Department of Chemical Engineering, Budapest University of Technology and Economics, H-1521 Budapest, Hungary Research activities CAPE-Forum, Veszprem,

Department of Chemical Engineering, Budapest University of Technology and Economics, H-1521

Budapest, Hungary

Research activities

CAPE-Forum, Veszprem, 2004

• DISTILLATION AND ABSORPTION• Determination of Vapour-Liquid Equilibria and design of Packed Columns.• Development on distillation and absorption technologies• Modelling and calculation of thermodynamic properties• Modelling of batch and continuous countercurrent separation processes

• EXTRACTION AND LEACHING• Kinetics of Soxhlet-type and Supercritical Solid-Liquid Extraction of Natural

Products. Mathematical modelling and optimization of the process.• Supercritical fluid extraction equipment and R&D capabilities

• REACTIONS• Mathematical modelling of residence time distribution and chemical reactions

• MIXING OF LIQUIDS

• PROCESS DESIGN AND INTEGRATION

• Feasibility of distillation for non/ideal systems• Hybrid separation systems• Reactive distillation• Design of Energy Efficient Distillation Processes• Energy integrated distillation system design enhanced by heat

pumping and dividing wall columns• Energy recovery systems• A global approach to the synthesis and preliminary design of• integrated total flow-sheets• Process Integration in Refineries for Energy and Environmental

Management

• CONTROL AND OPERABILITY• Assessing plant operability during process design• Transformation of Distillation Control Structures• Control of units in recycle

• ENVIRONMENTALS• Waste reduction in the Chemical Industry

• CLEAN TECHNOLOGIES• Membrane separations• Cleaning of waste water with physico-chemical tools.• Solvent recovery• Synthesis of mass exchange networks with mixed integer

nonlinear programming • Economic and controllability study of energy integrated separation

schemes• Process synthesis of chemical plants

Department of Chemical Engineering, Budapest University of Technology and Economics, H-1521 Budapest, Hungary

Selected topics of our CAPE activities:Analysis of energy integrated separations

and Synthesis of mass exchange networks

Mizsey, P., Z. Szitkai, Z. Fonyo

CAPE Forum 2004Challenges for East-West European Cooperation in

Process Modelling, Control, Synthesis and Optimization13-14 February 2004, Veszprém, Hungary

• Posters:

Integrated process design

• Challenge in chemical engineering

• Economical and environmental aspects

• Heat integration (HEN) & mass integration (MEN)

• Several synthesis strategies

• The design needs CAPE

Analysis of energy integrated separations(distillation based)

Budapest University of Technology and EconomicsDepartment of Chemical Engineering



Classical distillation schemes for ternary mixture

Col.1ABC

Col.2

A B

C

BC

L1 D1 L2 D2

Q2

B2

Figure 1. Direct sequence (D)

Col.1

ABC

Col.2

A

BC

AB

Figure 2. Indirect sequence (I)

Direct sequence

Indirect sequence

Base case

for comparison

Heat integration

Forward heat integrationdirect sequence (DQF)

Backward heat integrationdirect sequence (DQB)

Col.1`ABC

Col.2

A B

C

BC

L1 D1 L2 D2

Q2

B2

Figure 3. Direct sequence withforward heat integration (DQF)

Col.1

ABCCol.2

A B

CBC

L1 D1 L2 D2

Q2

B2

R1=L1/D1

V2

Thermocoupling, Petlyuk column or dividing wall column (SP)

Col.1Col.2

ABC

A

B

C

V12

V21

L21

L12

S

Q

B

L D

V

R=L/D

SR

Sloppy separation sequences

Col.1

ABC

Col.2

A

B

C

AB

BC

B

L D

S

Q

Forward heat integration (SQF)

Col.1

ABC

Col.2

A

B

C

AB

BC

L D

S

Q

B

Sloppy separation sequence, backward heat integration (SQB)

Mixture: ethanoln-propanoln-butanol

Equimolar feed composition (0.333, 0.333, 0,333)

