Process synthesis and equipment design of a solid handling ... · 3. a pinch point analysis has...
Transcript of Process synthesis and equipment design of a solid handling ... · 3. a pinch point analysis has...
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F. Milella, D. Sutter, J.F. Pérez-Calvo, M. Gazzani, M. Mazzotti
9th Trondheim conference on CO2 capture, transport and storage
June 14, 2017
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Process synthesis and equipment design of a solid
handling section for ammonia based post-combustion
CO2 capture processes
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Thermodynamics
Thermodynamic model: Thomsen and Rasmussen. Chem Eng Sci. 54 (1999)1787-1802 Darde et al., Ind Eng Chem Res. 49 (2010) 12663-74 Solid properties: Jänecke, Z Elektrochem 35 (1929) 6:332-34 Jänecke, Z Elektrochem. 35 (1929) 9:716-28
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Thermodynamics
Thermodynamic model: Thomsen and Rasmussen. Chem Eng Sci. 54 (1999)1787-1802 Darde et al., Ind Eng Chem Res. 49 (2010) 12663-74 Solid properties: Jänecke, Z Elektrochem 35 (1929) 6:332-34 Jänecke, Z Elektrochem. 35 (1929) 9:716-28
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Thermodynamics
Thermodynamic model: Thomsen and Rasmussen. Chem Eng Sci. 54 (1999)1787-1802 Darde et al., Ind Eng Chem Res. 49 (2010) 12663-74 Solid properties: Jänecke, Z Elektrochem 35 (1929) 6:332-34 Jänecke, Z Elektrochem. 35 (1929) 9:716-28
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Chilled Ammonia Process (L-CAP) Established absorption process, alternative to amines, that exploits aqueous
ammonia solutions as solvent
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• Solid formation in the absorber is avoided
• Absorption heat removed through the pump around
• Ammonia slip treated with a dedicated unit
• CO2 capture amine scrubbing technology exhibits plant complexity similar to L-CAP
Chilled Ammonia Process (L-CAP)
14-Jun-17 6 Sutter et al. Chem. Eng. Sci. 133, 170-180 (2015)
Sutter et al. Faraday Discuss.,192, (2016), 59-83
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CAP with controlled solid formation (CSF-CAP)
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• Additional solid handling section: crystallization and dissolution occur outside the packed columns
• NH4HCO3 as CO2 carrier increased CO2 uptake capacity of the solvent
• Reduction of the mass-flow rate sent to regeneration
Sutter et al. Chem. Eng. Sci. 133, 170-180 (2015)
Sutter et al. Faraday Discuss.,192, (2016), 59-83
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Motivation L-CAP CSF-CAP
Sutter et al. Faraday Discuss.,192, (2016), 59-83
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Rate-based simulations
• Boundary conditions
• Rate-based model
Crystallization kinetics
Nucleation rate (secondary nucleation)
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Rate-based simulations
• Boundary conditions
• Rate-based model
Crystallization kinetics
Size-independent growth rate
Sutter et al. Cryst. Growth Des. 17 (2017), 3048–3054 Thomsen and Rasmussen. Chem Eng Sci. 54 (1999) 1787-1802
Thomsen model
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Rate-based simulations
• Boundary conditions
• Rate-based model
Crystallization kinetics
Size-independent dissolution rate Thomsen model
Thomsen and Rasmussen. Chem Eng Sci. 54 (1999) 1787-1802
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Rate-based simulations
• Boundary conditions
• Rate-based model
• Flow-schemes design
Crystallization kinetics
Size-independent dissolution rate Thomsen model
Thomsen and Rasmussen. Chem Eng Sci. 54 (1999) 1787-1802
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Flow-schemes design
Equipment selection
Mixed suspension mixed
product removal
(MSMPR)
Scraped surface
heat exchanger
(SSHE)
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Flow-schemes design
Equipment selection
Mixed suspension mixed
product removal
(MSMPR)
Scraped surface
heat exchanger
(SSHE)
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Flow-schemes design
Equipment selection
Mixed suspension mixed
product removal
(MSMPR)
Scraped surface
heat exchanger
(SSHE)
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Flow-schemes design
Equipment selection
Mixed suspension mixed
product removal
(MSMPR)
Scraped surface
heat exchanger
(SSHE)
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Flow-schemes design
Equipment selection
Mixed suspension mixed
product removal
(MSMPR)
Scraped surface
heat exchanger
(SSHE)
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Flow-schemes design
Equipment selection
Mixed suspension mixed
product removal
(MSMPR)
Scraped surface
heat exchanger
(SSHE)
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Flow-schemes design
Equipment selection
Mixed suspension mixed
product removal
(MSMPR)
Scraped surface
heat exchanger
(SSHE)
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Flow-schemes design
Equipment selection
Mixed suspension mixed
product removal
(MSMPR)
Scraped surface
heat exchanger
(SSHE)
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Flow-schemes design
Equipment selection
Mixed suspension mixed
product removal
(MSMPR)
Scraped surface
heat exchanger
(SSHE)
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Flow-schemes design
Equipment selection
Mixed suspension mixed
product removal
(MSMPR)
Scraped surface
heat exchanger
