Extractive Distillation Design and Optimization

Extractive Distillation Design and Optimization Extractive distillation column composition profiles have a veiy characteristic... 

Optimization. Optimi2ation of the design variables is an important yet often neglected step in the design of extractive distillation sequences. The cost of the solvent recovery (qv) step affects the optimi2ation and thus must also be included. Optimi2ation not only yields the most efficient extractive distillation design, it is also a prerequisite for vaUd comparisons with other separation sequences and methods. 

There are many design variables to be determined, so to simphfy the optimization the more important and complex extractive distillation column is optimized first. We considered three different cases for the entrainer feed temperature. 

Whereas there is extensive Hterature on design methods for azeotropic and extractive distillation, much less has been pubUshed on operabiUty and control. It is, however, widely recognized that azeotropic distillation columns are difficult to operate and control because these columns exhibit complex dynamic behavior and parametric sensitivity (2—11). In contrast, extractive distillations do not exhibit such complex behavior and even highly optimized columns are no more difficult to control than ordinary distillation columns producing high purity products (12). 

Pressure-relieving systems are unique compared with other systems within a chemical plant hopefully they will never need to operate, but when they do, they must do so flawlessly. Other systems, such as extraction and distillation systems, usually evolve to their optimum performance and reliability. This evolution requires creativity, practical knowledge, hard work, time, and the cooperative efforts of the plant, design, and process engineers. This same effort and creativity is essential when developing relief systems however, in this case the relief system development must be optimally designed and demonstrated within a research environment before the plant start-up. 

The results received form the optimization using inherent safety as the objective function are somewhat different compared to those calculated with an economic objective function earlier (Hurme, 1996). With the inherent safety objective function the simple distillations were favoured more than with the economic function. Exceptions are cases where the extractive distillation could improve separation very dramatically. This is because in simple distillations only one column is required per split, but in extractive distillation two columns are needed, since the solvent has to be separated too. This causes larger fluid inventory since also the extraction solvent is highly flammable. The results of the calculation are well justified by common sense, since one of the principles of inherent safety is to use simpler designs and reduce inventories to enhance safety. 

This chapter contains examples of optimization techniques applied to the design and operation of two of the most common staged and continuous processes, namely, distillation and extraction. We also illustrate the use of parameter estimation for fitting a function to thermodynamic data. 

Process synthesis and design of these non-conventional distillation processes proceed in two steps. The first step—process synthesis—is the selection of one or more candidate entrainers along with the computation of thermodynamic properties like residue curve maps that help assess many column features such as the adequate column configuration and the corresponding product cuts sequence. The second step—process design—involves the search for optimal values of batch distillation parameters such as the entrainer amount, reflux ratio, boiler duty and number of stages. The complexity of the second step depends on the solutions obtained at the previous level, because efficiency in azeotropic and extractive distillation is largely determined by the mixture thermodynamic properties that are closely linked to the nature of the entrainer. Hence, we have established a complete set of rules for the selection of feasible entrainers for the separation of non ideal mixtures... 

The digital simulation of an extractive distillation column was performed in order to understand the dynamic behaviour of the system. Based on this results a considerably simplified dynamic model of sufficient accuracy could be developed. This model was employed in the design of a state observer and of an optimal control. After implementation in the large scale plant this new control system has proved to be highly efficient and reliable. 

The optimal feed concentration of the pervaporation unit depends on carrier flow rate, reflux ratio and number of theoretical trays of the extractive distillation. Retentate concentration and cut rate of the pervaporation stage follow from the requested product quality xlt + x31 <0.008. For the design of the pervaporation stage, the worst case has been assumed that only benzene and no furfural (3) will pervaporate. The major factor for the cost reduction is the much lower energy consumption of the hybrid process of 1.18 t/h heating steam against 1.7 t/h for the conventional process. 

Long, N.V.D. and Lee, M. (2013b) Optimal retrofit design of extractive distillation to energy efficient thermally coupled distillation scheme. AIChE Journal, 59, 1175-1182. 

