Article pubs.acs.org/IECR
Thermodynamic Analysis and Process Simulation of an Industrial Acetic Acid Dehydration System via Heterogeneous Azeotropic Distillation Xiuhui Huang,† Weimin Zhong,*,‡ Wenli Du,† and Feng Qian*,† †
Key Laboratory of Advanced Control, Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China ‡ Department of Automation, East China University of Science and Technology, Shanghai 200237, China ABSTRACT: In the production of pure terephthalic acid, a tiny amount of reactant p-xylene and byproduct methyl acetate may enter into the acetic acid dehydration system through the feed stream. In this work, considering p-xylene and methyl acetate as feed impurities in the industrial acetic acid dehydration process using n-propyl acetate as entrainer, the binary parameters for the UNIQUAC model of the quinary system were obtained by correlating the phase equilibrium data from experiment and literature. Based on the physical property model, the distillation character of this quinary system in the industrial dehydration process was analyzed, the models of the dehydration process via heterogeneous azeotropic distillation were developed, and the process simulation was conducted with Aspen Plus. The simulation results of key parameters agree well with the process data with the errors within ±6%. Based on the process model, the sensitivity analyses of the bottom water content, reflux flow, two side-draws, and two heat feeds were conducted, which can provide theoretical guidance for the operation optimization study in future work.
1. INTRODUCTION Heterogeneous azeotropic distillation is commonly used in industry to break azeotropes and separate mixtures with close relative-volatility. Widely used industrial applications include ethanol or isopropyl alcohol dehydration and acetic acid (HAc) dehydration. Parametric sensitivity, multiple steady states, and long transient and nonlinear dynamics in heterogeneous azeotropic distillation were found by many authors using theoretical models and process simulation.1 These are known to be difficult to operate and control in heterogeneous azeotropic distillation columns. HAc dehydration is one of the most common industrial examples and an important operation in the production of aromatic acids, such as pure terephthalic acid (PTA). Othmer2 described an azeotropic distillation system containing a dehydrating column, a decanter, and a water column for the separation of HAc and water. Although HAc and water do not form an azeotrope at atmospheric pressure, the system has a tangent pinch on the pure-water end; to separate these two components using conventional distillation would require more equilibrium stages and a large reflux ratio. To make the separation easier, an entrainer is often introduced into the system. The entrainer used before 1932 was ethylene dichloride, and later the most generally used entrainers are acetic esters, such as n-propyl acetate (NPA), n-butyl acetate (NBA), i-butyl acetate (IBA), and ethyl acetate (EA).3 Chien et al.4discussed the design and control of the HAc dehydration system via heterogeneous azeotropic distillation using three candidate entrainers (EA, IBA, and NBA) and obtained the optimal column designs and operating conditions for these three candidate systems through rigorous process simulation. Chien et al.5 then investigated the influence of feed impurity on the design and operation of an industrial HAc dehydration column with IBA as the entrainer. Huang et al.6 and Lee et al.7 © 2013 American Chemical Society
also addressed the design and control of HAc dehydration column with p-xylene (PX) as feed impurity in which IBA was used as the entrainer. A side stream is needed in the design to handle the accumulation problem of this impurity. In normal operation, PX in HAc dehydration distillation column accumulates in the top of dehydration distillation column and decanter. Li8 analyzed reboiler duties at different concentrations of PX in the reflux in the system using NBA as the entrainer and suggested that the concentration of PX be decreased by draining some organic reflux if the mass fraction of PX accumulation exceeds 0.15. Most of the above-mentioned work about the HAc dehydration system was dedicated to the issues of process synthesis, design, and control, and few works focused on the influence and control of impurities in the industrial azeotropic distillation column. Moreover, only quaternary components containing unreacted reactant PX in the feed have been considered, and the physical parameters have been either collected from Aspen Plus build-in or from the literature. For an industrial HAc dehydration system of the PTA plant using NPA as entrainer, there are unreacted reactant PX and byproduct methyl acetate (MA) in the feed besides the solvent HAc and Water, so the system contains five components including HAc, Water, NPA, PX, and MA. The physical property of the quinary system (HAc+Water+NPA+PX+MA) is very complex because it has multiboiling points, homogeneous azeotropes, and heterogeneous azeotropes, especially its strong nonideality of vapor−liquid equilibrium (VLE) caused by the association of HAc due to dimerization and Received: Revised: Accepted: Published: 2944
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Figure 1. PFD of an industrial HAc dehydration process.
conducted. Based on the process model, the sensitivity analyses of the bottom water content, reflux flow, two side-draws, and two heat feeds were carried out, and operation optimization suggestions were proposed.
