Improved Design and Control of Triacetin Reactive Distillation Process

Jul 9, 2014 - with acetic acid to produce triacetin. Hasabnis and Mahajani1 proposed an entrainer-based reactive column configuration with stoichiomet...
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Improved Design and Control of Triacetin Reactive Distillation Process for the Utilization of Glycerol Shih-Kai Hung,† Chung-Cheng Lee,† Hao-Yeh Lee,§ Chien-Lin Lee,§ and I-Lung Chien*,† †

Department of Chemical Engineering, National Taiwan University, Taipei 10617, Taiwan Department of Chemical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan

§

ABSTRACT: Glycerol utilization is an important research topic because of recent surging biodiesel production through transesterification of vegetable oils and animal fats. One of the valuable products from glycerol is gained through esterification with acetic acid to produce triacetin. Hasabnis and Mahajani1 proposed an entrainer-based reactive column configuration with stoichiometric feed ratio to obtain high selectivity and conversion. This paper corrects the kinetic parameters in Hasabnis and Mahajani1 to better describe this reaction system. A more effective reactive entrainer for this reactive distillation system is also proposed to better carry water to the top of the column. The other modification is to assume feed compositions of the glycerol and acetic acid feed streams containing some water as impurity as opposed to idealistic pure feed assumptions. The operation and control of this system are also investigated. The proposed tray-temperature control strategy is able to maintain product purity despite disturbances from throughput and feed composition changes.

1. INTRODUCTION Due to rapidly increasing production of biodiesel as a renewable fuel in recent years, the development of new products and processes that utilize glycerol (a byproduct in biodiesel manufacture) has become important. Ayoub and Abdullah2 gave a good review highlighting the current scenario on glycerol production from biodiesel industry, its global market, and its new emerging outlets as commodity chemicals. Various synthesis reactions are being explored to make high-value products from glycerol. Rahmat et al.3 gave another good review on various types of oxygenated biocomponents and rigorous studies of glycerol transformation into fuel additives. Esterification of glycerol (GLY) with acetic acid (HAc) giving mono-, di-, and triglycerides is one such reaction path. Triglyceride, CAS Registry No. 102-76-1, generally known as triacetin, is used as a plasticizer in various applications such as filters for cigarettes or as a food additive (solvent for flavoring).1 This product can also be used to improve the cold and viscosity properties of liquid fuel (including biodiesel) or as antiknocking additive for gasoline.3 The esterification reactions to produce triacetin involve three consecutive reactions to react glycerol with acetic acid to produce monoacetin, diacetin, and then triacetin. In each esterification reaction, water is formed as a byproduct. The conventional process for the production of triacetin4 often suffers from limited selectivity and conversion because all three consecutive reactions are reversible in nature. It is hoped that by continuous removal of the triester product and water byproduct from a reactive distillation (RD) column the otherwise low equilibrium conversion and selectivity with stoichiometric feed ratio can be greatly enhanced. There are numerous papers and applications of reactive distillation in the open literature. A good review paper of this technology was given by Malone and Doherty.5 There are also two fine books (Luyben and Yu;6 Sundmacher and Kienle7) highlighting hundreds of reaction systems that can be benefit © 2014 American Chemical Society

from RD configuration. The above references show the importance of the RD technology in industrial applications. Hasabnis and Mahajani1 studied a RD system for the production of triacetin. To increase the separation efficiency of water removal at the top part of the RD column and also to lower the temperature in the reaction zone, ethylene dichloride was used as an entrainer in their RD column. There are also a few other papers proposed to use entrainer-based RD configuration in the RD applications such as esterification of ethylene glycol with acetic acid,8 synthesis of 2-ethylhexyl acetate,9 and synthesis of fatty acid esters.10 In this paper, the study by Hasabnis and Mahajani1 for the production of triacetin is extended. The proposed contributions of this paper are four-fold. First, the reported reaction kinetics in Hasabnis and Mahajani1 is corrected to better fit the experimental data in Gelosa et al.11 Second, the two feed streams are not assumed to be totally pure. The assumption of allowing 5 mol % water impurity is assumed in the two feed streams. Third, the ethylene dichloride used as entrainer in Hasabnis and Mahajani1 will be replaced by another more effective entrainer, isobutyl acetate, in the design of an entrainer-based reactive distillation process. Fourth, the operation and control of the proposed RD process will also be investigated. The goal of the overall control strategy is to use tray-temperature control structure to hold the purities of both triacetin and water despite throughput and feed composition disturbances.

