Entrainer-assisted Pressure-swing Distillation for Separating Minimum

Entrainer-assisted Pressure-swing Distillation for Separating Minimum. Boiling Azeotrope Toluene/Pyridine: Design and Control. Ye Li, Weisong Li, Lei ...
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Entrainer-assisted Pressure-swing Distillation for Separating Minimum Boiling Azeotrope Toluene/Pyridine: Design and Control Ye Li, Weisong Li, Lei Zhong, and Chunjian Xu Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.7b02961 • Publication Date (Web): 26 Sep 2017 Downloaded from http://pubs.acs.org on September 30, 2017

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Entrainer-assisted Pressure-swing Distillation for Separating Minimum Boiling Azeotrope Toluene/Pyridine: Design and Control Ye Li, Weisong Li, Lei Zhong, Chunjian Xu* School of Chemical Engineering and Technology, Chemical Engineering Research Center and State Key Laboratory of Chemical Engineering, Tianjin University, Tianjin 300072, China Tel.: +86 022-27404440. Fax: +86 022-27404440. E-mail: [email protected]. ABSTRACT: The separation of toluene/pyridine by distillation still remains an obstacle in industry because of not only the formation of a minimum boiling azeotrope, but also their relative volatilities, which are close to unity in the whole composition region. Extractive distillation is still not feasible because it is hard to find suitable entrainers. Heterogeneous azeotropic distillation may require a large energy consumption to obtain both purified products. Conventional pressure-swing distillation is also not feasible. In this paper, we apply entrainer-assisted pressure-swing distillation to separate toluene/pyridine (95 mol%/5 mol%) via introducing n-propanol as an entrainer. Based on the different compositions of the recycling stream back to the azeotropic column, a two-column sequence and a three-column sequence are established. Both sequences are partially heat-integrated. The steady-state designs of both sequences are optimized based on the total annual cost (TAC). The results reveal that the optimal two-column sequence has a 16.07% reduction of TAC and a 14.39% energy savings compared with the three-column sequence. Furthermore, the dynamic controllability of the two-column sequence is investigated by introducing ±10% disturbances in the feed flow rate and ±20% disturbances in the pyridine concentration. A conventional temperature control structure is implemented. As the fresh feed is quite dilute in pyridine, its product purity will be significantly influenced by even a small change in the

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recycling stream flow rate. Therefore, the recycling stream flow rate must be selected as a manipulated variable, and it is manipulated to control the pyridine product purity. The results reveal that robust control can be achieved. 1. INTRODUCTION Toluene and pyridine are both widely used industrial chemicals.1, 2 Toluene product obtained from the coal coking process often contains a small quantity of pyridine. The mixture of toluene/pyridine form a minimum boiling azeotrope with their relative volatilities close to unity in the whole composition region, which leads to great difficulty in separating this mixture. Extractive distillation,3-10 heterogeneous azeotropic distillation11-16 and pressure-swing distillation17-24 (PSD) are widely used methods for separating azeotropes. Extractive distillation is currently not feasible for the separation of toluene/pyridine because it is hard to find suitable entrainers. Wu25, 26 investigated the separation of pyridine/water via heterogeneous azeotropic distillation with toluene as an entrainer. Zhao27 applied water as an entrainer to separate toluene/pyridine via heterogeneous azeotropic distillation, in which only the purified toluene product was obtained. When the feed is quite dilute in pyridine, the heterogeneous azeotropic distillation of toluene/pyridine with water as an entrainer to obtain both purified products may require a large energy consumption. Conventional pressure-swing distillation is also not feasible. Knapp28 developed an entrainer-assisted pressure-swing distillation (EA-PSD) for separating pressure-insensitive binary azeotropes via introducing a suitable pressure-swing entrainer. The entrainer must satisfy at least one of three principles as below: (1) The entrainer forms no new azeotropes at atmospheric pressure, but when the pressure is increased (decreased), new azeotrope(s) appear that