trimerization. The essence of the distillation process is a mass transfer process between light and heavy components via VLE, so the phase equilibrium thermodynamic character study and analysis of this quinary system must be carried out first so as to build a mechanism model to accurately simulate and describe the industrial HAc dehydration process. Most research shows that the nonideality of vapor phase caused by the association of HAc is commonly calculated with the second virial coefficient of the Hayden and O’Connell (HOC) model,9 and the nonideality caused by HAc in the liquid phase is considered by liquid activity coefficient models − Nonrandom Two-Liquid (NRTL) model10 and Universal Quasi-chemical (UNIQUAC) model.11 Sawistowski and Pilavakis12 measured the VLE data for the MA-Water-HAc system under 760 mmHg. Xiao et al.13 presented the liquid− liquid equilibrium (LLE) data of the Water-HAc-NPA system at 298.15 K, 313.15 K, and 363.65 K under 1 atm and also correlated the experimental data with the UNIQUAC model and obtained a good agreement. Lee and Lin14 experimentally determined that the quaternary mixture of Water-HAc-MA-PX had interesting phase behaviors of VLE and vapor−liquid− liquid equilibrium (VLLE) at 101.32 kPa. The experimental data of VLE and VLLE were listed out and correlated with the NRTL and UNIQUAC models. Chiu and Lee15 then studied the phase equilibrium of the ternary mixture of Water-HAc-PX. It is found that no ternary azeotropic existed, and the correlation by the UNIQUAC model was in good agreement with the experimental data of VLE and VLLE. To date, there is no complete binary parameter and phase behavior study in the literature for the quinary system containing HAc, Water, NPA, PX, and MA. In this work, based on the experimental VLE data at 101.33 kPa of four binary systems (HAc+PX, MA+NPA, MA+PX, and NPA+PX) measured in our previous work,16 the binary parameters for the UNIQUAC model of the quinary system were obtained by correlating the phase equilibrium data from experiment and literature. The distillation character of this quinary system in the industrial HAc dehydration process using NPA as entrainer was analyzed using these correlated parameters. Then the mechanism model of heterogeneous azeotropic distillation was developed, and the simulation of the industrial HAc dehydration process including dehydration column, PX pure column, and NPA recovered column was
2. PROCESS DESCRIPTION Figure 1 shows the process flow diagram (PFD) of an industrial HAc dehydration process with NPA as entrainer. F1, from which the feed impurities PX and MA come, is the water-draw-off (WDO) from the oxidation reactor and high pressure absorber; F2 is vapor from stripper recirculation; F3 is condensate from the combined first crystallizer; F4 is flash vapor from the second crystallizer. The four feeds are separated in the dehydration column C-1 using NPA as entrainer to make the top distillate D1 containing few HAc (ppm scale) and the bottom stream B1 containing 95 wt % HAc with the lowpressure steam Fs1 from F4 and the bottom reboiler providing the heat needed. S1 is a side-draw from the upper zone of C-1. A small quantity of PX accumulating in C-1 will weaken the column performance and the separation effect, so a side-draw S1 from the upper zone of C-1 is sent to the PX pure column C-2 to remove the accumulated PX in C-1, by introducing wastewater Fw to break the azeotropy and recover NPA in S1, and vapor Fs2 from F4 providing heat needed. The top distillate D2 returns to C-1, and the bottom stream B2 containing mainly PX and HAc is sent to the mother liquor tank and goes back to the reactor. The distillate from the top of C-1 is cooled in the cooler H-1, and then the condensate and vapor from H-1 go to the decanter D-1. The NPA makeup and NPA recycle are also feed to D-1. The mixture in D-1 is separated into organic phase which returns to C-1 as reflux R1, aqueous phase which is sent to the stripping section of NPA recovered column C-3, and the vapor phase is sent to the rectifying section of C-3. The C-3 is directly heated by bottom steam Fs3. Its top distillate is cooled by H-3, and the condensate D3 containing mainly MA goes back to the reactor to restrain side-reaction; its bottom stream B3 is sent to the wastewater user and sewage treatment plant after being cooled. The side-draw of C-3 S3 returns to the decanter for NPA recycle. 2945
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3. PHYSICAL PROPERTY AND PROCESS ANALYSIS 3.1. Phase Equilibrium Data. It is well-known that vapor− liquid equilibrium (VLE) of a multicomponent system can be predicted based on the VLE data of binary systems by NRTL and UNIQUAC models. For the quinary system in the HAc dehydration process which is operated under near atmospheric pressure, the isobaric binary VLE data under atmospheric pressure of Water+HAc was measured by many scholars such as Vercher et al.;17 NPA+HAc by Fu et al.;18 HAc+PX by Marek;19 MA+HAc by Sawistowski and Pilavakis;12 and MA +Water by Perelygin.20 For Water+NPA and Water+PX systems, which are partially miscible systems, the ternary LLE data of HAc+Water+NPA were measured by Xiao et al.13 and HAc+Water+PX by Chiu and Lee.15 The isobaric binary VLE data of MA+NPA measured by Korovina et al.21 presented thermodynamic inconsistency, and no VLE data of MA+PX and NPA+PX systems are available in the literature. In our previous work,16 the experiments were conducted with Ellis equilibrium still at 101.33 kPa to measure the isobaric VLE data of these three binary systems. The VLE data of the HAc+PX system were also measured to make a comparison with the literature data of Marek19 in order to ensure the reliability of experimental apparatus and skill. It can be seen that the experimental data fairly match the literature data except for a significant difference in vapor phase around 402 K as shown in Figure 2. The reason may be that the literature data are age-old and the analysis methods applied are different.
