The document investigates azeotropic distillation for separating an ethylene glycol (EG) and neopentyl glycol (NPG) system. Vapor-liquid equilibrium data was measured for the EG-NPG and NPG-para-xylene systems under atmospheric pressure. The data was found to be thermodynamically consistent and well-correlated by models like NRTL and UNIQUAC. An azeotropic distillation process was designed using para-xylene as an entrainer that can produce EG and NPG at 99.9% purity with minimal cost.
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Turbomachinery Engineers often conduct studies to determine if a hot gas bypass is required for a given centrifugal compressor system. This would mean building a process model and simulating it for Emergency Shutdown conditions (ESD) & Normal Shutdown conditions (NSD) to check if the compressor operating point crosses the surge limit line (SLL). A quick estimation method that uses dimensionless number called the inertia number can be used to check prior to the study, if a Hot gas bypass (a.k.a. Hot Recycle) is required in addition to an Anti-surge line (ASV or a.k.a Cold Recycle).
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Ebook purchase: https://play.google.com/store/books/details/MATLAB_Applications_in_Chemical_Engineering?id=kpxwEAAAQBAJ&hl=en_US&gl=US
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The slides of Chapter 3 of the book entitled "MATLAB Applications in Chemical Engineering": Interpolation, Differentiation, and Integration. Author: Prof. Chyi-Tsong Chen (陳奇中教授); Center for General Education, National Quemoy University; Kinmen, Taiwan; E-mail: chyitsongchen@gmail.com.
Ebook purchase: https://play.google.com/store/books/details/MATLAB_Applications_in_Chemical_Engineering?id=kpxwEAAAQBAJ&hl=en_US&gl=US
A QUICK ESTIMATION METHOD TO DETERMINE HOT RECYCLE REQUIREMENTS FOR CENTRIFUG...Vijay Sarathy
Turbomachinery Engineers often conduct studies to determine if a hot gas bypass is required for a given centrifugal compressor system. This would mean building a process model and simulating it for Emergency Shutdown conditions (ESD) & Normal Shutdown conditions (NSD) to check if the compressor operating point crosses the surge limit line (SLL). A quick estimation method that uses dimensionless number called the inertia number can be used to check prior to the study, if a Hot gas bypass (a.k.a. Hot Recycle) is required in addition to an Anti-surge line (ASV or a.k.a Cold Recycle).
Ch 01 MATLAB Applications in Chemical Engineering_陳奇中教授教學投影片Chyi-Tsong Chen
The slides of Chapter 1 of the book entitled "MATALB Applications in Chemical Engineering": Solution of a System of Linear Equations. Author: Prof. Chyi-Tsong Chen (陳奇中 教授); Center for General Education, National Quemoy University; Kinmen, Taiwan; E-mail: chyitsongchen@gmail.com.
Ebook purchase: https://play.google.com/store/books/details/MATLAB_Applications_in_Chemical_Engineering?id=kpxwEAAAQBAJ&hl=en_US&gl=US
Ch 03 MATLAB Applications in Chemical Engineering_陳奇中教授教學投影片Chyi-Tsong Chen
The slides of Chapter 3 of the book entitled "MATLAB Applications in Chemical Engineering": Interpolation, Differentiation, and Integration. Author: Prof. Chyi-Tsong Chen (陳奇中教授); Center for General Education, National Quemoy University; Kinmen, Taiwan; E-mail: chyitsongchen@gmail.com.
Ebook purchase: https://play.google.com/store/books/details/MATLAB_Applications_in_Chemical_Engineering?id=kpxwEAAAQBAJ&hl=en_US&gl=US
Design of Methanol Water Distillation Column Rita EL Khoury
Methanol is an essential feed stock for the manufacture of many industrial products such as adhesives and paints and it is widely used as a solvent in many chemical reactions. Crude methanol is obtained from steam reforming of natural gas and then a purification process is needed since it contains smaller and larger degree of impurities.
The purification process consists of two steps: a topping column used to remove the low boiling impurity called the light ends; and the remaining water methanol mixture is transferred to another column called the refining column where it is constantly boiled until separation occurs. Methanol rises to the top while the water accumulates in the bottom.
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Excess gibbs free energy models,MARGULES EQUATION
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Design of Methanol Water Distillation Column Rita EL Khoury
Methanol is an essential feed stock for the manufacture of many industrial products such as adhesives and paints and it is widely used as a solvent in many chemical reactions. Crude methanol is obtained from steam reforming of natural gas and then a purification process is needed since it contains smaller and larger degree of impurities.
