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Reactive distillation processes used as unique operation or finishing stage
Ian David Lockhart Bogle and Michael Fairweather (Editors), Proceedings of the 22nd European Symposium on Computer Aided Process Engineering, 17 - 20 June 2012, London. © 2012 Elsevier B.V. All rights reserved.
Reactive distillation processes used as unique operation or finishing stage: A comparison Juan P. Archenti, M.S. Diaz, P.M. Hoch Planta Piloto de Ingenieria Quimica, Departamento de Ingeniería Química, Universidad Nacional del Sur, 8000 Bahia Blanca,, Argentina
Abstract The main objective of this work is modeling and designing a reactive distillation unit with rigorous hydraulic constraints, determining the configuration at the same time. The RD unit is modeled using an equilibrium model (Taylor and Krishna, 2000) based on first principles (mass and energy balances and phase equilibrium relationships). Two different process schemes are proposed: one in which the reactive distillation unit represents the only reactive operation within the process and one in which reactive distillation is used as a finishing process, after a fixed bed adiabatic reactor stage. In both schemes, the reactive stages are modeled as trays with catalyst bags (Jones Jr., 1985). Two different optimization targets are evaluated: maximizing MTBE product purity and maximizing isobutylene global conversion to MTBE. The unit is sized according to rigorous hydraulic considerations (Stichlmair and Fair, 1998), while the number of reactive and non-reactive trays is estimated within an MINLP problem. Cost estimations are provided. Results for process variables are summarized for industrial size designs. Results show that lumping reaction and separation unit operations reduces the cost for the process equipment and also the energy consumption, still obtaining a similar process performance since product purity and reactant conversion are very similar to those of conventional processes. Keywords: Reactive distillation, optimization, Proces intensification
1. Introduction Reactive Distillation (RD) is an example of process intensification. The main advantages over the conventional processes reside in that it is possible to react away azeotropes, efficient heat integration is achieved and equilibrium conversions are shifted by continuously separating reaction products from the reactive section. Process equipment volume is also reduced optimizing available plant space usage. MTBE is a fuel additive. It can be obtained reacting Isobutylene and Methanol via conventional and unconventional processes. The conventional kind does not employ reactive distillation while the unconventional does. The most famous conventional processes are Phillips and Hüls (Myers, 1986). The UOP and ABB Lummus processes are worth mentioning among the unconventional kind (Al-Harthi, 2008). A conventional process comprehends several different sections: MTBE synthesis (consisting of two adiabatic fixed bed reactors in series), MTBE purification (consisting of 1 or 2 distillation towers) and Methanol Recovery. Unconventional processes lump the second reaction stage together with the first distillation tower. The main scope of this work is to model the synthesis section by using reactive distillation as a unique reactive process or as a finishing process, preceded by a single adiabatic reaction stage, such as it is used by unconventional processes. Different
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scenarios will be simulated pursuing different optimization targets. Finally, cost estimations will be provided for the different feasible alternatives.
2. Process and model description A typical feed for a conventional process is obtained from Meyers (1986). It consists of a hydrocarbon stream with a high content of Isobutylene. Methanol is used in excess but the excess amount is not reported. In a first approach, the entire plant’s MTBE synthesis section is replaced by a single reactive distillation unit. Two different simulation scenarios are run: scenario 1 maximizes the MTBE bottom purity and scenario 2 maximizes the Isobutylene to MTBE conversion. Figure 1 shows the process hardware and variables for scenarios 1 and 2. The column consists of 3 rectifying plates, 9 reactive plates and 6 stripping plates. The Methanol feed flow rate to each plate is left as an optimizer decision variable so that both the total excess and feed/s location will come out as a simulation result. As mentioned, unconventional processes use reactive distillation as a finishing reactive treatment. Hence, it is decided to simulate 2 extra scenarios to test how the addition of a pre-reaction stage impact the process performance and sizing variables for the reactive distillation unit. In a second instance, a pre-reactor is added to which the reactants streams are fed in the conditions showed in Figure 2. Kinetic considerations are left out to model pre-reaction. Instead, equilibrium conversion is calculated for the feed conditions