A number of works paid great attention to the questions of optimal designing of extractive distillation columns for separation of binary azeotropic mixtures (Levy Doherty, 1986 Knight Doherty, 1989 Knapp Doherty, 1990 Knapp Doherty, 1992 Wahnschafft Westerberg, 1993 Knapp Doherty, 1994 Bauer Stichlmair, 1995 Rooks, Malone, Doherty, 1996 1993). The region of possible mode parameters of extractive distillation process, limited by minimum rate of the entrainer and by limits of changing of reflux number between minimum and maximum values, was investigated. Some heuristic rules were introduced for the choice of rate of the entrainer and the reflux number. 

The task of designing of extractive distillation columns, besides calculation of section trajectories, includes a number of subtasks. These are the same subtasks as for two-section columns and additional subtasks of determination of minimum entrainer flow rate and of choice of design entrainer flow rate. Optimal designing of extractive or autoextractive distillation includes optimization by two parameters - by entrainer flow rate and by reflux number. Figure 7.14 shows influence of entrainer flow rate on section trajectories at fixed value of parameter a = LfV)mlK j (as is shown in Section 6.4 (L/y) = K j). 

In this chapter, design and control of the IPA dehydration process via extractive distillation will be studied. Since, in this distillation system, entrainer selection is an important step before working on the optimal design of the column sequence, we will start by comparing two alternative entrainers for this separation system in the following section. 

After the optimal design variables for the extractive distillation column are determined, the total TAC can be calculated with the entrainer recovery column and the recycle stream included. Additional costs in the TAC include the annualized capital cost for the entrainer recovery column, the costs associated with the cooler from B2 on the entrainer feed, the operating costs of the steam and cooling water to operate the entrainer recovery column, and the entrainer makeup cost. As an example. Figure 10.13 shows the results of the optimization runs for Case 1 with N2 and Np2 as the design variables. The y axis is the TAC of the complete flowsheet. From the flgure, N2 should be 24 and Afe should be at Stage 9. 

A commercial simirlation program, ASPEN, was used for simirlation of the fractional distillation columrr The flow diagram for propionic acid extraction process is show in Figure 14.7. The propionic acid concentration used in oitr design are 20 and 80 wt.%. By removing water from the product fliw, the propionic acid concentration the top of the distillation colutrm is 39.08 wt%.The distillation colirrrm was optimized at 12 plates with feed entering at plate 6. 

Reactive distillation is one of the classic techniques of process intensification. This combination of reaction and distillation was first developed by Eastman Kodak under the 1984 patent in which methyl acetate was produced from methanol and acetic acid. One of the key elements of the design is to use the acetic acid as both a reactant and an extraction solvent within the system, thereby breaking the azeotrope that exists within the system. Likewise, the addition of the catalyst to the system allowed sufficient residence time such that high yields could be obtained, making the process commercially viable. Other examples in which reactive distillation may enhance selectivity include those of serial reactions, in which the intermediate is the desired product, and the reaction and separation rates can be systematically controlled to optimize the yield of the desired intermediate. ... 

The practical difficulty with carrying out a crystalhzation DTR process is the need to operate under conditions that allow selective crystalhzation of the least soluble diastereomer while permitting the racemization to take place. Amine racemization catalysts, such as SCRAM , Shvo, Pd/C, and Adam s, are more active at higher temperatures, which runs counter to the conditions required for crystaUization. A solution to this problem is to separate the diastereomeric resolution and racemization steps but couple them with a flow engineering design. In this way each reaction can be operated under optimal conditions for example, temperature, concentration and solvent, via an intermediary solvent exchange unit Since the racemization catalyst itself may affect the crystalhzation (or indeed the crystalhzation may affect the catalyst), it is preferred to keep them separate. This can be achieved by having the catalyst or product either permanently or temporarily in a different phase by immobilization, extraction, precipitation, distil-... 

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