275827 Modeling Chemical-Looping Combustion in Bubbling Fluidized Bed Reactors

Thursday, November 1, 2012: 1:54 PM
307 (Convention Center )
Zhiquan Zhou1, Monica Navarro2 and George M. Bollas2, (1)Department of Chemical & Biomolecular Engineering, University of Connecticut, Storrs, CT, (2)Department of Chemical, Materials & Biomolecular Engineering, University of Connecticut, Storrs, CT

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.

Description: C:\Users\zhiquan\AppData\Local\Microsoft\Windows\Temporary Internet Files\Content.Word\bubbling bed central.jpg

Title: Fgure 2: 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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