and operative conversion is selected as 80 % of equilibrium conversion. Feed temperature to prereaction is established as 313 K, chosen as 10 ºC higher than cooling water typical temperature. Operative conversion turns out to be 50.9 %. Pre-reactor effluent stream is fed to the reactive distillation unit and once again the optimizer is allowed to decide on the addition of any further Methanol and its feed location (stage number). The new scenarios and optimization targets are: scenario 3 pursuing maximum MTBE purity and scenario 4 maximizing global Isobutylene conversion. The plate distribution (3 rectifying, 9 reactive and 6 stripping) for the latter scenarios is identical to that of scenarios 1 or 2. Columns’ sizes, however, will differ based on differences in internal flow rates between the different proposed scenarios. A constraint on MTBE minimum purity is included for all 4 scenarios in order to guarantee that a 95% MTBE mass fraction is obtained (fuel grade). An equilibrium stage model (Taylor and Krishna, 2000) is used to describe the reactive distillation tower. This model consists of first principles, such as mass and energy balances and vapor liquid equilibrium relationships, and it is based on the work by Almeida-Rivera (2005) and Domancich et al. (2007). All the thermodynamic, kinetic and other relevant mathematical expressions and parameters can be obtained from the latter references with the exception of the Wilson’s equation parameters utilized for the current work which were actually reported by Espinosa et al. (1995) because they exhibit better correspondence with experimental data. Once all the process variables related to separation and reaction processes have been obtained, a rigorous hydraulic design procedure is carried out in accordance with Stichlmair and Fair (1998). The pressure profile for the column is calculated within the optimization algorithm. Therefore, column feeds will have to be compressed or pumped to the proper pressure in order to flow into the column. A constraint on maximum column pressure of 12 bar (abs) is imposed for all 4 scenarios. All quantities related to hydraulic calculations are obtained as stated by Stichlmair and Fair (1998) except for the clear liquid height fraction in the froth which is taken from
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Bennet et al. (1983). Also, hydraulic calculations require knowing the value of physical properties for the process mixtures such as surface tension. The equations that relate the surface tension to temperature for pure components are obtained from the software TERMOINT (2003) together with the proper fitting constants. A mixing rule, suitable for the processed mixtures is used (Perry and Green, 1997). The catalyst to be used is an ion exchange resin. Its properties are obtained from the literature (Al-Harthi, 2008). Several alternatives exist for the catalyst location inside the column (Baur et al., 2001). The current work locates the catalyst onto the active area of the column plates. Hence, the area occupied by the catalyst is deducted from the active area in order to calculate vapor velocity. In other words, both downcomer area and catalyst occupied area are deducted from the total cross section in order to account for the available area for vapor flow. Details for the proposed catalyst location can be obtained from the corresponding patent (Jones, 1985).
Figure 1: Scenarios 1 and 2
Figure 2: Scenarios 3 and 4
(Stages are numbered top to bottom, stage 1=condenser, stage 21= reboiler for both figures)
3. Results and Discussion Table 1 shows the main process variables. Secondary process variables appear in Table 1(cont’), the Methanol to be recovered will have to be separated in the Methanol Recovery section of the plant and recycled to the synthesis section. Constructive variables specific for each scenario can be obtained from Table 2. Different section diameters and tray spacing are required to comply with the minimum and maximum liquid and vapour loads to the trayed column. Internal flow rates vary significantly due to the feed addition and the evaporation of liquid as a consequence of the heat released by the highly exothermic reaction taking place into the unit. Cost estimations do not include the condenser or reboiler. An estimation for scenario 1 cannot be provided given that the costing method (FPI, 1976) is not suited for such a large diameter (more than 5 m). Section diameters obtained exceed commercially common ones. This is due to the high reflux ratios used and the large amount of vapour produced by reaction heat. Such values, however, do not exceed values reported by other authors (Baur et al., 2001 and Almeida, 2005). Table 3 shows constructive variables held constant for all 4 scenarios. Results indicate that scenarios 2 and 4 are the most promising since the minimum purity is achieved and a high conversion of the limiting reactant has been obtained. Both purity and conversion are similar to those obtained by conventional processes (Meyers, 1986).
