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Opening new doors with Chemistry THINK SIMULATION! OLI’s Mixed Solvent Electrolyte with Aspen PLUS OLI Systems, Inc.

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Presentation on theme: "Opening new doors with Chemistry THINK SIMULATION! OLI’s Mixed Solvent Electrolyte with Aspen PLUS OLI Systems, Inc."— Presentation transcript:

1 Opening new doors with Chemistry THINK SIMULATION! OLI’s Mixed Solvent Electrolyte with Aspen PLUS OLI Systems, Inc.

2 THINK SIMULATION Think simulation 2 Agenda  OLI’s basic history  OLI’s history with Aspen Technologies  Advantages/disadvantages of Aspen PLUS OLI  Architecture of the Aspen PLUS OLI interface  Introduction to MSE  Overview of Aspen PLUS OLI (with MSE)  Demonstration

3 THINK SIMULATION Think simulation 3 OLI’s basic history  Company founded in 1971 by Marshall Rafal  First electrolyte simulator (ECES) 1973 ■ Developed for OLIN Chemical  First commercial sale of ECES 1975 ■ Dupont  The Environmental Simulation Program developed in 1991  Linkage to simulators in 1995  Windows program (Analyzers) became commercial in 2000  Mixed-Solvent Electrolytes commercially available 2005  Windows based process simulator (OLI Pro) to be available in 2007

4 THINK SIMULATION Think simulation 4 OLI’s history with Aspen Technologies  That “Other” chemical company that has a “D” in its name. ■ 25 years of process simulation experience with electrolyte ■ 1995 switched to Aspen PLUS as their process simulator ■ Wanted OLI’s electrolytes in Aspen PLUS  1996 first Aspen PLUS OLI interface created ■ No model manager, version 8.2  1997 Aspen PLUS OLI linked to model manager ■ Version 9.0  2006 Aspen PLUS OLI updated for Aspen ONE 2006 ■ Included change in concentration basis ■ Included MSE  2007 Aspen PLUS OLI updated for Aspen ONE ■ General release of MSE for all Aspen PLUS OLI clients

5 THINK SIMULATION Think simulation 5 Advantages of Aspen PLUS OLI  User Interface  Learn one flow sheeting system  Multiple Property Options in same flowsheet  Different Non-electrolyte capability  Sizing  Costing  Two Software Venders

6 THINK SIMULATION Think simulation 6 Disadvantages of Aspen PLUS OLI  No Corrosion  No advanced OLI technology ■ No Ion-exchange ■ No Surface Complexation ■ No Bio-kinetics  No Scaling Tendencies  Two Software Venders

7 THINK SIMULATION Think simulation 7 Architecture of the Aspen PLUS OLI interface OLI Chemistry Generator OLI Databases OLI/A+ XREF OLI Numerical Solver/Engine.BKP.ASP/.INP.DBS A+ Model Manager A+ Simulation Engine Electrolyte Flash or Property

8 THINK SIMULATION Think simulation 8 Architecture of the Aspen PLUS OLI interface  Aspen Unit Operations available with the OLI Property Set ■ MIXERS ■ FSPLIT ■ SEP ■ SEP2 ■ HEATER ■ FLASH2 ■ FLASH3 ■ HEATX ■ MHEATX ■ RADFRAC ■ RSTOIC ■ RYIELD ■ RCSTR ■ RPLUG ■ PUMP ■ COMPR

9 THINK SIMULATION Think simulation 9 Architecture of the Aspen PLUS OLI interface  Thermodynamic Properties from OLI used by Aspen PLUS (OLI propset)