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move rapidly with changing pressure. (2) The entrainer forms one or more new azeotropes whose composition(s) change rapidly with pressure. (3) The entrainer forms one or more new azeotropes at atmospheric pressure, but they disappear as the pressure is increased (decreased). They demonstrated the feasibility of this process through investigating the separation of ethanol/water with acetone as the pressure-swing entrainer. Li29 applied this EA-PSD to separate the pressure-insensitive maximum boiling azeotrope phenol/cyclohexanone with acetophenone as the heavy entrainer. Li30 compared this EA-PSD with extractive distillation for separating the pressure-insensitive minimum boiling azeotrope methanol/toluene. Modla31 investigated the feasibility of separating ternary minimum boiling azeotropes by batch PSD. In this paper, we adopt this EA-PSD to separate toluene/pyridine to obtain both purified products. Two partially heat-integrated sequences are established and optimized based on the total annual cost (TAC). Furthermore, the dynamic controllability of the optimal sequence is investigated. 2. STEADY-STATE DESIGN 2.1. Thermodynamic Model and Entrainer Screening. In this study, the NRTL model is selected and the built-in binary interaction parameters in Aspen Plus are used to predict the vapor-liquid equilibrium of the system. The details can be found in the Supporting Information. The vapor-liquid equilibrium diagram of toluene/pyridine at 1 atm is depicted in Figure 1. It can be seen clearly that toluene/pyridine not only a form minimum boiling azeotrope, but also feature relative volatilities close to unity in the whole composition region. The feeding conditions are 100 kmol/hr with 95 mol% toluene and 5 mol% pyridine at a temperature

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of 50 °C. Based on the heuristic entrainer screening procedure proposed by Foucher32 and the principles proposed by Knapp, four potential entrainers are selected after searching the Azeotropic Data33: ethanol, n-propanol, isopropanol and tert-butanol. All these entrainers form pressure-sensitive minimum boiling azeotropes with toluene, but not with pyridine. Further screening of these four entrainers is mainly determined by the recycling stream flow rate of the EA-PSD. For both conventional PSD and EA-PSD, the recycling stream flow rate is the crucial factor that influences the energy consumption. A larger differential pressure between the low-pressure column (LPC) and the high-pressure column (HPC) leads to a smaller recycling stream flow rate. Meanwhile, the temperatures of the cooling water and the high-pressure steam should also be considered when determining both the LPC and HPC operating pressures (OPs). Take the two-column sequence for example. The analysis of screening these four entrainers is shown in Figure 2, which is based on the residue curve map and lever-arm principle. It can be seen clearly that the selection of n-propanol will lead to the smallest recycling stream flow rate. Therefore, in this paper, n-propanol is selected as the pressure-swing entrainer. The influence of n-propanol as the entrainer on the relative volatility of toluene to pyridine at 1 atm for three compositions is shown in Figure 3. 2.2. Optimization. The product purities of toluene and pyridine are both specified at 99.9 mol%. In this work, the TAC suggested by Douglas34 is used as the objective function to be minimized to optimize the steady-state design. TAC (k$/year) = OC + ir·FCI

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where FCI is the fixed capital investment; ir is the fixed capital recovery rate applied to the FCI and it is assumed to be 0.3 here; OC is the operating cost. The details can be found in the Supporting Information. According to the different compositions of the recycling stream back to azeotropic column, there exist two sequences. For the two-column sequence, the LPC serves as the azeotropic column, while the HPC serves as the entrainer recovery column with the recycling stream back to the azeotropic column close to the binary azeotrope at the OP of the HPC. If the recycling stream of two-column sequence is further separated to pure entrainer by adding another LPC, then the three-column sequence can be obtained. The added LPC serves as an entrainer recovery column with pure entrainer as the bottom product recycling back to the azeotropic column and the toluene/n-propanol binary azeotrope as the distillate recycling back to the HPC. 2.2.1. Optimization of Two-column Sequence. The selection of the OPs for the LPC and HPC favors a large differential pressure, but should meet the requirements of utilizing cooling water in the condenser of the LPC and the low-pressure or medium-pressure steam in the reboiler of the HPC. Note that high-pressure steam is not considered to supply the reboiler duty of the HPC. When the OP of the HPC exceeds a certain value, the composition of the toluene/n-propanol binary azeotrope varies very slowly with the pressure, while high-pressure steam is substantially more expensive than low-pressure or medium-pressure steam. A reasonable differential temperature between the reflux drum of the LPC and the cooling water is at least 20 °C, as well as that of the reboiler of the HPC and the heating steam. As the complete optimization of both OPs of the HPC and LPC is time consuming, for simplicity purposes, we fix the OP of the LPC at 0.18 atm to

