Optimal Feed Locations

Finding the optimal feed locations can be formulated as an optimization problem in which the vapor rate is minimized by varying the feed tray locations. 

EFFECTS OF FEED TRAY LOCATIONS ON DESIGN AND CONTROL OF REACTIVE DISTILLATION 

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Viswanathan, J. and I. E. Grossmann. Optimal Feed Locations and Number of Trays for Distillation Columns with Multiple Feeds. Ind Eng Chem Res 32 2942-2949 (1993). 

In contrast, for those cases where the permeability of the reactant is either smaller or larger than those of both products or product (i.e., PaPb ot Pa>Pb plus Pa>Pc being the other), the optimal feed location is at the reactor entrance (z=0). 

Viswanathan, J. and Grossmann, I. Optimal feed locations and number of trays for distillation columns with multiple feeds. Industrial engineering chemistry research, 32(ll) 2942-2949, 1993. 

All the material streams are connected as shown in Figure 3.57, with two feed streams for the stripper. One feed stream to the stripper must enter on Stage 1 (this is the organic outlet stream of the decanter). Another feed stream (fresh feed) can be entered at any optimal feed location as determined by the design study. The top vapor-outlet stream of the stripper is connected as one feed stream of the decanter. Another feed stream of the decanter is the entrainer makeup stream. The AO stream of the decanter (deflned as the second liquid phase) is designed to go out of the system. 

The shortcut column performs Fenske-Underwood shortcut calculations for simple refluxed towers. The Fenske minimum number of trays and the Underwood minimum reflux are calculated. A specified reflux ratio can then be used to calculate the vapor and liquid traffic rates in the enriching and stripping sections, the condenser duty and reboiler duty, the number of ideal trays, and the optimal feed location. The shortcut column is only an estimate of the column performance and is restricted to simple refluxed columns. For more realistic results, the rigorous column operation should be used. This operation can provide initial estimates for most simple columns. 

Following the optimization procedure, the optimal feed locations are Np A = 9 and = 17. This results in only a 5.5% energy savings (Table 18.2). 

Optimal Feed Location for Production Rate Variation... 

The models presented correctly predict blend time and reaction product distribution. The reaction model correctly predicts the effects of scale, impeller speed, and feed location. This shows that such models can provide valuable tools for designing chemical reactors. Process problems may be avoided by using CFM early in the design stage. When designing an industrial chemical reactor it is recommended that the values of the model constants are determined on a laboratory scale. The reaction model constants can then be used to optimize the product conversion on the production scale varying agitator speed and feed position. 

In the present study, the stability of chromium oxide catalysts has been systematically examined to elucidate the deactivation mechanism by chlorinated compounds. The operating conditions, including the feed concentration of perchloroethylene (PCE), were optimized to locate the optimal region of the reactor operating condition where the catalyst deactivation can be avoided. It may also resolve the hesitation in the use of chromium catalyst and suggest an optimal operating condition of the reactor system for the removal of CVOCs. 

Optimal functioning of RD depends largely on relevant process design, properly selected column internals, feed locations, placement of catalyst as well as on sufficient understanding of the process behavior. All this unavoidably necessitates application of well-working, reliable and adequate process models [4]. 

The solution to the RD problems results in the optimum number of trays, the optimal feed tray location, reflux ratio, condenser and reboiler duties and liquid hold-ups on each tray. Since the model contains both continuous e.g. temperature and composition) and discrete i.e. number of trays) design variables, it should be solved by MINLP optimization technique. 

In all three MIDO iterations the primal problem resulted in a positive definite matrix Q indicating that both outputs are participating in the optimal control structure. In the process structure there are 30 possible feed tray locations and for the feed located on tray k there are 31 —k) alternatives for the reflux tray locations. Hence the total number of discrete alternatives is XI (31 — fc) = 465. Despite this large number of alternative discrete decisions the algorithm... 

The economics are explored by evaluating capital and energy costs. The design optimization variables are the nmnber of trays in each column, pressure, and feed location. As the Txy diagram given in Figure 7.1 shows, the separation between the saturated-hquid and saturated-vapor curves are quite similar on both sides of the azeotrope. This means that the difficulty of separation is similar and suggests that the number of trays in both... 

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