(SSHE)
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Mathematical modeling
Modeling MSMPRs
Solute population and mass balances for MSMPR1
A rigorous dimensionless mathematical model that exploits mass, energy and
population balances has been developed for the process simulations
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Mathematical modeling
Modeling SSHEs
Solute mass balance SSHE1 - crystallization side
Energy balance SSHE1 - crystallization side
Population balance SSHE1 - crystallization side
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Mathematical modeling
Modeling SSHEs
Solute mass balance SSHE1 - dissolution side
Population balance SSHE1 - dissolution side
• Countercurrent-flow in each SSHE
• SSHEs are solved as boundary value
problems (BVPs)
Energy balance SSHE1 - dissolution side
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Optimization framework
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Optimization framework
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Optimization framework
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Optimization framework
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Optimization framework
Key process indicators
• N: number of crystallizers
• : crystal mass flow-rate before S/L
• : specific chilling thermal duty
• : pressure losses or pumping
• : reversed Carnot cycle
• : isentropic efficiency
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Optimization framework
Decision variables
Operating parameters
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Optimization framework
Decision variables
Operating parameters
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Optimization framework
Decision variables
Operating parameters
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Optimization framework
Decision variables
Operating parameters
SSHE geometrical parameters
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Optimization framework
Decision variables
Operating parameters
SSHE geometrical parameters
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Optimization framework
The genetic algorithm NSGA-II, available in Matlab, has been used to perform a
multiobjective optimization based on the following problem:
Multiobjective optimization
Decision variables
Operating parameters
SSHE geometrical parameters
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Solid handling section optimization
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Solid handling section optimization
• ~ 104 simulations for each simulated
flowscheme during NSGA-II evolution
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Solid handling section optimization
• ~ 104 simulations for each simulated
flowscheme during NSGA-II evolution
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Solid handling section optimization
• ~ 104 simulations for each simulated
flowscheme during NSGA-II evolution
• Pareto-sets extraction
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Solid handling section optimization
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Decision variables analysis
• Decision variables vary along the Pareto-sets
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Solid handling section optimization
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Decision variables analysis
• Decision variables vary along the Pareto-sets
Scraped surface
heat exchanger
(SSHE)
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• UOL for
Solid handling section optimization
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Decision variables analysis
• Decision variables vary along the Pareto-sets
SSHE
cross-section
Scraped surface
heat exchanger
(SSHE)
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• Decision variables vary along the Pareto-sets
• UOL for
• for
Solid handling section optimization
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Decision variables analysis
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Solid handling section optimization
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Decision variables analysis
Heat recovered
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Solid handling section optimization
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Decision variables analysis
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Solid handling section optimization
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Decision variables analysis
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Conclusions
1. A thermodynamic comparative assessment of the conventional
CAP and of a new process with controlled solid formation has been
presented;
2. CSF-CAP shows promise, but requires the design of a new continuous
crystallization section as well as the complete characterization of the
crystallization kinetics;
3. design, modeling and optimization of a novel solid handling section have
been performed:
1. productivity and specific total energy consumptions are conflicting
objective functions, thus offering a set of optimal solutions;
2. the process optimization allows a minimization of OPEX;
3. a pinch point analysis has been used to identify and quantify heat
integration potentials;
4. future work will build on this modeling tool and these results considering:
1. experimental data on ammonium bicarbonate dissolution and
secondary nucleation rates;
2. an overall rate-based CAP-plant optimization.