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Scenario 4 allows for a little higher conversion, still closer to the reported 99 % for the best conventional process (Hüls). The remaining variables, associated with energy consumptions and required raw material, do not vary significantly. Cost estimations provided for the 3 feasible scenarios are very similar to each other so that options cannot be ruled out on economic basis (except for scenario 1). Table 1. Main Process Variables
Scenario Nº
MTBE Purity % weight
1 2 3 4
99.5 95 99.1 95
Isobut Global Conversion % 81.6 98.2 95.25 98.94
Isobut Step Conv in RD % 81.6 98.2 90.3 97.8
Reflux Ratio 6 2.908 3.768 2.415
Table 1(cont’). Secondary Process Variables
Condenser Duty MW
Reboiler Duty MW
Operative Max Press bar (abs)
Total Methanol Used mol/s
Methanol fed to RD Column mol/s
Methanol to be Recovered mol/s
13.5 6.87 8.81 5.98
8.99 2.24 5.37 2.71
9.24 11.63 9.69 11.63
60.31 71.05 69.21 70.95
60.31 71.05 2.24 3.98
21.71 24.63 21.96 24.33
Methanol molar fract in distillate 0.109 0.129 0.114 0.128
Table 2. Reactive Distillation Units’ Specific Constructive Variables Scenario Nº 1 2 3 4
Column Diam Stages 2-14 m 5.6 4.43 4.8 4.25
Column Diam Stages 15-20 m 4 1.71 2.9 2.2
Upper Sect Height m 13.05 13.05 13.05 13.05
Lower Sect Height m 7.56 6.38 6.38 7.56
Table 2(cont’). Reactive Distillation Units’ Specific Constructive Variables Tray Spac Tray Spac Cost Estimation St 2-17 St 18-20 M$ m m 0.91 1 0.91 0.91 1.295 0.91 0.91 1.542 0.91 1 1.327 Table 3. Reactive Distillation Units’ Common Constructive Variables Active Area Void Fraction % 6
Orifice Diameter mm
Weir Lenght
Weir Height cm
4
0.765 D
10
Catalyst Envelopes Height cm 8
Catalyst Bed Density kg/m3 760
Catal Load to React Stages kg 294
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Table 4: Optimal Methanol Feed/s to each Stage, mol/s Scenario Nº 1 2 3 4
St2
St3
St4
St5
St6
St7
St8
St9
St10
St11
St12
0.57
5.58
7.078
7.941
11.917
8.375
7.875
6.66
4.317
71.1 3.98
Table 4 shows the optimum amount of Methanol fed to each plate for optimizing the desired variable depending on each scenario. The reactant must be distributed almost all along the column in scenario 1 while scenario 3 needs no further Methanol than the amount that slips from the pre-reactor. For scenarios 2 and 4 the required Methanol is fed at the top plate.
Conclusions A model has been developed for the MTBE synthesis section considering different process units arrangements. Results show that both utilizing the reactive distillation unit as a finishing process or unique reactive stage seem feasible and comparable to the performance of the conventional processes. Using it as a finishing stage allows achieving a slightly higher conversion. Therefore, the decision is not straightforward and a more rigorous economic evaluation should be performed, rather than just costing the reactive distillation unit, in order to decide on the inclusion of the pre-reactor. The reactive distillation option seems to be comparable to that of conventional processes but it offers several advantages being a process intensification scheme.
References Almeida-Rivera C.P, 2005, Designing Reactive Distillation Processes with Improved Efficiency, PhD Thesis, Technische Universitet Delft, The Netherlands. Baur R., Taylor R. and Krishna R., 2001, Influence of Column Hardware on the performance of reactive Distillation Columns, Catalysis Today 66, 225-232. Bennet D.L., Agrawald R. and Cook P.J., 1983, New Pressure Drop Correlation for Sieve Tray Distillation Columns, AIChE Journal 29, 434-442. Domancich A.O, Brignole N.B. and Hoch P.M., 2007, Optimal structure of reactive and nonreactive stages in reactive distillation processes, Chem. Engng. Transactions, 12, 85-90. Espinosa, H.J., Aguirre P.A. and Pérez G., 1995, Product composition region of single-feed reactive distillation columns: mixtures containing inerts. I&ECR 34, 853-861. Al-Harthi, Fahad S., 2008, Modeling and Simulation of a Reactive Distillation Unit for the Production of MTBE, MSc Dissertation, King Saud University, Saudi Arabia. French Petroleum Institute, (FPI), 1981, Manual of Economic Analysis of Chemical Processes, McGraw-Hill, New York, USA. Jones Jr. E.M., 1985, US Patent 4536373. Meyers R. A., 1986, Handbook of Chemical Production Processes, McGraw-Hill, NY, USA. Perry R. H. and Green D. W., 1997, Perry’s Chemical Engineers’ Handbook 7th Edition, McGraw-Hill, New York, USA. Stichlmair J.G. and Fair J.R., 1998, Distillation: Principles and Practices, John Wiley and Sons, New York, USA. Taylor R. and Krishna R., 2000, Modeling Reactive Distillation, Chemical Engineering Science 55, 5183-5229. Termoint, Chemical compounds physical properties calculation software package based on the database DIPPR 801, 2003, developed by Nuñez D. and Zabaloy M. (PLAPIQUI), Bahía Blanca, Argentina (in Spanish).