10 THINK SIMULATION Think simulation 10 Architecture of the Aspen PLUS OLI interface  The OLI-Aspen Plus Cross Reference File (partial listing) ■ Full listing is available on your computer: ◊C:\Program Files\OLI Systems\Alliance Suites\Aspen OLI 2006\Databanks\OLIAspenPlusCompXRef.lis ESP-NAME DB 8-CHAR ASP-ALIAS ASP-NAME ================ = ====== ========= ===================================== AR P AR AR ARGON Ar ABIETICAC P ABIETICA C20H30O2 ABIETIC-ACID C20H30O2 ACENAPHTHN P ACENAPHT C12H10-D0 ACENAPHTHENE C12H10 ACENITRILE P ACENTL C2H3N ACETONITRILE C2H3N ACET2 P ACET C4H8O4 ACETACID P ACETACID C2H4O2-1 ACETIC-ACID C2H4O2 ACETAL P ACETAL C6H14O2-D1 ACETAL C6H14O2 ACETALDEHD P ACEALD C2H4O-1 ACETALDEHYDE C2H4O ACETAMIDEPPT P ACETAM-S C2H5NO ACETAMIDE P ACETAMD C2H5NO-D1 ACETAMIDE C2H5NO ACETANHYD P ACETAHYD C4H6O3 ACETIC-ANHYDRIDE C4H6O3 ACETANILID P ACEANILD C8H9NO ACETANILIDE ACETATEION P ACET- CH3COO- CH3COO C2H3O2-1 ACETBR P ACETBR C2H3BrO ACETCL P ACETCL C2H3CLO ACETYL-CHLORIDE C2H3ClO ACETONE P ACETONE C3H6O-1 ACETONE C3H6O ACETPHENON P ACEPHEN C8H8O METHYL-PHENYL-KETONE C8H8O ACETYLENE P ACETYLN C2H2 ACETYLENE C2H2 ACRIDINE P ACRIDINE C13H9N ACROLEIN2 P ACROLIN2 C3H4O ACROLEIN C3H4O ACRYLAMIDEPPT P ACRAMI-S C3H5NO ACRYLAMIDE P ACRYAMID C3H5NO-D1 ACRYLAMIDE C3H5NO

11 THINK SIMULATION Think simulation 11 Architecture of the Aspen PLUS OLI interface  OLI added user blocks to Aspen PLUS ■ EFRACH ■ EFLASH  Available during Aspen PLUS Installation ■ Must be enabled at run-time

12 THINK SIMULATION Think simulation 12 Architecture of the Aspen PLUS OLI interface  EFLASH Organic (3) Solid (4) EFLASH (Four outlet material streams) Feeds Heat Vapor (1) Aqueous (2)

13 THINK SIMULATION Think simulation 13 Architecture of the Aspen PLUS OLI interface  EFRACH DECANTER Vapor or Liquid Organic Heat N FeedsProducts Heat Bottoms

14 THINK SIMULATION Think simulation 14 Introduction to MSE  Why develop a new thermodynamic model? ■ The Bromley-Zemaitis model (a/k/a Aqueous Model-AE) had limitations ◊Water was required as a solvent ◊Mole fraction of all solutes was limited to approximately 0.35 ◊Limited in temperature (Approximately 300 o C) ◊LLE predictions exclude critical solution points (limited to strongly dissimilar phases) ■ A Mixed Solvent Electrolyte model (MSE) has advantages ◊Water is not required ◊Mole fraction of solute can approach and be equal to 1.0 ◊Temperature can be up to 0.9 T c of solution ◊Full range of LLE calculations including electrolytes in both phases

15 THINK SIMULATION Think simulation 15 Introduction to MSE Advantages and disadvantages between AE and MSE  MSE model ■ Model advantages: ◊No composition limitations ◊Reliable predictions for multicomponent concentrated solutions ◊Full range of LLE calculations including electrolytes in both phases ■ Methodological advantages ◊Multi-property regressions ◊Consistent use of thermochemical properties (no shortcuts like KFITs) ◊Rigorous quality assurance ■ Disadvantages: ◊A smaller in-place databank but it is continuously extended  AE Model ■ Advantages: ◊Larger existing databank ◊The only model available for rates of corrosion ■ Disadvantages: ◊Limitations with respect to composition (30 m with respect to electrolytes, x=0.3 with respect to nonelectrolytes ◊LLE predictions exclude critical solution points (limited to strongly dissimilar phases)

