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MODEL-DERIVED CHEMICAL-LOOPING SYSTEM DESIGNS George M. Bollas - - PowerPoint PPT Presentation
MODEL-DERIVED CHEMICAL-LOOPING SYSTEM DESIGNS George M. Bollas - - PowerPoint PPT Presentation
MODEL-DERIVED CHEMICAL-LOOPING SYSTEM DESIGNS George M. Bollas Department of Chemical & Biomolecular Engineering University of Connecticut http://pdsol.engr.uconn.edu 04/04/2014 1/37 IASE Seminar Series About Diploma in Chemical
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Research Group (PDSOL)
Catalysis for renewable fuels
Novel spouted-bed reactor for biomass thermochemical processes (pyrolysis, gasification, chemical-looping combustion) Comprehensive catalyst characterization and catalyst activity dynamic simulation
FTIR real time analyzer
T T T T T T TLiquid & Gas Analysis Char & Catalyst Collection N2 N2 vent vent vent Liquid Collection Gas Collection Gas Analysis Coolant Reactor Filter Flow Meter Auger Feeder
½ ¢µ µ z Annulus: @Ca @t = D@2Ca @½2 ¡ uij @Ca @½ + 2D ½ @Ca ½ Spout: @Cs @t + @Cs @z ¡ us + 1 2dus ¢ = 0Process Design, Scale-up & Control
Dynamic simulation & optimization Optimal experimental design Model-assisted scale-up based on dynamic sensitivity analysis Chemical-looping combustion & reforming
Spouted-bed reactor for biomass pyrolysis Catalyst characterization (ZSM-5 after pyrolysis) Fixed-bed reactor developed and simulated in PDSOL. Application
- f Optimal Experimental Design on the laboratory reactor. Scale-up
based on sensitivity analysis of the bench-scale reactor. Dynamic simulation
- f a spouted bed
Enabling emerging energy technologies via integration of modeling with experimentation of processes lacking fundamental understanding
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Carbon capture needs to be deployed to effectively lower the global CO2 portfolio
Climate change urgency
Fig.1: University of Maine Environmental Change Model (UM-ECM) potential biomes calculated for modern climate. From left to right: input cooled by 4°C; todays input; input warmed by 2.5°C. Note the effect on the arctic sea ice. Data/images
- btained using Climate Reanalyzer™ (http://cci-reanalyzer.org), Climate Change
Institute, University of Maine, USA.
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Estimated total storage capacity of over 100 Gt in the continental US
US-wide CO2 storage capacity
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Back in 2008
Resource: America’s Energy Future Technology And Transformation, Committee On America’s Energy Future, National Academy Of Sciences, National Academy of Engineering, National Research Council of The National Academies, The National Academies Press
CO2 Capture Options
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Boot-Handford ME, Abanades JC, Anthony EJ, Blunt MJ, Brandani S, Mac Dowell N, et al. Carbon capture and storage update. Energy Environ Sci 2014.
Chemical-looping progress
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A method for inherent CO2 separation
Oxygen carriers M : metal MO : metal oxide
Reduction: endothermic CH4 + 4MO CO2 + 2H2O + 4M Oxidation: exothermic M + ½ O2 MO Circulating oxygen carrier: active metal oxides (Ni, Cu, Fe, Mn) supported over Al2O3, MgAl2O4, NiAl2O4, YSZ, TiO2, ZrO2. Reactivity testing: TGA, fixed-bed, interconnected fluidized-beds.
Chemical-looping combustion (CLC)
Reducer Oxidizer CO2 H2O Fuel N2 O2 Air
MO M
water steam
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[1] Zhou Z, Han L, Bollas GM. Model-based analysis of bench-scale fixed-bed units for chemical-looping combustion. Chem Eng J 2013;233:331–48. [2] Han L, Zhou Z, Bollas GM. Heterogeneous Modeling of Chemical-Looping
- Combustion. Part 1: Reactor Model. Chem Eng Sci 2013;104:233 – 249.
[3] Han L, Zhou Z, Bollas GM. Heterogeneous Modeling of Chemical-Looping
- Combustion. Part 2: Particle Model. Chem Eng Sci 2014;in press.
