Simulation Studies and Sensitivity Analysis of Methyl Tert-butyl Ether Reactive Distillation

Transcription

1 Simulation Studies and Sensitivity Analysis of Methyl Tert-butyl Ether Reactive Distillation Sudibyo, Murat, M. N. and Aziz, N. School of Chemical Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal, Seberang Perai Selatan, Penang, Malaysia. * Abstract Methyl Tert-butyl Ether (MTBE) is an important chemical used as an octane booster in gasoline to replace tetra ethyl lead. Maximum production of the MTBE can be achieved using reactive distillation (RD) process at the optimum operating conditions and column configuration. However, optimizing the column configuration such as tray or catalyst location is experimentally expensive. Therefore, a reliable model of the MTBE reactive distillation is important to find the optimum conditions for MTBE production. In this work, continuous RD processes is simulated based on dynamic model using Aspen Dynamics. The model is then further used in Matlab environment for the singular value decomposition (SVD) analysis in order to select the feasible input-output pair for the control implementation. Finally, the step test is conducted in order to observe the sensitivity of the MTBE process toward changes of selected input variables. The results show that the output obtained from the Aspen is comparable with the literature and the tray temperature number 3 and 8 are the most sensitive output variables toward changes of reflux flowrate and reboiler duty. Keywords: Reactive distillation; Dynamic simulation; MTBE, sensitivity analysis 1. Introduction Separation and reaction processes can be combined in one unit process which is called as reactive distillation (RD). It has been used in several industries especially for the process which have reversible reaction [Sharma and Singh, 2010]. RD can reduce the capital investment, because two process steps can be carried out in the same device [Higler et al., 1999; Taylor and Krishna, 2000; Murat et al., 2003; Mohammed, 2009]. However, it is still difficult to bring a new reactive distillation column into industrial applications because of the complexities in design, synthesis and operability of RD, which is resulting from the interaction of reaction and distillation. [Satyanarayana and Saha, 2005]. Here, MTBE is considered because it is an important chemical that is used as solvent, chemical reagent and antiknock additive to improve octane number of gasoline [Sharma & Singh, 2010]. MTBE can be efficiently produced using RD; with isobutene conversion up to 99 % can be achieved [Taylor and Krishna, 2000]. The purpose of RD control is to maintain the product purity and the conversion at a desired value or range. However, to control the conversion directly is a difficult task and expensive to be applied in industry. Thus, MTBE purity can be controlled by controlling tray temperature because the MTBE purity can be correlated with tray temperature [Taylor and Krishna, 2000]. Many researchers have modeled or simulated the MTBE RD process using either first principle model or various commercial software

2 such as HYSIS and Aspen [Higler et al., 1999; Taylor and Krishna, 2000; Murat et al., 2003; Satyanarayana and Saha, 2005; López-Arenas et al., 2006; Mohammed, 2009;]. However, those who used the commercial software were aim for the steady state model. In this work, the industrial RD dynamic process model is developed using Aspen Dynamics which is more feasible to be used for design and verification of process control schemes and safety studies. At the same time, the SVD analysis and the step test are also carried out in order to evaluate the controllability and sensitivity of the process [Pearson, 2003]. The work is carried out in Matlab environment (Simulink) and interfacing with Aspen. 2. Description of the MTBE Column Methanol (215.5 mol/s) mol Fraction = 1 T = 320 K, P = 12 Atm Feed Stage = 4 Reflux ratio = 7 Rectification section Reaction section BUTENE (549 m/s) Isobutene (mol fraction) = T = 350 K, P = 12 Atm Feed Stage = 11 Stripping section Figure 1. MTBE Reactive Distillation Column Table 1. Tray and Packed Column Specification [Higler et al., 1999] Packed column specification Tray specification Parameters Reaction Section Parameters Rectifying Section Stripping Section Column Diameter 6 m Column Diameter 5.95 m m Total column area m 2 Total tray area m m 2 Packing height 0.7 m Number of pass 4 4 Packing size ¼ in Active area m m 2 Nominal size m Total hole area 2.12 m m 2 Packing factor Downcomer area MTBE reactive distillation column consists of three sections: rectification, reaction and stripping as shown in Fig. 1. For this case study, the RD column has 17 stages, including a total condenser and a partial reboiler as given in Fig. 1 [Higler et al., 1999]. The tray and packed column specifications and operation conditions are given in Table 1. The specification used here is similar to the specification used by Higler et al. [1999], except the number of passes, the pressure column and location of feed stages are different. In this work, 4 passes and 12 atm of pressure column while Higler et al. [1999] have used 5 passes and 11 atm. Meanwhile, the feed, methanol and butane, are

