ECUST PROII Advanced Training

ECUSTECUSTPRO/II PRO/II

Advanced Advanced TrainingTraining

PRO/II Training

Copyright © 2004 SIMSCI-ESSCOR™ All Rights Reserved

PRO/II Training

2

focused on simulation

trusted resultsWho we are– Provider of software and services to the

Hydrocarbon and Power industries that allow for efficient:

design operate

optimize

plants and processes –steady state & dynamic

simulation

(PRO/II, HEXTRAN, VISUAL FLOW,INPLANT

PIPEPHASE, DYNSIM, TACITE,

iFEED Suite/COMOS)

plant start-up, operation and training of operators with modeling, dynamic simulation & control emulation

(PRO/II, DATACON, OTS, DYNSIM, FSIM)

advisory and closed loop of their processes

(ROMeo, ARPM, Connoisseur, PRO/II, NETOPT)

increased profitability

What is the Power of Simulation3?

PRO/II Training

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Be the leading provider of software and solutions for– Simulation & Modeling– Performance Monitoring– Optimization– Operator Training– Integrated Process Engineering

Use the Best-in Class Technology & Expertise– Thermodynamics– Separations– Heat Exchange– Fluid Flow– Optimization

− Data Reconciliation− Collaborative Engineering− Control Checkout− Reactors− Intuitive Engineering GUI

Deliver Improved Asset Performance for our CustomersApplied Simulation on Every Engineer’s Desktop

SimSci-Esscor’s Vision

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4

sim4me

design

prod

uct

s

optimizeoperate

Plant Lifecycle Management

sam

ple

appl

icat

ion

sMRA &ROMeo

PowRx

Ethylene

CrudeFCCU

Gas LiftOptimization

ProcessDesign

Flare SystemDesign

Well Design/Nodal Analysis

Oil/GasCrudeFCCU

Ethylene

High FidelityOTS

DecisionSupport

EngineeringStudies

Debottlenecking

Oil/GasCrudeFCCU

HydrocarbonPower

Pulp & Papervert

ical

s

PRO/IIHEXTRANVISUAL FLOWPIPEPHASENETOPT

ROMeoARPMMRA

Connoisseur

DYNSIMOTSFSIM

TACITE

ATI/Hyprotech CANNOT do this easily with their

current architecture!

SIM4ME - Delivering on our Vision

PRO/II Training

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Concept

Basic DesignDetailed Design

PlantDesign

Construction

Controls

OperationCommissioning

Revamp

Steady State Engineering Dbs Dynamic Simulation

Control System

Operator Training

Simulation & Planning

Advanced Control

Online Optimization

SIM4MEApplication During Plant Lifecycle

PRO/II Training

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PRO/II® Process Flowsheet Simulator for Design, Operational Analysis, and Optimization

HEXTRAN® Heat Exchanger Network Simulator for Design, Operational Analysis, and Optimization

DATACON™ Data Reconciliation Program for Heat/Mass/Composition balance on plant data

INPLANT™ Plant Piping and Utility Systems Flow Simulator

VISUAL FLOW™ Flare Network and Regulatory Compliance Simulator

Process Engineering Suite

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PLANT PLANT LIFE LIFE

CYCLECYCLE


PlantDesign

Construction

Controls


Commissioning

Concept

Operation &Troubleshooting

Revamp

PES Features

Enhances productivity in the plant life cycle

PRO/II Training

8The Plant

Visual Flow

CompleteCould be done

Datacon Inplant

MS Office

PRO/II

Hextran

Integration within PES

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History of PRO/IIFirst Generation: 1974– SSI/100 Simulation Program

Second Generation: 1979– Process Simulation Program

Third Generation: 1988– PRO/II Simulation Program– Version 3.30 - Spring of 1993

Forth Generation: 1995– PRO/II with Provision 4.x

Fifth Generation: 1997– PRO/II with Provision 5.x– version 5.61 – March of 2002

Sixth Generation: 2003– Over 40 new features

Seven Generation: 2004– Just released in August 2004

Introduction

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PES Solution Client BenefitsReduced process engineering time & costReduced plant capital costReduced plant lifecycle costs Increased plant operating profits– higher product rates– improved product quality– lower operating costs– more feed flexibility

A valuable tool for experienced process manager and engineers

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Flowsheets FeaturesPRO/II is much better for larger flowsheets– No over-specify flowsheet– Recycles estimates not required– Recycle block not required– More option to define sequence– Easier diagnosis of problems since each specification in

linked to a particular unit operation and color indicates status.