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minimize the recycling stream flow rate, which can also guarantee the use of cooling water in the condenser, and optimize the OP of the HPC. The reboiler duty of the LPC and the condenser duty of the HPC are partially heat-integrated. The iteration procedure of the optimization can be found in the Supporting Information. In summary, with the OP of the LPC (P1) fixed, the OP of the HPC (P2), the total stage numbers of the LPC (NT1) and the HPC (NT2), the distillate composition of the LPC (xD1), the recycling stream flow rate (S), and the feeding locations (NF1, NFS and NF2) are the optimization variables to minimize the TAC. The reflux ratios of the LPC (RR1) and the HPC (RR2) and the reboiler duties of the LPC (QR1) and the HPC (QR2) are varied to meet the specifications of the compositions of D1, D2, B1 and B2. To select the optimal OP of the HPC, three case studies are implemented with OPs of the HPC at 3.0, 3.2 and 3.4 atm. The optimal steady-state designs are compared with details in Table 1. The optimal flowsheet of the two-column sequence is shown in Figure 4. 2.2.2. Optimization of Three-column Sequence. For simplicity, the OP of the azeotropic column is set at 0.18 atm to minimize the flow rate of the recycling stream back to the azeotropic column, and the OP of the entrainer recovery column is also set at 0.18 atm to minimize the flow rate of the recycling stream back to the HPC. Then the OP of the HPC is optimized. As the OPs of the azeotropic column and entrainer recovery column are equal, the distillate compositions of azeotropic column and entrainer recovery column are set as the same for simplified optimization. Thus, the distillates of the azeotropic column and entrainer recovery column are mixed to feed to the HPC. Note that in the three-column sequence, there exist two recycling streams. The recycling stream back to the azeotropic column is nearly pure entrainer, of which the flow rate is

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determined by the overall balance of materials. The recycling stream back to the HPC is then optimized. The reboiler duty of the azeotropic column and the condenser duty of the HPC are partially heat-integrated. The iteration procedure of the optimization can be found in the Supporting Information. In summary, with the OPs of the azeotropic column (P1) and entrainer recovery column (P3) fixed, the OP of the HPC (P2); the total stage numbers of the azeotropic column (NT1), the HPC (NT2) and the entrainer recovery column (NT3); the distillate compositions of the azeotropic column and entrainer recovery column (xD1and xD3); the recycling stream flow rate (SEH); and the feeding locations (NF1, NFS, NF2 and NF3) are the optimization variables to minimize the TAC. The reflux ratios of the azeotropic column (RR1), the HPC (RR2) and the entrainer recovery column (RR3) and the reboiler duties of the azeotropic column (QR1), the HPC (QR2) and the entrainer recovery column (QR3) are varied to meet the specifications of the compositions of D1, D2, D3, B1, B2 and B3. To select the optimal OP of the HPC, three case studies are implemented with OPs of the HPC at 3.0, 3.2 and 3.4 atm. The optimal steady-state designs are compared with details in Table 2. The optimal flowsheet of three-column sequence is shown in Figure 5. 2.3.3. Comparison. The results reveal that the optimal two-column sequence has a 16.07% reduction of the TAC and a 14.39% energy savings compared with the three-column sequence. 3. DYNAMIC CONTROL In this section, the dynamic performance of the two-column sequence is investigated. The details of the equipment sizing of converting a steady-state simulation to a dynamic one can be

