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INTRODUCTION TO CHEMICAL
PROCESS SIMULATORS
A. Carrero, N. Quirante, J. Javaloyes
October 2016
DWSIM Chemical Process Simulator
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
2
Contents
Monday, October 3rd 2016
 Introduction to Sequential – Modular Steady State Process
Simulators
 Get used to working with DWSIM and COCO
Monday, October 10th 2016
 Simulation of Chemical Reactors
Monday, October 17th 2016
 Simulation of Distillation Columns
Monday, October 24th 2016
 Case studies
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
3
Flowsheeting
Alexander C. Dimian (2003)
Flowsheeting is a systemic description of material and energy streams in a
process plant by means of computer simulation with the scope of
designing a new plant or improving the performance of an existing plant.
Flowsheeting can be used as aid to implement a plantwide control
strategy, as well as to manage the plant operation.
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
4
Process Flowsheet
Input streams
Operating
Conditions
Unit
Parameters
Output streams
Simulation
Process Flowsheet
Input streams
Operating
Conditions
Unit
Parameters
Output streams
Design
Process Flowsheet
Input streams
Operating
Conditions
Unit
Parameters
Output streams
Objective
Function
Optimization
Process
Flowsheet
Input streams
Operating
Conditions
Unit
Parameters
Output streams
Objective
Function
Synthesis
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
5
Architecture of Process Simulators
 Sequential-Modular
Based on the concept of modularity, which extends the chemical
engineering concept of the unit operation to a “unit calculation” by
the computer code responsible for the calculation of single process
unit. The computation of the flowsheet takes place unit by unit
following a calculation sequence.
 Equation-Oriented (Simultaneous-Nonmodular)
The complete model of the flowsheet is expressed in the form of one
large sparse system of nonlinear algebraic equations that is
simultaneously solved for all the unknowns.
 Simultaneous-Modular
Combination of Sequential-Modular and Equation Oriented
approaches
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
6
Commercial Steady-State Process Simulators
 Aspen Plus
 Aspen Hysys
 ChemCAD
 PRO II
 UniSim
 gProms
 VMGSim
 Aspen Plus in EO
 Aspen Custom Modeler
Sequential – Modular approach Equation – Oriented approach
Free Steady-State Process Simulators
 DWSIM
 COCO
Sequential – Modular approach
 ASCEND
Equation – Oriented approach
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
7
Sequential – Modular Process Simulators
Executive Program
Input
Output
Graphical User Interface
Numerical
routines
Unit module
library
Sizing and costing
database
Physical property
database
Themodynamic
methods
Figure reproduced from
Introduction to Software for Chemical Engineers, M. Martin (2015)
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
8
Sequential – Modular Process Simulators
+ Easy programming and maintenance.
+ Robustness and reliability. Specific solution methods are developed for each
process unit.
+ The unit blocks can be easily added to or removed from the flowsheet.
– SM is well suited to process simulator, but not to design or optimization, since
an iterative procedure is required to satisfy the constraints.
– Need for topological analysis and systematic initialization of tear streams.
– Present difficulties with flowsheets involving a large number of recycle
streams.
– Rigid direction of computation, normally outputs from inputs.
Advantages
Disadvantages
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
9
Physical Property Service Facilities
# Supply estimates for a number of different physical properties while the
simulation is running.
# Phase equilibrium represent one of the most important physical properties,
as many chemical processes simulations involve distillation, stripping,
evaporation or liquid-liquid separation. Solving the mass and energy
balances for these operations necessitates predicting the
 Vapor – Liquid Equilibrium (VLE)
 Liquid – Liquid Equilibrium (LLE)
# Estimation of physical properties can consume up to 90% of the
computation time of a simulation.
Property packages are used to predict the phase equilibrium
behavior of pure components and mixture systems
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
10
Phase Equilibrium
IsofugacitiesI II F
i i if f f  
A closed system that contains more than one phase, at constant Pressure and
Temperature, is at equilibrium if:
Where fi is the fugacity of Component i in Phases I, II,… F
V L
i if f
Vapor – Liquid Equilibrium
fi
V is the fugacity of Component i in the vapor phase
fi
L is the fugacity of Component i in the liquid phase
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
11
Equation-of-State Method
Vapor-phase fugacity
0
, ,
1
ln
j
P
i
i T P n
V RT
dp
RT n P

     
   