16 THINK SIMULATION Think simulation 16 Introduction to MSE  Overview of species coverage between AE and MSE models. Components Solute Mole Fraction AE MSE Build Growing with each build

17 THINK SIMULATION Think simulation 17 Structure of the thermodynamic model  Definition of species that may exist in the liquid, vapor, and solid phases  Excess Gibbs energy model for solution nonideality  Calculation of standard-state properties ■ Helgeson-Kirkham-Flowers equation for ionic and neutral aqueous species ■ Standard thermochemistry for solid and gas species  Algorithm for solving phase and chemical equilibria

18 THINK SIMULATION Think simulation Outline of the model: Solution nonideality LR Debye-Hückel theory for long-range electrostatic interactions LCLocal composition model (UNIQUAC) for neutral molecule interactions II Ionic interaction term for specific ion-ion and ion- molecule interactions Excess Gibbs energy

19 THINK SIMULATION Think simulation 19 Outline of the model: Chemical equilibrium calculations For a chemical reaction: At equilibrium with Standard-state chemical potential of i  Infinite-dilution properties ■ Thermochemical databases for aqueous systems ■ Helgeson-Kirkham-Flowers model for T and P dependence

20 THINK SIMULATION Think simulation 20 Outline of the model: Constraints  Activity coefficients are converted to unsymmetrical normalization to work with infinite-dilution properties  Constraining the parameters of the G E model to reproduce the Gibbs energy of transfer Activity coefficient of ion i in solvents R and S in unsymmetrical, mole-fraction based convention

21 THINK SIMULATION Think simulation 21 Mixed-solvent electrolyte model: Applicability  Simultaneous representation of multiple properties ■ Vapor-liquid equilibria ■ Osmotic coefficient/water activity and activity coefficients ■ Solid-liquid equilibria ■ Properties of electrolytes at infinite dilution, such as acid- base dissociation and complexation constants ■ Properties that reflect ionic equilibria, e.g., solution pH and species distribution ■ Enthalpy (  Hdil or  Hmix) ■ Heat capacity ■ Density

22 THINK SIMULATION Think simulation 22 Validity range  Concentrations from infinite dilution to saturation or fused salt or pure solute limit  Temperatures up to 0.9Tc of mixtures ■ This translates into 300 C for H2O – dominated systems ■ For concentrated inorganic systems, substantially higher temperatures can be reached  Solvents: water, various organics or solvent mixtures

23 THINK SIMULATION Think simulation 23 Representative applications of the MSE thermodynamic model  Strong acid systems ■ Simultaneous representation of phase equilibria and speciation  Salt systems ■ Prediction of properties of multicomponent systems  Organic – salt – water systems ■ Salt effects on VLE, LLE and SLE  Acid-base equilibria ■ pH of mixed-solvent systems

24 THINK SIMULATION Think simulation 24 VLE for H2SO4 + SO3 + H2O  Phase equilibria are accurately reproduced from 0 C to 500 C

25 THINK SIMULATION Think simulation 25 Speciation for H 2 SO 4 + SO 3 + H 2 O:  Predicted speciation in concentrated solutions agrees with spectroscopic data

26 THINK SIMULATION Think simulation 26 Partial pressures in the H 2 SO 4 + SO 3 + H 2 O system  Partial pressures of H 2 SO 4, SO 3 and H 2 O are also correctly reproduced Partial pressures of H 2 SO 4

27 THINK SIMULATION Think simulation 27 Salt systems: Na – K – Mg – Ca – Cl – NO 3  Step 1: Binary systems – solubility of solids  The model is valid for systems ranging from dilute solutions to the fused salt limit NaNO 3 – H 2 O Mg(NO 3 ) 2 – H 2 O

28 THINK SIMULATION Think simulation 28 Modeling salt systems: Na – K – Mg – Ca – Cl – NO 3  Step 1: Binary systems – solubility of solids  Water activity decreases with salt concentration until the solution becomes saturated with a solid phase

