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

14-Jun-17 1

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


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Thermodynamics


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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)

14-Jun-17 7

• 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)


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Motivation L-CAP CSF-CAP


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Rate-based simulations

• Boundary conditions

• Rate-based model

Crystallization kinetics

Nucleation rate (secondary nucleation)

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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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Size-independent dissolution rate Thomsen model

Thomsen and Rasmussen. Chem Eng Sci. 54 (1999) 1787-1802

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• Flow-schemes design


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


product removal

(MSMPR)

Scraped surface

heat exchanger

(SSHE)

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Flow-schemes design

Equipment selection


product removal

(MSMPR)

Scraped surface

heat exchanger

(SSHE)

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Flow-schemes design

Equipment selection


product removal

(MSMPR)

Scraped surface

heat exchanger

(SSHE)

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Flow-schemes design

Equipment selection


product removal

(MSMPR)

Scraped surface

heat exchanger

(SSHE)

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Flow-schemes design

Equipment selection


product removal

(MSMPR)

Scraped surface

heat exchanger

(SSHE)

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Flow-schemes design

Equipment selection


product removal

(MSMPR)

Scraped surface

heat exchanger

(SSHE)

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Flow-schemes design

Equipment selection


product removal

(MSMPR)

Scraped surface

heat exchanger

(SSHE)

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Flow-schemes design

Equipment selection


product removal

(MSMPR)

Scraped surface

heat exchanger

(SSHE)

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Flow-schemes design

Equipment selection


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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Modeling SSHEs

Solute mass balance SSHE1 - crystallization side

Energy balance SSHE1 - crystallization side

Population balance SSHE1 - crystallization side

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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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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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Decision variables

Operating parameters

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Decision variables


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Decision variables


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Decision variables


SSHE geometrical parameters

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Decision variables



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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



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Solid handling section optimization

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• ~ 104 simulations for each simulated

flowscheme during NSGA-II evolution

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• Pareto-sets extraction

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14-Jun-17 41

Decision variables analysis

• Decision variables vary along the Pareto-sets

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Scraped surface

heat exchanger

(SSHE)

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• UOL for


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SSHE

cross-section

Scraped surface

heat exchanger

(SSHE)

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• UOL for

• for


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Heat recovered

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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


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Thermodynamics


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Thermodynamics


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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


1. Non-dimensionalization

2. Integration

3. Scaling and normalization

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Flow-scheme design

Modeling MSMPRs


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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


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


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Comparative assessment: L-CAP vs. CSF-CAP


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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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14-Jun-17 63

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Effect of SSHEs geometrical parameters

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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)

process synthesis and equipment design of a solid handling ... · 3. a pinch point analysis has...

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