[4] Zhou Z. Han L, Bollas GM. Overview of Chemical-Looping Reduction in Fixed Bed and Fluidized Bed Reactors Focused on Oxygen Carrier Utilization and Reactor Efficiency. Aerosol Air Qual Res 2014;14:559–71. [5] Zhou Z, Han L, Bollas GM. Kinetics of NiO reduction by H2 and Ni oxidation at conditions relevant to chemical-looping combustion and reforming. Int J Hydrogen Energy 2014;in press. [6] Han L, Zhou Z, Bollas GM. Chemical-looping combustion in a reverse-flow fixed- bed reactor. Appl Energy 2014;in review. [7] Zhou Z, Han L, Bollas GM. Model-assisted analysis of fluidized bed chemical- looping reactors. AIChE J 2014;in review. [8] Han L, Zhou Z, Bollas GM. Optimal Experimental Design for Fixed Bed Chemical- Looping Experiments. Comput Chem Eng 2014;in preparation.
Our work
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OED for process scaling of chemical-looping: Measurements of bench- and pilot- scale processes are used to develop state/space models. These models are subsequently used to identify time-varying experimental conditions that maximize the statistical significance of the measurements with respect to process scale, subject to constraints.
The “dream concept”
maximize information content of experiments integrate experimentation with reactor design
- btain scale-
independent process models estimate model parameters that increase the accuracy of process scale-up/scale- down reduce risk of technology scale- up/scale-down.
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Heterogeneous model
Fluid phase
𝜁𝑐 𝜖𝐷𝑗 𝜖𝑢 + 𝜖𝐺
𝑗
𝜖𝑊 = 𝜖 𝜖𝑨 𝜁𝑐𝐸𝑏𝑦,𝑗 𝜖𝐷𝑗 𝜖𝑨 + 𝑙𝑑,𝑗𝑏𝑤 𝐷𝑑,𝑗|𝑆𝑞 − 𝐷𝑗 𝜁𝑐𝐷𝑞𝑔𝐷𝑈 𝜖𝑈 𝜖𝑢 + 𝐷𝑞𝑔𝐺𝑈 𝜖𝑈 𝜖𝑊 = 𝜖 𝜖𝑨 𝜁𝑐𝜇𝑏𝑦 𝜖𝑈 𝜖𝑨 +ℎ𝑔𝑏𝑤 𝑈
𝑑|𝑆𝑞 − 𝑈 + 4𝑉
𝐸𝑆 (𝑈
𝑥 − 𝑈)
Solid phase
𝜁𝑑 𝜖𝐷𝑑,𝑗 𝜖𝑢 = 1 𝑠
𝒅2
𝜖 𝜖𝑠
𝑑
𝐸𝑓,𝑗 𝑠
𝑑2 𝜖𝐷𝑑,𝑗
𝜖𝑠
𝑑
+ 𝜍𝑡 𝑆𝑗 1 − 𝜁𝑑 𝜍𝑡𝐷𝑞𝑡 + 𝜁𝑑𝐷𝑞𝑑𝐷𝑈,𝑑 𝜖𝑈
𝑑
𝜖𝑢 = 𝜇𝑡 𝑠
𝑑2
𝜖 𝜖𝑠 𝑠
𝑑2 𝜖𝑈 𝑑
𝜖𝑠
𝑑
+ 𝜍𝑡 (−𝛦𝐼𝑗)(𝑆𝑗)
Pressure drop
𝑒𝑄 𝑒𝑨 = − 1 − 𝜁𝑐 𝜁𝑐3 𝜍𝑣0
2
𝐸𝑞 150 𝑆𝑓𝑞 + 1.75
Fixed-bed model description
Furnace wall Tube wall Oxygen carrier particles
Axial convective heat + mass transfer in gas Heat transfer between packed bed and wall Axial dispersion of heat and mass External diffusion across film Reactions on pore surface Pore diffusion
Bulk fluid Solid phase
Heat conduction Heat conduction through packed-bed Han, L.; Zhou, Z.; Bollas, G. M. Heterogeneous Modeling of Chemical-Looping Combustion. Part 1: Reactor Model. Chemical Engineering Science 2013
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Application to experimental data of CLC by Iliuta et al. (2010), Ryden et al. (2008) and CLR data by Jin (2002)
Fixed-bed model application
Han, L.; Zhou, Z.; Bollas, G. M. Heterogeneous Modeling of Chemical-Looping
- Combustion. Part 1: Reactor Model. Chemical Engineering Science 2013
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Reduction reactions with NiO
Oxygen carrier reduction reactions CH4 oxidation CH4 + 2NiO ↔ 2Ni + CO2 + 2H2 ΔH°= 165 kJ/mol H2 oxidation H2 + NiO ↔ Ni + H2O ΔH°= -2.2 kJ/mol CO oxidation CO + NiO ↔ Ni + CO2 ΔH°= -43.3 kJ/mol Partial CH4 oxidation CH4 + NiO ↔ Ni + 2H2+CO ΔH°= 203 kJ/mol Reactions catalyzed by Ni Steam reforming CH4 + H2O ↔ 3H2 + CO ΔH°= 205 kJ/mol Water gas shift CO + H2O ↔ H2 + CO2 ΔH°= -41.1 kJ/mol Dry reforming CH4 + CO2 ↔ 2CO + 2H2 ΔH°= 247 kJ/mol Methane decomposition CH4 ↔ 2H2 + C ΔH°= 88 kJ/mol Carbon gasification by steam C + H2O ↔ CO + H2 ΔH°= 131 kJ/mol Carbon gasification by CO2 C + CO2 ↔ 2CO ΔH°= 173 kJ/mol