V V
i i if y P
L L
i i if x PLiquid-phase fugacity
,
, 
i i
V L
i i
y and x are the mole fraction of Comp i in the vapor and liquid phases respectively
and are the vapor and liquid phase fugacity coefficients respectively
P is the system pressure
where
The fugacity coefficients for each phase are determined with the following
expression
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
12
Equation-of-State Method
Vapor-phase fugacity
0
, ,
1
ln
j
P
i
i T P n
V RT
dp
RT n P

     
   

V V
i i if y P
L L
i i if x PLiquid-phase fugacity
,
, 
i i
V L
i i
y and x are the mole fraction of Comp i in the vapor and liquid phases respectively
and are the vapor and liquid phase fugacity coefficients respectively
P is the system pressure
where
The fugacity coefficients for each phase are determined with the following
expression
EOS
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
13
Activity Coefficient Method
0L
i i i if x f
Vapor-phase fugacity V V
i i if y P
Liquid-phase fugacity


i i
V
i
i
0
i
y and x are the mole fraction of Comp i in the vapor and liquid phases,respectively
is the vapor - phase fugacity coefficient
is the liquid - phase activity coefficient
f is the fugacity of Comp.i at standard state
where
In this case, thermodynamic models are required for i (from a equation of state)
and i (from a liquid-phase activity coefficient model)
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
14
Activity Coefficient Method
# The vapor phase can be considered ideal  1V
i 
# Standard State fugacity
0 0 0
exp sat
i
c
Psat i
i i i ip
v
f p dP p
RT

 
  
 

Poynting correction factor
0L
i i i if p x 
therefore
V
i if y P
therefore
At moderate pressures:
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
15
Vapor – Liquid Equilibrium Example (Dechema Chemestry Data Series)
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
16
Decision tree for the selection of the thermodynamic property model
Any polar
component?
Any Electrolyte?
Any pseudo
component?
YesNo
Yes
Under vacuum
conditions?
Ideal
Braun K-10
Yes
Chao-Seader
Grayson-Streed
Braun K-10
No
Peng-Robinson (PR)
Soave-Redlich-Kwong (SRK)
Lee-Kesler-Plöcker
No Yes
Electrolyte NRTL
Pitzer
Bromley-Pitzer
Operating pressure low
to medium ≤ 10 bar?
Binary iteration
coefficients available?
No
Yes
Schwartzentruber-Renon
PR or RKS with WS mixing rules
PR or RKS with MHV2 mixing rules
PSRK
PR or RKS with MHV2 mixing rules
No
No
Binary iteration
coefficients available?
Yes
Yes No
Liquid-liquid
equilibrium?
Yes
NRTL
UNIQUAC
Liquid-liquid
equilibrium?
No
UNIFAC
UNIFAC LLE
Yes
Wilson
NRTL
UNIQUAC
No
Activity coefficient modelEquationsof state model
Pressure
Polarity
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
17
Get used to working with Process Simulators
FIRST STEPS
1. Compounds
2. Property Packages
3. Flash Algorithm
4. System of Units
5. Feed inlet data
6. Units Specifications
7. Activate/recalculate all
8. Review of the results
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
18
DWSIM
Activate
Abort calculation
Recalculate All
Deactivate
COCO
Validate
Solve
Get used to working with Process Simulators
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
19
Get used to working with DWSIM and COCO
Flash distillation 1
An equimolar mixture of benzene and toluene is subjected to flash distillation at
a pressure of 1 bar in the separator. Determine the compositions (in mole
fraction benzene) of the liquid and vapor leaving the separator when the feed is
25% vaporized. Estimate the temperature in the separator.
Sensitivity analysis
0% vaporized
50% vaporized
75% vaporized
100% vaporized
A. Carrero , N. Quirante & J. Javaloyes20
Introduction to Chemical Process Simulators
Get used to working with DWSIM and COCO
Flash distillation 1
100 kmol/h
fv = 0.25
T ?
Vapor fraction Temperature (ºC)
0 91.55
0.25 93.17
0.5 94.89
0.75 96.59
1 98.15
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
21
Get used to working with DWSIM and COCO
Vapor Liquid Equilibrium
Bubble point
Dew point
A. Carrero , N. Quirante & J. Javaloyes
Introduction to Chemical Process Simulators
22
Get used to working with DWSIM and COCO
Flash distillation 2
Calculate the composition of the final stream in the following process
flowsheet.
Use UNIQUAC thermodynamic package
Ethanol
41.86 kmol/h
Acetone
38.64 kmol/h
25ºC
95 kPa
65ºC
25ºC
Xacetone
Xethanol
Xacetone
Xethanol