3 fed at stages 4 and 11, respectively (being optimized) in order to get the maximum value of isobutene conversion MTBE Reaction Scheme The most promising technique of producing MTBE is from methanol and isobutene, where the liquid-phase reaction is catalyzed by ion exchange resin (heterogeneous reaction). The reaction scheme is: i-c 4 H 8 + CH 3 -OH C 5 H 12 O (1) Chemical equilibrium constant for reaction (1) used in the Aspen is: ln k eq = ln k eq0 + α[(1/t) (1/T*)] + β ln (T/T ) + σ(t T*) + δ (T 2 T* 2 ) + ε(t 3 T* 3 ) + θ(t 4 -T* 4 ) (2) where α is x 10 3, β is , γ is x 10-1, δ is x 10-4, ε is x 10-6, θ is x 10-10, T* = K, keq0 = 284 [Murat et al., 2003]. 3. Results and Discussion 3.1. Modeling of Reactive Distillation The results obtained from the RD dynamic model using Aspen dynamics were compared with data available in literature and tabulated in Table 2. From the table, it is found that the simulation results obtained are comparable to the published results which verify that the proposed Aspen Dynamics model is capable to simulate the reactive distillation to produce MTBE. The small differences observed in the result obtained are due to some different specifications (as mentioned earlier) used in the simulation. The isobutene conversion can reach 99.82% using reactive distillation and which is in a good agreement with the value reported in the literature [Taylor and Krishna, 2000]. Table 2. Model Comparison Nijhuis et al Murat et al., 2003 This Work i -butene conversion 98.5% 99.5% 99.82% MTBE Purity 98% 98.6% 95.04% Software Aspen Fortran 90 Aspen Dynamics 3.2. Singular value decomposition (SVD) analysis Here, the most suitable tray temperature to be paired as controlled variable in respect of manipulated variable changes (reflux flowrate and reboiler duty) was determined using SVD analysis technique. The SVD test was conducted by changing the inputs of manipulated variable with the step magnitude of +0.1% from nominal input value [Luyben, 2006; Imam and Aziz, 2011]. The SVD analysis was performed by SVD command in Matlab which calculated the left singular vectors from SVD analysis result (U SVD ) as shown on Fig. 2. From Fig. 2, tray number 3 and 8 show the largest magnitude which signifies that they are the most sensitive trays temperature towards the changes of reflux flowrate and the reboiler duty, respectively Step Test Study Effect of Reflux Flowrate The study was performed by introducing several step-tests with different magnitude of manipulated variable (reflux flowrate) and the response on tray temperature (tray number 3) is observed. Fig. 3 shows the effect of reflux flowrate changes on the

4 temperature of tray number 3 and MTBE purity. From Fig. 3a, it is show that the temperature of tray number 3 is decrease when the reflux flowrate is increasing. The changes in the reflux flowrate produce an asymmetric form of the output response thus signify that the reactive column is a nonlinear process. The changing of reflux flowrate also affected the MTBE purity as shown in Fig. 3b, where the MTBE purity decrease as the reflux flowrate increase. Figure 2. U SVD versus tray number (a) (b) Figure 3. Effect of reflux flowrate change on (a) 3 rd tray temperature (b) MTBE Purity Effect of Reboiler Duty The result of step-test on reboiler duty towards the temperature of tray number 8 is shown in Fig. 4. From the figure, the changes in the reflux flowrate produce an asymmetric form on the output response thus again proved that the reactive column is a nonlinear process. Meanwhile, the effect of reboiler duty change on the MTBE purity in the bottom product is shown in Fig. 4a, where the MTBE purity increases as the reboiler duty increase. 4. Conclusion The dynamic model of MTBE RD has been developed using Aspen Dynamics which has been validated using data available from literature. The singular value decomposition (SVD) analysis show that the tray temperature number 3 and 8 are the

5 most sensitive toward changes of reflux flowrate and reboiler duty. Finally, the step test results show that MTBE RD is a nonlinear process hence need nonlinear controller to control MTBE reactive distillation. (a) (b) Figure 4. Effect reboiler duty change on (a) 8 th tray temperature (b) MTBE Purity Acknowledgement The financial support from Universiti Sains Malaysia through Research University (RU) Grant and Graduate Assistant (GA) to the first author are greatly acknowledged. References A.P. Higler, R. Taylor and R. Krishna, 1999, The influence of mass transfer and mixing on the performance of a tray column for reactive distillation, Chem. Eng. Science, 54, H. Lin and P. L. Douglas, 2000, Dynamic Simulation and Control of an MTBE Catalytic Distillation Column. Dev. Chem. Eng. Mineral Process., 8(3/4), I. M. Iqbal and N. Aziz, 2011, Comparison of Various Wiener Model Identification Approach in Modelling Nonlinear Process, 3 rd Conference on DMO, IEEE, N. Sharma and K.Singh, 2010, Control of Reactive Distillation Column: A Review, Int. J. Chemical Reactor Eng., 8, R5 M. N. Murat, A. R. Mohamed and S. Bhatia, 2003, Modelling of reactive distillation column: Methyl Tertiary Butyl Ether (MTBE) simulation studies, IIUM Engineering Journal, 4 R. Taylor. And R. Krishna, 2000, Review: Modelling reactive distillation, Chem. Eng. Science, 55, R. K. Pearson, 2003, Selecting Nonlinear model structures for computer control,journal of process control, 13,1-26 S. A. Nijhuis, F. P. J. M. Kerkhof, and A. N. S. Mak, 1993, Multiple steady states during reactive distillation of methyl tert-butyl ether, Ind. and Eng. Chemistry Res.,32, T. López-Arenas, S. Eduardo and R. Gani, 2006, Static/dynamic analysis and controllability issues in reactive distillation columns, Computer Aided Chemical Engineering, 21, T. Satyanarayana and P. Saha, 2005, Modeling and Control Structure Selection for Reactive Distillation Process using Aspen Custom Modeler, CHEMCON 05, Newdelhi W. L. Luyben, 2006, Evaluation of criteria for selecting temperature control trays in distillation columns Journal of Process Control, 16, Z. M. Mohammed, 2009, Mathematical Modeling and Simulation for Production of MTBE by Reactive Distillation MSc Thesis, Chemical Eng. Department, Univ. of Technology, KSA