Distillation sequence constraints

Distillation sequencing. Unless there are constraints severely restricting heat integration, sequencing of simple distillation columns can be carried out in two steps (1) identify the best few nonintegr-ated sequences, and (2) study the heat integration. In most cases, there is no need to solve the problems simultaneously. ... 

When liquid mixtures exhibit azeotropic behavior, it presents special challenges for distillation sequencing. At the azeotropic composition, the vapor and liquid are both at the same composition for the mixture. The order of volatility of components changes, depending on which side of the azeotrope the composition occurs. There are three ways of overcoming the constraints imposed by an azeotrope. 

The set of constraints for the synthesis of heat-integrated distillation sequences problem will consist of... 

Sophos et al. employed an optimal, heat-imegrated distillation sequence. By first identifying favorable unintegrated sequences, feey are able to limit the problem. They assume that the integrated optimum k a member of the set developed in the first screening. These sequences are then looked at for beat integration opportunities given whatever constraints ate appropriate. 

The optimal control of a process can be defined as a control sequence in time, which when applied to the process over a specified control interval, will cause it to operate in some optimal manner. The criterion for optimality is defined in terms of an objective function and constraints and the process is characterised by a dynamic model. The optimality criterion in batch distillation may have a number of forms, maximising a profit function, maximising the amount of product, minimising the batch time, etc. subject to any constraints on the system. The most common constraints in batch distillation are on the amount and on the purity of the product at the end of the process or at some intermediate point in time. The most common control variable of the process is the reflux ratio for a conventional column and reboil ratio for an inverted column and both for an MVC column. 

For cases 2-4, the optimal values of R in both intervals were less than Rmax meaning the column was never flooded during the operation. This is also evident from the reboiler holdup values at the end of each interval. Also for cases 2-4 the constraint given by Equation 10.5 was not active. Mujtaba (1999) noted that cases 2-4 were re-run with only one time interval for the distillate Task. The constraint given by Equation 10.5 was imposed on the optimisation problem. For cases 2-3 the maximum productivity obtained was about 0.55 and for case 4 no solution was obtained. This shows the importance of having time-sequenced operation. 

At this point, a question arises. Could we overcome the constraint of a distillation boundary The answer is not easy. In any case, the selection of a suitable entrainer is the key element. The number of columns involved in the separation sequence is not very important, because it can be either two or three. On the contrary, the recycle policy of the entrainer and of intermediate mixtures plays a major role. Sometimes the location of feeds, as for example the original mixture and the entrainer in the first column, may have also an effect on the overall feasibility. These issues will be developed in a lager extent in the next sections. 

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