Table 2. Experimental VLE Data of MA(1)+NPA(2) at 101.33 kPa no.
Texp/K
x1exp
y1exp
no.
Texp/K
x1exp
y1exp
1 2 3 4 5 6 7 8
332.00 334.25 336.70 337.75 341.10 343.35 348.25 349.90
0.8984 0.7907 0.6883 0.6645 0.5665 0.4982 0.3684 0.3382
0.9899 0.9584 0.9316 0.9101 0.8573 0.8229 0.7303 0.6917
9 10 11 12 13 14 15
351.85 354.10 357.50 362.75 364.65 368.05 371.85
0.2943 0.2469 0.2006 0.1197 0.1031 0.0535 0.0172
0.6578 0.6117 0.5082 0.3640 0.3031 0.1817 0.0665
3.2. Correlation of VLE Data. Some commonly used computing methods for thermodynamic phase equilibrium data processing include Least Square Method, Weighted Least Square Method, and Maximum Likelihood Method et al. Anderson and Prausnitz22 addressed that it was necessary to consider experimental data errors when correlating the optimal parameter of model because of the large number of parameters and the unavoidable experimental error. The Maximum Likelihood Method considers the influence of each variable’s error into the objective function, while the others do not. Prausnitz,23 Kemeny et al.,17 and many other scholars all verified the advantage. In this work, we used this method to correlate the model parameter with the measured data. The objective function for the VLE data correlation is 2 ⎡⎛ e m⎞ ⎢⎜ T j − T j ⎟ Q = ∑ ⎢⎜ + σTj ⎟⎠ ⎝ j=1 ⎢ ⎣ NP
Nc − 1
∑ i=1
⎛ y e − y m ⎞2 ⎤ j,i ⎟ ⎥ ⎜ j,i ⎜ σy ⎟⎥ ⎝ ⎠ ⎥⎦ j,i
(1)
where Q is the objective function to be minimized by data correlation, NP is the number of points in data group n, Nc is the number of components included in the data group, T and y severally denote the temperature and vapor mole fractions, and i and j are the data for data points i and j, respectively. The parameter σ is the standard deviation of the indicated data, and σT = 0.05 K, σy = 0.003. The superscripts e and m in eq 1 mean the estimated and measured data, respectively. When the system reaches phase equilibrium, the fugacity of component i in liquid and vapor phase (f Li and f Vi ) should be equal fiL = γixif i0L = fiV = ϕi V yp i
Figure 2. VLE data of HAc+PX at 101.33 kPa.
where xi and yi denote the mole fractions of component i in liquid and vapor phase, γi is the activity coefficient in liquid phase, ϕVi is the fugacity coefficients in vapor phase, and f 0L i is the fugacity at standard states. γi and ϕVi can be calculated using the thermodynamic model, and the properties and related parameters for five pure components that are needed in the calculation have been listed in Table 5.24,25 In this work, the fugacity coefficient ϕVi in vapor phase is calculated using the HOC model,9 and the Aspen Plus26 builtin binary parameters were employed. There are no parameters of NPA built-in in Aspen Plus, so we choose the values of its homologue n-butyl acetate (NBA) instead. All the HOC binary parameters are listed in Table 6. The liquid activity coefficient γi is calculated by the UNIQUAC model.11 The UNIQUAC model parameters for the quinary system were correlated using Maximum Likelihood Method with the phase equilibrium data from literature and experiment above. In order to be in accordance with the units and functional form in process
The measured binary VLE experimental results (x1exp and y1exp are all expressed as mole fraction) are shown as in Tables 1−4. Table 1. Experimental VLE Data of HAc(1)+PX(2) at 101.33 kPa no.
Texp/K
x1exp
y1exp
no.
