Design and Control of a Complete Azeotropic Distillation System

Article pubs.acs.org/IECR

Design and Control of a Complete Azeotropic Distillation System Incorporating Stripping Columns for Isopropyl Alcohol Dehydration Wen-Teng Chang,† Chi-Tsung Huang,† and Shueh-Hen Cheng*,† †

Department of Chemical and Materials Engineering, Tunghai University, Taichung 40704, Taiwan ABSTRACT: As demonstrated by Pham and Doherty [Chem. Eng. Sci. 1990, 45, 1823] in an ethanol dehydration process and by Arifin and Chien [Ind. Eng. Chem. Res. 2007, 46, 2535] in an isopropyl alcohol dehydration process, a three-column heterogeneous distillation sequence which contains a preconcentrator column, an azeotropic column, and an entrainer recovery column is more energy saving than two-column and four-column sequences. The three-column sequence for the isopropyl alcohol (IPA) dehydration process, according to Arifin and Chien, is more energy-saving than the two-column sequence, but the capital cost of the entire sequence is more expensive than that of the two-column sequence. Because the reflux ratio used either in the preconcentration column or the recovery column of the three-column IPA dehydration system is quite small, these two conventional distillation columns are both replaced by a stripping column, and in this study a new separation scheme is thereby developed. The economic analysis of the proposed system shows there is more saving in energy and capital costs than the twoand three-column sequences aforementioned. Further, in developing a plant-wide control structure, a tray temperature control loop is implemented in each of the three columns which regulates reboiler duty in order to maintain the bottom product compositions for the new scheme, and ratio control of the organic reflux flow to the feed flow rate of the azeotropic column is used to reject feed rate disturbance. The purities of water achieved in the preconcentrator and entrainer recovery columns are greater than 99.88 mol %, and the IPA purity in the product stream is greater than 99.99985 mol %. Closed-loop responses to ±20% changes in fresh feed rate and feed H2O composition show that the proposed strategy has good control performance.

1. INTRODUCTION The heterogeneous azeotropic distillation systems are frequently encountered in the chemical process industry for separating mixtures of close boilers or breaking azeotropes. One advantage of using this type of separation system is that one can utilize a decanter to cross a distillation boundary for obtaining high purity products. It is oftentimes a continuous process in which entrainer selection is a critical element in maintaining the product quality. One often applies this technique in industrial dehydration processes, such as alcohol dehydration and acetic acid dehydration processes. Widagdo and Seider1 gave a good review on azeotropic distillation. They pointed out that the heterogeneous azeotropic distillation column is difficult to operate and control. Pham and Doherty2 studied three different separation sequences for the ethanol−water−benzene system, which includes four-column, three-column, and two-column heterogeneous distillation sequences. The three-column sequence contains a preconcentrator column, an azeotropic column, and an entrainer recovery column. The two-column sequence, in fact, combines the preconcentrator column and the recovery column as one. Later, Ryan and Doherty3 pointed out that the four-column sequence has no advantage over the three-column sequence, and that the three-column sequence has lower operating costs but higher capital costs than the two-column sequence, so that the total annualized cost is about the same for both sequences. Recently, Luyben4 proposed a control strategy of a three-column sequence for ethanol dehydration. Chien et al.5 proposed a design and control system for a two-column sequence of isopropyl alcohol (IPA) dehydration. Arifin and Chien6 compared two-column and three-column sequences of IPA dehydration for a diluted IPA feed. They found that the operating cost © 2012 American Chemical Society

of a three-column sequence is slightly less than that of the twocolumn sequence, but the capital cost of the former is more than that of the latter. Nevertheless, their results are almost the same as that of Ryan and Doherty.3 Furthermore, Wu and Chien7 presented a design and control study for pyridine dehydration using a two-column sequence. On the other hand, distillation is one of the most energy intensive processes in the chemical and petrochemical industries. Due to rising oil prices and an increasing demand for reducing CO2 emissions, recent process design technologies tend to go for energy-saving options. In this context, this study explores the possibility of improving the design and control of an existing heterogeneous azeotropic distillation system for purposes of reducing energy consumption.

