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Journal of Physical Science and Application 2 (10) (2012) 434-440
Simulation of MEG Packed Distillation Column Using an
Equilibrium Stage Model-Case Study on Operating
Parameters of Farsa Petrochemical Company:
Assaluyeh-Iran
Noorallh Kasiri and Yousef Dorj
Computer Aided Process Engineering Lab. School of Chemical Eng, Iran University of Sci. and Tech, Iran
Received: April 20, 2012 / Accepted: May 26, 2012 / Published: October 15, 2012.
Abstract: Two types of equilibrium and non-equilibrium stage models are generally used to simulate the mass transfer of packed
distillation column. Using non-equilibrium model requires the calculation of mass transfer coefficients, thus, usually equilibrium-based
methods are preferred to be used for simulations of distillation columns. In this paper, packed column distillation of production of
Mono Ethylene Glycol in FARSA SHIMI Company (Assaluyeh-Iran)’s Ethylene Glycol portion has been simulated through using the
equilibrium model and solving the related equations. The simulation has been carried out in the MATLAB environment. The column
also has been simulated in the Aspen Hysys and Aspen Plus ver. 2006.5 environments. Then, the output has been compared with
software results, designing and operating data of the underlying columns which demonstrate good consistency with the model. Having
the model validated, the effect of some operating parameters has been analyzed through the model.
Key words: Distillation, packed column, modeling, equilibrium and non-equilibrium models.
1. Introduction
Simulation is a powerful tool for process engineers
to develop and design, and it can be used to produce
different products. Modeling the system helps to
determine whether the system can lead to the desired
product or not. A column model can also predict the
condition of the tower under various operations [1].
The process engineers would be interested in finding
ways to increase efficiency and capacity of the units at
minimum costs. The accuracy of the models strongly
depends on the proper definition of the inter-phase
interactions [2]. Consistent with major improvements
in computational technology, there have been great
improvements in modeling and simulation of
multi-phase separation processes and mathematical
modeling has become more flexible and realistic.
Corresponding author: Yousef Dorj, research field:
modeling and simulation. E-mail: [email protected].
Shortcut and rigorous procedures are two calculation
methods used for the design and simulation of such
operations. There are also two fundamentally different
kinds of rigorous models to describe such operation
(i.e., the equilibrium stage model and non-equilibrium
or rate-based model) [3]. Even though for the
conventional structures, formed by structured packing,
due to the complex nature of intra-phase forces,
accurate focus would be difficult. So, modeling the
separation phenomena is usually based on the conceptof stages in which equilibrium or non-equilibrium
models could be utilized.
With major improvements in computational
technology, there have been great improvements in
modeling and simulation of multi-phase separation
processes and mathematical modeling has become
more flexible and realistic. Shortcut and rigorous
procedures are two calculation methods used for the
DAVID PUBLISHING
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Simulation of MEG Packed Distillation Column Using an Equilibrium Stage Model-case Study onOperating Parameters of Farsa Petrochemical Company-Assaluyeh-Iran
435
design and simulation of such operations. There are
also two fundamentally different kinds of rigorous
models to describe such operation (i.e., the
equilibrium stage model and non-equilibrium or
rate-based model) [3]. Even though for the
conventional structures, formed by structured packing,
due to the complex nature of intra-phase forces,
accurate focus would be difficult. So, modeling the
separation phenomena is usually based on the concept
of stages in which equilibrium or non-equilibrium
models could be utilized.
2. Equilibrium Model
In the past century, equilibrium models have beenwidely used to describe separation processes. The
history of computation of separation process may date
back to 1893, when Sorel 1893 published an equation
for simple and continuous distillation. This equation
includes mass and energy balance for calculating heat
loss. His equations were not widely used until 1921,
when the graphic techniques were presented by
Panchon & Savarit, 1921 [1].
A new graphic technique was developed by McCabe
and Theile 1925. They used a simple assumption of
constant tray mole overflow and removed the energy
balance equation. From 1981 to 1989, simulation of
distillation columns has been studied by many
researchers including Seader 1981 and Gani, et al.