Texp/K
x1exp
y1exp
1 2 3 4 5 6 7
401.46 396.13 391.81 389.76 389.50 388.45 388.44
0.0783 0.2092 0.3632 0.5111 0.5520 0.6772 0.7561
0.3326 0.5334 0.6346 0.6988 0.7167 0.7564 0.7878
8 9 10 11 12 13 14
388.51 388.38 388.40 388.46 388.50 388.67 389.63
0.7782 0.7989 0.8213 0.8597 0.8828 0.8990 0.9561
0.7960 0.8067 0.8186 0.8409 0.8552 0.8705 0.9226
(2)
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Table 3. Experimental VLE Data of NPA(1)+PX(2) at 101.33 kPa no.
Texp/K
x1exp
y1exp
no.
Texp/K
x1exp
y1exp
1 2 3 4 5 6 7 8 9 10
375.30 375.70 376.75 377.75 379.05 379.93 381.15 383.10 384.95 389.75
0.9412 0.8801 0.8022 0.7432 0.6720 0.6646 0.5792 0.5158 0.4598 0.3228
0.9835 0.9559 0.9161 0.8892 0.8531 0.8398 0.8032 0.7779 0.7115 0.5958
11 12 13 14 15 16 17 18 19
391.55 393.95 395.50 397.85 399.55 402.40 404.05 406.35 407.65
0.2708 0.2289 0.1777 0.1407 0.1024 0.0840 0.0627 0.0364 0.0206
0.5530 0.4920 0.4318 0.3645 0.2955 0.2354 0.1796 0.1115 0.0636
simulation software Aspen Plus, the effective binary interaction τij in the UNIQUAC model was expressed as
Table 4. Experimental VLE Data of MA(1)+PX(2) at 101.33 kPa no.
Texp/K
x1exp
y1exp
no.
Texp/K
x1exp
y1exp
1 2 3
411.51 383.40 369.65
0.0000 0.0374 0.0635
0.0000 0.6595 0.8250
4 5 6
358.85 345.10 330.10
0.1172 0.3350 1.0000
0.9266 0.9684 1.0000
τij = exp(Aij + Bij /T + Cij ln T + DijT )
where Aij, Bij, Cij, and Dij are the binary parameters of the UNIQUAC model, and T/K is the temperature. We use τij = exp(Aij + Bij/T) for simplification and to correlate the binary parameters Aij and Aij. The correlated parameters of these 8 systems are shown in Table 7, and the estimated binary VLE Tx-y results using correlated parameters for these systems are shown in Figure 3 to make a comparison with measured data. For Water+NPA and Water+PX, which are partially miscible systems, Prausnitz23 proposed that binary VLE data, binary LLE data, and ternary LLE tie line data are needed to correlate the UNQUAC model parameters in order to make accurate prediction of multivariate phase equilibrium. Because of the lack of phase equilibrium data, we use the Aspen Plus26 built-in literature LLE-ASPEN parameters shown in Table 8 for these two binary systems, and the comparison results of the LLE estimated results and the literature measured LLE data for the ternary systems13,15 are shown in Figure 4. As shown in Figure 3 and Figure 4, it can be noted that the estimated results agree well with the measured data of all systems except the MA+PX system. There is an obvious deviation between the estimated results and measured results of the MA+PX system in the vapor phase, probably because it is difficult to obtain consistent VLE data due to the dramatically different boiling points and bumping phenomenon of this system. However, the trend of the data is in accord with the general rule of this kind of systems, and the results in the liquid phase fit well and all follow the same trend. 3.3. Physical Property Analysis. For the quinary system in the HAc dehydration process with PX and MA as impurities, the computed azeotropic compositions (hereinafter in order to comply with the process data, the composition is expressed as mass fraction (wt%)) and temperatures using theses parameters above are listed in Table 9. The temperatures of the normal boiling points of the pure components and azeotropes can be ranked as follows:
Table 5. Properties and Related Parameters for Four Pure Components24,25 physical quantity
water
HAc
molecular 18.015 60.053 weight (MW) boiling point 373.15 391.04 (Tb/K) critical 647.13 591.95 temperature (Tc/K) 22.064 5.775 critical pressure (Pc/MPa) critical volume 55.95 179.7 (Vc/mL/mol) Molecular Structure Parameters volume 0.92 2.20 parameter (r) area parameter 1.40 2.07 (q) associating 1.70 4.50 parameter (ηasso) 0.17 2.60 average cyclotron radius (RD/Å) dipole (μ) 1.83 1.74 Antoine Constanta A 11.6834 10.1878 B 3816.44 3405.57 C −46.13 −56.34 Tmin/K 284 290 Tmax/K 441 430 a
NPA
MA
PX
102.133
74.079
106.167
374.65
330.09
411.53
549.35
506.55
616.20
3.363
4.694
3.511
345.03
228
378
4.15
2.80
4.66
3.66
2.58
3.54
0.53
0.85
0.00
3.75
2.86
3.80
1.80
1.72
0.00
9.5410 2956.70 −64.36 278 375
9.9048 2811.41 −45.94 273 463
9.4761 3346.65 −57.84 300 440
Antoine equation: ln Ps/bar = A − B/(T/K + C).
