The Refined Electrolyte-NRTL Model applied to CO 2 -H 2 O-alkanolamine systems

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1 The Refined Electrolyte-NRTL Model applied to CO 2 -H 2 O-alkanolamine systems - Equilibrium model predictions - Implementation into the CO2SIM simulator., Finn Andrew Tobiesen*, Mehdi Karimi, Xiao Luo, Tore Haug-Warberg and Hallvard F. Svendsen Norwegian University of Science and Technology (NTNU) Department of Chemical Engineering *SINTEF Materials and Chemistry Trondheim, Norway, TCCS-9

2 Outline Equilibrium problem statement The refined electrolyte-nrtl model Theory Predictions of partial pressures, speciation and heat of absorption Implementation into CO2SIM

3 Equilibrium: Problem statement Vapour liquid equilibria (VLE): Chemical equilibria (liquid phase):

4 Model structure General model structure: Helmholtz energy formulation (EOS) : A= A SR + A LR e.g. A = A classical eos + A DH/MSA +(A Born ) Excess Gibbs energy formulation (γ) G E = G E,SR + G E,LR e.g. G E = G E,NRTL + G E,DH/MSA +(G E,Born ) SR Short range interactions G E : E-NRTL, UNIQUAC etc. EOS: cubic, CPA etc. Parameter estimation LR Long range interactions Coulombic interactions Stronger interactions Great deviations from ideality Debye-Hückel/MSA term Consistency issues Weak theoretical basis The latter structure is adopted in the e-nrtl framework

5 Model requirements (rigorous models) 1. Thermodynamic consistency 2. Must be able to deal with mixed solvents and molecular solutes 3. Reasonable computational effort 4. Reasonable number of parameters to be estimated 5. Versatility (easily applied to different systems) 6. Accurate predictions for variable loadings and process conditions 1. Partial pressure of CO 2 and amine 2. Speciation (distribution of species) 3. Heat of absorption (important for energy consumption in stripper)

6 Models found in literature Numerous models found in literature. Most are G E based. Non-rigorous (empiric) models Kent-Eisenberg, (Desmukh-Mather) Simple structure (+) Few parameters (+) Limited usefulness (-) Not speciation, γ H2O, γ amine and ΔH abs May be suited for early-phase studies EOS based models (φ -φ) Few models found weaker, but growing basis. Fürst - Renon (Cubic EOS + MSA) CPA models (cubic + association) G E models (γ-φ) E-NRTL, Pitzer, UNIFAC, UNIQUAC, etc. More complex (-) Often many parameters (-) Better predictability (+) Parameter databases (+) Much experience and know-how (+) Especially e-nrtl is much used Most work found in literature is done in this field. Versatile models (+) Complex models (-) Mixing rules (-) Less experience and know-how (-) Many parameters to be estimated (-)

7 The Electrolyte-NRTL model 1 Maybe the most used (rigorous) model for industrial electrolyte systems Simplifying assumption made in differentiation to yield the activity coefficients Inconsistent for multi-ionic solutions, Multi-ionic: Multiple cations and/or anions E G ¹ RTå niln g " i i RT ln g i G = n E i Recent paper by Bollas et al. 2 presented a corrected e-nrtl model The refined electrolyte NRTL model [1] C.-C. Chen and L. B. Evans, AIChE J., 32 (1986) 444 [2] G.M. Bollas, C.-C Chen and P.I. Barton, AIChE J.,54 (2008) 1608.

8 Refined vs. unrefined e-nrtl Refined e-nrtl: - Almost no applications so far - No parameters in literature - Complex model equations - (Complex parameter definitions) + Consistent Original e-nrtl: - Inconsistent - (Complex parameter definitions) + Less complex model equations + Parameters in literature + Implemented in Aspen Plus

9 Equilibrium model development Stand-alone equilibrium model is developed Solves phase and chemical equilibrium Speciation, partial pressures, heat of absorption Chemical equilibrium solved by using non-stoichiometric Gibbs energy minimization routine SRK or Peng-Robinson EOS for vapour phase. Pitzer-Debye-Hückel and Born term for long range forces Refined electrolyte-nrtl model implemented in the RGrad language RGrad is a tailor made language that performs analytical differentiations 3 Verified through implementation in FORTRAN and comparison with Bollas et al. Electrolyte interaction parameters fitted to PCO 2. H2O-NaCl-KCl system 4 interaction parameters (τsalt,salt= 0) H2O-MEA-CO 2 system 56 parameters! Major drawback of the e-nrtl framework [3] B.T. Løvfall, PhD. thesis, NTNU (2008)

10 Model predictions Partial pressure of CO 2, 30wt% MEA Electrolyte interaction parameters fitted to P CO2 Molecule-Molecule interaction parameters may be retained from original e-nrtl model

11 Heat of absorption and speciation, 30wt% MEA Over-prediction Revise carbamate constant Calculated rigorously: E ( ) H = h + h Δ n + h E ln γ h h i 0 phys. abs abs i i i i 2 = RT T P, n RT 2 2 = + phys. abs 2 ln H CO ln ϕ CO ln Φ T T T Poynting Minimization routine Good predictions for major species Problems with predicting free CO 2 P, n

12 Evaluation of activity coefficients Activity coefficients for CO 2 calculated from N 2 O solubility measurements and the N 2 O analogy 4 H H H = ; γ = CO N O CO 2 2 2 CO2 HCO H 2 N 2O HCO 2 When fitted to P CO2, activity coefficients may not represent the reality Subject to further study [4] A. Hartono, PhD. thesis, NTNU (2009)

13 The CO2SIM simulator Developed for simulating novel solvent systems Possibility of building complex flowsheets for performance studies testing and design (used for studying alternative process configurations) Stable solver numerical methods Fast convergence Graphical user interface The refined e-nrtl model is implemented in CO2SIM Converted to FORTRAN Simulations based on pilot plant runs are performed Only absorber is studied here

The CO2SIM simulator: GUI

15 Simulation results Example: Simulations based on NTNU/SINTEF pilot runs Temperature profiles (16032005-1) Temperature profiles (16032005-2) Heigth [m] 5 4.5 4 3.5 3 2.5 2 1.5 1 T VAP. CO2SIM (R-ENRTL) 0.5 T VAP. EXP T ASPEN 0 T VAP CO2SIM (SIMPLE) 48 49 50 51 52 53 54 55 56T LIQ. 57 CO2SIM 58(R-ENRTL) T LIQ CO2SIM (SIMPLE) T [GRC] Heig th [ m ] 5 4.5 4 3.5 3 2.5 2 1.5 1 T VAP. CO2SIM (R-ENRTL) T VAP. EXP 0.5 T ASPEN 0 T VAP CO2SIM (SIMPLE) T LIQ. CO2SIM (R-ENRTL) 59 61 63 65 67 69 71 73 T LIQ. CO2SIM SIMPLE T [GRC] Aspen simulations performed using ratebased Radfrac in Aspen Plus v7.1

16 Simulation results Example: Simulations based on NTNU/SINTEF pilot runs Equilibrium model will be continuously improved in order to get better predictions

17 Conclusions and further work Refined e-nrtl implemented in both RGRAD and FORTRAN Good overall predictions Problem with predicting free CO 2 Work to be done on physical activity coefficients and parameter estimation Compare with other thermodynamic models (e.g. UNIQUAC, EOS mod.) CO2SIM implementation Refined e-nrtl is implemented in CO2SIM Results demonstrate need for rigorous thermodynamic calculations Pilot rig at NTNU/SINTEF is simulated. Analysis will be extended to the whole pilot, not just absorber, and to other pilot results

18 Thank you for your attention.