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found in the Supporting Information. The temperature profiles of the LPC and the HPC are shown in Figure 6. The sensitive tray is selected by the “slope criterion” suggested by Luyben.35 The location of the stage in the LPC with the largest slope is the 16th. The location of the stage in the HPC with the largest slope is the 18th. The control loops are listed as below: (1) The fresh feed is flow controlled. (2) The distillate flow rate of the LPC is proportional to the feed flow rate, with the proportion being adjusted by a pyridine product composition controller. (3) The pressure of the LPC is controlled by manipulating the heat removal rate of the condenser. (4) The pressure of the HPC is not controlled because the overhead vapor of the HPC is completely used to heat the reboiler steam of the LPC. (5) The reflux ratios of the LPC and the HPC are both fixed. (6) The reflux drum level of the LPC is controlled by manipulating the makeup flow rate, while the reflux drum level of the HPC is controlled by manipulating the distillate flow rate. (7) The base levels of both columns are controlled by manipulating the bottoms flow rates. (8) The temperature of stage 16 in the LPC (T16) is controlled by manipulating the heat duty of the auxiliary reboiler. (9) The temperature of stage 18 in the HPC (T18) is controlled by manipulating the heat duty of the reboiler. The most noticeable issue of the control loops is manipulating the recycling stream flow rate to control pyridine product purity. As pyridine is quite dilute in the fresh feed, its product purity will be

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significantly influenced by even a small change in the recycling stream flow rate. Preliminary simulations with just fixing the ratio of the recycling stream flow rate to feed flow rate cannot resist the disturbances. Therefore, the recycling stream flow rate must be selected as a manipulated variable. Thus, we select the recycling stream flow rate to control pyridine product purity. Utilizing the recycling stream flow rate to control product purity was investigated by Wang.36 The flowsheet of the control strategy is shown in Figure 7. All the controllers are PI (proportional and integral) controllers. Relay-feedback tests are run on the two temperature controllers and the composition controller to achieve ultimate gains and periods. The Tyreus-Luyben turning is applied to obtain the gain constant and integral time constant. For the heat-integrated PSD, the pressure compensated temperature control is widely used to obtain robust controllability.37, 38 The bubble point of the liquid phase on stages 18 of the HPC is investigated at 2.6-3.8 bar. T18 is deemed as a linear function of the pressure with a slope of 15.0304 ℃/bar. The “flowsheet equations” function is employed to achieve this partial heat-integration.39, 40 The parameters of all the controllers, the controller faceplate, “flowsheet equations” and the linear function of temperature vs. pressure can be found in the Supporting Information. The dynamic performances are tested by introducing ±10% disturbances in the feed flow rate and ±20% disturbances in the pyridine concentration at a time equal to 0.2 h. Preliminary simulations show that this process cannot resist a +20% disturbance of feed flow rate, so we just implement ±10% disturbances in the feed flow rate in this paper. The dynamic responses for the feed flow rate and the concentration disturbances are shown in Figure 8 and 9, respectively. The results show that for all the disturbances, the pyridine product purity can

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return to its set point quickly, with that of the toluene product being maintained close to its set point. All the controlled temperature points can also return to their set points quickly. Therefore, the dynamic controllability of this process is robust. 4. CONCLUSION In this paper, EA-PSD is applied to separate toluene/pyridine effectively via introducing n-propanol as an entrainer. Two partially heat-integrated sequences are optimized based on the TAC. The results show that the optimal two-column sequence has a 16.07% reduction of TAC and a 14.39% energy savings compared with the three-column sequence. The dynamic performance of the two-column sequence is investigated. Two single-point temperature control loops and a composition control loop for manipulating the recycling stream flow rate to control the pyridine product purity are implemented. The results show that robust control can be achieved. Therefore, this EA-PSD is applicable and effective to separate toluene/pyridine.

Supporting Information (1) Binary interaction parameters of the NRTL model in Aspen Plus, (2) comparison between predicted and experimental azeotropic compositions and bubble points, (3) details of calculating the TAC, (4) iteration procedures of optimization, (5) details of the equipment sizing of converting a steady-state simulation to a dynamic one, (6) parameters of all the controllers, (7) the controller faceplate, (8) flowsheet equations of the control strategy, (9) the linear function of temperature vs. pressure.