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Distillation FeaturesMultiple column algorithms to model complex columns– IO, Sure, Chemdist, Liquid-Liquid, Electrolytes, Enhanced IO

Multiple methods for generating initial estimated values– Simple, Conventional, Refinery, Chemdist, Electrolytes

Reactive distillation– robust algorithm– derivative data not required

Tray Hydraulic for rating and design– Volve, Sieve, and Cap structured tray– Sulzer structured packing– Norton random packing

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First Createa Library of

Reaction Data

Then SelectReactions

for Each Unit

Reaction OptionEnter reactions in the reaction data sectionIn Reactor units, select which reactions to use

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Reactor TypesGeneral: (no reactor geometry required)– CONVERSION REACTOR (multiple reactions)– EQUILIBRIUM REACTOR (multiple reactions)

Kinetic: (reactor geometry required)– PLUG FLOW REACTOR (PFR)– CONTINUOUS STIRRED TANK REACTOR (CSTR)

GIBBS: (stoichiometry optional)– Free energy minimization– Kinetics not considered

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Optimizer FeaturesOptimize based on an objective functionUtilizing tag data valuesNo needs to have a dynamic calculationAutomatic identification of the best design or operating conditions from a collection of alternativesFrees user from evaluating all possible cases

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User-Added Program FeaturesUAS/PDTS enhancements– additional function calls– additional subroutines– additional simulation database access– full documentation– supported in PROVISION

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Tag Data FeaturesDirectly access plant historical dataRead tag data from a fileRead tag data from server– PI– ODBC– @aGlance/IT– AIM

Write tag data back to a file

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OLE FeaturesOLE/COM Automation Layer– documented access to simulation database for most

data– two way link

simulation data out, design/plant data in

– any OLE compliant applicatione.g. MS Office can use VB or VBA

– used for Zyqad or Icarus interface– examples available at www.simsci.com

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Spreadsheet Tools

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OLE Automation

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D1

V1

X1

1

2

3

4

5

6

7

8

9

10T1

E1

E2

C1

3

4

5

6

7

8

9

100

2

10

3X

11

TURBOEXPANDER PLANT

Feed 100 Range Products 9 11Flowrate 1016700.0000 FT3/HR Flowrate 483.7454 2195.4231 LB-MOL/HRPressure 587.0000 PSIG Pressure 125.0000 161.2292 PSIGTemperature 120.0000 F Temperature 24.0874 157.5738 FComposition Composition

N2 7.9100 N2 0.0000 0.0965C1 73.0500 C1 0.0086 0.8896C2 7.6800 C2 0.3633 0.0137C3 5.6900 C3 0.3141 0.0002IC4 0.9900 IC4 0.0548 0.0000NC4 2.4400 NC4 0.1351 0.0000IC5 0.6900 IC5 0.0382 0.0000NC5 0.8200 NC5 0.0454 0.0000NC6 0.4200 NC6 0.0233 0.0000NC7 0.3100 NC7 0.0172 0.0000

UnitsX1 adiabatic efficiency 80.0000 % 0-100 UnitsX1 outlet pressure 125.0000 PSIG Reboiler duty 2.2889 MM BTU/HRC1 adiabatic efficiency 75.0000 % 0-100 E1 duty 5.2814 MM BTU/HRC1 work from X1 0.9000 0-1 E2 duty 4.9133 MM BTU/HRT1 top pressure 125.0000 PSIG X1 actual work 392.2247 HPT1 C1:C2 ratio bottom 0.0150 0-1 C1 actual work 353.0023 HPE1 HICO 10.0000 FStream 3 temperature -83.9990 F Run Simulation

Operator Interface

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1Build

Flowsheet

2 Check Units

of Measur

e

Simulation in Seven StepsIntroduction

Define Compone

nts

3

4Select Therm

oSuppl

y Strea

m Data

5

Provide Process

Conditions

6

Run & View

Results

7

PRO/II Training

Defining the Defining the ComponentsComponents

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Component Types

Library componentPetroleum componentUser-defined componentSolid componentPolymer componentIonic component

Defining the Components

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Component SelectionDefining the Components