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Introduction to free and open source Chemical Process Simulators - (DWSIM & COCO)

  • 1. INTRODUCTION TO CHEMICAL PROCESS SIMULATORS A. Carrero, N. Quirante, J. Javaloyes October 2016 DWSIM Chemical Process Simulator
  • 2. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 2 Contents Monday, October 3rd 2016  Introduction to Sequential – Modular Steady State Process Simulators  Get used to working with DWSIM and COCO Monday, October 10th 2016  Simulation of Chemical Reactors Monday, October 17th 2016  Simulation of Distillation Columns Monday, October 24th 2016  Case studies
  • 3. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 3 Flowsheeting Alexander C. Dimian (2003) Flowsheeting is a systemic description of material and energy streams in a process plant by means of computer simulation with the scope of designing a new plant or improving the performance of an existing plant. Flowsheeting can be used as aid to implement a plantwide control strategy, as well as to manage the plant operation.
  • 4. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 4 Process Flowsheet Input streams Operating Conditions Unit Parameters Output streams Simulation Process Flowsheet Input streams Operating Conditions Unit Parameters Output streams Design Process Flowsheet Input streams Operating Conditions Unit Parameters Output streams Objective Function Optimization Process Flowsheet Input streams Operating Conditions Unit Parameters Output streams Objective Function Synthesis
  • 5. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 5 Architecture of Process Simulators  Sequential-Modular Based on the concept of modularity, which extends the chemical engineering concept of the unit operation to a “unit calculation” by the computer code responsible for the calculation of single process unit. The computation of the flowsheet takes place unit by unit following a calculation sequence.  Equation-Oriented (Simultaneous-Nonmodular) The complete model of the flowsheet is expressed in the form of one large sparse system of nonlinear algebraic equations that is simultaneously solved for all the unknowns.  Simultaneous-Modular Combination of Sequential-Modular and Equation Oriented approaches
  • 6. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 6 Commercial Steady-State Process Simulators  Aspen Plus  Aspen Hysys  ChemCAD  PRO II  UniSim  gProms  VMGSim  Aspen Plus in EO  Aspen Custom Modeler Sequential – Modular approach Equation – Oriented approach Free Steady-State Process Simulators  DWSIM  COCO Sequential – Modular approach  ASCEND Equation – Oriented approach
  • 7. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 7 Sequential – Modular Process Simulators Executive Program Input Output Graphical User Interface Numerical routines Unit module library Sizing and costing database Physical property database Themodynamic methods Figure reproduced from Introduction to Software for Chemical Engineers, M. Martin (2015)
  • 8. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 8 Sequential – Modular Process Simulators + Easy programming and maintenance. + Robustness and reliability. Specific solution methods are developed for each process unit. + The unit blocks can be easily added to or removed from the flowsheet. – SM is well suited to process simulator, but not to design or optimization, since an iterative procedure is required to satisfy the constraints. – Need for topological analysis and systematic initialization of tear streams. – Present difficulties with flowsheets involving a large number of recycle streams. – Rigid direction of computation, normally outputs from inputs. Advantages Disadvantages
  • 9. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 9 Physical Property Service Facilities # Supply estimates for a number of different physical properties while the simulation is running. # Phase equilibrium represent one of the most important physical properties, as many chemical processes simulations involve distillation, stripping, evaporation or liquid-liquid separation. Solving the mass and energy balances for these operations necessitates predicting the  Vapor – Liquid Equilibrium (VLE)  Liquid – Liquid Equilibrium (LLE) # Estimation of physical properties can consume up to 90% of the computation time of a simulation. Property packages are used to predict the phase equilibrium behavior of pure components and mixture systems
  • 10. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 10 Phase Equilibrium IsofugacitiesI II F i i if f f   A closed system that contains more than one phase, at constant Pressure and Temperature, is at equilibrium if: Where fi is the fugacity of Component i in Phases I, II,… F V L i if f Vapor – Liquid Equilibrium fi V is the fugacity of Component i in the vapor phase fi L is the fugacity of Component i in the liquid phase