2. KINETIC AND THERMODYNAMIC MODELS 2.1. Kinetic Model. Hasabnis and Mahajani1 gave a good survey of the literature on esterification of glycerol with acetic acid using various catalysts. Among all of the catalysts, ion-exchange Received: Revised: Accepted: Published: 11989

January 24, 2014 April 8, 2014 July 9, 2014 July 9, 2014 dx.doi.org/10.1021/ie500346w | Ind. Eng. Chem. Res. 2014, 53, 11989−12002

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Figure 1. Reaction rate constants for the esterification reactions in Gelosa et al.11

Figure 3. Calculated mole fractions as a function of time for the sixth experimental run in Table 3 of Gelosa et al.:11 (a) using kinetic parameters in this paper; (b) using kinetic parameters in Hasabnis and Mahajani.1

acid consists of three consecutive reversible reactions. Glycerol (GLY) reacts with acetic acid (HAc) stepwise to form monoacetin (MONO), diacetin (DI), and triacetin (TRI) with water as byproduct. The reactions are as follows: Figure 2. Equilibrium constants in Gelosa et al.11

k1

GLY + HAc ↔ MONO + H 2O k −1

resin (e.g., Amberlyst 15) is a promising candidate because of its high reactivity in both aqueous and nonaqueous media and also its proven performance in a reactive distillation column. Ionexchange resin also shows reasonably good yield toward triacetin at lower temperature and pressure than other catalysts such as p-toluenesulfonic acid, heteropoly acids, and MgSO4. Hasabnis and Mahajani1 chose to use a concentration-based kinetic model proposed by Gelosa et al.11 Esterification of glycerol with acetic

(1)

k2

MONO + HAc ← → DI + H 2O k −2

(2)

k3

DI + HAc ← → TRI + H 2O

(3)

k −3

The kinetics of the above three reversible reactions are described using a first-order rate expression with respect to both

Table 1. Pre-exponential Factors and Activation Energy Used in This Paper reaction

activation energy (kJ/kmol)

GLY + HAc → MONO + H 2O

MONO + HAc → DI + H 2O DI + HAc → TRI + H 2O

(1) (2)

(3)

MONO + H 2O → GLY + HAc

(4)

3.14 × 1025

4.07 × 104

1.06 × 109

4.24 × 10

6.85 × 108

4

1.48 × 105

2.89 × 1024

1.4 × 10 (in ref 1)

1.02 × 1026 (in ref 1)

2.92 × 104

7.61 × 106

5.29 × 104 (in ref 1)

1.93 × 1011 (in ref 1)

9.46 × 103

7.63 × 104

7.52 × 104 (in ref 1)

6.3 × 1012 (in ref 1)

5

DI + H 2O → MONO + HAc

TRI + H 2O → DI + HAc

(6)

(5)

pre-exponential factor (kg/kmol·s)

1.46 × 105

11990

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Article N Γ ] ∏ (Γi)νi ,1 /KEQ,1

r1 = k1ΓGLYΓHAc[1 −

(4)

i=1 N

r2 = k 2 ΓMONOΓHAc[1 −

Γ ] ∏ (Γi)νi ,2 /KEQ,2

(5)

i=1 N

r3 = k 3 ΓDIΓHAc[1 −

Γ ] ∏ (Γi)νi ,3 /KEQ,3

(6)

i=1

where km is the rate constant of the mth reaction, Γi is the concentration of ith component in the adsorbed phase calculated by using the Langmuir adsorption isotherm given by eq 7, KEQ,m is the equilibrium constant of the mth reaction, and νi,m is the stoichiometric coefficient of the mth reaction. It should be noted that the concentration appearing in the rate expression (eqs 4−6) refers to the adsorbed phase concentrations as below.