Table 6. HOC Binary Parameters HAc Water PX MA NPA
HAc
Water
PX
MA
NPA
4.5 2.5 0.4 2 2
2.5 1.7 0 1.3 1.3
0.4 0 0 0.6 0.6
2 1.3 0.6 0.85 0.53
2 1.3 0.6 0.53 0.53
(4)
Water‐MA(329.5 K) < MA(330.2 K) < Water‐NPA(356.31 K) < Water‐PX(365.44 K) < Water(373.17 K) < NPA(374.59 K) < HAc‐PX(388.4 K) < HAc(391.16 K) < PX(411.52 K) 2947
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Table 7. UNIQUAC Binary Parameters of 8 Correlated Systems parameter comp i comp j Aij Aji Bij/K Aij/K
remarks Water HAc 0.046 −2.918 128.083 877.943
NPA HAc 12.541 −6.011 −5103.140 2439.448
HAc PX 3.957 −9.981 −1519.200 3608.611
MA HAC 5.746 −3.328 −2315.220 1348.713
There are 5 pure components and 4 azeotropes; PX has the maximum boiling temperature, and Water-MA has the minimum azeotropic boiling temperature of the system. According to the design principle of this separation system, the dehydration column (C-1) has all the 9 boiling points components, so it has the most complex character. The entrainer NPA is added into the C-1 to avoid the tangent pinch of the pure-water side at the top of the column. The MA mostly comes out from the top of C-1 as azeotrope Water-MA. The PX can form azeotropes with water and HAc, so it is mainly accumulated in the upper zone of C-1 between the two azeotropes’ boiling points 356.31 K (Water-NPA) and 388.4 K (HAc-PX). Its presence changes the relative volatility of water and HAc, which has a great effect on the separation of water and HAc, so a side-draw from the upper side of C-1 (between 356.31 K and 388.4 K) is sent to the PX pure column C-2 to remove the accumulated PX in C-1. Without considering the impurities PX and MA, the residue curve map (RCM) of the HAc-Water-NPA system in C-1 is shown as Figure 5. It can be found that the column top vapor composition and temperature should be near the NPA-Water azeotrope (point D), whereas the bottom should be near the pure HAc corner. The bottom composition is 95 wt % HAc and 5 wt % Water (point B) according to the process data, so the composition profile of C-1 should be consistent with the trend of curve A across points B and D. In C-2, a wastewater stream Fw is introduced in at the top of C-2 to break the azeotropic balance and reform low-boiling azeotropes with MA, NPA, and part of PX in the side-draw S1. With a certain amount of water from Fw and heating steam from Fs2, these low-boiling azeotropes can mostly go back into C-1 from the top of C-2, and the other part of PX and most of HAc in S1 can go back to the reactor from the bottom of C-2. Thus, the NPA is S1 can be recovered, and the accumulated PX in C-1 can be removed. Without considering MA, the RCM of the PX-Water-NPA system and the HAc-Water-PX system in C-2 are shown as Figure 6 and Figure 7. As seen in the figure, due to the distillation boundary, the column top vapor composition and temperature are decided by the quantity of the heat steam of the column bottom and should be one point on the curve EF in Figure 6 for the PX-Water-NPA system and one point on the curve DE in Figure 7 for the HAc-Water-PX system, whereas the bottom is decided by the feed. The top composition is as point D shows in Figure 6 and the bottom composition is as point B shows in Figure 7 according to the process data, so, in C-2, the composition profile of PX-WaterNPA should be consistent with the trend of curve A across D in Figure 6 and it of HAc-Water-PX should be consistent with the trend of curve A across B in Figure 7. The composition profile of C-2 should be consistent with the combined effects of the two composition profile curves. The overhead vapor of C-1 is mainly heterogeneous azeotrope NPA-Water and also contains most MA and part
MA Water −17.966 2.009 5504.401 −688.879
NPA PX 0 0 120.006 −169.884
MA NPA −19.485 −0.320 5921.619 433.949
MA PX −5.884 1.900 1861.191 −676.366
of PX of this system. It is sent into the decanter after condensing to the azeotropic point of NPA-Water in the condenser to mix with the NPA makeup and NPA recycle from C-3 and then gets VLLE. As shown in Figure 5, the composition of HAc-Water-NPA entering into the decanter is near point D; according to the tie line in Figure 6, the composition of aqueous phase should near point E, the organic phase should near point F, and the vapor phase should near point G after the mixture gets phase equilibrium. Considering PX and MA in it, MA is almost in the vapor phase because its boiling point is lower than the decanter temperature, and it can be seen in Figure 6 that almost all the PX should be in the organic phase because there are few PX in the aqueous phase when the mixture of PX-Water-NPA gets phase split. All the vapor phase and aqueous phase are sent to C-3, so it is mainly the Water-NPA-MA system separated in C-3. The RCM of the Water-NPA-MA system in C-3 is shown as Figure 8. The composition of the side-draw is as point S shows in Figure 8 according to the process data, so, in C-3, the composition profile of Water-NPA-MA should be consistent with the trend of curve A across S in Figure 8. The column top vapor composition and temperature should be near the MA-Water azeotropes (point D), whereas the bottom should be near the pure water corner (point B).