29 THINK SIMULATION Think simulation 29 Step 2: Ternary systems  Solubility in the system NaNO 3 – KNO 3 – H 2 O at various temperatures  Activity of water over saturated NaNO 3 – KNO 3 solutions at 90 C: Strong depression at the eutectic point

30 THINK SIMULATION Think simulation 30 Step 3: Verification of predictions for multicomponent systems  Deliquescence data simultaneously reflect solid solubilities and water activities Mixed nitrate systems at 140 C

31 THINK SIMULATION Think simulation 31 Electrolyte + organic systems: Examples  Effect of electrolytes on phase equilibria in nonelectrolyte – water systems ■ Salting out(in) effects  Liquid-liquid equilibria in aqueous systems containing water- soluble polymers and salts ■ Liquid immiscibility is induced by the presence of a salt

32 THINK SIMULATION Think simulation 32 LLE results – salt effect Solubility of benzene in aqueous (NH 4 ) 2 SO 4 and NaCl solutions at 25ºC

33 THINK SIMULATION Think simulation 33 VLE: salting-out effect P=1 bar ---- Salt-free —— Saturated NaCl Solubility 25°C Simultaneous representation of thermodynamic properties: NaCl-methanol-water

34 THINK SIMULATION Think simulation 34 LLE in aqueous polymer – salt systems  PEG (MW=1000) + NaH 2 PO 4 + H 2 O at 25 C  PEG (MW=4000) + (NH 4 ) 2 SO 4 + H 2 O at 25 C

35 THINK SIMULATION Think simulation 35 Acid-base and phase equilibria: Treatment of pH in mixed solvents  Classical treatment ■ pH scale can be defined separately for each, pure or mixed, solvent ■ pH scales can be converted using the Gibbs energy of transfer of the proton ■ Such a conversion is inconvenient (availability of Gibbs energy of transfer, extrathermodynamic assumptions) ■ However, it opens the possibility of a uniform calculation of pH using an activity coefficient model as long as the model accurately reproduces activity coefficients of individual species and the Gibbs energy of transfer

36 THINK SIMULATION Think simulation 36 Treatment of pH in mixed-solvents  Uniform treatment of apparent pH ■ Starting point: Aqueous definition of pH ■ Conversion to mole fraction scale and solvated proton basis ■ Activity coefficients are obtained directly from the model ■ Values can be compared with measurements using glass electrode ■ Does not require the presence of water – equivalent expressions can be obtained for other solvents

37 THINK SIMULATION Think simulation 37 Speciation Effects Acetic Acid in EtOH-H 2 O Acetic Acid in MeOH-H 2 O Apparent (Mixed Solvent-Based) Ionization Constants Equilibrium constant obtained from aqueous solutions

38 THINK SIMULATION Think simulation 38 Parameters in the MSE Databank (1)  Binary and principal ternary systems composed of the following primary ions and their hydrolyzed forms ■ Cations: Na +, K +, Mg 2+, Ca 2+, Al 3+, NH 4 + ■ Anions: Cl -, F -, NO 3 -, CO 3 2-, SO 4 2-, PO 4 3-, OH -  Aqueous acids, associated acid oxides and acid-dominated mixtures ■ H 2 SO 4 – SO 3 ■ HNO 3 – N 2 O 5 ■ H 3 PO 4 – H 4 P 2 O 7 – H 5 P 3 O 10 – P 2 O 5 ■ H 3 PO 2 ■ H 3 PO 3 ■ HF ■ HCl ■ HBr ■ HI H 3 BO 3 CH 3 SO 3 H NH 2 SO 3 H HFSO 3 – HF – H 2 SO 4 HI – I 2 – H 2 SO 4 HNO 3 – H 2 SO 4 – SO 3 H 3 PO 4 with calcium phosphates H – Na – Cl – NO 3 H – Na – Cl – F

