Batch operations differential distillation

The results of the differential distillation end the same as the flash distillation, although the mechanism is somewhat different. This is a batch type operation distilling differentially. All sensible and latent heat are supplied separately from the steam or by superheat in the steam. Steam acts as an inert in the vapor phase, and quantity will vary as the distillation proceeds, while temperature and pressure are maintained. 

With a single equilibrium stage and no reflux, the separation power in differential distillation is obviously limited. It is the equivalent of a batch flash operation. Consequently, practical applications would include the separation of wide-boiling mixtures, with low expectations on the purity of the products. 

Early distillations were of the batch, takeover type, sometimes called simple distillation or differential distillation. A charge of liquid mixture is vaporized from a still, or stillpot, by heat addition, and the product vapor is condensed into one or more fractions. Thus the term fractional distillation, or fractionation, has become associated with any distillation operation designed to obtain defined or specified constituent fractions. 

Differential extraction. This is a batch operation wherein a definite amount of solution to be extracted is contacted with differential portions of extracting solvent, the differential portions of extract being removed as fast as formed. The operation is exactly analogous to differential distillation and has been termed cocurrent infinite stageby Varteressian and Fenske (22). 

One form of separation is differential distillation, in which a batch of liquid vaporizes until a certain amount is left as residue. The Rayleigh equation [2] for such an operation is... 

Differential Distillation. This type of distillation is usually carried out as a batch operation although continuous units may also-operate in this manner. Considering first a batch distillation, if a mixture of liquid is distilled, the distillate contains a greater portion of the more volatile material than the residue, and as distillation proceeds both the distillate and the residue become poorer in the more volatile components. This change in composition may be estimated quantitatively if the relation of the composition of vapor to that of the liquid is known. Consider W parts of original mixture containing Xo fraction of component A, Allow a differential amount —dW to be vaporized of a composition, y, under such conditions that the vapor is continually removed from the system. 

Batch Dehydration of Benzene. As another example of the use of Rayleigh s equation, consider the dehydration of benzene. Benzene saturated with water at 20 0. contains 0.25 mol per cent water, and it is to be given a simple differential distillation at a constant pressure of 1 atm. The operation is to proceed until the mol per cent water in the liquid remaining in the still is 0.00025. The following data and simplifying assumptions will be used in the calculations ... 

Operation of a batch distillation is an unsteady state process whose mathematical formulation is in terms of differential equations since the compositions in the still and of the holdups on individual trays change with time. This problem and methods of solution are treated at length in the literature, for instance, by Holland and Liapis (Computer Methods for Solving Dynamic Separation Problems, 1983, pp. 177-213). In the present section, a simplified analysis will be made of batch distillation of binary mixtures in columns with negligible holdup on the trays. Two principal modes of operating batch distillation columns may be employed ... 

Unlike continuous distillation, batch distillation is inherently an unsteady state process. Dynamics in continuous distillation are usually in the form of relatively small upsets from steady state operation, whereas in batch distillation individual species can completely disappear from the column, first from the reboiler (in the case of CBD columns) and then from the entire column. Therefore the model describing a batch column is always dynamic in nature and results in a system of Ordinary Differential Equations (ODEs) or a coupled system of Differential and Algebraic Equations (DAEs) (model types III, IV and V). 

This is the differential design equation for a distillation reactor, written for the mth-independent chemical reaction. Note that Eq. 9.3.2 is identical to the design equation of an ideal batch reactor. The difference between the two cases is in the variation of the reactor volume and species concentrations during the operation. 

The suitability of the different operating modes can be determined with the aid of programs for modeling batch distillations. The treatment of batch distillations is much more laborious than that for continuous distillations. However, the decision can be simplified by using Equations (2.3.2-29) and (2.3.2-30), which were determined for the different operating modes with the aid of differential equations. The minimum vapor quantity G is used for comparison ... 

Flowsheets for processes are sometimes generated without following the hierarchy of properties described previously. As an example, Siirola [20] proposed a reactive-distiUation solution to make methyl acetate. Unit operations that combine the property differences present abrupt departures from common methodologies. With the advent of various pieces of equipment, such as differential side-stream feed reactors (i.e., semicontinuously fed batch reactors), continuous evaporator-reactors (e.g., wiped-film evaporators), and reactive distillation columns, one can consider these unit operations in the development of conceptual designs. As an example, Doherty and Malone [21] have presented systematic methods for reactive distillation design. 

The rigorous model of batch distillation operation involves a solution of several stiff differential equations and the semirigorous model involves a set of highly nonlinear equations. The computational intensity and memory requirement of the problem increase with an increase in the number of plates and components. The computational complexity associated with these models does not allow us to derive global properties such as feasible regions of operation, which are critical for optimization, optimal control, and synthesis problems. Even if such information is available, the computational costs of optimization, optimal control, or synthesis using these models are prohibitive. One way to deal with these problems associated with these models is to develop simphfied models such as the shortcut model. 

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