Γi =

L K i Γ∞ i Ci N

1 + Σ K iCiL

(7)

i=1

CLi

is the concentration of the ith component in liquid phase, Ki corresponds to the adsorption equilibrium constant, and Γ∞ i is the saturation constant for a pure component. The values of the parameters of the multicomponent adsorption Langmuir isotherm are given in Table 2 of Gelosa et al.11 Forward reaction rate constants of three esterification reactions at various temperatures were reported in Table 4 of

Figure 4. Products of glycerol esterification reactions.

reactants and also accounting for the reverse reaction through the equilibrium constants. The expressions of the three reactions according to Gelosa et al.11 are

Table 2. UNIQUAC Model Parameters of the Glycerol Esterification Systema

a

compd i compd j source aij aji bij bji

GLY HAc UNIFAC 0 0 −334.403218 233.351750

GLY MONO UNIFAC 0 0 35.9674555 −93.1953955

GLY DI UNIFAC 0 0 29.7404849 −224.443542

GLY TRI UNIFAC 0 0 −3.18364710 −402.524796

GLY H2O ASPEN 0.2984 0.8580 −52.6872 −156.6248

HAc MONO UNIFAC 0 0 24.3849880 58.8955827

HAc DI UNIFAC 0 0 304.825921 −493.961947

compd i compd j source aij aji bij bji

HAc TRI UNIFAC 0 0 247.825921 −498.527155

HAc H2O ASPEN 0.7446 0.0042 −615.2641 196.8993

MONO DI UNIFAC 0 0 37.2469188 −72.6515010

MONO TRI UNIFAC 0 0 46.6225660 −176.111689

MONO H2O UNIFAC 0 0 272.521613 −476.783446

DI TRI UNIFAC 0 0 38.8727873 −65.6229642

DI H2O UNIFAC 0 0 46.9553087 −194.958254

compd i compd j source aij aji bij bji

TRI H2O UNIFAC 0 0 −257.505002 −74.8811199

IBA GLY UNIFAC 0 0 −577.824497 45.5665628

IBA HAc ASPEN 0 0 195.0500 −67.74900

IBA MONO UNIFAC 0 0 −301.304958 82.2031609

IBA DI UNIFAC 0 0 −141.9900000 55.3840900

IBA TRI UNIFAC 0 0 −34.6166058 −7.23225717

IBA H2O ASPEN 0 0 −478.3300 −130.7800

compd i compd j source aij aji bij bji

EDC GLY UNIFAC 0 0 −685.884040 21.3917394

EDC HAc ASPEN 0 0 64.053000 −140.930000

EDC MONO UNIFAC 0 0 −371.176892 108.515413

EDC DI UNIFAC 0 0 −231.162000 137.3563000

EDC TRI UNIFAC 0 0 −2.27385515 21.4133396

EDC H2O ASPEN 0 0 −768.940000 −317.470000

UNIFAC, predicted by UNIFAC method in Aspen Plus; ASPEN, built-in parameters in the databank of Aspen Plus. 11991