Zhou, Z.; Han, L.; Bollas, G. M. Model-based Analysis of Bench-Scale Fixed-Bed Units for Chemical-Looping Combustion. Chemical Engineering Journal 2013
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Mass balance Intraparticle velocity (forced convection)
Boundary Conditions
Mass Balance around the crucible
Boundary Conditions
TGA Model
, 2 2 , eff, , 2 2
1 1
c i c c c i c i c i s c c c c j c c
C r C r D C t r r r r r v R
1 , 1 j j c i c c i
R r v C
eff, , , c, ,
( )
c c p c p c p p
i c i c c i i c i i r r r r r r c r r
D C v C k C C r
,
c c
r r c i c c
C v r
, c, ,
( )
c p
v r r i i b b ax i i c i i
a C C D k C C t z z
, ,
( )
TGA i z m i i b ax i i z
z C D C D C
i z h
C z
Han, L.; Zhou, Z.; Bollas, G. M. Heterogeneous Modeling of Chemical-Looping
- Combustion. Part 2: Particle Model. Chemical Engineering Science 2013
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Analysis of available literature on reduction
- f supported and unsupported NiO by H2
Models of varying degree of fidelity (number of parameters) F-test Akaike Information Criterion
Non-catalytic gas-solid reactions
Zhou, Z.; Han, L.; Bollas, G. M. Kinetics of NiO reduction by H2 and Ni oxidation at conditions relevant to chemical-looping combustion and reforming. Int. Journal of Hydrogen Energy, 2014
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Fixed-bed apparatus NiO/Al2O3 oxygen carrier preparation
Dry impregnation with loading of 20 wt% Ni Particle size: 50-150 μm Surface area: 90 m2/g
Current experimental setup
Experimental conditions Reduction temperature 800°C Reduction time 1 min Reducing gas flow 20 CH4 + 80 Ar ml/min Solid loading 2 g Purge time 3 min Oxidizing gas 100 air ml/min Oxidation time 3 min Tube ID 0.99 cm Tube length 30 cm
Ar Air CH4 Filter Mass selective detector Vent Reactor Oxygen Carrier
F MFC3 F MFC2 F MFC1 T1 T2
Vent Pressure Regulator Furnace
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Model, system of DAE’s
𝐠 𝐲 𝑢 , 𝐲 𝑢 , 𝐯 𝑢 , 𝐱 , 𝛊, 𝑢 = 0 𝐳 𝑢 = 𝐢(𝐲 𝑢 )
Sensitivity matrix
𝑹 =
𝜖𝑧 1 𝜖𝜄𝑗
⋯
𝜖𝑧 1 𝜖𝜄𝑞
⋮ ⋱ ⋮
𝜖𝑧 𝑜 𝜖𝜄𝑗
⋯
𝜖𝑧 𝑜 𝜖𝜄𝑞
Dynamic Sensitivity Analysis
Local methods
Differentiation of model equations d dt 𝜖𝐳 𝜖𝛊 = 𝜖𝐠 𝜖𝐳 ∙ 𝜖𝐳 𝜖θ + 𝜖𝐠 𝜖𝛊
𝐠 : continuous function 𝐲 𝑢 ∶ differential state variables 𝐯 𝑢 ∶ time-varying controls 𝐱 ∶ time-constant controls 𝛊 ∶ parameter vector 𝐢 𝐲 𝑢 : measured state variables 𝐳 t ∶ measured responses
Results for CLC fixed-bed reactor:
0.2 0.4 0.6 0.8 1 5 10 15 20 25 30 20 40 60 Length (normalized) Time [sec]
Normalized sensitivity
0.2 0.4 0.6 0.8 1 5 10 15 20 25 30 0.2 0.4 0.6 0.8 Length (normalized) TIme [sec]
Normalized sensitivity
0.2 0.4 0.6 0.8 1 5 10 15 20 25 30 0.5 1 1.5 Length (normalized) Time [sec]
Normalized sensitivity
k1 k2 k3 k4
0.2 0.4 0.6 0.8 1 5 10 15 20 25 30 0.2 0.4 0.6 0.8
Length (normalized) Time [sec]
Normalized sensitivity
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Structural local identifiability test (SLI)