The purification process consists of two steps: a topping column used to remove the low boiling impurity called the light ends; and the remaining water methanol mixture is transferred to another column called the refining column where it is constantly boiled until separation occurs. Methanol rises to the top while the water accumulates in the bottom.
This document focuses on methanol water separation. A detailed design study for the distillation column is conducted where the separation occurs at atmospheric pressure with a total condenser and a partial reboiler.
Excess gibbs free energy models,MARGULES EQUATION
,REDLICH-KISTER EQUATION,VAN LAAR EQUATION
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,UNIversal QUAsi Chemical equation
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A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
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An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
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It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
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2. 3. THERMODYNAMIC MODELING
3.1. Experimental Data. The experimental isobaric VLE
data and calculated activity coefficients for EG + NPG and
NPG + PX systems were listed in Table 2 and Table 3,
respectively. The activity coefficient γi was calculated with the
following equation
φ γφ̑ =
−⎡
⎣
⎢
⎢
⎤
⎦
⎥
⎥
py x p
V p p
RT
exp
( )
i i i i i
i iV s s
L s
(1)
Under mesolow circumstances, the values of φ̑V
and φi
s
can
both thought to equal to 1. Equation 1 can be simplified as
γ=py x pi i i i
s
(2)
The saturation vapor pressure was calculated by Antoine
equation8
= + + +p A
B
T
C T DTln lni
Es
(3)
The constants of Antoine equation for vapor pressures of the
pure compounds were listed in Table 4.
3.2. Thermodynamic Consistency Test. The thermody-
namic consistency tests for the two binary systems were based
on the Gibbs−Duhem equation9,10
and verified with the
Herington area test.11
The Gibbs−Duhem equation was
γ γ+ = −x x
H
RT
T
V
RT
pdln dln d d
E E
1 1 2 2 2 (4)
Under constant pressure circumstance, the Gibbs−Duhem
equation can be simplified as
∫ ∫
γ
γ
= −
=
=
=
=
x
H
RT
Tln d ln d
x
x
x
x E
1
2
1 2
1 0
1 1
1 0
1 1
(5)
As Herington proposed, the experimental isobaric VLE data
can be regarded thermodynamically consistent when |D − J| <
10. D and J were calculated in the equations
∫
∫
γ γ
γ γ
= ×
| |
| |
D
x
x
100
ln( / )d
ln( / ) d
0
1
1 2 1
0
1
1 2 1 (6)
= ×
−
J
T T
T
150 max min
min (7)
Tmax and Tmin are the highest and lowest temperature,
respectively. The results of thermodynamics consistency test
are shown in Table 5, the experimental isobaric VLE data of the
two binary systems both passed the Herington area test.
3.3. Data Regression. The interaction parameters of the
two binary systems were regressed by means of Wilson, NRTL,
and UNIQUAC models and the values were listed in Table 6.
The interaction parameter α in NRTL was fixed at 0.3.4
The
root-mean-square deviations (σT and σy1) between the
evaluated and experimental data were defined as12
σ =
∑ −=
T
T T
N
( )i
N
i i1
cal exp 2
(8)
σ =
∑ −=
y
y y
N
( )i
N
i i
1
1 1
cal
1
exp 2
(9)
The calculated root-mean-squared deviations were also given
in Table 6. The comparison results indicated that NRTL model
Table 2. Experimental VLE Data for Temperature T, Liquid-
Phase Mole Fraction x, and Gas-Phase Mole Fraction y, for
the System Ethylene Glycol (1) + Neopentyl Glycol (2)a
at
at 101.3 kPa
T/K x1 y1 γ1 γ2 ln(γ1/γ2)
470.22 1.0000 1.0000
470.80 0.9242 0.9382 0.9994 1.0025 −0.0031
471.28 0.8524 0.8763 0.9981 1.0138 −0.0156
471.77 0.7727 0.8047 0.9960 1.0236 −0.0273
472.29 0.6841 0.7216 0.9936 1.0312 −0.0371
472.71 0.6115 0.6518 0.9921 1.0347 −0.0419
473.31 0.4966 0.5394 0.9925 1.0351 −0.0420
473.76 0.4165 0.4601 0.9969 1.0318 −0.0344
474.79 0.2439 0.2870 1.0293 1.0177 0.0113
475.76 0.1333 0.1696 1.0815 1.0071 0.0713
476.63 0.0587 0.0813 1.1430 1.0016 0.1320
478.95 0.0000 0.0000
a
Standard uncertainties are u(P) = 1 kPa, u(T) = 0.1 K, u(x1) = u(y1)
= 0.001.