1986 [4].
Ruiz and Cameron 1986 have suggested a model to
simulate a continuous distillation [5]. Many
researchers discussed different assumptions used in the
simulation of separation towers and the errors theyhave caused over the years. Ranzi et al 1988 discussed
the effects of energy balance on the simulation
equation [6]. They found that the energy balance must
be taken into account in order to simulate correct phase
behavior. Choe & Luyben 1987 concluded that the
vapor phases should not be ignored [7]. The
equilibrium stage model assumes that the contact time
of the streams is infinite in each stage. The product
distributions and temperature profiles calculated by
using the equilibrium stage model does not correspond
to real stages and therefore, cannot describe the actual
operating conditions in the packed column [3].
Commercial softwares are usually based on
equilibrium models.
3. Non-Equilibrium Model
Non-equilibrium or rate-based models are another
class of models providing a method to model
separation process using direct rates of mass and heat
transfer. Many models have been presented within this
structure. Since the late 1970s, several non-equilibrium
models (Krishnamurthy & Taylor, 1985 [8];Sivasubramanian et al 1987 [9]) have been proposed to
overcome the shortcomings of equilibrium stage
models. All these models have discarded the
assumption that each stage operates at equilibrium.
Instead, they introduced mass and heat transfer
coefficients to describe the varying status at which each
stage operates. The equilibrium stage models are still
widely used in the design and simulation of distillation
processes due to the difficulty of predicting the
required transfer coefficients [3].
In some models, the film and penetration theory are
used for modeling and the required parameters are
achieved by experimental techniques. The film model,
based on comparisons with various experimental
methods is superior to other models. Based on the film
theory, mass transfer resistance is focused on the
two-phase boundary layer of the film. Film thickness
defines the parameters of model that can be estimated
by experimental methods. Obviously, the mass transferoccurring at the two-layer film is only limited to
molecular diffusion. Outside the film, mass transfer
rate disappears completely due to high mixing levels
[10]. In these models, unlike equilibrium models,
thermodynamic equilibrium is assumed only at the
phase interface as demonstrated in Fig. 1. The Mass
balance for each phase has been written separately and
diffusion rate of each component has been shown. In
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Sim
436
Fig. 1 A sch
multi-comp
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4. The M
A modifi
model has b
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and heat t
modeling re
equations t
including eequations,
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each stage,
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Therefore, t
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ransfer thro
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ass balance
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i j ji j ji Z F yV x
quilibrium e
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hich:
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2 An equili
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yzed. The c
ess is simul
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tertainment
mulating, th
. Mass and
ch stage (Fi
equations:
(,11
j ji j U L x E
quations are:
ji y
,
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T f K ,
,
on equations
1
C
j
1
C
j
ons would b
).(11
j j
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V
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ding to N(C
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nergy balan
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,,.
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,,
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,,
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(4)
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(7)
(8)
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s of freedom
specificatio
sition, reflu
d definition
.
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Simulation of MEG Packed Distillation Column Using an Equilibrium Stage Model-case Study onOperating Parameters of Farsa Petrochemical Company-Assaluyeh-Iran
437
Fig. 3 Diagram for an element of model for MESCHEC.
of composition and temperature profiles through thecolumn, as well as the liquid and gas flow rates on each
stage.
(2) Having specified the composition and
temperature profiles and liquid and gas flow rates on
each stage; it is assumed that a stage is equivalent to a
part of one HETP called a sub-bed. The vapor leaving
top of the sub-bed is in equilibrium with the liquid
leaving the bottom. An element of height dH is selected.
It is assumed that the phases are uniformly distributed
throughout this stage.
Mass balance is the same as Eq. (1). Liquid phase is
at its bubble point and the vapor phase is at its dew
point. It should be noted that the temperature of vapor
and liquid phase leaving the element are not the same,
however the temperature of vapor phase at the top and
liquid phase temperature at the bottom are the same.