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Back-up slides
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Activity-based model and look-up table
Extended UNIQUAC + DH contribution (Thomsen thermodynamic model)
Look-up table for BC ionic product (fast consultation of the thermodynamic model)
Ammonium bicarbonate solubility computed for the CO2-rich stream leaving the
absorber relative to the minimum SPECCA equilibrium simulation (Thomsen thermodynamic model)
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Thermodynamics
Thermodynamic model: Thomsen and Rasmussen. Chem Eng Sci. 54 (1999)1787-1802 Darde et al., Ind Eng Chem Res. 49 (2010) 12663-74 Solid properties: Jänecke, Z Elektrochem 35 (1929) 6:332-34 Jänecke, Z Elektrochem. 35 (1929) 9:716-28
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Thermodynamics
Thermodynamic model: Thomsen and Rasmussen. Chem Eng Sci. 54 (1999)1787-1802 Darde et al., Ind Eng Chem Res. 49 (2010) 12663-74 Solid properties: Jänecke, Z Elektrochem 35 (1929) 6:332-34 Jänecke, Z Elektrochem. 35 (1929) 9:716-28
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Thermodynamics
Thermodynamic model: Thomsen and Rasmussen. Chem Eng Sci. 54 (1999)1787-1802 Darde et al., Ind Eng Chem Res. 49 (2010) 12663-74 Solid properties: Jänecke, Z Elektrochem 35 (1929) 6:332-34 Jänecke, Z Elektrochem. 35 (1929) 9:716-28
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Ternary phase diagrams
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p=1 bar
Sutter et al. Chem. Eng. Sci. 133, 170-180 (2015)
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Scaling variables
Modeling MSMPRs
Solute population and mass balances for MSMPR1
1. Non-dimensionalization
2. Integration
3. Scaling and normalization
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Flow-scheme design
Modeling MSMPRs
Solute population and mass balances for MSMPR2
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Kinetics of solid formation Experimental setup for seeded growth experiments
Composition range reduced to NH4HCO3-H2O binary
Batch-type autoclave
pressurized system
minimized vapor volume
magnetic clutch stirrer
syringe-based injector for seeds
In-situ analysis
Focused Beam Reflectance Measurement (FBRM):
Detection of solid particles
Attenuated Total Reflectance – Fourier Transform Infrared
(ATR-FTIR) spectroscopy:
Concentration in liquid phase
Sutter et al. Cryst. Growth Des. 17 (2017), 3048–3054
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Solid handling section design Dimensionless mathematical model
Solute mass balance
Energy balance
Population balance
SSHE – dissolution side
Mixed suspension mixed
product removal
(MSMPR)
Population balance and solute
mass balance
A rigorous dimensionless mathematical model that exploits mass, energy and
population balances has been developed for the process simulations
Double-pipe scraped surface
heat exchanger
(SSHE)
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Comparative assessment: L-CAP vs. CSF-CAP
Sutter et al. Faraday Discuss.,192, (2016), 59-83
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Comparative assessment: L-CAP vs. CSF-CAP
Sutter et al. Faraday Discuss.,192, (2016), 59-83
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On the effect of flow-scheme selection on PSD
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On the effect of flow-scheme selection on PSD
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Solid handling section optimization
Decision variables analysis
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Effect of SSHEs geometrical parameters
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Optimization framework
Key process indicators
• N: number of crystallizers
• : crystal mass flow-rate before S/L
• : specific chilling thermal duty
• : pressure losses or pumping
• : reversed Carnot cycle
• : isentropic efficiency
• : overall cooling crystallization heat
duty (sensible + latent)