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PRO/II Component LibraryComposite of several databanksDatabank search order– PROCESS (default)– SIMSCI (default)– DIPPR or OLI available as an optional PRO/II add-on

Component selection by list or access namePure component data– Fixed properties– Temperature-dependent properties


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Adding Library ComponentsDefining the Components

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Component Data PrintoutComponent nameComponent type

PROJECT TRAINING PRO/II INPUTPROBLEM COMPONENTS COMPONENT DATA============================================================================

NO. COMPONENT NAME COMP. TYPE PHASE MOL. WEIGHT SPGR --- -------------- ----------- ----------- ----------- ---------- 1 N2 LIBRARY VAP/LIQ 28.013 0.80811 2 C1 LIBRARY VAP/LIQ 16.043 0.30000 3 C2 LIBRARY VAP/LIQ 30.070 0.35640 4 C3 LIBRARY VAP/LIQ 44.097 0.50770

NO. COMPONENT NAME NBP CRIT. TEMP. CRIT. PRES. CRIT. VOLM. F F PSIG GAL/LB-MOL --- -------------- ----------- ----------- ----------- ----------- 1 N2 -320.440 -232.420 477.619 10.7963 2 C1 -258.682 -116.680 652.499 11.8628 3 C2 -127.534 90.140 693.648 17.7343 4 C3 -43.726 206.006 601.652 24.3247

NO. COMPONENT NAME ACEN. FACT. HEAT FORM. G FORM. BTU/LB-MOL BTU/LB-MOL --- -------------- ----------- ----------- ----------- 1 N2 0.04500 0.00 0.00 2 C1 0.01040 -32066.21 -21726.14 3 C2 0.09860 -36120.21 -13810.45 4 C3 0.15290 -44650.04 -10139.64


Phase typeNine fixed properties

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Using DATAPREPMenu-driven DOS interfaceTotal access to PRO/II component databaseAdditional information:– Fixed properties– Data source – Data accuracy– Plots and tables


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Enthalpy Curve for Water from DATAPREP

-500 -250 0 250 500 750-80

0

80

160

240

320(10E+ 2)

Temperature F

ENTH

ALPY

BTU

/lbm

ol Heat of Vaporizat ion at NBP

Sat urat ed Vapor Curve

Ideal Gas Curve

Crit ical Point

Sat urat ed Liquid Curve

Solid CurveHeat of Fusion

at NMP


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Petroleum ComponentsNormal Boiling PointGravity Molecular Weight

At least two of three required


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User-defined ComponentsComponent NameComponent Properties


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Component PropertiesFixed propertiesTemperature-dependent propertiesUser Defined and Refinery Inspection propertiesSolid propertiesPolymer propertiesStructure data


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Component Property Window Defining the Components

Selecting the Selecting the ThermodynamicsThermodynamics

PRO/II Training

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Example: Propane-Propylene SplitterChoice of Thermo strongly effects results!

ThermodynamicSystem

CondenserDuty

Reflux/FeedRatio

Peng-Robinson -59.6 13.1

Grayson-Streed -37.3 8.2

Selecting the Thermodynamics

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Thermodynamic DataRequired for all flowsheetsThermodynamic Property MethodsTransport Property Methods– Required for certain units:

Column DissolverRigorous heat exchanger Depressuring unitPipe Output tables


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Thermodynamic PropertiesK-Values(Mass Balances)

Enthalpies(Heat Balances)

EntropiesDensities


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K-Value Calculation MethodsIdealEquation of StateLiquid ActivityGeneralized CorrelationsSpecial PackagesElectrolytesPolymers


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Selecting the Thermodynamic MethodSelecting the Thermodynamics

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Enabling VLLE Calculations

Default


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ModificationsVery important to choose the correct thermodynamic methodEven more important to insure that binary interaction parameters are available


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Modifications (Cont.)Advanced Equations of State– Model hydrocarbon behavior– Advanced Alpha forms– Advanced mixing rules– Databank of regressed binary interaction

coefficient


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Modifications (Cont.)Liquid Activity Coefficient methods– Model non-ideal behavior– Databank of regressed binaries– Databank of azeotropes– Fill options for binaries


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Modifications (Cont.)Generalized Correlation– Typically designed for a specific application– Do a good job for heavier hydrocarbons


