preFEED

Solutions for R&D to Design
KIChE Fall Meeting

Industrial Practice for Process Operation and R&D – Present and Future

Importance of Modeling & Its TechniqueOctober 2006
Dr. Yoshio Kumagae, preFEED Corporation
Solutions for R&D to Design1

preFEEDAgenda
Why Modeling ?
Modeling as Current Practice
Practices for Better Modeling
１．Reduce the Number of Parameters
２．Two Things before Numerical Calculation
Recommendations
2
Solutions for R&D to Design

preFEEDWhy Modeling ?

3
Solutions for R&D to Design

preFEEDEthylene Production, 1996
(19MM ton)

Ethylene Production, 2008
(40MM ton, expected)

Korea

Korea

TaiwanChina

Taiwan
China

ASEAN

ASEAN

IndiaIndiaJapanJapan

Modeling is the key to differentiation.
4
Solutions for R&D to Design

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Modeling As Current Practice5
Solutions for R&D to Design

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Unit Operation Model in 1970’s
Binary, Mass Balance only,
Graphical Methods
1990’sAcetone-water VLE

Multi-component, stage-to-stage
calculation, Heat & Mass Balance,
3-phase distillation

6
Solutions for R&D to Design

1preFEED
0.8

by Margules eq.
m easured

VLE Model in 1970’s

y0.60.4

Empirical Activity
Coefficient Model0.2000.20.40.60.81ln γ 1 = A' x 22 + B' x 23 + C ' x 24x

38ln γ 2 = ( A'+ B'+2C ' ) x12 − ( B'+ C ' ) x13 + C ' x1423A' = −0.553, B' = −0.276, C ' = 0

Acetone – Chloroform VLE
360

P-y
P-x
P-y, measured
P-x, measured

340

P

320

Margules’ equation

300
280
260
240
00.2

Solutions for R&D to Design

0.40.6x, y0.817

preFEED1990’sRigorousness based onsolution theory

UNIQUAC

8
Solutions for R&D to DesignpreFEED

Modeling As Current Practice

Benefit:
Rigorousness to represent data
Shortcomings:
1. Too many parameters
2. Numerical calculation oriented

9
Solutions for R&D to Design

preFEEDPractices for Better Modeling
１．Reduce the Number of Parameters
２．Two Things before Numerical Calculation

10Solutions for R&D to Design

preFEED

1. Reduce the Number of Parameters
Antoine equation

11
Solutions for R&D to DesignVapor Pressure Data with Errors

preFEEDpress [mmHg]

10000

1000

100
measured data

10-20
Solutions for R&D to Design

02040temp [C]

6080
12

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Correlation Equations
Use A & B (C=0) forcorrelation

Extended Antoine(AspenPlus)

Use A, B, C, D & E (F=G=0)
for correlation

13Solutions for R&D to DesignpreFEED

2-parameter Antoine: log10P=A-B/T

press [mmHg]

10000

1000

100

measured data
2-parameter eq.

10-20
Solutions for R&D to Design

02040

temp [C]6080
14

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Extended Antoine： loge(P)=A-B/(C+T)+D*T+E*loge(T)press [mmHg]

10000

1000

100

measured data
5-parameter eq.
2-parameter eq.

10-20
Solutions for R&D to Design

02040temp [C]

6080
15

Extended Antoine: Unreliable Behavior outsidecorrelation range

preFEEDpress [mmHg]

10000010000
1000
measured data

1005-parameter eq.
2-parameter eq.

10-50050

100

150200temp [C]
16Solutions for R&D to Design

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1. Reduce the Number of Parameters
Model of Vapor Liquid Equilibrium

17Solutions for R&D to Design1.0
preFEED

0.8

Acetone – Chloroform VLE

0.4• Difficult to correlate with
empirical model such as
Margules’ eq.

y0.6

0.2

acetone - chloroform

0.000.2

0.4

0.81• UNIQUAC was applied
successfully to represent
the data.

x1.2
activity coefficient

0.6

1.0
0.80.6acetonechloroform

0.40.2acetone-chloroform VLE

0.00.00.2

Solutions for R&D to Design

0.4

0.6
x10.8

1.018

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Local-composition Model (Wilson, NRTL, UNIQUAC etc.)

Mol frac.: y1 (acetone), y2 (chloroform)

uniform
Not uniform

Mol frac.: x1 (acetone), x2 (chloroform)
19
Solutions for R&D to Design

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Local-composition Model (Wilson, NRTL, UNIQUAC etc.)

Mol frac.: y1 (acetone), y2 (chloroform)

Non-ideality of solution attributed todifference of local composition
around molecules

Mol frac.: x1 (acetone), x2 (chloroform)
20
Solutions for R&D to Design

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Alternative Approach: Chemical Theory Model
Mol frac.: y1 (acetone), y2 (chloroform)

Acetone + chloroform ÅÆ associatedMol frac.: e1 (acetone), e2 (chloroform), e3 (associated)21
Solutions for R&D to DesignChemical Theory Model

preFEEDMol frac.: y1 (acetone), y2 (chloroform)

Considering all true species resulting
from association allows us to model
the system as ideal system.
Acetone + chloroform ÅÆ associatedMol frac.: e1 (acetone), e2 (chloroform), e3 (associated)22
Solutions for R&D to Design

