(408b) Dynamic Modeling and Optimization of Thermally Coupled Dual-Column Batch Distillation Processes

Joglekar, G. S., Batch Process Technologies, Inc.
Moon, J., Purdue University
Reklaitis, G. V., Purdue University

A novel, dual-column batch distillation process has been developed to distill multicomponent mixtures into multiple pure product streams. An important feature of this process is that it retains the flexibility of the original conventional batch distillation column and yet provides large reduction in energy consumption. A simplified model of such a process clearly demonstrated the significant gains in productivity, and reduction in waste stream(1) as compared to the conventional batch distillation process. The dual-column batch distillation processes are expected to find application in pharmaceutical, specialty chemical and agricultural industrial facilities that utilize a wide range of solvents.

In this study, a detailed process dynamics model of the thermally coupled columns was constructed. Distefano's quasi steady-state formulation(2) was used for mass balance on all plates, while the rest of the variables were updated after the specified elapsed time. The important variables that affect the column performance are the reflux ratio, cut durations and fraction of liquid stream within the column that is diverted to the side column. A mixture of Benzene, Toluene and Ortho-Xylene with mass fractions 0.33, 0.33 and 0.34, respectively, was charged to the column.

The following key operating variables associated with each cut affect the overall column performance: reflux ratio, duration and fraction of liquid stream within the main column that is diverted to the side column. To find the optimum values of the operating variables, a two-level approach was used. The Genetic Algorithm function in Matlab was used to create the members in the population. The fitness function value for each member was computed by simulating the column dynamics. The objective function value of each member in turn was used by the GA to create new population. The iterative process was terminated when either the maximum number of iterations were competed or when the best objective function value reached a plateau (change below specified threshold).

For a three component mixture of Benzene, Toluene and Ortho-Xylene, the optimum cycle time for the dual-column process is reduced by 40% compared to the optimum cycle time for a conventional column.

1. AIChE presentation, 2007 Annual Meeting, paper 211a.

2. AIChE Journal, 14(1), 190-199 (1968).