39 THINK SIMULATION Think simulation 39 Parameters in the MSE Databank (2)  Inorganic gases in aqueous systems ■ CO 2 + NH 3 ■ H 2 S + NH 3 ■ SO 2 + H 2 SO 4 ■ N 2 ■ O 2 ■ H 2  Transition metal aqueous systems ■ Fe(III) – H – O – SO 4, NO 3 ■ Fe(II) – H – O – SO 4, Br ■ Sn(II, IV) – H – O – CH 3 SO 3 ■ Zn(II) – H – SO 4, NO 3, Cl ■ Zn(II) – Li - Cl

40 THINK SIMULATION Think simulation 40 Parameters in the MSE Databank (3)  Transition metal aqueous systems - continued ■ Cu(II) – H – SO 4, NO 3 ■ Ni(II) – H – SO 4, NO 3, Cl ■ Mo(VI, IV) – H – O – Cl, SO 4, NO 3 ■ W(VI) – H - O - Na – Cl, NO 3  Most elements from the periodic table in their elemental form  Base ions and hydrolyzed forms for the majority of elements from the periodic table  Hydrogen peroxide chemistry ■ H 2 O 2 – H 2 O – H - Na – OH – SO 4 – NO 3

41 THINK SIMULATION Think simulation 41 Parameters in the MSE Databank (4)  Miscellaneous inorganic systems in water ■ NH 2 OH ■ NH 4 HS + H 2 S + NH 3 ■ LiCl – KCl ■ LiCl – CaCl 2 ■ Na 2 S 2 O 3 ■ LiOH – H 3 BO 3 – H 2 O  Organic acids in water, methanol and ethanol and their Na salts ■ Formic ■ Acetic (also K salt) ■ Citric ■ Adipic ■ Nicotinic ■ Terephthalic ■ Isophthalic ■ Trimellitic

42 THINK SIMULATION Think simulation 42 Parameters in the MSE Databank (5)  Organic components and their mixtures with water ■ Hydrocarbons ◊Straight chain alkanes: C1 through C30 ◊Isomeric alkanes: isobutane, isopentane, neopentane ◊Alkenes: ethene, propene, 1-butene, 2-butene, 2-methylpropene ◊Aromatics: benzene, toluene, o-, m-, p-xylenes, ethylbenzene, cumene, naphthalene, anthracene, phenantrene ■ Alcohols ◊Methanol, ethanol, 1-propanol, 2-propanol, cyclohexanol ■ Glycols ◊Mono, di- and triethylene glycols, propylene glycol, polyethylene glycols ■ Phenols ◊Phenol, catechol ■ Ketones ◊Acetone, methylisobutyl ketone ■ Aldehydes ◊Butylaldehyde

43 THINK SIMULATION Think simulation 43 Parameters in the MSE Databank (6)  Organic solvents and their mixtures with water ■ Carbonates ◊Diethylcarbonate, propylene carbonate ■ Amines ◊Tri-N-octylamine, triethylamine, methyldiethanolamine ■ Nitriles ◊Acetonitrile ■ Amides ◊Dimethylacetamide, dimethylformamide ■ Halogen derivatives ◊Chloroform ■ Aminoacids ◊Methionine ■ Heterocyclic components ◊N-methylpyrrolidone, 2,6-dimethylmorpholine

44 THINK SIMULATION Think simulation 44 Parameters in the MSE Databank (7)  Polyelectrolytes ■ Polyacrylic acid ◊Complexes with Cu, Zn, Ca  Mixed-solvent organic systems ■ HAc – tri-N-octylamine – toluene – H 2 O ■ HAc – tri-N-octylamine – methylisobutylketone – H 2 O ■ HAc – MeOH – EtOH – H 2 O ■ HAc – MeOH – CO 2 – H 2 O ■ Dimethylformamide – HFo – H 2 O