Product purity specification: 99 m%

Case study

-20

-10

0

10

20

30

40%

D base case

I

DQF DQB SP SQF SQB

Comparison of TAC savings (%)

Controllability study

•steady state indices: Niederlinski index, Morari index, condition number, relative gain array

•Selection of controlled variables & manipulated variables,

•degrees of freedom analysis

•dynamic evaluation: open-loop & closed-loop

Studied Schemes NI MRI CN 11 22 33

D-(D1-L2-B2) 1.137 0.099 8.890 1.000 0.880 0.880

D-(L1-D2-Q2) 1.995 0.065 32.113 1.000 0.500 0.500

D-(L1-D2-B2) 1.865 0.234 4.934 0.580 0.540 0.920

DQF-(D1-L2-B2) 1.136 0.024 36.320 1.000 0.880 0.880

DQF-(L1-D2-Q2) 1.890 0.033 21.290 1.000 0.530 0.530

DQF-(L1-D2-B2) 1.678 0.226 5.240 0.586 0.595 1.020

DQB-(D1-L2-B2) 1.093 0.023 39.660 1.000 0.910 0.910

DQB-(L1-D2-Q2) 2.283 0.040 18.110 1.000 0.440 0.440

DQB-(L1-D2-B2) 1.540 0.246 5.040 0.647 0.645 1.000

SP-(D-S-Q) 3.515 0.182 6.890 1.000 0.320 0.280

SP-(L-S-B) 7.438 0.089 14.380 0.130 0.570 0.990

SQF-(D-S-Q) 6.470 0.010 137.400 1.000 0.250 0.150

SQF-(L-S-B) 4.030 0.008 158.100 0.250 0.250 0.998

SQB-(D-S-Q) 5.080 0.038 33.310 0.997 0.470 0.196

SQB-(L-S-B) 1.287 0.022 64.388 0.770 0.827 1.000

Steady state controllability indices

• base case (D) and heat-integrated schemes (DQF and DQB) show less interactions,

• (D1-L2-B2) manipulated set proves to be better than (L1-D2-Q2) and (L1-D2-B2) for D, DQF and DQB

Evaluation of steady state indices

• serious interactions can be expected for the sloppy schemes (SQF & SQB) and for the Petlyuk column (SP)

Dynamic simulations

Open composition control loops:

• quite similar dynamic behaviour but

• sloppy backward heat integrated (SQB) is the slowest scheme

0.975

0.980

0.985

0.990

0.995

0 10 20 30 40 50 60 70

Time (unit)

Pro

duct

mol

e fr

actio

n

99.5

100.5

101.5

102.5

103.5

104.5

Fee

d ra

te (

kmol

/hr)

Ethanol (A)Propanol (B)Butanol (C)

A

B

C

Feed rate disturbance

Open loop transient behaviour of Petlyuk column for feed rate disturbance

Petlyuk column, open loop, feed rate

0.977

0.981

0.985

0.989

0.993

0 10 20 30 40 50 60 70 80 90

Time (unit)

Pro

duct

mol

e fr

actio

n

99.5

100.5

101.5

102.5

103.5

104.5

105.5

Fee

d ra

te (

kmol

/h)


A

B

C


Open loop transient behaviour of DQB scheme for feed rate disturbance

Heat integrated (DQB) column, open loop, feed rate

Evaluation of closed composition control loops:

overshoot, settling time, and their product are evaluated

0.9897

0.9898

0.9899

0.9900

0.9901

0.9902

0 5 10 15 20 25 30 35 40

Time (unit)

Prod

uct m

ole

frac

tion

99

102

105

108

Feed

rate

(km

ol/h

r)

Ethanol(A)Propanol(B)Butanol(C)


Closed-loop transient behaviour of Petlyuk column for feed rate disturbance(L-S-B )

Petlyuk column, closed loop (L-S-B), feed rate

0.9895

0.9898

0.9900

0.9903

0 5 10 15 20 25 30 35 40 45 50 55

Time (unit)