  • 11. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 11 Equation-of-State Method Vapor-phase fugacity 0 , , 1 ln j P i i T P n V RT dp RT n P             V V i i if y P L L i i if x PLiquid-phase fugacity , ,  i i V L i i y and x are the mole fraction of Comp i in the vapor and liquid phases respectively and are the vapor and liquid phase fugacity coefficients respectively P is the system pressure where The fugacity coefficients for each phase are determined with the following expression
  • 12. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 12 Equation-of-State Method Vapor-phase fugacity 0 , , 1 ln j P i i T P n V RT dp RT n P             V V i i if y P L L i i if x PLiquid-phase fugacity , ,  i i V L i i y and x are the mole fraction of Comp i in the vapor and liquid phases respectively and are the vapor and liquid phase fugacity coefficients respectively P is the system pressure where The fugacity coefficients for each phase are determined with the following expression EOS
  • 13. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 13 Activity Coefficient Method 0L i i i if x f Vapor-phase fugacity V V i i if y P Liquid-phase fugacity   i i V i i 0 i y and x are the mole fraction of Comp i in the vapor and liquid phases,respectively is the vapor - phase fugacity coefficient is the liquid - phase activity coefficient f is the fugacity of Comp.i at standard state where In this case, thermodynamic models are required for i (from a equation of state) and i (from a liquid-phase activity coefficient model)
  • 14. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 14 Activity Coefficient Method # The vapor phase can be considered ideal  1V i  # Standard State fugacity 0 0 0 exp sat i c Psat i i i i ip v f p dP p RT          Poynting correction factor 0L i i i if p x  therefore V i if y P therefore At moderate pressures:
  • 15. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 15 Vapor – Liquid Equilibrium Example (Dechema Chemestry Data Series)
  • 16. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 16 Decision tree for the selection of the thermodynamic property model Any polar component? Any Electrolyte? Any pseudo component? YesNo Yes Under vacuum conditions? Ideal Braun K-10 Yes Chao-Seader Grayson-Streed Braun K-10 No Peng-Robinson (PR) Soave-Redlich-Kwong (SRK) Lee-Kesler-Plöcker No Yes Electrolyte NRTL Pitzer Bromley-Pitzer Operating pressure low to medium ≤ 10 bar? Binary iteration coefficients available? No Yes Schwartzentruber-Renon PR or RKS with WS mixing rules PR or RKS with MHV2 mixing rules PSRK PR or RKS with MHV2 mixing rules No No Binary iteration coefficients available? Yes Yes No Liquid-liquid equilibrium? Yes NRTL UNIQUAC Liquid-liquid equilibrium? No UNIFAC UNIFAC LLE Yes Wilson NRTL UNIQUAC No Activity coefficient modelEquationsof state model Pressure Polarity
  • 17. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 17 Get used to working with Process Simulators FIRST STEPS 1. Compounds 2. Property Packages 3. Flash Algorithm 4. System of Units 5. Feed inlet data 6. Units Specifications 7. Activate/recalculate all 8. Review of the results
  • 18. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 18 DWSIM Activate Abort calculation Recalculate All Deactivate COCO Validate Solve Get used to working with Process Simulators
  • 19. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 19 Get used to working with DWSIM and COCO Flash distillation 1 An equimolar mixture of benzene and toluene is subjected to flash distillation at a pressure of 1 bar in the separator. Determine the compositions (in mole fraction benzene) of the liquid and vapor leaving the separator when the feed is 25% vaporized. Estimate the temperature in the separator. Sensitivity analysis 0% vaporized 50% vaporized 75% vaporized 100% vaporized
  • 20. A. Carrero , N. Quirante & J. Javaloyes20 Introduction to Chemical Process Simulators Get used to working with DWSIM and COCO Flash distillation 1 100 kmol/h fv = 0.25 T ? Vapor fraction Temperature (ºC) 0 91.55 0.25 93.17 0.5 94.89 0.75 96.59 1 98.15
  • 21. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 21 Get used to working with DWSIM and COCO Vapor Liquid Equilibrium Bubble point Dew point
  • 22. A. Carrero , N. Quirante & J. Javaloyes Introduction to Chemical Process Simulators 22 Get used to working with DWSIM and COCO Flash distillation 2 Calculate the composition of the final stream in the following process flowsheet. Use UNIQUAC thermodynamic package Ethanol 41.86 kmol/h Acetone 38.64 kmol/h 25ºC 95 kPa 65ºC 25ºC Xacetone Xethanol Xacetone Xethanol