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Modifications (Cont.)Enthalpy, Entropy and Density– Library correlation for enthalpy– No Library correlation for entropy– Library correlation for density– Rackett parameters in Library


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Transport PropertiesViscositiesThermal conductivitiesSurface tensionLiquid diffusivity

4 methods: Pure, Petroleum, Trapp, User-defined


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Calculation with Two Liquid PhasesWater decant option Rigorous VLLE

calculations


V

L = HC + W

W = pure water

V

L1 = HC + W

L2 = W + HC

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Water Decant Option

Vapor

Pure WaterLiquid

Water VaporPressureVLE K-values

Water Solubility


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Rigorous VLLE Calculations

Vapor

Liquid 2Liquid 1

VLE K-valuesVLE K-values

LLE K-values

Must enable two-liquid phase calculations.


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Hydrocarbon SystemsRefining Processes:– Grayson-Streed: Hydrogen rich systems, Crude tower,

Vacuum unit, Coker fractionator, FCC main fractionator

– SRK and PR: Light ends columns, Splitters, Gas recovery plants, Hydrogen rich systems (SRKM)

– SOUR, GPSWATER: Sour water systems

– SRKK, SRKM, SRKS, IGS: Use if H/C solubility in liquid water (VLLE) is important.


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Hydrocarbon SystemsGas Processing:– SRK and PR: All types of processing plants, cryogenic

systems– SRKM, PRM, and SRKS: Systems with water,

methanol, and other polar components– GLYCOL: Dehydration with TEG. Improved for

aromatic emissions. Based on SRKM.– AMINE: Natural gas sweetening.– SRKK, IGS, SRKM, SRKS: Use if light gas solubility in

water (VLLE) is important.


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Online Thermodynamic HelpReference Manual– Detailed technical reference

Application Guidelines– When to use each method


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Chemical Systems: Activity coefficient methods

Non-ideal componentsLow to medium pressuresRely on binary interaction parameters (if missing will be close to Ideal!)Missing parameters estimated from structures, azeotrope composition, mutual solubilities etc.Used with Henry’s Law for non-condensiblesVLLE with some methods


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Chemical Systems: Activity coefficient methods

Two Binary parameters Liquids? in databank?

NRTL Yes Yes

UNIQUAC Yes Yes

WILSON No No

UNIFAC Yes Estimates non-ideality from structure

Other methods - see Reference Manual


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Chemical Systems: Equations of StateSRK-SIMSCI, SRKM, and PRM for polar mixturesSRK-Hexamer for mixtures involving HFCan model high-pressuresAlso rely on binary interaction parametersSome binary parameters in databanks for above methods


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MulticomponentDistillation

MulticomponentMulticomponentDistillationDistillation

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Tray Model

Subscript denotestray number

Tj Pj

Qj

LDj

VDj

Vj yj_

Lj-1 xj-1_

Lj xj_

Vj+1 yj+1_

Fj XF

_

Overbar denotes component vectors: e.g., x = (x1, x2, ...xNC)

_

_

Lj , Vj

Fj

Qj

xj , yj

XF

hj , Hj

Tj , Pj

LDj

VDj

Liquid, vapor flowrate

Feed flowrate

Heater/cooler duty

Liquid, vapor mole frac

Feed mole fractions

Liquid, vapor enthalpies

Temperature, pressure

Liquid Draw rate

Vapor Draw rate

__

Multicomponent Distillation

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Tray NumberingNormally use Theoretical Trays (Stages)Numbered from top downCondenser is Stage 1– Even for subcooled condenser

Reboiler is last stage – Thermosiphon adds 2 stages

Convert packing to stages– Rule of Thumb: 2 to 3 feet of packing per stage


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Tray Efficiency

xA

75% efficient:step 3/4 to

equilibrium curve

yA

xA

100% efficient:step to

equilibrium curve

Murphree Efficiency = 75%


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Other Tray Efficiency ModelsVaporization yi = ciKixi

Equilibrium K’s adjusted towards 1.0Vapor leaving stage not at dew pointCan lead to Mixed Phase Condenser productBetter to use Overall Efficiencies– Theoretical / Actual trays to carry out separation– Use different values in different column zones– Tune from experimental data if possible


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Overall EfficienciesEfficiency increases as components decreaseEfficiency increases as reflux increasesResults can be very sensitive to number of trays