2. STEADY-STATE DESIGN OF THE OVERALL PROCESS The study considers the design of an isopropyl alcohol (IPA) dehydration system with a feed composition of 50 mol % IPA and 50 mol % water and a feed rate of 100 kmol/h at 25 °C. Cyclohexane is used as an entrainer for the system, and a decanter is employed for the scheme and is operated at 40 °C. Purities are set at 99.9999 mol % IPA for the IPA product stream and 99.9 mol % H2O for the wastewater stream. These specifications were, in fact, adopted by Arifin and Chien.6 Similar to the approach by Arifin and Chien,6 Aspen Plus is Received: Revised: Accepted: Published: 2997

September 5, 2011 December 22, 2011 January 4, 2012 January 4, 2012 dx.doi.org/10.1021/ie202021g | Ind. Eng.Chem. Res. 2012, 51, 2997−3006

Industrial & Engineering Chemistry Research

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Figure 1. Operating conditions for Scheme 1.

Figure 2. Operating conditions for scheme 2.

composition of the preconcentrator column is close to that of the IPA-water azeotrope. A small makeup stream of entrainer is added to the decanter. The organic entrainer-rich phase of the decanter is refluxed back to the heterogeneous azeotropic column, and the aqueous phase is sent to the recovery column. Their respective bottom products are 99.9999 mol IPA and 99.9 mol % water. An alternative two-column sequence, which was proposed by Arifin and Chien,6 is shown in Figure 2 and named as Scheme 2 here. One difference from these two Schemes is that the feed stream of Scheme 2, mixed with the aqueous-phase of the decanter, flows directly into the recovery column, and there is no preconcentration column in Scheme 2. According to Ryan and Doherty3 and Chien et al.,5 the threecolumn sequence (Scheme 1) can save more energy than the

employed for the rigorous steady-state simulation in this study. The vapor phase of the system is assumed to be ideal, and the NRTL model is used to describe the nonideality of the liquid phase. In addition, a set of NRTL binary parameters is obtained from Wang et al.9 All other physical properties are obtained from the Aspen Plus data bank. A three-column sequence, which was studied by Arifin and Chien,6 is shown in Figure 1 and is named as Scheme 1 in this study. As shown in Figure 1, the fresh dilute feed stream flows into a preconcentrator column (C101). The bottom product of the preconcentrator column is 99.9 mol % of water. The distillate of the preconcentrator column is mixed with a recycle stream from an entrainer recovery column (C301) and flows into a heterogeneous azeotropic column (C201). The distillate 2998

dx.doi.org/10.1021/ie202021g | Ind. Eng.Chem. Res. 2012, 51, 2997−3006


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Figure 3. Operating conditions for Scheme 3.

two-column sequence (Scheme 2). From the simulation results of Arifin and Chien,6 it can be found that the reflux ratio used either in the preconcentration column or the recovery column in Scheme 1 is quite small. Also, the variation of the reflux ratio in either of these two distillation columns may not be so important, since there is no rigid specification in the top product stream. This can be interpreted as that either of these two columns requires a very pure bottoms product, but a pure top product is not needed. Thus, these two conventional distillation columns can be replaced by two stripping columns. A stripping column can be thought of as a conventional distillation column with no external reflux in the rectifying section. In contrast, one shortcoming associated with the conventional distillation column is that it has a reboiler to vaporize liquid in the stripping section and also has a condenser to condense vapor in the rectifying section. From the perspective of energy conservation, a stripping column is a tower without a condenser, in which energy carried by the overhead vapor is conserved instead of being removed in a condenser, and is considered to be more energy-efficient here than the conventional distillation. In addition, using the stripping column to replace the conventional distillation column can not only reduce energy cost but also cut capital cost. Accordingly, a modified separation system, named Scheme 3 here, is proposed in this study, for which a simple process flow diagram (PFD) is presented in Figure 3. As shown in Figure 3, the fresh feed (stream 1) flows into a preconcentration stripping column (C101), yielding a highpurity water stream (99.9 mol %) at the bottom (stream 10) and an overhead vapor stream (stream 3). This vapor stream then mixes with the overhead stream (stream 9) of another stripping column (C301) to form a feed stream (stream 4) to a heterogeneous azeotropic column (C201). An ultrahigh purity (99.9999 mol %) IPA product, i.e, stream 11, can be obtained in the bottoms. The overhead vapor of C201 (stream 5), whose