45 THINK SIMULATION Think simulation 45 Parameters in the MSE Databank (8)  Mixed-solvent inorganic/organic system ■ Hydrocarbon – water – salt (Na, K, Ca, Mg, NH 4, H, Cl, SO 4, NO 3 ) systems ■ Mono, di- and triethylene glycols - H – Na – Ca – Cl – CO 3 – HCO 3 - CO 2 – H 2 S – H 2 O ■ Phenol - acetone - SO 2 - HFo - HCl – H 2 O ■ Benzene – NaCl and (NH 4 ) 2 SO 4 - H 2 O ■ Cyclohexane – NaCl - H 2 O ■ n-Butylaldehyde – NaCl - H 2 O ■ LiPF 6 – diethylcarbonate – propylene carbonate ■ Ethanol – LiCl - H 2 O ■ Methanol - H 2 O + NaCl, HCl

46 THINK SIMULATION Think simulation 46 Predictive character of the model  Levels of predictivity ■ Prediction of the properties of multicomponent systems based on parameters determined from simpler (especially binary) subsystems ◊Extensively validated for salts and organics ■ Prediction of certain properties based on parameters determined from other properties ◊Extensively validated (e.g., speciation or caloric property predictions)

47 THINK SIMULATION Think simulation 47 What does it mean for the model to be predictive?  Parameters were determined using only binary salt + H 2 O data  SLE for the ternary system was predicted without making any ternary fits  MSE is clearly superior even in the applicability range of the aqueous model  This can work only when the ternary system does not introduce a chemistry change (e.g., double salts) MSE (no ternary fits) Aqueous model (no ternary fits)

48 THINK SIMULATION Think simulation 48 Predictive character of the model  Levels of predictivity - continued ■ Prediction of properties without any knowledge of properties of binary systems ◊Standard-state properties: Correlations to predict the parameters of the HKF equation ∆ Ensures predictivity for dilute solutions ◊Properties of solids: Correlations based on family analysis ◊Parameters for nonelectrolyte subsystems ∆ Group contributions: UNIFAC estimation ∆ Quantum chemistry + solvation: CosmoTherm estimation »Also has limited applicability to electrolytes as long as dissociation/chemical equilibria can be independently calculated

49 THINK SIMULATION Think simulation 49 Transport properties in the OLI software  Available transport properties: ■ Diffusivity ■ Viscosity ■ Electrical conductivity  OLI was the first to develop transport property models for concentrated, multicomponent aqueous solutions  More recently, the models have been extended to mixed-solvent systems

50 THINK SIMULATION Think simulation 50 Modeling diffusivity in electrolyte systems  Limiting diffusivity –  Long-range electrostatic interactions – Relaxation effect:  Short-range interactions – Hard-sphere contribution:  Combination of the two effects: Enskog theory: Significant for concentrated solutions MSA theory: Important in relatively dilute solutions

51 THINK SIMULATION Think simulation 51 Calculation of diffusivity in MSE solutions D methanol in methanol-water-LiCl system at 25ºC at various LiCl concentrations D methanol in methanol-water-NaCl system at 25ºC at various NaCl concentrations

52 THINK SIMULATION Think simulation 52 Computation of diffusion coefficients: Species in NiCl 2 solutions  For complexed species, measured diffusion coefficients are weighted averages of diffusion coefficients of individual complexes:

53 THINK SIMULATION Think simulation 53 Modeling electrical conductivity Limiting conductivity Dependence of i on electrolyte concentration relaxation effect electrophoretic correction The model includes the computation of 1.Limiting conductivities of ions as a function of temperature and solvent composition 2.Dependence of electrical conductivity on electrolyte concentration (the mean spherical approximation theory)

54 THINK SIMULATION Think simulation 54 Electrical conductivity model: H 2 O – H 2 SO 4 – SO 3

55 THINK SIMULATION Think simulation 55 Electrolytes in mixed solvents: MgCl 2 + ethanol + water

56 THINK SIMULATION Think simulation 56 Viscosity model viscosity of the MSE solution viscosity of the solvent mixture long-range electrostatic contribution individual ion contributions interactions between species Dependence of  on electrolyte concentration  In MSE solutions,  -  0 is found to show regularities with respect to both electrolyte concentrations and solvent composition, and is the most convenient quantity to define the model