Number of Stages

Low reflux:number of stagesis less important

High reflux: number ofstages stronglyaffects results

Ref

lux


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Typical Overall Tray EfficienciesSERVICE PERCENT

Simple Absorbers/StrippersReboiled Absorbers/StrippersDeethanizersDepropanizersDebutanizersDeisobutanizers (Refluxed)

20-3040-5060-6565-7580-9085-95

SplittersC2, C2-C3, C3-C4抯 or C5抯

85-9595-10090-100

Notes:1) Assume 65-75% for most columns with reboilers and condensers.2) At low reflux, split insensitive to number of trays in the model.3) Pumparounds usually modeled as 2 stages.


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All Column Algorithms are IterativeWant to solve f(x) = 0Generate a sequence of estimates of solution:

x0, x1, x2, ... xN

Equations are satisfied when x stops changing:| xN - xN-1 | < 0.00001

xN is regarded as the solution


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Convergence of Newton’s method ...

x x fx

f xn n

x

n

n

+

−

= −⎡

⎣⎢

⎤

⎦⎥

11

∂∂

( )

Solution

f(X)

0

Xx1 x2 x*

Good initial guessleads to solution

x0


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Convergence is not guaranteed!

f(x)

x* X

0


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f(x)

x* X

0

Periodic


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X

Bad guessconverges...

But betterguess fails!

f(x)

x*

0


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Available Distillation Algorithms in PRO/II


Inside Out (I/O)

Chemdist

Sure

Liquid-liquid

Enhanced I/O

PRO/II Training

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Inside Out (I/O) Algorithm– Relatively ideal thermodynamics including hydrocarbon

with water decant– Incorporates sidestrippers into column -- No recycle!– Thermosiphon reboilers– Flash zone model– Very forgiving of bad initial estimates– Fast!– No VLLE


PRO/II Training

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I/O ColumnFeatures

2 phasecondenser +water decant

N-1

21

Side Columns

Side Streams

Heater/Cooler

Heat Source/Sink

Multiple Feeds

Kettle andThermosiphon

Reboilers

Pumparounds

N


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I/O Algorithm Uses Nested LoopsInner Loop– Simple thermo model (Fast)– Approximate Matrix Inversion (Fast)– Converge enthalpy balance and performance specs

Outer Loop– Updates, checks thermo using rigorous model (Slow)– Checks Bubble Point Criteria– If thermo changing or not bubble point, goto Inner Loop


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I/O Algorithm

x, T, L, V, Q ...

1) Calculate rigorous K(x,T,P), H(x,T,P).2) If K and H differ significantly from

previous iterate, repeat from beginning.Done, solution is: x, T, L, V,

Q ...

Inner Loop

Out

er L

oop

Approx. Thermo.Model

ConvergenceCheck

Iteratively solve the column equations using approximate thermo, K*(T,P) and H*(T,P).

Prepare approximate thermo models for K*(K) and H*L(HL), and H*V(HV).


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Initial Estimate Generator (IEG)Generates “good” initial estimates for all column variables

P1 P2PN LN x* y* T*

P V* L*

Q*R Q*

C

x0 y0 T0

P V0 L0

Q0R Q0

C

IEG Solver

You supply columnspecs and guessesfor a few variables...

IEG calculatesinitial estimates for

all column variables...

Solver (I/O, Chemdist)converges on solution

ColumnSpec’s


PRO/II Training

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Four Types of IEGSIMPLE (default): Simple columns– Only choice for liquid-liquid extraction

CONVENTIONAL: Works well with most columns– Based on shortcut methods– Strongly dependent on your product rate estimates

REFINING: Complex refinery columns (e.g., Crude, Vacuum, FCC main fractionator, Coker)

CHEMICAL: Nonideal thermodynamics (e.g., azeotropicand extractive distillation). Can be slow.


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Specifications and VariablesSpecifications are constraints to be met by the column

Variables are calculated to meet specifications.

Column always balances equations and unknowns

To impose a specification, you must add a variable, otherwise equations and unknowns don’t balance.

Example: Impose two product specifications by declaring reboiler & condenser duties as variables.


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Column Status at InitializationFixed quantities remain at their current values unless you declare them as variables.