composition is close to that of the ternary azeotrope, then passes through a total condenser and is cooled to 40 °C. The condensate from the condenser is split into two liquid phases at the decanter where the organic phase (stream 7) is refluxed to the top of the heterogeneous azeotropic column, and the aqueous phase (stream 8) flows into the entrainer-recovery stripping column (C301). A product stream (stream 12) containing 99.9 mol % water can be easily obtained at its bottom of this stripping column. In order to facilitate the transport of overhead vapor streams from C101 and C301, the top pressures of C101 and C301 are both set at 1.1 atm, while that of C201 is set at 1.05 atm, instead of fixing all column pressures at 1 atm as in the work of Arifin and Chien.6 A stream summary for this flowsheet based on rigorous simulation results with Aspen Plus is presented in Table 1. Residue curve map (RCM) and conceptual material balance (MB) lines for Scheme 3 including MB lines for Columns C101, C201, and C301 can be visualized in Figure 4 with major process streams being labeled.

3. ECONOMIC ANALYSIS In order to evaluate the cost effectiveness of these three schemes, viz. the flowsheets in Figures 1−3, an economic analysis is performed in this study. All of these schemes are designed under the same operating conditions, i.e. the same inputs and outputs, the same cooling water temperature, and the same steam conditions, etc. These operating conditions in fact come from Arifin and Chien.6 Column diameter for each distillation unit is estimated using the Aspen Plus, and a tray spacing of 0.6 m and flooding of 80% are assumed. The overall tray efficiency for each column is conservatively assumed to be 50%.5,6 Thus, the height of each column (H) is estimated from the number of actual plates (Nactual) and disengagement heights as 2999



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Table 1. Stream Summary Based on Simulation Results for Scheme 3 stream number

1

2

3

4

5

6

7

pressure (atm) temperature (°C) vapor fraction mole frac CyH IPA H2O total flow (mol/min) stream number

1.20 25.0 0

1.00 25.0 0

1.10 82.7 1

1.10 82.0 0.99998

1.05 65.0 1

1.00 40.0 0

1.00 40.0 0

0 0.5 0.5 1666.67 8

1 0 0 1.34 × 10−4 9

0 0.610320 0.389680 1364.91 10

0.030453 0.586216 0.383331 3516.48 11

0.534671 0.260252 0.205077 6698.69 12

0.534671 0.260252 0.205077 6698.69 13

0.865440 0.128140 0.006420 4014.73 14

pressure (atm) temperature (°C) vapor fraction mole frac CyH IPA H2O total flow (mol/min)

1.00 40.0 0

1.10 81.6 1

1.16 103.5 0

1.20 86.9 0

1.16 103.7 0

1.20 40.0 0

1.20 40.0 0

0.039899 0.457875 0.502227 2683.97

0.049771 0.570925 0.379304 2151.57

0.000000 0.001000 0.999000 301.76

trace 0.999999 0.000001 832.52

trace 0.001000 0.999000 532.39

0.865440 0.128140 0.006420 4014.73

0.039899 0.457875 0.502227 2683.97

Figure 4. RCM and material balance lines for Scheme 3.

Economic analysis in this study follows closely the method of Turton et al.9 To estimate the capital cost, bare module equipment cost (CBM) is calculated for each unit. The bare module cost (CBM) is a function of purchased cost (Cp0), bare module cost factor (FBM), number of trays (N) in the column, and quantity factor ( fq) based on the number of trays in the column, i.e.

H = (Nactual − 1)(tray spacing) + disengagement heights

(1)

According to Truton et al.,9 we add 1.2 m for vapor disengagement at the top and 1.8 m at the bottom for liquid level and reboiler return. In addition, the overall heat transfer coefficients are 850 and 1140 (W/m2°C) for condenser and reboiler, respectively. The correction factor9 of 0.9 for logarithmic mean temperature difference (LMTD) is used for each heat exchanger. Low pressure steam is assumed to be available at 5 barg (160 °C) and cooling water of 30 °C is employed. A stream factor9 of 0.95, which is the fraction of working days in a year, is used for calculating the yearly cost of utilities. The decanter is sized with a liquid holdup of 20 min half full and an aspect ratio (length-to-diameter ratio) of 3. It should be noted that the above design specifications together with utility costs are obtained from Truton et al.9 Table 2 gives an equipment list with sizing results for all major equipment units.