(1) Correlation of sensitivity matrix is different from ±1 (2) Fisher information matrix is non-singular
Structural global identifiability test (SGI)
Verifies if parameter sets do not provide the same model responses
Identifiability Analysis
SLI test
Design experiment
SGI test det (𝐼𝜄
∗) = 0
? Y N
Change model structure
𝑄𝑏𝑡𝑡? End Y N
* 1 1
y ts
N N T θ ij i j i j
H Q Q
* * , *
max ε
T I θ θ
θ θ
θ θ W θ θ
y τ y T
dt ε , , , ,
* *
θ u y θ u y W θ u y θ u y
Subject to:
𝛊, 𝛊∗: parameter sets 𝐳 ∶ model trajectory 𝒗𝟏 ∶ initial controls 𝐗 ∶ weights 𝜁𝜄, 𝜁𝑧 ∶ small numbers
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Arrhenius Expression: SLI results:
1 experiment
High correlation Unidentifiable
2 experiments
Identifiable
SGI results:
Φ𝐽 = 4E-10 < εθ = 1E-6 ε𝑧 = 1E-3
Identifiability Analysis: Arrhenius Expression
Optimal experiments T [℃] 600 800 QCH4 [sccm] 30 30 Solids [g] 1.2 2.2 Ea1 Ea2 Ea3 Ea4 k1 k2 k3 k4 Ea1 1.000 Ea2
- 0.394
1.000 Ea3
- 0.247 -0.022
1.000 Ea4
- 0.140 -0.143 -0.589
1.000 k1
- 0.817
0.287 0.644
- 0.271
1.000 k2
- 0.396
1.000
- 0.025 -0.140
0.289 1.000 k3
- 0.290 -0.017
0.999
- 0.575
0.666
- 0.019
1.000 k4
- 0.052
0.316
- 0.165 -0.573
0.045 0.317
- 0.158 1.000
Ea1 Ea2 Ea3 Ea4 k1 k2 k3 k4 Ea1 1.000 Ea2
- 0.108
1.000 Ea3
- 0.917
0.199 1.000 Ea4
- 0.726
0.164 0.810 1.000 k1
- 0.385
0.035 0.213
- 0.002
1.000 k2
- 0.134 -0.044
0.317 0.339
- 0.048
1.000 k3
- 0.758
0.193 0.886 0.818
- 0.214
0.333 1.000 k4 0.027 0.166 0.047
- 0.050 -0.291 -0.053
0.145 1.000
Correlation matrix of Arrhenius parameters Correlation matrix of Arrhenius parameters
Han L, Zhou Z, Bollas GM. Optimal Experimental Design for Fixed Bed Chemical-Looping Experiments. Comput Chem Eng 2014
k = kref exp −
E R 1 T − 1 Tref
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Build first principles process model
T
Design optimal experiment Conduct experiment at specified conditions Estimate parameters & confidence intervals
Interval #1 Interval #2
Model-guided experiment
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Motivation: maximize information content for parameter estimation 𝝌𝑝𝑞𝑢 = arg min
𝛘
det 𝑰𝛊
−1 𝛊, 𝛘
subject to: 𝐠 𝐲 𝑢 , 𝐲 𝑢 , 𝐯 𝑢 , 𝐱 , 𝛊, 𝑢 = 0 φ𝑗
𝑀 ≤ φ𝑗 ≤ φ𝑗 𝑉
Model + experimental results
Optimal experimental design (OED)
Kinetics Nominal exp. Optimal exp. k1
0.3880 0.1654
k2
1.4416 0.8379
k3
0.6005 0.1461
k4
3.2706 0.3118
Norm 95% confidence interval
5 10 15 20 25 30 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2
Time [sec]
Mole fraction of gas species
Comparison of optimal (-) and baseline (--) experiments
CO2 CO CH4 data4 data5 data6 data7 data8 data9 data10 data11
Design criterion: D-OPTIMALITY
Improves parameter estimation for all uncertain kinetic parameters
Experiments Standard Optimal T [℃] 700 700 QCH4 [sccm] 10 20 Solids [g] 2 2
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Kunii & Levenspiel 3-phase model
ub uo us ue
Bubble phase
us
Wake Emulsion phase
Dense phase Freeboard uf us,f
Fluidized bed model
Zhou, Z.; Han, L.; Bollas, G. M. Modeling Chemical-Looping Combustion in Bubbling Fluidized Bed Reactors. AIChE
- J. 2014
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Fluidized Bed chemical-looping – prediction and analysis