Reactive distillation processes used as unique operation or finishing stage: A comparison Juan P. Archenti, M.S. Diaz, P.M. Hoch Planta Piloto de Ingenieria Quimica, Departamento de Ingeniería Química, Universidad Nacional del Sur, 8000 Bahia Blanca,, Argentina
Abstract The main objective of this work is modeling and designing a reactive distillation unit with rigorous hydraulic constraints, determining the configuration at the same time. The RD unit is modeled using an equilibrium model (Taylor and Krishna, 2000) based on first principles (mass and energy balances and phase equilibrium relationships). Two different process schemes are proposed: one in which the reactive distillation unit represents the only reactive operation within the process and one in which reactive distillation is used as a finishing process, after a fixed bed adiabatic reactor stage. In both schemes, the reactive stages are modeled as trays with catalyst bags (Jones Jr., 1985). Two different optimization targets are evaluated: maximizing MTBE product purity and maximizing isobutylene global conversion to MTBE. The unit is sized according to rigorous hydraulic considerations (Stichlmair and Fair, 1998), while the number of reactive and non-reactive trays is estimated within an MINLP problem. Cost estimations are provided. Results for process variables are summarized for industrial size designs. Results show that lumping reaction and separation unit operations reduces the cost for the process equipment and also the energy consumption, still obtaining a similar process performance since product purity and reactant conversion are very similar to those of conventional processes. Keywords: Reactive distillation, optimization, Proces intensification
1. Introduction Reactive Distillation (RD) is an example of process intensification. The main advantages over the conventional processes reside in that it is possible to react away azeotropes, efficient heat integration is achieved and equilibrium conversions are shifted by continuously separating reaction products from the reactive section. Process equipment volume is also reduced optimizing available plant space usage. MTBE is a fuel additive. It can be obtained reacting Isobutylene and Methanol via conventional and unconventional processes. The conventional kind does not employ reactive distillation while the unconventional does. The most famous conventional processes are Phillips and Hüls (Myers, 1986). The UOP and ABB Lummus processes are worth mentioning among the unconventional kind (Al-Harthi, 2008). A conventional process comprehends several different sections: MTBE synthesis (consisting of two adiabatic fixed bed reactors in series), MTBE purification (consisting of 1 or 2 distillation towers) and Methanol Recovery. Unconventional processes lump the second reaction stage together with the first distillation tower. The main scope of this work is to model the synthesis section by using reactive distillation as a unique reactive process or as a finishing process, preceded by a single adiabatic reaction stage, such as it is used by unconventional processes. Different
733
Reactive distillation processes used as ...
scenarios will be simulated pursuing different optimization targets. Finally, cost estimations will be provided for the different feasible alternatives.
2. Process and model description A typical feed for a conventional process is obtained from Meyers (1986). It consists of a hydrocarbon stream with a high content of Isobutylene. Methanol is used in excess but the excess amount is not reported. In a first approach, the entire plant’s MTBE synthesis section is replaced by a single reactive distillation unit. Two different simulation scenarios are run: scenario 1 maximizes the MTBE bottom purity and scenario 2 maximizes the Isobutylene to MTBE conversion. Figure 1 shows the process hardware and variables for scenarios 1 and 2. The column consists of 3 rectifying plates, 9 reactive plates and 6 stripping plates. The Methanol feed flow rate to each plate is left as an optimizer decision variable so that both the total excess and feed/s location will come out as a simulation result. As mentioned, unconventional processes use reactive distillation as a finishing reactive treatment. Hence, it is decided to simulate 2 extra scenarios to test how the addition of a pre-reaction stage impact the process performance and sizing variables for the reactive distillation unit. In a second instance, a pre-reactor is added to which the reactants streams are fed in the conditions showed in Figure 2. Kinetic considerations are left out to model pre-reaction. Instead, equilibrium conversion is calculated for the feed conditions and operative conversion is selected as 80 % of equilibrium conversion. Feed temperature to prereaction is established as 313 K, chosen as 10 ºC higher than cooling water typical