CBM = C p0FBM for vessels and heat exchangers CBM = C p0FBMNfq for sieve trays in the column

(2)

The purchased cost for base conditions (Cp0) is calculated by

log10 C p0 = K1 + K2 log10(A) + K3[log10(A)]2

(3)

where K1, K2, and K3 are constants specific to the type of equipment, and A is the capacity/size parameter of the equipment. 3000



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Table 2. Constants of Bare Module Equipment Cost E101 E201 E301 E102 E202 E302 V101 C101 C201 C301 a

equipmenta

type

K1

K2

K3

B1

B2

Fm

Fp

HEX HEX HEX HEX HEX HEX DC COL tray COL tray COL tray

multiple-pipe fixed-tube multiple-pipe kettle reboiler kettle reboiler kettle reboiler horizontal vessel vertical vessel sieve vertical vessel sieve vertical vessel sieve

2.7652 4.3247 2.7652 4.4646 4.4646 4.4646 3.5565 3.4974 2.9949 3.4974 2.9949 3.4974 2.9949

0.7282 −0.303 0.7282 −0.5277 −0.5277 −0.5277 0.3776 0.4485 0.4465 0.4485 0.4465 0.4485 0.4465

0.0783 0.1634 0.0783 0.3955 0.3955 0.3955 0.0905 0.1074 0.3961 0.1074 0.3961 0.1074 0.3961

1.74 1.63 1.74 1.63 1.63 1.63 1.49 2.25 2.25 2.25 -

1.55 1.66 1.55 1.66 1.66 1.66 1.52 1.82 1.82 1.82 -

1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 -

1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 -

HEX: heat exchanger, DC: decanter, COL: column.

cost (CBM) shown in Table 2 is based on the CEPCI of 397, which is an average value during the period of May to September of 2001.9The current CEPCI on December of 2010 is found to be 560.4. Thus, the total capital cost for each scheme can be calculated as

The bare module cost factor (FBM), a function of operating pressure and the construction materials, is calculated as

FBM = B1 + B2 FMFP for vessels and heat exchanger FBM = 1 for sieve trays in the column

Total capital cost

(4)

where B1 and B2 are constants depending on the equipment type. FM is material factor, and FP is pressure factor. Carbon steel is chosen as the material of construction throughout, since the process under study is operating near ambient pressure and no corrosive chemicals are present. The quantity factor (fq) based on the number of trays (N) in the column, is calculated as

= Total bare module cost × 560.4/397

Furthermore, Seider et al.10 recommend that imin be taken as 0.2. Based on a three-year payback period, Arifin and Chien6 adopt imin = 1/3. Olujic et al.11 consider that imin = 0.1, according to an assumed plant lifetime of 10 years. A comparison of all the calculated TACs as well as cost ratios (determined with reference to the cost of Scheme 1) is summarized in Table 4 for the three alternative schemes using various values of imin. Pump costs however are not included in the TAC, like those in the work of Arifin and Chien,6 as they are relatively small when compared with the costs of other equipment. It is found from Table 4 that the required TAC for Scheme 1 and Scheme 2 are almost the same at different imin values. Scheme 3, however, requires much less TAC than the other two schemes. Despite the fact that Scheme 3 has one more column than Scheme 2, Scheme 3 consumes less energy than Scheme 2. On the other hand, Scheme 3 has the least total capital cost among all the alternative schemes.

log10 fq = 0.4771 + 0.08516 log10 N − 0.3473(log10 N )2 for N < 20 fq = 1 for N ≥ 20

(4a)

The bare module costs (CBM) for all of the major equipment units are shown in Table 2. The total bare module cost for each scheme is also presented in Table 2. In addition, the unit cost of 13.28 ($/GJ) for low-pressure steam and the unit cost of 0.354 ($/GJ) for cooling water are used according to Truton et al.9 The annual steam and cooling water costs, together with the total annual utility cost for each scheme, are given in Table 3. It should be noted that the utility cost here, which is equivalent to the operating cost in Arifin and Chien,6 is the sum of the steam cost and the cooling water cost. On the other hand, the total annual cost (TAC) is employed here as a measure of economic potential, which does not involve sales revenues for products and is used for preliminary cost estimates when comparing alternative flowsheets during process synthesis. According to Seider et al.,10 the TAC in this study, with which several alternative distillation sequences are examined, can be calculated as