57 THINK SIMULATION Think simulation 57 Viscosities of solvent mixtures,  0 mix acetone + water Mixing rule Modified volume fractions

58 THINK SIMULATION Think simulation 58 Effects of electrolyte concentration   LR – From the analytical model by Onsager and Fuoss (1932)   s – defined for multiple solvents   s-s – defined for solvent combinations calculated using  and i 0 in the mixed solvent j = solvent; i = ion or neutral j,l = solvent; i,k = ion or neutral B i,j evaluated based on viscosities of electrolyte in pure solvent D ik,jl ( I,T) adjusted based on experimental data

59 THINK SIMULATION Think simulation 59 Viscosity of H 2 O – H 2 SO 4 – SO 3

60 THINK SIMULATION Think simulation 60 Viscosity of salt – organic - water systems: LiNO 3 -ethanol-H 2 O Viscosities of the ternary solutions of LiNO 3 -ethanol-H 2 O as a function of the molarity of LiNO 3 at 25ºC and at various ethanol weight percent.

61 THINK SIMULATION Think simulation 61 Sublimation / salt point calculations  Solid-gas equilibrium computations for pure NH 4 Cl and NH 4 HS NH 4 Cl NH 4 HS

62 THINK SIMULATION Think simulation 62 HI - I2 - H2O  H2O/HI/I2 full range of concentration, T  The heart of the IS Process  Challenge: presence of more than one LLE region together with regions of VLE and SLE

63 THINK SIMULATION Think simulation 63 MSE Challenge  For systems within the AQ model limits, yes ■ Binary systems give reasonable results when water remains the dominant solvent  When the 2 nd solvent, or different solvent predominates ■ All major components must be studied with respect to all solvents ◊ e.g., for MEG systems, MEG – Ca and MEG – Na must be regressed, along with Will MSE work out-of-the-box?

64 THINK SIMULATION Think simulation 64 Overview of Aspen PLUS OLI (with MSE)  Using the Aspen PLUS OLI Chemistry Generator

65 THINK SIMULATION Think simulation 65 Aspen OLI Chemistry Generator

66 THINK SIMULATION Think simulation 66 Aspen OLI Chemistry Generator

67 THINK SIMULATION Think simulation 67 Aspen OLI Chemistry Generator

68 THINK SIMULATION Think simulation 68 Aspen OLI Chemistry Generator

69 THINK SIMULATION Think simulation 69 Aspen OLI Chemistry Generator

70 THINK SIMULATION Think simulation 70 Aspen OLI Chemistry Generator

71 THINK SIMULATION Think simulation 71 Aspen OLI Chemistry Generator

72 THINK SIMULATION Think simulation 72 Aspen OLI Chemistry Generator

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76 THINK SIMULATION Think simulation 76 Aspen OLI Chemistry Generator

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83 THINK SIMULATION Think simulation 83 Aspen OLI Chemistry Wizard

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110 THINK SIMULATION Think simulation 110 Aspen Plus OLI with EFRACH

111 THINK SIMULATION Think simulation 111 Aspen Plus OLI with EFRACH

112 THINK SIMULATION Think simulation 112 Aspen Plus OLI with EFRACH

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114 THINK SIMULATION Think simulation 114 Aspen Plus OLI with EFRACH

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119 THINK SIMULATION Think simulation 119 Aspen Plus OLI with EFRACH

120 THINK SIMULATION Think simulation 120 Aspen Plus OLI with EFRACH

121 THINK SIMULATION Think simulation 121 Aspen OLI  More examples?  Live cases?  Questions?

122 THINK SIMULATION Think simulation 122 Conclusion  Using MSE in Aspen Plus is very similar to using any property set.  The OLI property sets can be used with standard Aspen PLUS unit operations or with OLI unit operations


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