temperature. Operative conversion turns out to be 50.9 %. Pre-reactor effluent stream is fed to the reactive distillation unit and once again the optimizer is allowed to decide on the addition of any further Methanol and its feed location (stage number). The new scenarios and optimization targets are: scenario 3 pursuing maximum MTBE purity and scenario 4 maximizing global Isobutylene conversion. The plate distribution (3 rectifying, 9 reactive and 6 stripping) for the latter scenarios is identical to that of scenarios 1 or 2. Columns’ sizes, however, will differ based on differences in internal flow rates between the different proposed scenarios. A constraint on MTBE minimum purity is included for all 4 scenarios in order to guarantee that a 95% MTBE mass fraction is obtained (fuel grade). An equilibrium stage model (Taylor and Krishna, 2000) is used to describe the reactive distillation tower. This model consists of first principles, such as mass and energy balances and vapor liquid equilibrium relationships, and it is based on the work by Almeida-Rivera (2005) and Domancich et al. (2007). All the thermodynamic, kinetic and other relevant mathematical expressions and parameters can be obtained from the latter references with the exception of the Wilson’s equation parameters utilized for the current work which were actually reported by Espinosa et al. (1995) because they exhibit better correspondence with experimental data. Once all the process variables related to separation and reaction processes have been obtained, a rigorous hydraulic design procedure is carried out in accordance with Stichlmair and Fair (1998). The pressure profile for the column is calculated within the optimization algorithm. Therefore, column feeds will have to be compressed or pumped to the proper pressure in order to flow into the column. A constraint on maximum column pressure of 12 bar (abs) is imposed for all 4 scenarios. All quantities related to hydraulic calculations are obtained as stated by Stichlmair and Fair (1998) except for the clear liquid height fraction in the froth which is taken from
734
J.P Archenti et. al
Bennet et al. (1983). Also, hydraulic calculations require knowing the value of physical properties for the process mixtures such as surface tension. The equations that relate the surface tension to temperature for pure components are obtained from the software TERMOINT (2003) together with the proper fitting constants. A mixing rule, suitable for the processed mixtures is used (Perry and Green, 1997). The catalyst to be used is an ion exchange resin. Its properties are obtained from the literature (Al-Harthi, 2008). Several alternatives exist for the catalyst location inside the column (Baur et al., 2001). The current work locates the catalyst onto the active area of the column plates. Hence, the area occupied by the catalyst is deducted from the active area in order to calculate vapor velocity. In other words, both downcomer area and catalyst occupied area are deducted from the total cross section in order to account for the available area for vapor flow. Details for the proposed catalyst location can be obtained from the corresponding patent (Jones, 1985).
Figure 1: Scenarios 1 and 2
Figure 2: Scenarios 3 and 4
(Stages are numbered top to bottom, stage 1=condenser, stage 21= reboiler for both figures)
3. Results and Discussion Table 1 shows the main process variables. Secondary process variables appear in Table 1(cont’), the Methanol to be recovered will have to be separated in the Methanol Recovery section of the plant and recycled to the synthesis section. Constructive variables specific for each scenario can be obtained from Table 2. Different section diameters and tray spacing are required to comply with the minimum and maximum liquid and vapour loads to the trayed column. Internal flow rates vary significantly due to the feed addition and the evaporation of liquid as a consequence of the heat released by the highly exothermic reaction taking place into the unit. Cost estimations do not include the condenser or reboiler. An estimation for scenario 1 cannot be provided given that the costing method (FPI, 1976) is not suited for such a large diameter (more than 5 m). Section diameters obtained exceed commercially common ones. This is due to the high reflux ratios used and the large amount of vapour produced by reaction heat. Such values, however, do not exceed values reported by other authors (Baur et al., 2001 and Almeida, 2005). Table 3 shows constructive variables held constant for all 4 scenarios. Results indicate that scenarios 2 and 4 are the most promising since the minimum purity is achieved and a high conversion of the limiting reactant has been obtained. Both purity and conversion are similar to those obtained by conventional processes (Meyers, 1986).
735
Reactive distillation processes used as ...