If no specs/variables provided, default status used:


QUANTITY STATUS

Overhead and Bottoms RatesSide Draw RatesDutiesFeed RatesTray TemperaturesTray PressuresVapor and Liquid RatesProduct Properties (e.g. Viscosity)Tray Vapor or Liquid Properties

CalculatedFixedFixedFixed

CalculatedFixed

CalculatedCalculatedCalculated

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Improper Specifications 0% methane in crude column bottoms– Infinitely many solutions

300 lb-mole/hr propylene in overhead– No solutions if column feed only 250 mol/hr propylene

98% ethanol product– No solutions if Water-Ethanol Azeotrope present


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What is alpha (α)?Length of correction: Xn+1 = Xn + αn δn 0< |α| < 1

Decrease α if full step increases error

Unknown 2

Unknown 1

X1

X3

X2

Solution

δ3

α1 = .7

α2 = 1

Reject: full stepincreases error


PRO/II Training

80

You Can Help I/O by Using DampingDamping reduces iteration step and suppresses oscillationConventional columns: DAMP = 1.0 (default)Columns with steam: DAMP = 0.6 - 0.8– Crude, Vacuum, FCC Main Fractionator

Less-ideal: DAMP = 0.2 - 0.6– Increase number of allowed iterations– If oscillations persist, use Chemdist


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Reboiler ModelsMost reboilers can be simulated as:– Kettle– Thermosiphon with Baffles– Thermosiphon without Baffles


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N-1Bottom Tray

NReboilerBTMS Q

VN-1 LN-2

VN LN-1

BTMS

LN-1

VN

Kettle Reboilers

Vapor in Equilibriumwith Bottoms


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BTMS

LN-1

VN

BottomSump Reboiler

Sump

Baffle

LN-1

VN

BTMS

Bottom Sump

Single Pass (Once Through) Thermosiphon

Equivalent to a Kettle Reboiler because Bottoms is in Equilibrium with VN


PRO/II Training

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N-2Bottom Tray

N-1Combined Sump

NReboiler

BTMS

Q

VN-1 LN-2

RL RF

R V

LN-2

VN-1R V

RL

RFBTMS

Combined Sump

Circulating Thermosiphon Adds 2 Stages

Simulate as TS without Baffles


PRO/II Training

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BTMS

VN-1

BottomSump

RF

RV

RL

LN-2

ReboilerSump

N-2Bottom Tray

N-1Reboiler Sump

NReboiler

BTMS

Q

VN-1 LN-2

RL RF

R V

Circulating Thermosiphonä Simulate as TS without baffle


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BTMS RL

RF

Lo

RV

N-2Bottom Tray

N-1Reboiler Sump

NReboiler

BottomSump

Q

VN-1 LN-2

BTMS

LN-2

VN-1

BottomSump Reboiler

Sump

RF

RV

RL

LO

Preferential Thermosiphonä Simulate as TS with baffle


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Tips...Start simple– Converge water decant thermo before trying VLLE– Converge side draws before trying sidestrippers– Test pumparound duties with side coolers– Remove coolers from pumparounds so all cooling is

taken at condenser. Then add duties to pumparound.

Recovery usually safer than composition specsSpec reflux ratio and product rateSpec reflux rate and component recovery


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Tips...If Water condenses in column:– Increase temperature estimates to keep water in vapor – Reduce steam flow:

0.1 lb/Gallon bottoms in main column0.1--0.2 lb/Gallon sidestripper product

Pumparounds solve best when you:– Fix rate and duty, calculate return temperature


PRO/II Training

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Tips...

FZ


Excess cooling cause drying above PA return– Remedy: Specify liquid

flow above return tray and calculate pumparound duty

Eliminate loops whenever possible– Break thermal recycles

with reference stream– Simulate furnace as

column tray heater

Specify TrayLiquid rate

Declare Dutyas a Variable

PRO/II Training

90

Tips...Don’t believe your answers until you:– Verify thermodynamic method with expert– Rerun with tighter column and loop tolerances– Rerun with more pseudocomponents– Rerun with different assay characterization method– Check sensitivity to estimated parameters, i.e.,

number of traysExample: Add a stage to column. If results change drastically, then model is very sensitive to this parameter.Assess if this is physical reality or model defect.