Pro

duct

mol

e fr

actio

n

99.5

101.5

103.5

105.5

Fee

d ra

te (

kmol

/h)



Closed-loop transient behaviour of DQB scheme for feed rate disturbance(D1-L2-B2 )

Heat integrated (DQB) column, closed loop (D-L-B), feed rate

Closed loop dynamic simulations

•Simple energy integration (heat integration) doesn’t influence dynamic behaviour compared to the non-integrated base case

•The cases, where material and energy flows (energy integration) go into the same direction (DQF, SQF), are better than the opposite

•more complicated systems: higher detuning factor is needed due to stronger interactions (they became slower in closed loop)

Conclusions

•with energy integration about 35% TAC saving can be realised

•simple heat integration shows the best economic and controllability features

•sloppy schemes show good economic features but the selection is made according to their different controllability features (SQF,SQB)

•example also for the complexity of the process design: economic and controllability features are to be simultaneously handled

New directions: control of units in recycle

Example:

Water C2

IPAC

D2

B2

C3

ETAC(MEK)

B3

D3

ETOH95 w%

H2O

Feedmix

C1F1

W1

D1F2

Group 2

Synthesis of Mass Exchange NetworksUsing Mathematical Programming

Budapest University of Technology and EconomicsDepartment of Chemical Engineering



Outline

I. Mass Exchange Network Synthesis (MENS)

A Extension of the MINLP model of Papalexandri et al. (1994)

B Comparison of the advanced pinch method of Hallale and Fraser (2000) and the extended model of Papalexandri et al.

C New, fairly linear MINLP model for MENS

Approach:Mixed Integer Nonlinear Programming (MINLP)optimisation software: GAMS / DICOPT

II. Rigorous MINLP model for the design ofdistillation-pervaporation systems

III. Rigorous MINLP model for thedesign of wastewater strippers

I. Mass Exchange Network SynthesisEl-Halwagi and Manousiouthakis, AIChE Journal, Vol 35, No.8, pp. 1233-1244

21

NR

ysi

2

NS=NSE+NSP

yti

xsj

xtj

1

RICH

STR

EAM

S

LEAN STREAMS

MASS EXCHANGENETWORK

. . .

.

.

.

Gi

yi=f(xj)

Mass integration for the analogy of the concept of heat integration. Absorber, extractor etc. network synthesis

(MSAs)

The synthesis task:Stream data + equipment data +equilibrium data + costing

Network structurelean stream flow ratesmin (Total Annual Cost, TAC)

Previous work:early pinch methods (no supertargeting)Water pinch: Wang & Smith (1994, 1995), Kuo & Smith (1998)El-Halwagi & Manousiouthakis (1989a)El-Halwagi (1997)

advanced pinch method (includes supertargeting)

Hallale & Fraser (1998, 2000)

sequential mathematical programming methodsEl-Halwagi (1997), Garrison et al. (1995)Alva-Argaez et al. (1999)

simultaneous mathematical programming modelsPapalexandri et al. (1994)Papalexandri & Pistikopoulos (1995, 1996)Comeaux (2000); Wastewater: Benkő, Rév & Fonyó (2000)

I/A Extensions of the MINLP model of Papalexandri et al. (1994)

• Integer stage numbers• Generation of feasible initial values

• Kremser equation:

A

Abxmy

bxmy

AN

ijinjij

outi

ijinjij

ini

A ln

111ln

1

iij

j

Rm

LA

ijinjij

outi

outi

ini

A bxmy

yyN

1

yi*=mijxj*+bij Removable discontinuity at A=1

cx

cxxfxf

if definednot

if 1

UPLO xxx

f(x)

xc

f1(x)

xLO xUP

• Previous mathematical programming models for MENS assumed that A is always greater than 1

• Numerical difficulty when using GAMS

Adopted literature methods

New method

(the models are nonconvex anyway)