Scenario 4 allows for a little higher conversion, still closer to the reported 99 % for the best conventional process (Hüls). The remaining variables, associated with energy consumptions and required raw material, do not vary significantly. Cost estimations provided for the 3 feasible scenarios are very similar to each other so that options cannot be ruled out on economic basis (except for scenario 1). Table 1. Main Process Variables
Scenario Nº
MTBE Purity % weight
1 2 3 4
99.5 95 99.1 95
Isobut Global Conversion % 81.6 98.2 95.25 98.94
Isobut Step Conv in RD % 81.6 98.2 90.3 97.8
Reflux Ratio 6 2.908 3.768 2.415
Table 1(cont’). Secondary Process Variables
Condenser Duty MW
Reboiler Duty MW
Operative Max Press bar (abs)
Total Methanol Used mol/s
Methanol fed to RD Column mol/s
Methanol to be Recovered mol/s
13.5 6.87 8.81 5.98
8.99 2.24 5.37 2.71
9.24 11.63 9.69 11.63
60.31 71.05 69.21 70.95
60.31 71.05 2.24 3.98
21.71 24.63 21.96 24.33
Methanol molar fract in distillate 0.109 0.129 0.114 0.128
Table 2. Reactive Distillation Units’ Specific Constructive Variables Scenario Nº 1 2 3 4
Column Diam Stages 2-14 m 5.6 4.43 4.8 4.25
Column Diam Stages 15-20 m 4 1.71 2.9 2.2
Upper Sect Height m 13.05 13.05 13.05 13.05
Lower Sect Height m 7.56 6.38 6.38 7.56
Table 2(cont’). Reactive Distillation Units’ Specific Constructive Variables Tray Spac Tray Spac Cost Estimation St 2-17 St 18-20 M$ m m 0.91 1 0.91 0.91 1.295 0.91 0.91 1.542 0.91 1 1.327 Table 3. Reactive Distillation Units’ Common Constructive Variables Active Area Void Fraction % 6
Orifice Diameter mm
Weir Lenght
Weir Height cm
4
0.765 D
10
Catalyst Envelopes Height cm 8
Catalyst Bed Density kg/m3 760
Catal Load to React Stages kg 294
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Table 4: Optimal Methanol Feed/s to each Stage, mol/s Scenario Nº 1 2 3 4
St2
St3
St4
St5
St6
St7
St8
St9
St10
St11
St12
0.57
5.58
7.078
7.941
11.917
8.375
7.875
6.66
4.317
71.1 3.98
Table 4 shows the optimum amount of Methanol fed to each plate for optimizing the desired variable depending on each scenario. The reactant must be distributed almost all along the column in scenario 1 while scenario 3 needs no further Methanol than the amount that slips from the pre-reactor. For scenarios 2 and 4 the required Methanol is fed at the top plate.
Conclusions A model has been developed for the MTBE synthesis section considering different process units arrangements. Results show that both utilizing the reactive distillation unit as a finishing process or unique reactive stage seem feasible and comparable to the performance of the conventional processes. Using it as a finishing stage allows achieving a slightly higher conversion. Therefore, the decision is not straightforward and a more rigorous economic evaluation should be performed, rather than just costing the reactive distillation unit, in order to decide on the inclusion of the pre-reactor. The reactive distillation option seems to be comparable to that of conventional processes but it offers several advantages being a process intensification scheme.
References Almeida-Rivera C.P, 2005, Designing Reactive Distillation Processes with Improved Efficiency, PhD Thesis, Technische Universitet Delft, The Netherlands. Baur R., Taylor R. and Krishna R., 2001, Influence of Column Hardware on the performance of reactive Distillation Columns, Catalysis Today 66, 225-232. Bennet D.L., Agrawald R. and Cook P.J., 1983, New Pressure Drop Correlation for Sieve Tray Distillation Columns, AIChE Journal 29, 434-442. Domancich A.O, Brignole N.B. and Hoch P.M., 2007, Optimal structure of reactive and nonreactive stages in reactive distillation processes, Chem. Engng. Transactions, 12, 85-90. Espinosa, H.J., Aguirre P.A. and Pérez G., 1995, Product composition region of single-feed reactive distillation columns: mixtures containing inerts. I&ECR 34, 853-861. Al-Harthi, Fahad S., 2008, Modeling and Simulation of a Reactive Distillation Unit for the Production of MTBE, MSc Dissertation, King Saud University, Saudi Arabia. French Petroleum Institute, (FPI), 1981, Manual of Economic Analysis of Chemical Processes, McGraw-Hill, New York, USA. Jones Jr. E.M., 1985, US Patent 4536373. Meyers R. A., 1986, Handbook of Chemical Production Processes, McGraw-Hill, NY, USA. Perry R. H. and Green D. W., 1997, Perry’s Chemical Engineers’ Handbook 7th Edition, McGraw-Hill, New York, USA. Stichlmair J.G. and Fair J.R., 1998, Distillation: Principles and Practices, John Wiley and Sons, New York, USA. Taylor R. and Krishna R., 2000, Modeling Reactive Distillation, Chemical Engineering Science 55, 5183-5229. Termoint, Chemical compounds physical properties calculation software package based on the database DIPPR 801, 2003, developed by Nuñez D. and Zabaloy M. (PLAPIQUI), Bahía Blanca, Argentina (in Spanish).