NOMENCLATURE

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B = bottom flow rate D = distillate flow rate EA-PSD = entrainer-assisted pressure-swing distillation E = entrainer flow rate F = feed flow rate FCI = fixed capital investment HPC = high-pressure column ir = fixed capital recovery rate ID = column diameter LPC = low-pressure column NF = feeding location of fresh feed NFS = feeding location of entrainer NT = total number of stages OC = operating cost OP = operating pressure P = pressure PSD = pressure-swing distillation Q = heat exchanger duty QC = condenser duty QR = reboiler duty RR = reflux ratio

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S = recycling stream flow rate T = stage temperature TAC= total annual cost x = liquid mole fraction y= vapor mole fraction α= relative volatility

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Germany, 2004. (34) Douglas, J. M. Conceptual Design of Chemical Processes; McGraw Hill: New York, 1998. (35) Luyben, W. L. Distillation Design and Control Using Aspen Simulation; John Wiley & Sons: New York, 2006. (36) Wang, Y.; Liang, S.; Bu, G.; Liu, W.; Zhang, Z.; Zhu, Z. Effect of Solvent Flow Rates on Controllability of Extractive Distillation for Separating Binary Azeotropic Mixture. Ind. Eng. Chem. Res. 2015, 54, 12908-12919. (37) Luyben, W. L. Control of a Heat-Integrated Pressure-Swing Distillation Process for the Separation of a Maximum-Boiling Azeotrope. Ind. Eng. Chem. Res. 2014, 53, 18042-18053. (38) Wang, Y.; Zhang, Z.; Zhang, H.; Zhang, Q. Control of Heat Integrated Pressure-Swing-Distillation Process for Separating Azeotropic Mixture of Tetrahydrofuran and Methanol. Ind. Eng. Chem. Res. 2015, 54, 1646-1655. (39) Luyben, W. L. Design and control of a fully heat-integrated pressure-swing azeotropic distillation system. Ind. Eng. Chem. Res. 2008, 47, 2681-2695. (40) Zhu, Z.; Wang, L.; Ma, Y.; Wang, W.; Wang, Y. Separating an azeotropic mixture of toluene and ethanol via heat integration pressure swing distillation. Comput. Chem. Eng. 2015, 76, 137-149.

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Table 1. The influence of the OP of the Two-column Sequence Variables

Case 1

Case 2

Case 3

P1 (atm)

0.18

0.18

0.18

NT1

35

35

35

NF1/NFS

11/12

11/12

11/12

RR1

0.586

0.586

0.591

ID1 (m)

3.067

3.029

2.996

QC1 (kW)

-3779.82

-3689.01

-3609.09

P2 (atm)

3.0

3.2

3.4

NT2

25

26

30

NF2

14

15

18

RR2

1.071

1.257

1.445

ID2 (m)

1.855

1.871

1.882

QR2 (kW)

3374.71

3471.48

3553.36

Q (kW)

2249.75

2341.04

2419.76

Qaux (kW)

951.18

780.77

637.08

S (kmol/hr)

114.99

109.99

104.99

FCI (k$/year)

2579.97

2616.31

2704.56

OC (k$/year)

1781.48

1754.92

1732.62

TAC (k$/year)

2555.47

2539.81

2543.98

LPC

HPC

Heat Exchanger

Recycling Stream

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Table 2. The influence of the OP of the Three-column Sequence Variables

Case 1

Case 2

Case 3

P1 (atm)

0.18

0.18

0.18

NT1

40

40

40

NF1/NFS

14/16

14/16

14/16

RR1

0.647

0.647

0.647

ID1 (m)

2.802

2.801

2.802

QC1 (kW)

-3158.06

-3157.31

-3157.54

P2 (atm)

3.0

3.2

3.4

NT2

24

25

26

NF2

14

14

15

RR2

1.105

1.163

1.278

ID2 (m)

1.866

1.849

1.848

QR2 (kW)

3408.92

3394.74

3431.21

Entrainer Recovery

P3 (atm)

0.18

0.18

0.18

Column

NT3

25

25

25

NF3

10

10

10

RR3

1.878

2.074

2.316

ID3 (m)

1.824

1.791

1.758

QR3 (kW)