11 1 AA NYNYN

y1 y2 y3

0.01 1000.99 1.010

yVcA 2)(

UPLO AAA

UPLO VVV

A U PA = 1

y = 0 y = 1y = 1

A L O

LOLO VAA 1 UPLO AAV 1

are linear but use 3 binary variables

nonlinear but uses 1 binary variable only

• Big-M formulation• Multi-M formulation• a Convex-hull like formulation• Raman & Grossmann (1991)• Simple logic formulation

Advantages:1. faster2. larger problems can be solved

Large nonconvex MINLP problems solved by DICOPT++:There exists a critical upper limit of the number of binary variables

Example Objective

function

Pinch solution of

Nick Hallale

Target / Design

MINLP

Solution

(CMINLP-CPinch) /

CMINLP *100

3.1 CAP 830 000 / 860 000 1 044 285 +17.6 %

3.2 CAP 448 000 / 455 000 453 302 -0.4 %

3.3 CAP 819 000 / 751 000 637 280 -17.8 %

3.4 CAP 591 760 / 637 000 637 000 0.0 %

4.1 CAP 296 000 / 298 000 255 068 -16.8 %

5.1 TAC 226 000 / 228 000 226 000 -0.9 %

5.2 TAC 226 000 / 228 000 226 000 -0.9 %

5.3 TAC 226 000 / 228 000 226 000 -0.9 %

5.4 TAC 49 000 / 49 000 50 279 +2.5 %

5.5 TAC 524 000 / 526 000 527 000 +0.2 %

6.1 TAC 692 000 / 706 000 720 000 +1.9 %

6.2 TAC 28 000 / 28 000 32 000 +12.5 %

6.3 CAP 591 000 / 539 000 536 000 -0.6 %

TAC-total annual cost in USD/yr, CAP–annualised capital cost in USD, C - cost

I/B Comparison of the advanced pinch method ofHallale and Fraser (2000)and the extended model of Papalexandri et al. (1994)

13 exampleproblems

have been solved

The two methods perform more or less the same.Why are the MINLP solutions not always better? The MINLP model is nonconvex.

I/C New, fairly linear MINLP model for MENS

The stagewise superstructure enables almost linear mass balance formulation

L1

R1

k=1 k=2concentrationlocation 1

concentrationlocation 2

concentrationlocation 3

R1-L1

R1-L2

R1-L1

R1-L2

L2

R2

R2-L1

R2-L2

R2-L1

R2-L2

y 1,T

x 1,S

y 2,S

y 1,S

y 2,T

x 2,T x 2,S

x 1,T x 1,1

x 2,1

y 1,1

y 2,1

x 1,2

x 2,2

y 1,2

y 2,2

x 1,3

x 2,3

y 1,3

y 2,3

Similar to the HEN superstructure of Yee & Grossmann (1990)

j

kjime

kiy

kiy

iR

,,1,,

stjstji

melasti

ysi

yi

R,

,,,

i

kjime

kjx

kjx

jL

,,1,,

stistji

mesj

xfirstj

xj

L,

,,,

1,, ki

yki

y

1,, kj

xkj

x

Ti

Ylasti

y ,

Tj

Xfirstj

x ,

si

Yfirsti

y ,

sj

Xlastj

x ,

0,,,,,

kji

zjikji

me

kjiz

kjijib

kjx

jim

kiy

kjidy

,,1

,,,,,,,,

kji

zkjiji

bkj

xji

mki

ykji

dy,,

1,,,1,,1,1,,

kji

kjiz

,,

maxU,,

kji

kjizU

,,,,

min

3/1

2/1,,,,1,,,,,,

kji

dykji

dykji

dykji

dykji

lmcd

kjime

kjilmcdK

kjimass W ,,,,,,

jj

Lj

ckji

kjimassfTAC

,,,,

Model equationsminimise s.t.

mass balances

concentration constraints

big-M constraints for the existenxe of the units

driving force constraints

constraints on the number of existing units

Chen’s approximation for the log mean conc differences

calculation of the mass of the exchangers

Only the lean stream mass balances are bilinear

Example problems

Extensions: stagewise exchangers, multiple components

Example 4.1 (Hallale, 1998)