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91

Distillation Algorithm Selection

• Generality: complex column and thermo

• Total pumparounds• VLWE on any tray• Water draw any tray

• Slow• Sensitive to initial guesses

• Free water or water draw on trays other than condenser

• Total pumparounds or vapor bypass

Inside/Out (I/O) CHEMDIST

• Very fast• Insensitive to initial estimates

• Thermo non-ideality • NO VLLE capability (VLWE at condenser)

• Hydrocarbons• EOS & slightly non-ideal LACT thermo

• Interlinked columns

• Side and main columns solved simultaneously

• Reactive distillation• VLLE on any tray

• Highly non-idealsystems

• No pumparounds• Side columns solved as recycles

• Non-ideal systems• Mechanically simple columns

• VLLE within column

Unique Features

Strengths

Limitations

Applicability

SURE


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Distillation Algorithm SelectionLiquid-Liquid Enhanced I/O

• Thermo must be a liquid activity method

• LLE on each stage • Total draws and waterdecants off trays

• Converges when zero flowrates on trays

• IEG does not work for all cases

• Same as I/O

Unique Features

Strengths

Limitations

Applicability

• Perform liquid-liquid extraction

• Liquid-liquid extraction columns


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FlowsheetFlowsheetOptimizationOptimization

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Optimization allows...Automatic identification of the best design or operating conditions from a collection of alternativesFrees you from evaluating all possible cases

Flowsheet Optimization

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95

Setting Up the OptimizerObjective function– A result calculated in PRO/II (duty, product recovery,...)– Usually evaluated with a calculator unit operation– Minimize or maximize this value (i.e., maximize profit)– Include all relevant costs

Optimization variables– A fixed input parameter with defined MIN, MAX values


PRO/II Training

96

Setting Up the OptimizerProcess constraints (inequality)– Limits on flowsheet values which cannot be violated– Physical limitations on equipment

Constrain compressor operation to prevent surgingConstrain column tray flows to prevent flooding

Process specifications (equality)– Additional criteria imposed on optimum solution

Total cooling water flowrate = 100Kerosene product rate = 10000


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One Variable OptimizationValue of OVHD [$/lb-mole] is proportional to the square of its mole fraction C1 and C2What temperature maximizes profit from OVHD?Objective: maximize [ OVHD (YC1 + YC2)2 ]

H2O; C1-C6-60ºF900 psia

T=?30 psia

OVHD


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One Variable Optimization

0

200

400

600

800

1000

-150 -110 -50 10 70

Flash TemperatureOptimization Variable

Flowrate of C1 and C2 times Purity of C1 and C2

OptimalTemperature

ObjectiveFunction

110


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Multivariable OptimizationWhat temperature and pressure maximize profit from OVHD?Objective: maximize [ OVHD (YC1 + YC2)2 ]


T=?P=?

OVHD


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Multivariable Optimization

-150

-110

-70

-30 10

50 90

5

15

25

35

0

200

400

600

800

1000

1200

1400

Temperature

ObjectiveFunction

Maximum

Pressure


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Optimization with ConstraintsVary temperature and pressure to maximize flowrate of C1 and C2 in OVHD The OVHD purity must be at least 90%


T=?P=?

OVHD YC1 + YC2 > 0.9


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Optimization with Constraints

Flash Pressure

OptimizationVariable

Flash TemperatureOptimization Variable

-150 -110 -70 -30 10 50 905

15

25

35

Constraint

Optimum(1411)

0

360

650

860

1147


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Analyzing your Results: Shadow Prices


Indicates the potential benefit of relaxing a limit, specification, or constraint– Positive: Increasing the value increases the

objective function

– Negative: Increasing the value decreases the objective function

– Zero: Constraints and/or limits on optimization variables (MINI, MAXI) are not active

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Reading the Optimizer SummaryBest results– Objective Function– Values of Variables

Optimizer history at each cycle– Values for objective function and variables– Derivatives (Objective Function/Variable)– Shadow Prices

Convergence plots in output report


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- SHADOW PRICES ----CYCLE 1 5 BEST - 6 7 8---------- ----------- ----------- ----------- ----------- -----------VARY 1 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00VARY 2 0.0000E+00 -3.1750E+01 -3.1430E+01 -3.1428E+01 -3.1116E+01CNSTR 1 -2.4824E+03 -1.4458E+03 -1.4146E+03 -1.4149E+03 -1.4338E+03