831.72

788.89

748.23

QC3 (kW)

-1337.39

-1289.51

-1240.96

Q (kW)

2285.85

2259.44

2287.17

Qaux (kW)

799.49

825.14

797.64

SEH (kmol/hr)

40.98

36.99

33.00

FCI (k$/year)

3223.35

3253.95

3300.20

OC (k$/year)

2062.84

2049.98

2038.32

TAC (k$/year)

3029.85

3026.17

3028.38

Azeotropic Column

HPC

Heat Exchanger

Recycling Stream

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Figure Captions Figure 1: (a) T-xy diagram of toluene/pyridine at 1 atm. (b) x-y diagram of toluene/pyridine at 1 atm. Figure 2: (a) The analysis of using ethanol as the entrainer. (b) The analysis of using n-propanol as the entrainer. (c) The analysis of using isopropanol as the entrainer. (d) The analysis of using tert-butanol as the entrainer. Figure 3: The influence of n-propanol as the entrainer on the relative volatility of toluene (1) to pyridine (2) at 1 atm for three compositions. Figure 4: The optimal flowsheet of the two-column sequence. Figure 5: The optimal flowsheet of the three-column sequence. Figure 6: (a) The temperature profile of the LPC. (b) The temperature profile of the HPC. Figure 7: The flowsheet of the control strategy. Figure 8: The dynamic responses for the feed flow rate disturbances. Figure 9: The dynamic responses for the feed concentration disturbances.

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(a)

116 115 T-x (1 atm) T-y (1 atm)

114 T (°C)

113 112 111 110 109 0.0

0.2 0.4 0.6 Mole Fraction of Toluene

0.8

1.0

0.8

1.0

Figure 1. (a)

(b)

1.0 0.8

x-y (1atm)

0.6 y

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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0.4 0.2 0.0 0.0

0.2

0.4

0.6 x

Figure 1. (b) Figure 1. (a) T-xy diagram of toluene/pyridine at 1 atm. (b) x-y diagram of toluene/pyridine at 1 atm.

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Pyridine 1.0 0.9

Pyridine 1.0

80.14 °C (0.32 atm) B1

(a)

0.9

0.8

0.8

0.7

0.7

0.6

0.6

0.5

0.3

Azo (3.5 atm) 0.4 161.16 °C

0.2 Azo (0.32 atm) 0.1 74.64 °C F

0.2 Azo (0.18 atm) 0.1 59.48 °C F

0.3

0.0

Toluene 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Azo (0.32 atm) 161.46 °C (3.5 atm) 49.73 °C B2 D1

0.9 1.0

Ethanol

Azo (3.5 atm) 113.36 °C S(D2)

0.0

Toluene 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Azo (0.18 atm) 161.46 °C (3.5 atm) 49.79 °C B2 D1

Pyridine 0.9

(b)

0.5

Azo (3.5 atm) 0.4 161.16 °C

1.0

65.13 °C (0.18 atm) B1

0.9 1.0

n-Propanol

Azo (3.5 atm) 133.71 °C S(D2)

Pyridine 1.0

74.54 °C (0.26 atm) B1

(c)

0.9

0.8

0.8

0.7

0.7

0.6

0.6

0.5

(d)

0.5

Azo (3.5 atm) 0.4 161.16 °C

Azo (3.5 atm) 0.4 161.16 °C

0.2

0.2 Azo (0.24 atm) 0.1 66.86 °C F

0.3

0.3

Azo (0.26 atm) 0.1 68.98 °C F 0.0

Toluene 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Azo (0.26 atm) 161.46 °C (3.5 atm) 50.00 °C B2 D1

72.44 °C (0.24 atm) B1

0.9 1.0

Isopropanol

Azo (3.5 atm) 117.47 °C S(D2)

0.0

Toluene 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Azo (0.24 atm) 161.46 °C (3.5 atm) 49.81 °C B2 D1

0.9 1.0

tert-Butanol

Azo (3.5 atm) 119.07 °C S(D2)

Figure 2 Figure 2. (a) The analysis of using ethanol as the entrainer. (b) The analysis of using n-propanol as the entrainer. (c) The analysis of using isopropanol as the entrainer. (d) The analysis of using tert-butanol as the entrainer.

