The economic optimization of a distillation column involves the selection of the number of trays
and the feed- and side-streams locations, as well as the operating conditions that minimize the
total investment and operation cost. In this paper, we present a superstructure-based optimization algorithm that combines the capabilities of commercial process simulatorstaking advantage
of the tailored algorithms designed for distillation and property estimation implemented in these
simulatorsand generalized disjunctive programming (GDP). The proposed algorithm iterates
between two types of subproblems: A nonlinear programming (NLP) subproblem, in which the
trays are divided into existing and nonexisting (nonexisting trays behave like simple bypasses
without mass or heat exchange through the use of Murphree efficiencies), and a specially tailored
master mixed integer linear programming (MILP) problem. The NLP subproblems are solved
by integrating the process simulator with an external NLP solver. Several examples are presented
which show promising results.
The sonoelectrochemical treatment of aqueous solutions of trichloroacetic acid (TCAA) has been scaled-up from the voltammetric analysis to pre-pilot stage. The degradation in absence of ultrasound field has yield to a poor performance which has been improved in presence of ultrasound. The sonovoltametry study has provided the range of potentials and/or current densities to be used with the lowest current efficiency penalty. Sonoelectrolyses at batch scale (carried out with a horn-transducer 24 kHz positioned at about 3 cm from the surface of the electrode) achieved little improvement in the degradation. However, when a specifically designed sonoelectrochemical reactor (not optimized) was used during the scale-up, the presence of ultrasound field provided better results (fractional conversion 97%, degradation efficiency 26%, selectivity 0.92 and current efficiency 8%) at lower ultrasonic intensities and volumetric flow.
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