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The resulting kinetic parameters for the three reverse reactions can be seen in reactions 4−6 of Table 1. Note that these kinetic parameters are significantly different from the ones in Table 4 of Hasabnis and Mahajani.1 To verify which sets of the kinetic parameters better describe the experimental data in Gelosa et al.,11 Figure 8 in Gelosa et al.11 showed the experimental data of mole fractions as a function of time for the sixth experimental run in their Table 3. We repeated the reaction condition of this sixth experimental run using corrected kinetic parameters as in Table 1 with the wrong parameters in Hasabnis and Mahajani.1 The simulation results can be seen in Figure 3. From Figure 3a using our proposed kinetic parameters, glycerol mole fraction (solid line) was decreased from the initial value of 0.250 (at t = 0 min) to 0.039 (at t = 100 min), whereas HAc mole fraction (longdashed line) was also decreased from the initial value of 0.750 (at t = 0 min) to 0.419 (at t = 100 min). This transient response closely matched the result from the observation of Figure 8 in Gelosa et al.11 On the contrary, using kinetic parameters in Hasabnis and Mahajani1 results in much less consumption of the two reactants. The reported kinetic parameters in Hasabnis and Mahajani1 also predicted much less yield of the products due to erroneous kinetic parameters of the three reverse reactions. Note that Hasabnis and Mahajani1 gave much larger pre-exponential factors for the reverse reactions. The possible reason is because KΓEQ,m was mistakenly assumed to be k−m/km in their calculations. The corrected kinetic parameters will be used in the following design study in section 3. 2.2. Thermodynamic Model. For predicting the phase equilibriums of this system, the UNIQUAC-HOC property method is used in the Aspen Plus simulation. The UNIQUAC model is selected (same as in Hasabnis and Mahajani1) to describe the nonideal VLE and possibly VLLE behavior, and the

Table 3. Boiling Point Ranking for Pure Components and Azeotropes for This System at 1 bar component

boiling point (°C)

H2O acetic acid glycerol/triacetin triacetin monoacetin glycerol/diacetin glycerol diacetin

99.65 117.58 257.62 258.80 282.37 284.45 287.21 294.10

mole basis

0.1975/0.8025

0.7052/0.2948

Gelosa et al.11 The kinetic parameters in the Arrehnius form (km,0 and EA,m) can be obtained from data in that table using linear regression. The results of the linear regression are shown in Figure 1 with the kinetic parameters shown in the first part (reactions 1−3) of Table 1. Note that these parameters are the same as reported in Table 4 of Hasabnis and Mahajani.1 The problems occur for the kinetic parameters for the three reverse reactions (reactions 4−6) in Table 4 of Hasabnis and Mahajani.1 In Gelosa et al.11 the values of the reaction equilibrium constants at various temperatures were also reported in their Table 3. From that table, the kinetic parameters in the Arrehnius form (K0 and EA,K) for the equilibrium constants can also be obtained from linear regression. The results of the linear regression are shown in Figure 2. With this information, the kinetic parameters of the reverse reactions can be calculated according to the following relationship: k −m =

km Γ KEQ, m

=

km ,0 e−EA,m / RT K0 e

−EA, K / RT

=

km ,0 K0

e−(EA,m − EA,K )/ RT (8)

Figure 5. RCM and LLE of the four main components at 1 bar. 11992

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Figure 6. Design flowsheet for no-entrainer case.

HOC (Hayden−O’Connell12) model is used to account for nonideality such as dimerization of acetic acid in the vapor phase. In the reaction system without entrainer, there are a total of six components (GLY, HAc, MONO, DI, TRI, and water). According to the reaction path in Figure 4, there are two isomers for MONO (1-monoacetin and 2-monoacetin) and also two isomers for DI (1,2-diacetin and 1,3-diacetin). Because from the experimental studies in Liao et al.13 and Zhou et al.,14 1-monoacetin and 1,3-diacetin are the main mono- and diesters to form, these two components will be used to represent MONO and DI. For rigorous design study, Aspen Plus will be used as simulation tool. Note that 1-monacetin and 1,3-diacetin are nondatabank components in Aspen Plus. Following the procedure outlined in Luyben and Chien,15 these two components can be created into Aspen Plus giving 2D molecular structure into Aspen and then also provide as many physical properties as possible from literature studies. The 2D molecular structure of 1-monoacetin can be found in NIST Chemistry WebBook16 and imported into Aspen. The second non-databank component, 1,3diacetin, cannot be found in the NIST Chemistry WebBook;16 thus, the molecular structure was manually input into Aspen. The other physical properties of these two components cannot be found from reliable sources; hence, only molecular structures and molecular weights are given with the other properties estimated by Aspen. Two other components, isobutyl acetate (IBA) or ethylene dicholoride (EDC), need to be used as candidate entrainers to remove water from the RD system; thus, there are a total of 27 pairs of binary UNIQUAC parameters to be given in the simulation. Aspen built-in parameters were taken for the following six pairs: GLY−water, HAc−water, IBA−HAc, IBA− water, EDC−HAc, and EDC−water; the rest were estimated using the UNIFAC method in Aspen Plus. All UNIQUAC binary parameters are given in Table 2. The boiling point ranking of all pure components (not including entrainer) and azeotropes can be found in Table 3 with