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3.4 3.2 3.0 2.8 2.6 2.4

αs12

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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2.2 2.0 1.8

Toluene 0.25/Pyridine 0.75 Toluene 0.5/Pyridine 0.5 Toluene 0.7264/Pyridine 0.2736

1.6 1.4 1.2 1.0 0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

E/F ratio

Figure 3. The influence of n-propanol as the entrainer on the relative volatility of toluene (1) to pyridine (2) at 1 atm for three compositions.

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Figure 4. The optimal flowsheet of the two-column sequence.

Figure 5. The optimal flowsheet of the three-column sequence.

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(a)

90 85 80

T (°C)

75 70 65 60 55 50 45

0

5

10

15

20

25

30

35

Stage (LPC)

Figure 6. (a)

(b)

165 160 155 150 T (°C)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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145 140 135 130 125

0

5

10

15

20

25

30

Stage (HPC)

Figure 6. (b) Figure 6. (a) The temperature profile of the LPC. (b) The temperature profile of the HPC.

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Figure 7. The flowsheet of the control strategy.

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1.0000

Mole Fraction of Toluene

+10% Flow Rate - 10% Flow Rate

0.9996 0.9992 0.9988 0.9984 0.9980

0

5

10

15

20

25

30

+10% Flow Rate - 10% Flow Rate

0.9996 0.9992 0.9988 0.9984 0.9980

0

5

10

Time (hr)

+10% Flow Rate - 10% Flow Rate

66.5

730

66.3

680

0

5

10

15

20

25

630

30

+10% Flow Rate - 10% Flow Rate

780

66.4

0

5

10

Time (hr)

15

20

25

30

Time (hr)

155

4050

153

3850

151 QR2 (kw)

3650

149

+10% Flow Rate - 10% Flow Rate

147

+10% Flow Rate - 10% Flow Rate

3450 3250

145

3050

143 0

5

10

15

20

25

30

2850

0

5

Time (hr)

10

15

20

25

Time (hr)

230 220 210 +10% Flow Rate - 10% Flow Rate

200 190 180

30

830 Qaux (kw)

T16 (°C)

25

880

66.6

141

20

930

66.7

66.2

15 Time (hr)

66.8

T18 (°C)

Mole Fraction of Pyridine

1.0000

Distillate Flow Rate of LPC (kmol/hr)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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0

5

10

15

20

25

30

Time (hr)

Figure 8. The dynamic responses for the feed flow rate disturbances.

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1.0000

1.0000

Mole Fraction of Pyridine

0.9992 0.9988 0.9984 0.9980

0

5

10

15

20

25

+20% Composition of Pyridine - 20% Composition of Pyridine

0.9996

Mole Fraction of Toluene

+20% Composition of Pyridine - 20% Composition of Pyridine

0.9996

0.9992 0.9988 0.9984 0.9980

30

0

5

10

Time (hr)

15

20

25

30

Time (hr)

66.56

795 790

+20% Composition of Pyridine - 20% Composition of Pyridine

66.54 66.52

Qaux (kw)

T16 (°C)

785

66.50

+20% Composition of Pyridine - 20% Composition of Pyridine

780 775

66.48 66.46

770

0

5

10

15

20

25

765

30

0

5

10

Time (hr) 148.7

3520

148.5

3505

QR2 (kw)

T18 (°C)

20

25

+20% Composition of Pyridine - 20% Composition of Pyridine

147.9

+20% Composition of Pyridine - 20% Composition of Pyridine

3475 3460

147.7

3445

147.5 0

5

10

15

20

25

30

3430

0

5

Time (hr)

10

15

20

25

Time (hr)

208 207 206 +20% Composition of Pyridine - 20% Composition of Pyridine

205 204 203 202

30

3490

148.1

147.3

15 Time (hr)

148.3

Distillate Flow Rate of LPC (kmol/hr)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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0

5

10

15

20

25

30

Time (hr)

Figure 9. The dynamic responses for the feed concentration disturbances.

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