4. INDUSTRIAL PROCESS MODELING AND SIMULATION 4.1. Process Modeling and Simulation. For the steadystate mathematical model of rectifying tower, in this paper, a VLL three-phase mechanism model based upon a rigorous equilibrium stage model for solving the mass balance (M), phase equilibrium (E), summation (S), and energy balance (H) equations is adopted, and the most commonly used Murphree efficiency is adopted to correct the departure from equilibrium in the industrial column. According to the phase equilibrium thermodynamic character study and analysis of the quinary system above, the UNIQUAC-HOC model of Aspen Plus, whose binary association parameters were made up and modified by the data in Tables 6−8, is chosen to compute and amend the phase equilibrium coefficient. Referring to the process specification,27 C-1 is a 3-layer structure packed column, C-2 is a 25-tray column, and C-3 is a mix-structure column with 16-tray in the upper section and packing in the lower section. In this paper, the packed column is converted to equivalent tray column to simulate according to the theoretical tray number calculation. Table 10 shows the tray number (Nt), operation pressure (P), presser drop (ΔP), the feed and side-draw stream tray number, and the desired product purities of each column. For the heterogeneous quinary system of this study, the RadFrac model in Aspen Plus which can perform rigorous three-phase calculations is chosen to simulate the heteroge2948
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Figure 3. Binary VLE T-x-y diagrams (M-measured, E-estimated; x and y are mole fraction.). Measured data of Water+HAc is from Vercher et al.;17 NPA+HAc from Fu et al.;18 MA+HAc from Sawistowski and Pilavakis;12 and MA+Water from Perelygin.20
phase flash vessel model is for the decanter. Then add a module such as splitter, condenser, pump, etc., and also each feed stream and discharge stream according to the process specification. According to the process data as shown in
neous azeotropic distillation of the HAc dehydration columns system. A RadFrac model with reboiler and without condenser is for C-1, one with neither reboiler nor condenser is for C-2, one with both reboiler and condenser is for C-3, and a three2949
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recycle” method is used to make the process model easily to adjust and converge. That is to treat the reflux R1 as a feed of C-1 and input its temperature, pressure, flow rate, and composition according to the process data as its initial value. Then calculate the model by a trial and error method until the error between the organic phase comes from the decanter and the reflux is small enough. For the streams D2 recycled to C-1 and S3 recycled to D-1, the streams S1, Dw, and Dv which connect two units, the same method is adopted as R1. Until the error between the two broken streams is small enough, connect these broken streams S1, Dw, and Dv by the “trans from to” tool first, then connect the recycled streams D2 and S3 until all the calculated specs of each unit agree well with the process data, and get the process model all through and converged ultimately. The physical property of C-1 is complex, so the convergence method ”Azeotropic” build-in Aspen Plus which is appropriate for large nonlinear equations of a strong nonideal and azeotrope system is chosen. For the relatively simple columns C-2 and C-3, the standard convergence method build-in Aspen Plus is chosen. On the premise of model convergence, the objective is to make each key performance indicator of the model be in an allowable error scope and to get a relatively minimum average error of the overall simulation results. The HAc dehydration process especially the unit C-1 is hard to converge for its complicate character. The adjusting method can be decided according to the simulation results and error analysis of the model. The initial value of the model is vital for the convergence, and it will accelerate the model convergence rate greatly to replace the initial value repeatedly with the relatively better simulation results including the temperature, composition, and the flow rate of vapor and liquid of each tray in the “Estimate” module of Aspen Plus. If the design specs do not satisfy the requirements according to the simulation result, we can gradually increase or decrease the design specs toward the simulation result value and then gradually decrease or increase the design specs toward the required value after the model converge. In addition, each input parameter of the model, such as the temperature, flow rate, composition, and tray number of feed, and the flow rate and tray number of side-draw, has a certain effect on the model convergence, so we can make small changes to them in the allowable error scope to help the model convergence and disperse the result error of each specs of the
