Finite Reflux Design

Let us set the product specification such that X =X = [0.700,0.010] for an equimolar feed of 1 mol/s and pure liquid 1). There is only one remaining design 

FIGURE 5,11 Feasible design for the benzene/p xylene/toluene system at P = 1 atm at a reflux of 2 using Raoult s law (ideal solution). 

Tiy this for yourself reproduce the infeaable design in figure 5.12 with the given parameters using ODS-SiCo. Investigate the effect of pressure and product compositions on feasibility. 

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We start the chapter by explaining the graphical thermodynamic representations for ternary mixtures known as Residue Curve Maps. The next section deals with the separation of homogeneous azeotropes, where the existence of a distillation boundary is a serious obstacle to separation. Therefore, the choice of the entrainer is essential. We discuss some design issues, as entrainer ratio, optimum energy requirements and finite reflux effects. The following subchapter treats the heterogeneous azeotropic distillation, where liquid-liquid split is a powerful method to overcome the constraint of a distillation boundary. Finally, we will present the combination of distillation with other separation techniques, as extraction or membranes. 

Hence, the RCM representation allows the designer to identify the feasible separations. In the case of zeotropic mixtures if the separation is possible at total reflux, then it is certainly feasible at finite reflux, the problem being only finding a... 

FIGURE 7.7 A possible design for the infinite reflux Petlyuk in Hgure 7.2 colunui (with CS and CSc at finite reflux) achieving > 90% intermediate boiling component in the sidestream. 

This section has thus presented a quick synthesis and analysis method for two simplified infinite reflux cases. Just like simple columns, it can be generally stated that if a design is considered feasible at infinite reflux conditions, then a feasible design can be found at finite reflux too. This fact is particularly useful for nonideal systems. An illustration of a more complex infinite Petlyuk column example is given in the following example for the azeotropic acetone/benzene/chloroform system. 

Recall that for all our previous designs we had to satisfy the condition for all products to be connected by a set of profiles for the design to be classified as feasible. The finite reflux Petlyuk is no different, but as alluded to in the infinite reflux case, the thermal coupling in two sections means this composition matching constraint is a little more complicated. Thus, let us consider where we need to search for profile intersections in the column by systematically highlighting areas of interest. 

Knowledge about the regularities of the trajectory bundles arrangement under the finite reflux provides an opportunity to develop the reliable and fast-acting algorithm to fulfill design calculations of distillation to determine the required number of trays for each section. 

This chapter is the central one of the book all previous chapters being introductory ones to it, and all posterior chapters arising from this one. Distillation process in inhnite column at finite refiux is the most similar to the real process in finite columns. The difference in results of finite and infinite column distillation can be made as small as one wants by increasing the number of plates. Therefore, the main practical questions of distillation unit creation are those of separation flowsheet synthesis and of optimal design parameters determination (i.e., the questions of conceptual design) that can be solved only on the basis of theory of distillation in infinite columns at finite reflux. 

Petlyuk, F. B., Danilov, R. Yu. (2001b). Theory of Distillation Trajectory Bundles and Its Application to the Optimal Design of Separation Units Distillation Trajectory Bundles at Finite Reflux. Trans IChemE, 79, Part A, 733-46. 

The knowledge of the trajectory bundles structure at finite reflux and of their location in the concentration simplex allowed a new class of design calculation algorithms to be developed that guarantees a full optimal solution of the task without the participation of the user. 

Having design parameters fixed in the outer problem and with a specific choice of D° (discussed in section 7.2) the inner loop optimisation can be partitioned into M independent sequences (one for each mixture) of NTm dynamic optimisation problems. This will result to a total of ND = 2 NTm problems. In each (one for each task) problem the control vector m for each task is optimised. This can be clearly explained with reference to Figure 7.3 which shows separation of M (=2) mixtures (mixture 1 = ternary and mixture 2 = binary) and number of tasks involved in each separation duty (3 tasks for mixture 1 and 2 tasks for mixture 2). Therefore, there are 5 (= ND) independent inner loop optimal control problems. In each task a parameterisation of the time varying control vector into a number of control intervals (typically 1-4) is used, so that a finite number of parameters is obtained to represent the control functions. Mujtaba and Macchietto (1996) used a piecewise constant approximation to the reflux ratio profile, yielding two optimisation parameters (a control level and interval length) for each control interval. For any task i in operation m the inner loop optimisation problem (problem Pl-i) can be stated as ... 

For standard types of finite-stage contactor columns operated in the range of allowable velocities where the overall column efficiencies are essentially constant, O Connell has correlated efficiency data on the basis of liquid viscosity and relative volatility (or gas solubility). The results for fractionators and absorbers are presented in Fig. 16-9. This correlation is based, primarily, on experimental data obtained with bubble-cap columns having a liquid path of less than 5 ft and operated at a reflux ratio near the minimum value. Figure 16-9 is adequate for design estimates with most types of commercial equipment and... 

From the standpoint of design, the most useful definition of total reflux consists of the one in which the total flow rates [Lj (j = 1, 2,. .., N — 1), Vj (j = 2,. .., N)] are unbounded while the feed and product rates are finite. More precisely... 

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