Distillation optimum control

An on line analysis of product composition is not always available. In these instances, there is no measurement to feedback from, so a forward loop can be a great help in maintaining control in the face of disturbances. Furthermore, if the real controlled variable is profit or loss, an optimum control program can be based on a feedforward model. Consequently the feedforward approach to control is of utmost importance in distillation processes, whatever the nature of the separation. 

Redux Ra.te, The optimum reflux rate for a distillation column depends on the value of energy, but is generally between 1.05 times and 1.25 times the reflux rate, which could be used with infinite trays. At this level, excess reflux is a secondary contributor to column inefficiency. However, when designing to this tolerance, correct vapor—Hquid equiUbrium data and adequate controls are essential. 

Continuous binary distillation is illustrated by the simulation example CON-STILL. Here the dynamic simulation example is seen as a valuable adjunct to steady state design calculations, since with MADONNA the most important column design parameters (total column plate number, feed plate location and reflux ratio) come under the direct control of the simulator as facilitated by the use of sliders. Provided that sufficient simulation time is allowed for the column conditions to reach steady state, the resultant steady state profiles of composition versus plate number are easily obtained. In this way, the effects of changes in reflux ratio or choice of the optimum plate location on the resultant steady state profiles become almost immediately apparent. 

Since relative volatilities increase in most distillation systems as pressure decreases, the optimum operation would be to minimize the pressure at all times. One way to do this is to just completely open the control valve on the cooling water. The pressure would then float up and down as cooling water temperatures changed. 

Both modes usually are conducted with constant vaporization rate at an optimum value for the particular type of column construction. Figure 13.10 represents these modes on McCabe-Thiele diagrams. Small scale distillations often are controlled... 

Many industrial users of batch distillation (Chen, 1998 Greaves, 2003) find it difficult to implement the optimum reflux ratio profiles, obtained using rigorous mathematical methods, in their pilot plants. This is due to the fact that most models for batch distillation available in the literature treat the reflux ratio as a continuous variable (either constant or variable) while most pilot plants use an on-off type (switch between total reflux and total distillate operation) reflux ratio controller. In Greaves et al. 2001) a relationship between the continuous reflux ratio used in a model and the discrete reflux ratio used in the pilot plant is developed. This allows easy comparison between the model and the plant on a common basis. 

The previous section assumed that product composition (or product flow) requirements are fixed. In this very common situation, the optimum design minimizes the costs of achieving these requirements. Often, product specs are not fixed, but depend on economics. Even when a product must obey a "less than" purity spec, better purity may fetch a better price. The better price may justify additional investment in equipment and/or a higher operating cost. Here, a design must optimize product purity value versus distillation cost. This optimization is also important in an operating column and is commonly performed by on-line computer control. It is outlined below, and discussed in detail elsewhere (1,2). 

Z-Pro-Leu-Gly-SCm (33 1.97 mg, 3.99 xmol) and H-Leu-Ala-Phe-Ala-Lys-Ala-Asp-AIa-Phe-Gly-OH-2TFA 2.5H2O (34 29.64 mg, 23.1 pmol) were dissolved in 0.2 M Hepes buffer (1 mL, pH 8.5) containing 5% DMSO. The apparent pH was readjusted to 8.5 with 6M NaOH (small portions, pH control). Because of the temperature optimum of V8 protease it is important to carry out the reaction at 37 °C. After thermal equilibration the reaction was started by addition of V8 protease (0.011 mg, 33.3 pL stock soln 1.53 x 10M in distilled HjO). After approximately 2h the enz5rmatic reaction was stopped by addition of 10% TFA in 50% MeOH/H20 (0.5 mL) and the product 35 separated by RP-HPLC (H2O/ MeCN gradient with 0.1% TFA) yield 2.8mg (55% by analytical RP-HPLC, calculated at complete ester consumption based on the difference between the measured concentration of Z-Pro-Leu-Gly-OH for reactions with and without the decapeptide, respectively) MALDI-TOF (C,j9H98N]40i8) m/z calcd for (M+Na+) 1433.71 found 1434.17. 

Both modes usually are conducted with constant vaporization rate at an optimum value for the particular type of column construction. Figure 13.9 represents these modes on McCabe-Thiele diagrams. Small scale distillations often are controlled manually, but an automatic control scheme is shown in Figure 13.9(c). Constant overhead composition can be assured by control of temperature or directly of composition at the top of the column. Constant reflux is assured by flow control on that stream. Sometimes there is an advantage in operating at several different reflux rates at different times during the process, particularly with multicomponent mixtures as on Figure 13.10. 

In these, the gas phase is suitably collected and subjected to the subsequent analytical determinations in a discontinuous fashion. Although the classical distillation systems have fallen into disuse since the advent of the advantageous gas chromatography, their automation has fostered the development of assemblies of some Interest. Chipperfleld et al. [2] reported a computer-controlled laboratory fractional column for small-scale preparations in which a microcomputer controls the column-jacket temperatures, boil-up rate and reflux ratio to achieve optimum separations. A schematic diagram of the dls-... 

As in the case of reboilers and condensers, distillation control is too wide a topic to be adequately covered in a handful of chapters. Entire texts (68, 89, 301, 332, 362) deal exclusively with distillation control. Most of these strike a balance between theory, practice, controls design, and controls optimization. In contrast, the coverage here emphasizes operational aspects what various control schemes can and cannot do, how to put together a control system (not necessarily optimum, but one that works), how to recognize and avoid a troublesome system, what are the ill effects of various poor control schemes, and what corrective action can restore trouble-free operation. 

Nevertheless, a lot is known about the overall philosophy of column control. Although this knowledge may fall short of predicting the optimum philosophy, it is usually sufficient for detecting poor and troublesome practices and distinguishing them from good practices. This aspect is of greatest interest to the distillation troubleshooter, superintendent, and operator, and is promoted here. 

Based on these results, the optimum process controlling conditions and raw material parameters are Dimethyl sulfate sodium nitrite is 1 1.29, the reaction temperature is from room temperature to 53-57 °C, distillation temperature is... 

Your assignment is to develop both conventional and extractive distillation processes for recovering HFC-125 and HCl from the specified feed mixture. You will need to develop optimum flow sheets, size and cost equipment for each case, and compare the economics of the two processes. Your flow sheets should include energy recovery (heat integration) as appropriate. You will also need to develop a control strategy for your preferred case the control scheme should address start-up and shut-down conditions as well as steady-state operation. 

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