Table 8. UNIQUAC Binary Parameters of Water+NPA and Water+PX parameter comp i comp j Aij Aji Bij/K Bij/K Cij/K Cij/K
remarks Water PX −42.494 37.147 1588.464 −1764.090 6.330 −6.049
Water NPA −26.902 31.708 1604.009 −2633.390 3.708 −4.281
Table 11,27 input the temperature, pressure, flow rate, and composition of each feed and the flow rate of side-draw. Column setting refers to Table 10. For C-1, the bottom flow rate is set as a manipulated variable and 5 wt % water content of the bottom flow as the design value while the reflux rate as control variable. For C-2, the flow rate of Fw is about 1/3 of S1, and Fs2 is the manipulated variable which is set in flow split S-1 to ensure the recovery of NPA and the removal of accumulated PX. For C-3, the top distillate rate and the reboiler duty are set as manipulated variables. The temperature and pressure of the condenser is 356.15 K and 0.12 MPa, and so is the decanter. The pure NPA makeup for the decanter is 20.5 kg/h with 298.15 K. The heterogeneous azeotropic distillation system of this study is extremely complex. Its parameters sensitivity, multiple steady states, long transient, highly nonlinear dynamics, and so on, all make the model difficult to converge. These characteristics of heterogeneous azeotropic distillation were discussed by Bekiaris et al.28 and Alliet-Gaubert et al.29 The ethanol/water separation, studied in detail by Ryan, Doherty,30 and W. L. Luyben,31 was used as an example, and the difficulties of performing the steady-state design of this highly nonlinear and multiple steady states system with two recycle streams were also discussed. In this study, there is not only a quinary system with two heterogeneous azeotropes but also three columns and three recycle streams in the HAc dehydration columns system. It is extremely difficult to simulate it to be identical with the actual industrial process on the condition that it converges well. There is no entrainer NPA feed into the column because it is recycled in the system when the process is under normal operation, and the model does not calculate the component which is not contained in the feed. So for C-1, the “breaking
Figure 4. LLE curve for HAc-Water-NPA and HAc-Water-PX (M-measured, E-estimated; x is mole fraction.). Measured data of HAc+Water+NPA is from Xiao et al.13 and HAc+Water+PX from Chiu and Lee.15 2950
dx.doi.org/10.1021/ie3012006 | Ind. Eng. Chem. Res. 2013, 52, 2944−2957
Industrial & Engineering Chemistry Research
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Table 9. Computed Azeotropic Compositions (Mass Fraction) and Temperatures temp, K
type
HAc
Water
PX
MA
NPA
329.5 356.31 365.44 388.4
homogeneous heterogeneous heterogeneous homogeneous
0 0 0 0.7117
0.0288 0.1664 0.3429 0
0 0 0.6571 0.2883
0.9712 0 0 0
0 0.8336 0 0
Figure 5. RCM of HAc-Water-NPA in C-1 (mass fraction). Figure 7. RCM of HAc-Water-PX in C-2 (mass fraction).
Figure 6. RCM of PX-Water-NPA in C-2 (mass fraction). Figure 8. RCM of Water-NPA-MA in C-3 (mass fraction).
model. Furthermore, the plate efficiency is also a critical influencing factor of the column separating effect, so we can set different efficiency in different tray sections and change it gradually according to the simulation results. During the regulation process, it is necessary to use the regulation methods above alternately to get a relatively optimal convergence result within allowable error scope on the premise of satisfying all process indexes. C-1 is a 3-layer structure packed column, so we divide it into 3 sections (rectifying section, middle section, and stripping section) to set its Murphre efficiency. When the model reaches a relatively optimal result, the final Murphre efficiency of these 3 sections is 0.7, 0.7, and 0.6, respectively. The Murphre efficiency of C-2 is 0.8 and C-3 is 0.85. 4.2. Simulation Results and Analysis. Figures 9−11 show the simulated results of temperature, vapor composition, and liquid composition profile in each column. There should be
two liquid phases at some of the stages in the three columns, so the composition profiles for liquid-1 and liquid-2 are also given out, and the figures show that there are two liquid phases at stages 1−21 in C-1, stages 1−24 in C-2, and stages 12−16 in C3 where the composition profiles for liquid, liquid-1, and liquid2 are different. According to the physical property analysis of the three columns in section 3.3 above, it can be seen that the simulation results agree with the analysis results on the whole comparing to the temperature and composition of each columns’ top and bottom. Table 12 shows the data comparison between simulation results and process data of the HAc dehydration process. It shows that the simulation results agree well with the process data. Compared to the process data, the errors of simulation results of key parameters are almost within ±3%, the maximum 2951
