gas bubbles
flowing through a dense emulsion phase at a relative velocity given by minimum
fluidization with gas percolating through the bed of solids (shown in Figure
1). Using this model the gas profiles predicted for the data published by Iliuta
et al. [7] are shown in Figure 2. Gas composition profiles are
in good agreement with experiment data.

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Chemical-looping selectivity using Ni/NiO and CH4 in fluidized bed at 645

Figure 1: Bubbling fluidized bed reactor physical model

Figure 2: Chemical-looping selectivity using Ni/NiO and CH4 in bubbling fluidized bed at 645°C

A
summary of the bubbling bed experimental data analyzed and modeled in this work,
including all the relevant published data for CLC with CH4 and NiO
as the oxygen carrier, is presented in Table 1.

Table
1:  CLC
bubbling bed units

Author

Iliuta et al.

[7]

Hoteit et al.

[8]

Jerndal et al. [9]

Gayán et al.

[10]

Ryu et al.

[11]

T(°C)

623 ? 810

800 ? 900

950

950

900

NiO/Support

15% NiO/Al2O3

60% NiO/NiAl2O4

40% NiO/αAl2O3

18% NiO/ αAl2O3

28% NiO/ γAl2O3

60% NiO/bentonite

70% NiO/NiAl2O4

OC load (kg)

0.3

2.5 ? 4 

0.015

0.3

2.3

Particle size (µm)

140

171

125 ? 180

100 ? 300

106 ? 212

Specific surface area (m2/g)

102

7

0.91

7, 77.5

-

CH4 composition

10%, 50% in Ar

100%

100%

25% in N2

45% syngas in N2

H2: CO2: CO = 30:10:60

Gas flow rate (m3/s)

2E-05

2E-05 ? 2E-04

7.5E-06

2E-04

3.33E-05

I.D. (mm)

46

96

22

54

50

Bed height(m)

0.23

1

0.0179

~0.1

0.4

Space time (s gNiO0 /gCH4)

5297

9747

1254

1643

-

Bulk density (kg/m3)

785

2200

2400

2500, 1800

1172

In this
presentation, implementation of this model in different bubbling fluidized bed
units of the various CLC laboratories will be shown. A comparison of the
predicted results with the experimental results for the different reactors will
be illustrated and discussed. Dynamic parameter estimation is performed to re-optimize
the kinetics of Ni-based oxygen carriers for chemical-looping reduction in
bubbling fluidized beds. Best fit kinetic parameters between different bubbling
bed units will be presented, along with the consistency and discrepancy of the
kinetic parameters estimated for their fixed bed reactor equivalents.

Acknowledgement:
This material is based upon work supported by the National Science Foundation
under Grant No. 1054718.

References:

[1]         A. Lyngfelt, B. Leckner, T. Mattisson,
Chemical Engineering Science 56 (2001) 3101-3113.

[2]         G.
Adanez Juan  Francisco, L.F.D. Diego, P. Gaya, J. Celaya, A. Abad, Ind.
Eng. Chem. Res. (2006) 2617-2625.

[3]         T.
Proll, P. Kolbitsch, J. Bolhar-Nordenkampf, H. Hofbauer, AIChE Journal 55
(2009) 3255-3266.

[4]         Z.
Zhou, G. Bollas, AIChE Annual Meeting, Pittsburgh, PA (2012).

[5]         D.
Kunii, O. Levenspiel, I & EC Fundamentals 7 (1968) 446-452.

[6]         D.
Kunii, O. Levenspiel, I & EC Process Design and Development 7 (1968)
481-492.

[7]         I.
Iliuta, R. Tahoces, G.S. Patience, S. Rifflart, F. Luck, AIChE Journal 56
(2010) 1063-1079.

[8]         A.
Hoteit, M.K. Chandel, A. Delebarre, Chemical Engineering & Technology 32
(2009) 443-449.

[9]         E.
Jerndal, T. Mattisson, A. Lyngfelt, Energy 94 (2009) 665-676.

[10]       P.
Gayán, C. Dueso, A. Abad, J. Adanez, L.F. de Diego, F. García-Labiano, Fuel 88
(2009) 1016-1023.

[11]       H.-J.
Ryu, D. Shun, D.-H. Bae, M.-H. Park, Korean Journal of Chemical Engineering 26
(2009) 523-527.

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