The temperature profiles of liquid and vapor phase
would be determined by mass transfer rate. The
temperature of liquid and vapor leaving each stage orany height of the bed are identical. Of course, this
assumption is not always true. Hence, in order to
modify the model, the equations are rewritten as below:
Phase-corrected equilibrium equations model is
written as:
Yii ji
T F Y ,
(9)
Xii ji
T f X ,
(10)
Sum equations can be written as:
11
,
n
j
ji X (11)
11
,
n
j
jiY (12)
As well as the energy balance in equilibrium stage
the following term must also be added to Eq. (6):
dH
T T A iPiP
d
1
dH
T T A iPiP
d
1
(13)
In vacuum distillation gas load (gas velocity× square
root of gas density) is low and therefore, total mass
transfer rate is controlled by the gas phase (Van Winkle
1967)[11]. Thus, the efficiency for the vapor phase can
be written as:
HETPdH i
Y Y Y Y
j N j N
j N ji .
,1,
,1,
(14)
And for liquid phase:
HETP
dH i
X X
X X
j N j N
j N ji .
,,1
,,
(15)
The equations above can be solved using an iterative
method like the bubbles and Newton, Raphsoon.
5. Simulation of Mono Ethylene Glycol
Column
Ethylene glycol is produced under vacuum
distillation conditions. Water contamination in Glycol
mixture must be removed before the separation of
Mono Ethylene Glycol from heavier Glycols like DEG
& TEG. In Industrial practice, MEG is separated from
heavier Glycols using two vacuum columns in a
sequence.
In this study, top and bottom pressures of T-5001 are
kept at 23 and 25 KPa respectively. The temperature is
then increased from 154 to 160 °C. MEG of high purity
(99.99 wt.%) was drawn out from the first bed and sent
to storage. Heavier product was taken from bottom of
distillation column and sent to next unit to be separated.
In this column, structured packing (of
MELLAPACK250Y type) has been used. There are 3
beds in the columns of heights of 1,470, 4,620, 1,890
mm respectively from top to bottom with a total height
of 7,980 mm.
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Simulation of MEG Packed Distillation Column Using an Equilibrium Stage Model-case Study onOperating Parameters of Farsa Petrochemical Company-Assaluyeh-Iran
438
To simulate the column, above equations were
solved in the MATLAB environment. The HETP value
is considered 400 mm based on the manufacturer’s data.
Rault’s law and Antoine equations are used to evaluate
vapor component pressure and the equilibrium
constants as the column is at vacuum pressure. For
vapor and liquid enthalpy, ideal gas and Clausius-
Clapeyron equations have been used. The influence of
conduction heat transfer between packing and fluid has
been neglected. Component concentration and
temperature profiles in the columns are as
demonstrated in Figs. 4 and 5.
As shown in Fig. 4, MEG concentration (increasing
from bottom to top) tends to one. Stages are numberedfrom top to bottom with MEG & TEG concentration
increasing from top to bottom which is in accordance
with actual plant conditions. The MEG product is
drawn out from stage 5 with the maximum MEG and
TEG existing in the reboiler stage.
As shown in Fig. 5, packed bed temperature
increases gradually from top to bottom of the column
with the maximum temperature occurring at the
reboiler. This demonstrates a good agreement with
practical conditions of the column in the plant. The
steep of temperature at the last stage shows the
reboiler’s heat production.
As it can be seen in Fig. 6, temperature profile
obtained from this model has good consistency with
actual operating profile and compared to the results
produced from the Aspen Hysys simulation outputs,
demonstrates even a better match. This column has
been simulated in the Aspen Hysys and Aspen plus Ver.
2006. 5 environments and Tables 3 and 4 show thecomparison between the present model, actual, design
and software simulation results for top and bottom
products.
In Tables 1 and 2, the results of simulation by using
this model and Aspen Plus 2006 & Aspen Hysys 2006
softwares with design and operational data for the
tower’s top and bottom products are compared.
As can be seen in the tables, for main product (MEG),
the value calculated from the model is consistent with
design, operational value and ASPEN Hysys which
indicates that the model is adequately accurate for this
system and provides good agreement with actual data.