Table 3. Experimental VLE data for Temperature T, Liquid-
Phase Mole Fraction x, and Gas-Phase Mole Fraction y, for
the System Neopentyl Glycol (1) + para-Xylene (2)a
at
101.3 kPa
T/K x1 y1 γ1 γ2 ln(γ1/γ2)
411.21 0.0000 0.0000
414.70 0.0751 0.0097 0.7152 0.9992 −0.3343
419.62 0.2237 0.0218 0.8455 0.9898 −0.1576
427.69 0.3512 0.0497 0.9122 0.9762 −0.0678
432.33 0.4310 0.0776 0.9460 0.9638 −0.0186
442.49 0.5764 0.1631 0.9936 0.9288 0.0674
449.35 0.6626 0.2465 1.0127 0.8996 0.1184
456.64 0.7508 0.3634 1.0233 0.8698 0.1625
466.21 0.8711 0.5824 1.0183 0.8785 0.1477
472.57 0.9468 0.7754 1.0057 1.0005 0.0052
475.19 0.9752 0.8775 1.0004 1.0307 −0.0262
478.95 1.0000 1.0000
a
Standard uncertainties are u(P) = 1 kPa, u(T) = 0.1 K, u(x1) = u(y1)
= 0.001.
Table 4. Antoine Constants of EG, NPG, and PX
Antoine equation EG NPG PX
A 72.577 75.011 77.207
B −10411 −11276 −7741.2
C −8.198 −8.336 −9.869
D 1.65 × 10−18
4.45 × 10−18
6.08 × 10−6
E 6 6 2
Table 5. Thermodynamics Consistency Test for Two Binary
System at 101.3 kPa
system D J |D − J|
EG + NPG 5.068 1.857 3.211
NPG + PX 23.972 20.932 3.040
Journal of Chemical & Engineering Data Article
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2331
3. was more suitable to regress the interaction parameters in this
study than others did, which fit the experimental isobaric VLE
data in a similar way. The experimental isobaric VLE data of the
two binary systems were plotted in Figure 1 and Figure 2, in
which the NRTL model was showed in solid lines.
4. DISTILLATION PROCESS DESIGN
Figure 3 illustrated the residue curve map (RCM) for EG +
NPG + PX heterogeneous azeotropic system at 101.3 kPa
computed by Aspen Plus with NRTL model based on the
regressed interaction parameters. Only a binary heterogeneous
azeotrope with composition of 89.14 mol % PX/10.86 mol %
EG and an azeotropic temperature of 135.42 °C existed in EG
+ NPG + PX heterogeneous azeotropic system.13
The
Table 6. Binary Interaction Parameters of Wilson, NRTL, and UNIQUAC Models for Two Binary System
model parameters root-mean-square deviation
models A12/(J·mol−1
)a
A21/(J·mol−1
)a
α σT/Kb
σy1
b
EG (1) + NPG (2) System
Wilson −590.2820 334.3378 0.5025 0.0015
NRTL −449.4958 686.3341 0.3000 0.5000 0.0005
UNIQUAC 235.3980 −365.8704 0.4978 0.0019
NPG (1) + PX (2) System
Wilson 488.4102 −958.3601 0.8548 0.0086
NRTL 896.7799 −602.2680 0.3000 0.9119 0.0091
UNIQUAC −502.2751 353.6040 0.9198 0.0077
a
Wilson: A12 = (λ12 − λ11)/R, A21 = (λ21 − λ22)/R. NRTL: A12 = (g12 − g22)/R, A21 = (g21 − g11)/R. UNIQUAC: A12 = (u12 − u22)/R, A21 = (u21 −
u11)/R. b
σT = [∑i = 1
N
(Ti
cal
− Ti
exp
)2
/N]1/2
; σy1 = [∑i = 1
N
(y1i
cal
− y1i
exp
)2
/N]1/2
Figure 1. T−x−y diagram for EG (1) + NPG (2) at 101.3 kPa: (red ●
and black ■), experimental data; solid lines, NRTL equation.
Figure 2. T−x−y diagram for NPG (1) + PX (2) at 101.3 kPa: (red ●
and black ■), experimental data; solid lines, NRTL equation.
Figure 3. RCM for the EG + NPG + PX heterogeneous azeotropic
system at 101.3 kPa simulated by Aspen Plus using NRTL model.
Figure 4. Simulation flowsheet of the conventional azeotropic
distillation process.
Journal of Chemical & Engineering Data Article
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4. conventional two-column/decanter flowsheet14
was designed
for separating the heterogeneous azeotropic system (Figure 4).