dx.doi.org/10.1021/ie3012006 | Ind. Eng. Chem. Res. 2013, 52, 2944−2957
Industrial & Engineering Chemistry Research
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Table 10. Specifications of Each Column column
Nt
P/ΔP, MPa
streamtray
C-1
61
0.12/0.01
C-2
25
0.12/0.02
C-3
31
0.11/0.01
F1-21# F2-45# F3-45# F4-45# R1-1# D2-21# S1-20# S1-1# Fs225# Fw-1# Dv-16# Dw17# Fs331# S3-16#
desired product purities B1:5 wt % Water, D1: ppm HAc, S1: 367.15 K
B2: ppm NPA, B2: 384.15 K
B3: ppm NPA, D3: >97 wt % MA, S3: 353.15 K
Table 11. Specifications of Input Streams stream
T, K
P, Mpa
flow rate, kg/h
F1
351.15
1.54
71158.7
F2 F3 F4 S1 Fw Fs2 Fs3 S3
402.15 392.15 431.35 313.15 431.35 421.15 -
1.17 0.14 0.43 1.43 0.43 0.45 -
24468.1 32911.5 27970 2700 850 2980 4000 16000
composition (mass fraction) 0.681HAc, 0.283Water, 0.002PX, 0.034MA 0.832HAc, 0.158Water, 0.01MA 0.857HAc, 0.138Water, 0.005MA 0.87HAc, 0.12Water, 0.01MA 0.001HAc, 0.999Water 0.87HAc, 0.12Water, 0.01MA Pure Water -
one is not more than ±6%. Thus, it indicates that the correlated binary parameters are appropriate for the quinary heterogeneous azeotropic system, and the mechanism model can describe the HAc dehydration process accurately. The property method and setting rules used in the model have wide extensionality, so that it can further be used for different operation conditions simulation, sensitivity analysis, dynamic simulation, control study, optimization, and so on. 4.3. Sensitivity Analysis. Based on the operating experience of a plant and the analysis of the mechanism model, the bottom water content and the reflux rate of C-1 are the key parameters mainly affecting the energy consumption of the dehydration system. The feed flows Fs2 and Fs3 which provide heat the system needed and the flow rate of side-draws S1 and S3 also will directly influence the separation performance of the columns. It is necessary to do the sensitivity analysis of these parameters first for the operation optimization. Based on the built model and simulation above, the sensitivity analysis shows that the variation of reboiler duty with the bottom water content in C-1 is as the trends shown in Figure 12. As Figure 12 shows, increasing the bottom water content makes the reboiler duty reduced obviously. That is, there will be more than 1.5 t/h low-pressure steam saved if to reduce the bottom water content by 0.5 wt %. The variation of reboiler duty and the bottom water content may have influence on the top HAc content and the consumption of entrainer NPA in C-1, so the sensitivity
Figure 9. Temperature, vapor composition, and liquid composition profile in C-1.
analysis of the top HAc content and the bottom NPA content varying with the reboiler duty in C-1 is investigated. As the analysis results show in Figure 13, the top HAc content is pretty much constant and remains ppm scale as the 2952
dx.doi.org/10.1021/ie3012006 | Ind. Eng. Chem. Res. 2013, 52, 2944−2957
Industrial & Engineering Chemistry Research
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Figure 10. Temperature, vapor composition, and liquid composition profile in C-2.
Figure 11. Temperature, vapor composition, and liquid composition profile in C-3.
reboiler duty decreases, meanwhile the bottom NPA content has an inconspicuous rising trend for it is extremely small as such.
To further confirm the influence, a flash vessel model with the liquid stream coming from the 60th stage of the dehydration column as feed is chosen to investigate the variation of the NPA content in the liquid and vapor phase of 2953
dx.doi.org/10.1021/ie3012006 | Ind. Eng. Chem. Res. 2013, 52, 2944−2957
Industrial & Engineering Chemistry Research
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Table 12. Data Comparison between Simulation Result and Process Data column
item
process data
simulated result
relative error, %
C-1
top pressure, MPa pressure drop, kPa top temperature, K bottom temperature, K side-draw temperature, K top distillate, kg/h bottom stream, kg/h side-draw, kg/h top HAc content, wt% bottom water content, wt% side-draw PX content, wt% reflux, t/h reboiler duty, MMkcal/h condenser duty, MMkcal/h top pressure, MPa pressure drop, kPa top temperature, K bottom temperature, K top distillate, kg/h bottom stream, kg/h bottom PX content, wt% bottom NPA content, wt% bottom steam, kg/h top pressure, MPa pressure drop, kPa top temperature, K side-draw temperature, K top distillate, kg/h side-draw, kg/h top MA content, wt% bottom water content, wt% side-draw NPA content, wt% bottom stream, kg/h condenser duty, MMkcal/h
0.12 10 359.15 392.15 369.15 201988.9 124545.6 2699.6