** BEST OBJECTIVE FUNCTION = 1.41158E+03 AT CYCLE NUMBER 6

VARY --------- VARIABLE ----------INDEX INITIAL VALUE OPTIMUM VALUE----- ------------- ------------- 1 1.00000E+01 -4.12426E+01 2 3.00000E+01 5.00000E+00

---- VALUES ----CYCLE 1 5 BEST - 6 7 8---------- ----------- ----------- ----------- ----------- -----------VARY 1 1.0000E+01 -3.9238E+01 -4.1243E+01 -4.1439E+01 -4.1454E+01VARY 2 3.0000E+01 5.0000E+00 5.0000E+00 5.0000E+00 5.0000E+00CNSTR 1 9.2355E-01 8.9303E-01 8.9935E-01 8.9995E-01 9.0000E-01

REL ERR 0.00E+00 -7.74E-03 0.00E+00 0.00E+00 0.00E+00SUM SQ ERR 0.0000E+00 5.9977E-05 0.0000E+00 0.0000E+00 0.0000E+00OBJECTIVE 9.5967E+02 1.4210E+03 1.4116E+03 1.4106E+03 1.4106E+03

Optimizer OutputFlowsheet Optimization

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Shadow Price Examples1) Where should you send any extra steam?

ProcessStm1

Stm2

Stm3Profit

2) Which heat exchanger should you clean first?

1 2 3 4GasT=200ºF

GasT=10ºF


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Solution Technique: Successive Quadratic

Programming (SQP)Initialization

Second order method(with derivatives) to

determine search direction

First order method(no derivatives) to check

progress towards the solution

Convergence

QuadraticProgrammingSub problem

Line Search


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ConvergenceConverging loops requires more interventionDerivative step sizes are very importantTolerances of units in loops should be lowered


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ConvergenceSpecifications and constraints are satisfied and– Scaled error below tolerance (10-7) or– Variables stop changing (tol=0.1%) or– Objective function stops changing (tol=0.5%)

Warning: Optimum is T=100, but any guess between 50 and 150 satisfies objective test

150

1000

1005

50 T (ºC)

Objective Function

995

Tn

100


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Convergence: Relative TolerancesExample: want L = 0.99 FWhich specification should you use?– Form 1: L/F = 0.99– Form 2: V/F = 0.01

PRO/II converges this to a relative tolerance εForm 1:– Converges when: | (L/F - 0.99) / 0.99 | < ε– so L = 0.99F ± 0.99F ε

LF

V


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Convergence: Relative TolerancesForm 2:– Converges when: | (V/F - 0.01) / 0.01 | < ε– But, V=F-L : | (1-L/F - 0.01) / 0.01 | < ε– so L = 0.99F ± 0.01F ε

If ε=0.01 (the default) and F=1000– Form 1: L=990 ± 9.9– Form 2: L=990 ± 0.1

Form 2 is much more accurate!To use Form 2, tighten relative tolerance


PRO/II Training

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Convergence: Compounding of ErrorsExample: specify each flash as Ln = 1/2 Ln-1

Exact solution: LN = (1/2)N L0

If each flash specification relative tolerance = εThen worst case LN relative error ~ NεExample: N=5, ε=1%, then L5 = L0/32 ± 5%

1 L1 2 L2 3 L3 N LNLN-1L0


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Flowsheet TolerancesOptimization requires flowsheets to be solved more accurately than for simulation– Tighten tolerances (columns, recycle loops, controllers)– Choose appropriate finite difference steps– Tighter tolerances allow smaller finite difference

steps to be used which is more efficientInaccurate flowsheet information may cause optimizer to fail or converge prematurely


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Finite Difference DerivativedF(xn)/dx = [F(xn +Δx) - F(xn)] / Δx

xn+Δx

F(x) Largest slope

Smallest slope

Error Bar

xn


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Finite Difference DerivativeSmaller step size can worsen derivatives

xn+Δx

F(x)

Calculated slopecan be negative!

xn


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Finite Difference Derivative

xn+Δx

F(x)

xn

Smaller error bars improve derivative calculations


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RecommendationsSolve base case separately - Check resultsTighten flowsheet tolerances for improved accuracyCarefully select bounds and constraints to ensure physically well-defined flowsheetSelect appropriate convergence criteria


PRO/II Training

QuestionsQuestionsQuestions

Getting Started

ECUST PROII Advanced Training

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