4. DYNAMIC SIMULATION AND BASIC CONTROL STRUCTURE Dynamic simulation of Scheme 3 is established with a program written in FORTRAN language. The dynamic simulation program is built on an equilibrium-stage model of Franks,12 and Figure 5 shows the computational flowchart associated with the model for stage j. A cubic spline interpolation (Rovaglio and Doherty13) can be used to fit the data, and a binodal curve can thus be generated, with which liquid composition on each tray will be checked to see whether it is located inside the phase envelope or not (i.e., phase splitting). If phase splitting takes place on a tray, the VLLE computation mode will be adopted. Otherwise, the VLE computation mode is used. Given a stage pressure and initial liquid composition of component i, the vapor composition of component i leaving stage j and the temperature on stage j can both be computed based on a bubblepoint temperature calculation. Once the stage temperature is known, the density of liquid mixture at bubble-point condition

TAC = Annual utility cost + imin × Total capital cost

(6)

(5)

The term imin is a minimum acceptable (or threshold) return on investment. The total capital cost is, in fact, the total bare-module costs for all columns and their auxiliaries based on the current Chemical Engineering Plant Cost Index (CEPCI). The bare module 3001



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stream is calculated. Through the use of overall and component material balances, liquid holdup and liquid composition on the stage are integrated with fourth-order Runge−Kutta method with a time interval of 0.01 min. A dynamic simulation run is done using the FORTRAN program, and the operating conditions of Scheme 3 at steady state are computed until the conditions of the system do not change with time. Also, the steady state results of all streams from the dynamic simulation in FORTRAN are about the same as the results from the design study using Aspen Plus. Physical properties and model parameters used in the dynamic simulation, such as critical properties, heat capacity coefficients, and Antoine constants, are taken from the Aspen Plus data bank and binary parameters of NRTL model are obtained from Wang et al.9 Their values are the same as those used in the steady-state simulation for Scheme 3 using Aspen Plus. On the basis of 80% flooding and a tray spacing of 0.6 m, Columns C101, C201, and C301 are designed to have diameters of 0.75, 1.73, and 0.92 m, respectively. The weir height of each tray in every column is assumed to be 0.05 m. In addition, the column base volumes for the three columns are all sized for a liquid hold-up of 10 min. Pressure drops per tray for the three columns are set at 0.007 bar. A holdup time of 20 min in the decanter is assumed to allow for two liquid phases to separate. The basic control for Scheme 3 is investigated, and Figure 6 depicts its plant-wide control structure. In order to maintain the column head pressures, three pressure control loops have been employed. The bottom product qualities of the three columns are maintained by adjusting reboiler duty, and a tray temperature control loop is used for each column. Open-loop sensitivity analysis for the tray temperature control loop in each column is carried out using Aspen Plus. Figure 7 shows openloop sensitivity analysis results of the three columns by changing ±0.5% of reboiler duties. Tray #7 of the C101 column, tray #10 of the C201 column, and tray #8 of the C301 column are chosen as three temperature control points, in view of the high sensitivity of tray temperature with respect to variations in reboiler duty. PID control is used in these three tray temperature control loops. The tuning constants are Kc (proportional gain) = 0.8, τI (integral time) = 8.0, and τD (derivative time) = 0.125 for these three tray temperature control loops. A ratio control scheme is implemented to reject feed rate disturbance of the C201 column, and the ratio of the organic reflux flow to the feed flow rate of the C201 column is kept constant. The organic-phase liquid level of the decanter is controlled by manipulating entrainer makeup flow, and the aqueous-phase level of the decanter is controlled by manipulating aqueous flow rate. For the organic-phase level loop and the aqueous-phase level loop of the decanter, the P-only controllers are used and Kc = 10 is used as in Arifin and Chien.6 The bottom liquid levels of the three columns are controlled by manipulating the bottom product flow. The column bottom level control loops are considered to be ideal. As the overhead vapor of Column C201 is condensed into liquid, the condensate temperature is controlled at 40 °C by manipulating cooling water flow. The top temperature control loop of the C201 column is also assumed to be ideal control. Two types of disturbances are used to test the proposed plant-wide control structure, namely ±20% changes in both fresh feed rate and fresh feed H2O composition. Figure 8 shows the dynamic responses for ±20% step change in fresh feed rate. The plots in the first and second rows show responses of top