Figure 7. Temperature and liquid composition profiles for the case with no entrainer: (a) temperature profile; (b) liquid composition profile.

the residue curve maps and LLE of the four main components shown in Figure 5. Note that the lightest component of this system is water, which can be designed to draw out as distillate from the top of the RD column. However, it is observed that HAc is the second lightest component. Thus, with a stringent specification of HAc impurity in the water outlet stream, the typical separation problem will occur because of tangent pinch toward the pure water end of the HAc−water mixture. It is also noted that the heaviest component of this system is not triacetin. Thus, to have a feasible RD flowsheet, the conversion and selectivity have to be quite high to consume most of the glycerol and also the intermediate products, 1-monoacetin and 1,3-diacetin. Three design flowsheets will be developed in the next section.

3. STEADY-STATE DESIGN The first design flowsheet is the RD column without entrainer. The idea of the next two design flowsheets is to use an entrainer to circumvent the tangent pinch problem toward the pure water end for the HAc−water mixture. Aspen Plus will be used in the steady-state design. 3.1. Reactive Distillation Column without Entrainer. In this design flowsheet as seen in Figure 6, two feed streams are set at stoichiometric feed ratio to simplify the separation. The flow rates of glycerol and acetic acid feeds are set at 5 and 15 kmol/h, respectively. The two feeds are assumed to be not completely 11993

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Figure 8. RCM and LLE of triacetin−water−entrainer system at 1 bar: (a) IBA as entrainer; (b) EDC as entrainer.

The optimal design flowsheet is determined by minimizing the total annual cost (TAC):

pure but to have 5 mol % water in the feed streams. There are two degrees of freedoms for the RD column, with reboiler duty varying to keep the bottom triacetin product at 99.0 mol % purity and with reflux ratio varying to keep the distillate HAc impurity at 0.01 mol %. There are five design variables needed to be determined in this design flowsheet including the stage numbers of the reactive section (Nrxn), the rectifying stage (Nrec), the stripping stage (Nstr), glycerol feed location (NFGLY), and HAc feed location (NFHAc).

TAC = operating cost +

capital cost payback period

(9)

Here, a payback period of 3 years is used. The operating cost includes the costs of steam, cooling water, and catalyst. The capital cost includes the costs of column shell, internal trays, reboiler, and condenser. The formulas for the installed capital costs for all of the 11994

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Figure 9. Design flowsheet for the case using IBA as entrainer.

Figure 11. Vapor and liquid flow rate profiles for the case using IBA entrainer: (a) mass flow rates; (b) molar flow rates.

Figure 10. Temperature and vapor composition profiles for the case using IBA entrainer: (a) temperature profile; (b) vapor composition profile.

Figure 12. Design flowsheet for the case using EDC as entrainer with the same design configuration as in Figure 9.

process equipment can be found on pages 572−575 in Appendix D of Douglas’ book, Conceptual Design of Chemical Processes.17 The unit prices of the steam and cooling water were

adopted from Table 23.1 of Seider et al.’s book, Product and Process Design Principles.18 The unit price of the catalyst was 11995