Model is predictive (kinetic mechanism and constants of the fixed bed models used) Freeboard contributes significantly to CH4 conversion and completion of oxidation Consistent with all relevant experimental observations from various laboratories
Fluidized bed operation
- Zhou, Z.; Han, L.; Bollas, G. M. Modeling Chemical-Looping Combustion in Bubbling Fluidized Bed Reactors. AIChE J. 2014
- Zhou, Z.; Han, L.; Bollas, G. M. Overview of chemical-looping reduction in fixed-bed and fluidized-bed reactors focused on oxygen carrier utilization
and reactor efficiency. Aerosol & Air Quality Research. 2014
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Comprehensive comparison of two reactor designs (fixed and fluidized bed) of the same oxygen carrier loading The fixed bed reactor is inferior in all aspects including
CO2 selectivity Carbon formation Bed isothermality
Fixed/Fluidized beds comparison
Zhou Z, Han L, Bollas GM, Overview of Chemical-Looping Reduction in Fixed Bed and Fluidized Bed Reactors Focused on Oxygen Carrier Utilization and Reactor Efficiency. Aerosol Air Qual Res 2014;14:559–71
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Chemical-Looping
Most efficient method for CO2 capture Very high research effort Tremendous research expenditure Combustion or reforming are feasible Mature process
Summary of background
Our work
Modeled all fixed bed reactors with CH4 and NiO Predicted all fluidized beds with CH4 & NiO Compared fixed and fluidized bed CLC and CLR Setup a bench-scale fixed bed reactor
Process Options
Fluidized beds Fixed beds Rotary beds Rotating beds Moving beds
Reactor options for Chemical-looping Combustion (CLC): (a) circulating fluidized-bed; (b) rotating reactor; and (c) alternating flow over a fixed-bed.
O2 N2 Air CO2 H2O Fuel MeO Me Reducer Reactor Oxidizer Reactor O2 N2 Air CO2 H2O Rotating Reactor MeO Me O2 N2 Air CO2 H2O Fuel Alternating Flow Fuel MeO Me Me MeO
(a) (b) (c)
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Typical fixed-bed experiment
Experimental settings Reduction temperature 800°C Reduction time 1 min Reducing gas flow 10 CH4 in 100 ml/min Solid loading 2 g Oxygen carrier conversion
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Design of the novel reactor setup
Reverse-Flow Fixed-bed CLC Reactor
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A novel fixed-bed chemical-looping reactor configuration was invented, in which the fuel flow direction is periodically switched during each cycle. The new design significantly improves the performance of fixed-bed chemical- looping reactors, making them competitive to their fluidized-bed equivalents, while overcoming their operating bottlenecks. The novel system enables:
(1) improved oxygen carrier utilization, (2) higher CO2 capture efficiency (by up to 50%), (3) mitigation of hot and cold zones, (4) elimination of gas-solids separation steps, (5) resistance to carbon deposition.
Advantages relevant to the oxygen carrier used (as compared to current process configurations) relate to the elimination of:
(6) need for oxygen carrier fluidizability, (7) attrition, (8) toxic solid fines effluents, (9) need for oxygen carrier addition.