Table 3. Comparison of Equipment Specifications and Costs of the Schemes column 1 (C101) total no. of trays diameter (m) height (m) CBM ($) condenser (E101) heat transfer area (m2) CBM ($) reboiler (E102) heat transfer area (m2) CBM ($) column 2 (C102) total no. of trays diameter (m) height (m) CBM ($) condenser (E201) heat transfer area (m2) CBM ($) reboiler (E202) heat transfer area (m2) CBM ($) column 3 (C103) total no. of trays diameter (m) height (m) CBM ($) condenser (E301) heat transfer area (m2) CBM ($) reboiler (E302) heat transfer area (m2) CBM ($) decanter total flow rate (m3/min) diameter (m) height (m) CBM ($) total capital cost ($) annual steam cost ($/year) annual cooling water cost ($/year) annual utility cost ($/year)

Scheme 1

Scheme 2

Scheme 3

14 0.83 10.80 61,900

-

14 0.75 10.8 56,000

27.94 44,500

-

-

21.98 137,000

-

19.43 128,000

34 1.63 22.80 277,000

34 1.61 22.80 272,000

38 1.73 25.2 333,000

191.78 142,000

186.66 140,000

243.12 158,000

42.43 209,000

42.03 208,000

24.42 145,000

16 0.90 12.00 73,400

16 1.25 12.00 109,200

16 0.91 12 74,300

39.10 61,700

72.59 114,000

-

26.27 151,000

50.09 238,000

28.95 160,000

0.430 1.94 5.82 63,000 1,220,500 2,464,500 63,200 2,527,700

0.418 1.92 5.76 61,600 1,142,800 2,474,300 63,600 2,537,900

0.552 2.11 6.33 75,200 1,054,300 1,843,000 47,000 1,890,000

Table 4. Comparison of TACs and Cost Ratios of the Schemes imin = 0.1 imin = 0.2 imin = 1/3

TAC ($) cost ratio TAC ($) cost ratio TAC ($) cost ratio

Scheme 1

Scheme 2

Scheme 3

2,649,750 1.000 (base) 2,771,800 1.000 (base) 2,934,533 1.000 (base)

2,652,180 1.001 2,766,460 0.998 2,918,833 0.995

1,995,430 0.753 2,100,860 0.758 2,241,433 0.764

is estimated by modified Rackett equation (Reid et al.).14 The liquid flow rate leaving stage j can then be calculated by Francis weir formula. The liquid and vapor mixture enthalpies at the stage temperature can be estimated by assuming ideal mixing. By energy balance on the stage, the flow rate of leaving vapor 3002



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Figure 5. Computational flowchart of equilibrium stage j.

Figure 6. Plant-wide control structure for Scheme 3.

vapor flow and bottom product flow of the three columns. Due to the ±20% change in the fresh feed rate, the vapor flow and the product flow, for the most part, increase or decrease over time before reaching their steady-state values. The water

product flows (from C101 and C301) and IPA product flow also increase (or decrease) and reach their new values in 80 min with a +20% (or −20%) change in fresh feed rate. For +20% change in fresh feed rate, the total water product flow rate 3003



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Figure 7. Open-loop sensitivity analysis for the three columns in Scheme 3 (a) C101, (b) C201, and (c) C301.

Figure 8. Closed-loop responses with ±20% fresh feed rate changes (dashed lines, −20%; solid lines, +20%).

changes from 834.20 to 1001.03 mol/min, and the IPA product flow rate changes from 832.49 to 998.65 mol/min. The plots in

the third row show that the three tray temperatures are brought back to their desired set-points. The plots in the last row show 3004



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Figure 9. Closed-loop responses with ±20% feed H2O composition changes (dashed lines, −20%; solid lines, +20%).

investment being used (i.e., 1/3, 0.2, or 0.1), the total annual cost of the proposed scheme is less than that of the other schemes. The basic control for the proposed scheme has also been looked into. A tray temperature control loop implemented in each of these three columns can be used to maintain the bottom product compositions. In addition, ratio control of the organic reflux flow to the feed flow of the IPA purification column is capable of rejecting feed rate disturbances. Furthermore, if fresh feed rate or water composition in the feed is subject to a ±20% change, the simulation results of the closedloop system reveal that the control strategy for the proposed scheme can yield good control performance.