P*y1=P10*e1
preFEEDP*y2=P20*e2
P*y3=P30*e3
e1+e2+e3=1
y1+y2+y3=1
K=e3/(e1*e2)

Raoult’s Law
Sum ofcompositions=1
association
A+BÅÆC

P10=10^(7.23157-1277.03/(t+237.22))
P20=10^(6.9371-1171.2/(t+226.99))
P30=0
Associated being
K=5
non-volatile
t=35.17

e1e2

e3

g.c.

x1x2

We are more interested in xi, rather than ei.
x1=(e1+1*e3)/(e1+e2+2*e3)
x1=0.2
Solutions for R&D to Design

Conversion of true mol. frac.
to apparent mol frac. 23

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1.0

1.0

y10.8
0.6

0.8

0.4

K=00.6

0.2

y0.0
0.0

0.2

0.4

0.6

0.8

1.0m easured
K=0
K=1
K=1.5
K=2
K=5

0.4

x1

0.2

1.0

y1

0.8

0.0

0.6

0.0

0.4

0.2

0.4

0.6

0.8

1.0x

K=1.5

0.2
0.0
0.0

0.2

0.4

0.6

0.8

1.0x1

24
Solutions for R&D to Design

1.0
K=1.5

preFEED0.8m easured• K=1.5 gives goodcorrelation to VLE
data.

y0.6
0.4
0.20.000.2

0.4

0.6

0.81x

P

360
340

K=1.5
P-y, measured

320P-x, measured

300
280
260
240
00.2

0.4

0.6x, ySolutions for R&D to Design

0.8

1• Pxy is reasonably
correlated; better thanMargules’ eq.
• One-adjustableparameter (K) withchemical meaning ismore manageable than
UNIQUAC.
25

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2. Two Things before Numerical
Calculation

26
Solutions for R&D to Design

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Consider following reactions:
A + B Æ C (desired product)
B + B Æ D (impurity)
We do not know the rate constants yet.

Can we consider reaction process tomaximize C and minimize D ?
27
Solutions for R&D to Design

1. Numerical Approach

preFEED

Assume following:• k1 & k2• CSTR (continuous process) & number of stages• A/B molar ratio at feed
• conversion of A to calculate residence time
1.0

A trial simulation was made.

[mol/l]

0.8
1:A

0.6

2:B
3:C

0.4

4:D

Should we vary k1, k2, n,
molar ratio, A-conversion

0.2

etc. to consider process

0.0

design?
051015residence time

20

25

We seem to have too many28Solutions for R&D to Design

assumptions….

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2. Analytical Approach before Numerical Approachk1
A + B ⎯⎯→C2k 2 B
dB − k1 AB − 2k 2 B 2= 1+=− k1 AB
dAk1 Ak2
B + B ⎯⎯→DdA= −k1 ABdt
dB
= −k1 AB − 2k 2 B 2dt

BA2 k2−k1−− B0 A0Solutions for R&D to Design

2 k2
k1

dB 2k 2 B∴−= 1..(linear..differential..eq.)dA k1 A

We now understand that k1/k2
ratio determines the reaction
performance.

⎛1⎜A=⎜2k 2−+1⎝k12 k2−+1k1−− A02 k2k1+129⎞⎟⎟⎠

preFEED

3. Consider the equations before solving them

k1A + B ⎯⎯→Ck2
B + B ⎯⎯→DdA= −k1 ABdt
dB
= −k1 AB − 2k 2 B 2
dt

dC= k1 ABdt
dD= k2 B 2dt
dC k1 AB k1 A==2dD k 2 B
k2 B

What is required to maximize C/D?
Æ A/B must be maximized (B to be minimized)
Then, B must be added by small portions.
Our understanding is much better than before !

Solutions for R&D to Design30

preFEED

Industrial Example: Alkylation

parafin + olefin → productolefin + olefin → byproductWe cannot apply
A+BÆC andB+BÆD to thisprocess rigorously,
due to gas
absorption step.
However, theinterpretation of
approximate
equations can givethe right answer“Unit Porcesses in Organic Synthesis” (Groggins, p834) for conceptual
31
design.
Solutions for R&D to Design

preFEED

Recommendations

32
Solutions for R&D to Design

preFEED"If the only tool you have is a hammer,

you will treat every problem as a nail."
But simulator is not the only tool you have.
33
Solutions for R&D to Design

Use appropriate methods

preFEEDExperimental
WorkSimulatorYour own modeling

Equation solvers
can help you model
various problems.
34

Solutions for R&D to Design

P*y1=P10*e1
preFEEDP*y2=P20*e2
Solving these equations
P*y3=P30*e3
are not easy with Excel.
e1+e2+e3=1
BASIC is time consuming.
y1+y2+y3=1
K=e3/(e1*e2)
P10=10^(7.23157-1277.03/(t+237.22))
P20=10^(6.9371-1171.2/(t+226.99))
P30=0Equation Solver can help
K=5you.
t=35.17x1=(e1+1*e3)/(e1+e2+2*e3)
x1=0.2
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Solutions for R&D to Design

Solutions for R&D to Design
preFEED

Thank you for your attention !
PreFEED Corporation provide(1) Advanced Chemical Engineering Training (Data Analysis; Phase
Equilibrium; Batch vs. Continuous; Modeling; Rule-Of-Thumb)(2) Modeling Consultancy
Solutions for R&D to Design(3) Support to Equation Solver36