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assumed to be $3.50/lb with the frequency of catalyst replacement assumed to be every 3 months. An exhaustively iterative sequential optimization procedure was used to find the optimal design flowsheet. Although timeconsuming, all combinations of the design variables were investigated to obtain the minimization of TAC. The optimization procedure is described in the following steps: (1) Guess Nrxn. (2) Guess Nrec (3) Guess Nstr. (4) Guess NFGLY and NFHAc. (5) Change the reflux ratio and reboiler duty of the RD column until the two product specifications (xB,TAG = 99 mol%; xD,HAc = 0.01 mol%) are met. (6) Go back to (4) and change NFGLY and NFHAc until the TAC is minimized. (7) Go back to (3) and change Nstr until the TAC is minimized. (8) Go back to (2) and change Nrec until the TAC is minimized. (9) Go back to (1) and change Nrxn until the TAC is minimized. Nrxn is the most sensitive design variable in terms of TAC changes and thus was set at the outmost iterative loop. There will be a minimum value of Nrxn because below this minimum value the two product specifications cannot be met. Above this minimum value, several Nrxn were set until a definite trend of TAC was observed. Note that for a specific value of Nrxn, many simulation runs are needed for the inner iterative loops. The same argument is used for the other inner design variables; several values were tried until a definite trend of TAC was observed. Another issue that needs to be addressed in each simulation run of the optimization procedure is that the reaction tray holdup used in the component balance equations needs to be consistent with the one obtained from the tray sizing calculation. In the reaction tray holdup calculation, the column diameter is determined by the tray sizing calculation in Aspen Plus, the wire height is set at 0.1 m, and the active area of the reactive tray is assumed to be 90% of the total cross-sectional area with 50% of the liquid volume occupied by the catalyst. Iterations of simulation runs are often needed to have the above consistency. The resulting optimal design flowsheet is shown in Figure 6. In this flowsheet, the naming convention is that the first stage is the condenser/reflux drum and the last stage is the reboiler. Note that the RD column is operated at a condenser pressure of 0.15 bar. The reason for operating at this vacuum pressure is to set the maximum temperature of the reactive section not to exceed 120 °C to follow the suggestion of maximum operating temperature of Amberlyst 15 catalyst (see Figure 7a). Note also that a large number of the reactive section is required to obtain high conversion and selectivity. The other thing worth mentioning is that nine rectifying stages are needed to meet the HAc impurity specification in the distillate stream. This point can be observed from the liquid composition profile in Figure 7b. This design flowsheet will serve as a base case to compare with the alternative design flowsheet by adding entrainer into the RD system. 3.2. Reactive Distillation Column with Isobutyl Acetate as Entrainer. Previous papers19−21 show that isobutyl acetate (IBA) is an effective entrainer for the acetic acid dehydration system. In Figure 8, it is demonstrated that the capability of IBA to carry water to the top of the heterogeneous azeotropic distillation column is very high (azeotropic molar composition of 0.6424 (water)/0.3576 (IBA) at 1 bar). On the contrary, the azeotropic molar composition using ethylene dichloride as

Table 4. Results Comparison of Three Designs for the Triacetin RD System configuration annualized capital cost for column shell (1000 $/year) annualized capital cost for column tray (1000 $/year) annualized capital cost for reboiler (1000 $/year) annualized capital cost for condenser (1000 $/year) annualized capital cost for decanter (1000 $/year) cooling water cost (1000 $/year) catalyst cost (1000 $/year) entrainer makeup (1000 $/year) steam cost (1000 $/year) TAC (1000 $/year) (% difference)

RD with no RD with IBA RD with EDC entrainer as entrainer as entrainer 103.02

27.79

60.36

13.30

2.55

7.88

77.34

28.55

209.58

53.89

53.30

128.21

9.55

51.17

2.63 4.32 41.65 77.91 (−24.81%) 248.25 (−34.69%)

20.57 15.92 14.73 598.2 (+477.3%) 1106.62 (+191.2%)