Both of the two columns were operated at 1.0 atm and the
bottom purities were set at 99.9 mol %. The compositions of
the two vapor streams fed to a single heater exchanger (HX)
were almost the same. The vapor condensate separated into
aqueous and organic phases in a decanter. The organic phase 1
(containing mainly entrainer) was fed to the first tray of
column C1, which served as a heterogeneous azeotropic
distillation column. The organic phase 2 (containing lesser
entrainer) was returned to the first tray of column C2, which
served as a product column.
Several parameters should be optimized for the design with
optimized operation conditions of this azeotropic distillation
process. Optimum parameters can be achieved through
elaborate comparison of the minimal TAC values. TAC was
defined as the sum of the annual operation cost and capital
investment divided by a three-year payback period.15
Parameters of the columns were obtained based on the TAC
results by the methods proposed by Douglas.16
The capital
investment was considered as the investment of the major piece
of equipment such as vessels and HXs. Other minor pieces such
as pipes, valves, and pumps can usually be neglected as the
investment were much less than that of major ones. Only utility
consumption was taken into consideration when calculating
operating cost in this study. The price of high-pressure steams
and the relation between equipment sizes with investment were
followed the recommendation by Luyben.15
Sequential iterative
optimization procedure for the conventional azeotropic
distillation process (Figure 5) is follows:
(1) Fix total number of trays (NT) of column C2.
(2) Fix NT of column C1.
(3) Give the feed tray (NF) of the fresh feed.
(4) Change the reboiler duty (QR) of the two columns until
two product meet their specifications.
(5) Back to the third step, if the previous step can not
proceed, until the minimized TAC obtained.
(6) Back to the second step, if the previous step can not
proceed, until the minimized TAC obtained.
(7) Back to the first step, if the previous step can not
proceed, until the minimized TAC obtained.
The optimum NT of the azeotropic distillation column is 37
with feed location at fifth tray. The optimum NT of the product
column is 4. The effect of NT1 and NT2 on the TAC of the
conventional heterogeneous azeotropic distillation process were
showed in Figures 6 and 7, respectively. The results for all of
the streams in each column were shown in Table 7.
5. CONCLUSION
The thermodynamics was studied in detail in order to make an
appropriate azeotropic distillation process design in this article.
The experimental isobaric VLE data for the two binary systems
of EG + NPG and NPG + PX were measured under pressure of
Figure 5. Sequential iterative optimization procedure for the
conventional azeotropic distillation process.
Figure 6. Effect of NT1 on the TAC of the conventional azeotropic
distillation process.
Figure 7. Effect of NT2 on the TAC of the conventional azeotropic
distillation process.
Journal of Chemical & Engineering Data Article
DOI: 10.1021/acs.jced.5b01044
J. Chem. Eng. Data 2016, 61, 2330−2334
2333
5. 101.3 kPa. Reasonable thermodynamic consistency were
confirmed by means of Herington area tests. The experimental
isobaric VLE data were regressed by Wilson, NRTL, and
UNIQUAC models. A conventional azeotropic distillation
process was designed and optimized with minimal TAC to
achieve 99.9 mol % of EG and NPG based on preceding results.
■ AUTHOR INFORMATION
Corresponding Author
*Tel.: +86 519 86330355. Fax: +86 519 86330355. E-mail:
huagonglou508@126.com.
Funding
There is no grant of financial support in the study.
Notes
The authors declare no competing financial interest.
■ ACKNOWLEDGMENTS
We are thankful for assistance from the staff at the School of
Petrochemical Technology (Changzhou University).
■ NOMENCLATURE
VLE = vapor−liquid equilibrium
EG = ethylene glycol
NPG = neopentyl glycol
PX = para-xylene
NRTL = nonrandom two-liquid
UNIQUAC = universal quasichemical activity coefficient
TAC = total annual cost
FID = flame ionization detector
ADD = average absolute deviation
NT = total number of trays
QR = reboiler duty
HX = heater exchanger
NF = feed tray
■ REFERENCES
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Ding, H. Isobaric Vapor−Liquid Equilibria for the Binary Mixtures
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Table 7. Specifications for Flows in Column C1 and Column C2
column C1 column C2
B1 V1 B2 V2
mole flow/kmol·h−1
50.00 531.78 50.00 0.52
temperature/K 483.88 408.58 471.58 408.56
EG/mol fraction 7.69 × 10−2
11.11 99.92 10.86
NPG/mol fraction 99.92 7.23 × 10−33
7.69 × 10−2
2.01 × 10−3
PX/mol fraction 4.81 × 10−31
88.88 4.86 × 10−10
89.14
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