Patent Claims (Bollas, Han 2014)
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Model Description
1D heterogeneous model Dusty-gas model (concentrated transport) Time varying boundary conditions for the fluid phase
Full heterogeneous design equations
Reverse-Flow Fixed-bed Reactor Model
, 2 2
( 1 )
c c i c s i i c c
C r R t r r J
,i 1 ij i
1
N c i k i i k e e j c K
C J y J y J r D D
, , , 2 2
1 1 ( )
c c s p s c p c T c c c s s i i c c
T C C C t T r H R r r r
Solid phase Fluid phase
, , ,
) ( ( )
c P
b i i i b ax i c i v r c i r i
C uC C D k a C C t z z z
, ,
( ) (C )
c P
b p f T T p f b ax f v c r r
u C C T C T T h a T t z z z T
2 3
1 150 1.75
b b p p
u dP dz d Re
- ut
z L
P P
c c
c i r c r
T J r
, ,
P c c p
i c i c i i r r r r
J k C C
c p c p
c s f c r r c r r
T h T T r
U t t u
1, 1 , 1 2 1, 1 2 ,
s s s s
t n t n t t t n t nt
,in , ,in
1 , 2 1 , 2
i i i b ax i i i
C z t C u C C D z t u C z L
, ,
, 1 2 1 , 2
in T p f b ax in T p f
t u T T C C T z t u T T C C z z L
Han L, Zhou Z, Bollas GM. Chemical-looping combustion in a reverse- flow fixed-bed reactor. Applied Energy 2014
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CH4 conversion and CO2 selectivity
Reactor in this study is suboptimal for fair comparison with existing fixed bed reactors
Performance metrics I
Table: CO2 capture efficiency for varying oxygen carrier conversion
← Bench-scale reactor Industrial-scale reactor →
Han L, Zhou Z, Bollas GM. Chemical-looping combustion in a reverse- flow fixed-bed reactor. Applied Energy 2014 Bollas GM, Han L. Reverse-Flow Reactor for Chemical-Looping Combustion and Reforming of Gaseous Fuels; US Provisional Patent - University of Connecticut, 2014.
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Performance metrics II
Oxygen carrier conversion Bed Temperature Profile Carbon Formation Solid Carbon selectivity and Max Bed T drop
Han L, Zhou Z, Bollas GM. Chemical-looping combustion in a reverse- flow fixed-bed reactor. Applied Energy 2014
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Scaled-up Performance metrics I
Scale-up procedure
Commercially realistic industrial-scale fixed-bed reactor Small particle size (300 µm) to minimize diffusion effects Significant pressure drop in the system =>
Constraint: bed height should not exceed 1 m
Scaling factors:
L/D ratio and Froude number Reactor still suboptimal Performance enhancement improved
Han L, Zhou Z, Bollas GM. Chemical-looping combustion in a reverse- flow fixed-bed reactor. Appl Energy 2014 Bollas GM, Han L. Reverse-Flow Reactor for Chemical-Looping Combustion and Reforming of Gaseous Fuels; US Provisional Patent - University of Connecticut, 2014.
Bench-scale reactor Industrial-scale reactor L [m] 0.22 1.0 D [m] 0.055 0.25 Q (L/min) 16.68 (100% CH4) 3000 (100% CH4) Fr 0.34 0.39 L/D 4 4 Rep 0.80 6.9 ΔP [bar] 0.3 4
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Scaled-up Performance metrics II
Han L, Zhou Z, Bollas GM. Chemical-looping combustion in a reverse- flow fixed-bed reactor. Applied Energy 2014
Oxygen carrier conversion Bed Temperature Profile Carbon Formation Solid Carbon selectivity and Max Bed T drop
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What we should have done (Model-Based Development)
Statistical Analysis of Existing Data and Kinetics Models (F-test, AICc) Fixed-bed model utilizing statistically significant kinetics Optimal Experimental Design for derivation/validation of unknown kinetics Fluidized-bed model prediction and validation Fixed-bed / Fluidized-bed comparison Reverse-flow fixed-bed reactor invention
What we accomplished so far:
A novel reactor concept was invented that addresses the roadblocks to commercialization of existing chemical-looping processes
Our Aim
to put chemical-looping research and technology on a fundamentally new learning curve; one that relaxes the requirement for fluidized-bed reactor systems and is capable of making chemical-looping a disruptive new technology
Conclusions
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Zhiquan Zhou
4th year PhD Student, CBE UConn Fluidized bed modeling, dynamic parameter estimation, statistical analysis
Lu Han
3rd year PhD Student, CBE UConn gPROMS, sensitivity analysis, optimal experimental design
Acknowledgments
NSF CAREER Award
- No. 1054718
Process and Reaction Engineering Program, CBET UCONN Prototype Fund Office of the Vice President for Research
Ari Fischer Oscar Nordness Catherine Cheu Kyle Such Clarke Palmer
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