S3

R1

S1

R2

Capital cost, based on exchanger mass: 284,440 USD

S2

4.08e-3

1e-3

7.1e-3

2.5e-3

5e-3

1 kg/s

2.48 kg/s

8e-3

4.05e-3

9.16e-3

5e-3

3.66e-32.5e-3 1.059e-2

3.26e-3

R3

R4

R5

0

2.5e-3 5e-3

1e-2

0.01

1.8 kg/s

2 kg/s

2.5e-3

1.7e-3 3.63e-3

8.48e-35.82e-33.86e-3

1.64e-3 3.77e-3 7.79e-3 1.7e-2

4 kg/s

0.5kg/s

1.5kg/s

3.5kg/s

S1

R1

S2

N=4.23

R2

2.169 kg/s

0.9 kg/s

0.1 kg/s

0.566 kg/s

0.487 kg/s

N=2.73

N=4.93

N=3.25

N=2.88

TAC=436,289 USD/yr

1.752 kg/s

0.022 kg/s 0.062 kg/s

Two component exampleThe new model is most suitable for solving single component

MENS problems, where packed columns are used exclusively.In this case, no special initialization is needed.

II. Rigorous MINLP model for the design of distillation-pervaporation systems

Vacuum vessel

retentate(dehydratedethanol)

permeate(mainly water)

Inlet ethanol~80 m/m% EtOH

Pervaporationunit

Distillationcolumn The synthesis task

is to determine:

• Nth of the column• feed tray position• reflux ratio• membrane structure• reflux scheme

Rigorous modelling: Dist. Column: 1 bar, MESH equations, tray by tray, Margules activity coeff. for the liquid phase, ideal vapour phase, latent heat enthalpy

Membrane unit: transport calculation is based on experimental data 1/3 m2 flat membranes, costing - industrial practice

Adequate costing equations, utility prices

Superstructure

Distillation column superstructure:Viswanathan & Grossmann (1993)

Membrane superstructure: new

N-1

N

bui

P2

refi

P1

ifeed

ibmax

imin

12

feed

column bottomproduct

columnfeed

mixer

RFF

P4recycledpermeate

P3

1

2

n

pump

to the vacuum pump

con-denser

heatexchanger

feed pump

i=1…m

ethanolproduct

to the nextsection of

membranes

recycledpermeate

distillatefrom thecolumn

max n pieces ofmembranemodules

permeate

retentate

max m sectionslike this

permeatesplitter

permeatecondensate

1/3 m2 flatPVA membranes

in blocks

The blocks (or modules)can be connected in both

series or parallel

Multiple level optimisation (successive refinement)enables reducing the number of binary model variables

Modelling of the membranes is based on experimental data

Industrial example

80theor.stages

reflux ratio:3.262

retentate (product): 920.7 kg/hr99.7 mass % EtOH

1175kg/hr

4

1

TAC=373,820 USD/yr

feed80 mass%

EtOH

992.7 kg/hr 94.56 mass%

D=0.875 m

72 kg/hr28.96 mass% EtOH

recycled permeate bottom product254.3 kg/hr

0.087 mass% EtOH

12 x 81 piecesof 1/3 m2 flat membranes

=324 m2 total(fixed industrial configuration)

total permeate recycling

membrane capital investment : 52,362 USDmembrane replacement : 83,936 USDcolumn capital investment : 18,05 USDcolumn operating cost : 219,472 USD

min=97.5%

Base case

84theor.stages

reflux ratio:1.38

retentate (product): 920.7 kg/hr99.7 mass % EtOH

1175kg/hr

7

1

TAC=328,124 USD/yr

feed80 mass%

EtOH

1046.3 kg/hr 91.44 mass%

D=0.679 m

125.6 kg/hr30.86 mass% EtOH

recycled permeate bottom product 254.3 kg/hr

0.087 mass% EtOH

12 x 107 piecesof 1/3 m2 flat membranes

= 428 m2 total

total permeate recycling

membrane capital investment : 69,058 USDmembrane replacement : 110,758 USDcolumn capital investment : 13,931 USDcolumn operating cost : 134,377 USD

min=97.5%

Optimised12% savings in the TAC

0

50

100

150

200

250

300

350

400

300 350 400 450 500

overall membrane surface in square meters

TAC

(tho

usan

d U

SD

/yr)