that the stabilized product compositions of the three columns are very near their purity specifications. The water product compositions are back to 99.9 mol %, and the IPA product composition is also greater than 99.99989 mol %. Figure 9, on the other hand, shows the dynamic responses for ±20% changes of water composition in the feed. The plots in the first row show that top vapor flows of the three columns all generally decrease over time with an increase in the water composition in the feed. However, as shown in the second-row plots, the response to a positive step change in the H2O composition is such that the product flow of Column C101 generally increases over time before finally approaching a steady-state value, whereas the steady-state product flows of Columns C201 and C301 decrease with the same step change. The plots in the third row also show that the three tray temperatures can be effectively brought back to their set-point values. The plots in the last row show that the product compositions of the three columns are still in the ultrapure region. The water product compositions of the C101 column are greater than 99.88 mol %, and the water product compositions of the C301 column are very near to 99.9 mol %. The IPA composition in the product stream is greater than 99.99987 mol %.

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AUTHOR INFORMATION

Corresponding Author

*Phone: +886-4-2359-0262. Fax: +886-4-2359-0009. E-mail: [email protected].

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REFERENCES

(1) Widagdo, S.; Seider, W. D. Azeotropic distillation. AIChE J. 1996, 42, 96. (2) Pham, H. N.; Doherty, M. F. Design and Synthesis of Heterogeneous Azeotropic Distillation − III. Column Sequences. Chem. Eng. Sci. 1990, 45, 1845. (3) Ryan, P. J.; Doherty, M. F. Design/Optimization of Ternary Heterogeneous Azeotropic Distillation Sequences. AIChE J. 1989, 35, 1592. (4) Luyben, W. L. Control of a Multiunit Heterogeneous Azeotropic Distillation Process. AIChE J. 2006, 52, 623. (5) Chien, I. L.; Zeng, K. L.; Chao, H. Y. Design and Control of a Complete Heterogeneous Azeotropic Distillation Column System. Ind. Eng. Chem. Res. 2004, 43, 2160. (6) Arifin, S.; Chien, I. L. Combined Preconcentrator/Recovery Column Design for Isopropyl Alcohol Dehydration Process. Ind. Eng. Chem. Res. 2007, 46, 2535.

5. CONCLUSIONS This article presents a study of designing a three-column heterogeneous azeotropic distillation configuration to separate IPA and water using cyclohexane as the entrainer, featuring energy saving and cost-effective. Due to low reflux ratios, a preconcentrator column and an entrainer recovery column employed in the previous works are replaced by stripping columns. Our proposed scheme, essentially a three-column sequence using stripping columns in place of conventional distillation columns, saves more energy and is more cost-effective than other schemes in the literature. Regardless of the minimum acceptable return on 3005



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(7) Wu, Y. C.; Chien, I. L. Design and Control of Heterogeneous Azeotropic Column System for Separation of Pyridine and Water. Ind. Eng. Chem. Res. 2009, 48, 10564. (8) Wang, C. J.; Wong, D. S. H.; Chien, I.-L.; Shih, R. F.; Liu, W. T.; Tsai, C. S. Critical Reflux, Parametric Sensitivity, and Hysteresis in Azeotropic Distillation of Isopropyl Alcohol+Water+Cyclohexane. Ind. Eng. Chem. Res. 1998, 37, 2835. (9) Turton, R.; Bailie, R. C.; Whiting, W. B.; Shaeiwitz, J. A. Analysis, Synthesis, and Design of Chemical Processes, 3rd ed.; Pearson Education: Boston, 2009. (10) Seider, W. D.; Seader, J. D.; Lewin, D. R. Product and Process Design Principles: Synthesis, Analysis, and Evaluation, 2nd ed.; John Wiley and Sons: New York, 2004. (11) Olujic, Z.; Sun, L.; de Rijke, A.; Jansens, P. J. Conceptual Design of an Internally Heat Integrated Propylene-Propane Splitter. Energy 2006, 31, 3083. (12) Franks, R. G. E. Modeling and Simulation in Chemical Engineering; John Wiley and Sons: Canada, 1972. (13) Rovaglio, M.; Doherty, M. F. Dynamics of Heterogeneous Azeotropic Distillation Columns. AIChE J. 1990, 36, 39. (14) Reid, R. C.; Prausnitz, J. M.; Poling, B. E. Properties of Gases and Liquids, 4th ed.; McGraw-Hill Book Company: New York, 1987.

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Design and Control of a Complete Azeotropic Distillation System

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