This table also shows that Aspen Hysys is preferable to
Fig. 4 Composition profile on packing height (dH = 50
mm).
Fig. 5 Temraure profile in stages.
Fig. 6 Temperature profile Comparison.
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Simulation of MEG Packed Distillation Column Using an Equilibrium Stage Model-case Study onOperating Parameters of Farsa Petrochemical Company-Assaluyeh-Iran
439
Table 1 Comparison between the model, practical, design and software results for MEG product.
Component Design (kg/hr) Operation data Aspen Hysys Aspen Plus Present ModelError compared to
design
Error compared
to operation
MEG 50,577.9 50,565.2 50,560 49,783.9 50,577 0.00 0.02
DEG 9.8 5.06 0.003 791.1 4.92 49.80 2.77TEG 0 0 0 12.19 0 0.00 0.00
WATER 0 17.7 5.9 0.76 0 0.00 0.00
Table 2 Comparison between the model, practical, design and software results for bottom product.
Component Design (kg/hr) Aspen Hysys Aspen Plus Model Error with Design
MEG 17,734.7 17,755 18,419.4 17,403.5 1.9
DEG 5,536.3 5,546.2 5,333.4 5,892 6.4
TEG 360.4 360.4 410.34 348.7 3.2
WATER 0 2.995E-09 0 0 0.0
Table 3 The effect of reflux rate on the reboiler duty and product concentration.
Reflux rate 20% decreases 10% decreases Design
Product concentration 0.9937 0.9987 0.9998
Reboiler duty (KW) 17,900 19,730 21,260
Reduction rate Percent for reboiler 16 7
Fig. 7 Feed tray effect of the MEG quality.
Aspen Plus in simulating this system. Compared to
design value, maximum error is associated with DEG
concentration at the bottom product but error between
reality and model is much lower (3%). The error is
mainly due to the ignoring components heavier than
TEG in the calculation procedure in the model. These
assumptions can be corrected as in the actual plant
conditions the heavier component are present with a
0.018 wt% composition.
6. Studying the Effect of Reflux on the
Product Quality and Reboiler Duty
Having validated the model in order to study the
effect of reflux rate, it is reduced to 10 and 20 percent
of the design value. Thus, the result obtained from the
model is shown in Table 3
As it can be seen in the table above, reducing reflux
has little effect on product concentration but reboiler
duty reduces by 7% and 16%.
7. Studying the Effect of Changing the Feed
Tray on the Product Quality
The design feed tray location is 16. Varying the feed
tray location from 10 to 20 leads to little change in
MEG quality but if it changes to lower locations,
product quality will slightly improve (Fig. 7) . Under
these conditions, other operation parameters such as
reflux rate and required condenser duty will also
decrease.
8. Summaries
The model for processing Glycol plants has been
built up in two different Hysys environments. A
mathematical model has also been developed to predict
the columns of the plant. The design and plant
operational data have been used for verification. The
investigation shows that the Hysys based simulations
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440
provide good predictions but the predictions based
onthe equilibrium model are of better capability in
predicting thermal behavior. Further studies have been
carried out on the reflux ratio and feed tray location
using the same model.
References
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column in Arak. PC, in: 13th Iranian Chemical
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[3] L. Yang, K.T. Chuang, A new approach to simulation of
distillation in packed columns, Computers and Chemical
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[4] H.A. Kooijman, Dynamic nonequilibrium column
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nonequilibrium stage model of multicomponent
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[6]
E. Ranzi, M. Rovaglio, T. Faravelli, G. Biardi, Role of
energy balances in dynamic simulation of multicomponent
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distillation columns: Part 1. Model description and method
of solution, Journal of American Institute of Chemical
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[8] R. Krishnamurthy, A nonequilibrium stage model of
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[9] R Gani, C.A. Ruiz, I.T. Cameron, A generalized model for
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[10]
A.M. Katariya, R.S. Kamath, Kannan M. Moudgalya,
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[11] Process description and document of Farsa Pc.
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