0,5

1

1,5

2

2,5

3

3,5

reflu

x ra

tio

membrane capital investment

membrane replacement

column capital investment

column operational cost

TAC

reflux ratio

base case optimally designedsystem

Membrane surface - TAC

100

150

200

250

300

350

400

94,5 95 95,5 96 96,5 97 97,5 98 98,5 99 99,5

specified ethanol yield (%)

TAC

(th

ou

sa

nd

US

D/y

r)

plant membrane cost

plant TAC

optimised membrane cost

optimised TAC

optimised column cost

plant column cost

Ethanol yield - TAC

Other calculationsusing the MINLPmodel

III. Rigorous MINLP model for the design ofwastewater strippers

1

20

18

2

3

17

.

.

.

feedtop product

bottom product

boil-up vapour

5 mol/sxacetone = 0.05xmethanol= 0.04xwater = 0.90xethanol = 0.01

Xwater0.999

water85%

Nth=?19

total condenser

Wilson binary interactionsIdeal vapour phaseTheoretical stages1 barLatent heat enthalpyAntoine vapour pressure

Wastewater cleaning by stripping

VLE calculation

Superstructure

Similar to the distillation columnsuperstructure of Viswanathan &Grossmann (1993)

Minor quantities of acetone,methanol, and ethanol in water

Conclusions:Complex evaluation of distillation based heat integrated separation schemes is presented. Beside the heat integration the new sloppy structures proved to be competitive.

New, fairly linear, MINLP modell for MENS is developed and succesfully tested for literature examples and industrial case studies.

Thank you for your attention.

Utility Temperature

level (ºC)

Price

($/ton, kWh)

Low pressure steam 160 17.7

Middle pressure steam 184 21.8

Cooling water 30-45 0.0272

Electricity -------- 0.1 $

Utility prices

Controllability investigations, design

– interactive and challenging part of process design or development.

Control structure synthesis* control targets are defined, * the sets of controlled variables and possible manipulated

variables are determined (degrees of freedom)* pairing of the controlled and manipulated variables: steady

state control indices, dynamic behaviours in the cases of open and closed control loops of the promising control structures.

Demonstration of interaction between design and control

• comprehensive design of five energy integrated separation schemes

• three-component-alcohol-mixture is separated in five distillation based energy integrated two-column separation systems:– two heat integrated distillation schemes

– fully thermally coupled distillation column (Petlyuk, Kaibel)

– sloppy separation sequences

Table 3. Results of the economic optimizationD I DQF DQB SP SQF SQBDescription

Col.1 Col.2 Col.1 Col.2 Col.1 Col.2 Col.1 Col.2 Col. 1 Col.2 Col. 1 Col.2 Col. 1 Col.2Bottom temperature (oC) 102.32 117.22 117.19 96.93 153.60 117.21 102.32 134.11 102.37 117.19 150.45 117.24 103.82 158.77Column pressure (kPa) 101.33 101.33 101.33 101.33 511.00 101.33 101.33 178.50 101.33 101.33 451.00 101.33 101.33 367.00Column diameter (m) 0.84 0.82 0.96 0.78 0.76 0.87 0.84 0.85 0.72 0.98 0.65 0.74 0.71 0.71

Reflux ratio 2.25 1.67 0.90 1.87 2.56 2.38 2.25 2.20 0.67 2.99 0.82 1.92 0.67 1.61Overall column efficiency 0.52 0.49 0.46 0.49 0.63 0.49 0.52 0.53 0.51 0.49 0.59 0.48 0.49 0.56