3.50 25.42 103.62 (0%) 380.09 (0%)

entrainer is only 0.3311 (water)/0.6689 (EDC) at 1 bar. Although the azeotropic temperature of water/EDC is lower than that of water/IBA and also the boiling point of EDC is much lower than that of IBA, the reactive distillation process using IBA as entrainer can still meet the high temperature limitation in the reaction section by lowering the operating pressure of the system. The same feed and product conditions are assumed in this RD development. The only difference in the design flowsheet is at top of the RD column. The top vapor of RD is designed to approach the lowest temperature of the system. In this case with an addition of IBA into this RD system, the component with the lowest temperature becomes the H2O/IBA azeotrope. From Figure 8, it is observed that this top vapor, after condensation, can naturally be separated into two liquid phases. The aqueous phase can be drawn out of the system, whereas the organic phase, containing mostly IBA, is designed to be recycled back to the RD column for further carrying water out of the system. A small IBA makeup stream is needed to balance out the loss of IBA at the aqueous outlet stream. The number of design variables needed to be determined in the TAC minimization study is the same. The reboiler duty is again used to maintain the bottom product purity at 99.0 mol %. The only difference is about the top product specification. This aqueous purity of 0.01 mol % HAc can be maintained by varying the makeup flow rate. Note that there is a recycle loop, which is very important to get the simulation to converge. Our experience is to define the tear stream as the organic reflux stream and then give a good initial guess of its composition and flow rate. The initial guess of the composition of this stream can be estimated from Figure 8a by assuming the top vapor composition is right at the IBA−water azeotrope. The top vapor flow rate can also be estimated by carrying all water into this stream. Then, the initial guess of organic flow rate can be estimated by lever rule. The same iterative sequential optimization procedure as outlined in the previous subsection was followed to find the optimal design flowsheet. There are two extra terms in the TAC calculations, which are a stream cost for the IBA makeup flow and a capital cost for the decanter. Because the entrainer makeup flow rate is small, the capital cost of an entrainer storage tank can be neglected. Note also that in comparison with the case of no entrainer, a one-time entrainer startup cost is additionally required to provide recirculation of IBA inside the process system. 11996

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Figure 13. Sensitivity analyses plots: (a) closed-loop sensitivity analyses; (b) open-loop sensitivity analyses.

However, because it is only a one-time cost, we did not put this term into TAC. Also, to be more accurate in the TAC calculation, the costs associated with the vacuum system to generate an operating pressure at 0.25 bar should also be included. However, by following the procedure outlined on pages 589−590 of Seider et al.’s book,18 the costs associated with this moderate vacuum system of a small-sized RD column can be neglected in comparison with other main terms in the TAC calculation. The optimal flowsheet of the proposed design is shown in Figure 9 with the temperature and vapor composition profiles shown in Figure 10 and vapor and liquid flow rate profiles shown in Figure 11. Note that the naming convention is a little different from the regular RD column in the above subsection. Because the

Table 5. Results of Close-Loop Sensitivity Analyses H2O in GLY + 50%

H2O in GLY − 50%

H2O in HAc + 50%

H2O in HAc − 50%

−2.21%

2.24%

2.34%

−2.19%

reboiler duty/HAc feed

0.44%

−0.38%

−0.35%

0.38%

reboiler duty/ bottom product

0.44%

−0.38%

2.34%

−2.19%

reboiler duty

−1.95%

1.98%

2.24%

−2.09%

IBA makeup/HAc feed

0.70%

−0.63%

−0.45%

0.49%

IBA makeup/ bottom product

0.70%

−0.63%

2.24%

−2.09%

IBA makeup

11997

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Figure 14. Proposed overall control strategy of the studied system.

condenser and decanter are separated from the main RD column in the simulation, the top tray is now the first stage and the last stage is still the reboiler. It is noted that significant reductions in the reactive stages and also the rectifying stages are observed. The number of reactive stages is reduced from 35 to 7, whereas the number of rectifying stages is reduced from 9 to 2. It is also noted that significant reduction in the reboiler duty (436.11 vs 327.90 kW) can also be realized by using this entrainer-based RD design. The top pressure of the RD column is set to be 0.25 bar so that the maximum temperature in the reactive section is still