Actual number of trays 91 98 93 88 93 55 92 61 87 145 57 147 79 143Total actual trays 189 181 148 153 232 204 223

Heating rate (kJ/hr) 8.01E+06 8.99E+06 5.19E+06 4.56E+06 5.28E+06 3.91E+06 3.94E+06Cooling rate (kJ/hr) 7.88E+06 8.85E+06 4.78E+06 4.19E+06 5.15E+06 3.78E+06 3.00E+06

Main HX duty (kJ/hr) ………….. ………….. 3.94E+06 4.26E+06 ………….. 2.89E+06 3.07E+06Auxiliary heat exchanger ………….. ………….. TC,MP TR,LP LP TC,MP TC,MP

Steam cost ($/yr) 5.45E+05 6.11E+05 4.52E+05 3.10E+05 3.59E+05 3.41E+05 3.43E+05C.W cost ($/yr) 2.73E+04 3.07E+04 1.66E+04 1.45E+04 1.79E+04 1.31E+04 1.04E+04

Operating cost ($/yr) 5.72E+05 6.41E+05 4.69E+05 3.25E+05 3.77E+05 3.54E+05 3.54E+05Capital cost ($/yr) 7.54E+04 7.85E+04 7.80E+04 8.14E+04 8.18E+04 7.62E+04 7.98E+04

TAC ($/yr) 6.48E+05 7.20E+05 5.47E+05 4.06E+05 4.59E+05 4.30E+05 4.33E+05Capital cost saving (%) 0 -4 -3 -8 -8 -1 -6

Operating cost saving (%) 0 -12 18 43 34 38 38TAC saving (%) 0 -11 16 37 29 34 33

Detailed results of economic studies

Estimation of capital cost

Douglas, J. M., Conceptual design of chemical processes, McGraw-Hill Book Company

Marshall & Swift index: 1056.8/280 Project life: 10years

Major sizes are estimated byHYSYS flowsheet simulator

(Feed: 100 kmol/h)

0.97

0.974

0.978

0.982

0.986

0.99

0.994

0 10 20 30 40 50 60 70 80

Time (unit)

Pro

duct

mol

e fr

actio

n

0.31

0.34

0.37

0.4

0.43

Fee

d m

ole

frac

tion


A

B

C

Feed composition disturbance

Open loop transient behaviour of Petlyuk column for feed composition disturbance

Petlyuk column, open loop, feed composition

Open loop transient behaviour of DQB scheme for feed composition disturbance

0.97

0.975

0.98

0.985

0.99

0.995

0 10 20 30 40 50 60 70

Time (unit)

Pro

duct

mol

e fr

actio

n

0.31

0.34

0.37

0.4

0.43

Fee

d m

ole

frac

tion


A

B

C


Heat integrated (DQB) column, open loop, feed composition

0.9895

0.9897

0.9899

0.9901

0.9903

0 5 10 15 20 25 30 35 40

Time (unit)

Pro

duct

mol

e fr

actio

n

0.31

0.34

0.37

0.4

0.43

Fee

d m

ole

frac

tion

Ethanol(A)Propanol(B)Butanol(C)


Closed-loop transient behaviour of Petlyuk column for feed composition disturbance(L-S-B )

Petlyuk (dividing wall) column, closed loop (L-S-B), feed composition

0.9894

0.9896

0.9898

0.9900

0.9902

0 5 10 15 20 25 30 35

Time (unit)

Pro

duct

mol

e fr

actio

n

0.31

0.34

0.37

0.4

0.43

Fee

d m

ole

frac

tion



Closed-loop transient behaviour of DQB scheme for feed composition disturbance(D1-L2-B2 )

Heat integrated (DQB) column, closed loop (D-L-B), feed composition

Documents

Department of Chemical Engineering, Budapest University of Technology and Economics, H-1521 Budapest, Hungary Research activities CAPE-Forum, Veszprem,