This paper is the subsequent work of our previous study in which the liquid distribution on the imperforate structured packing sheet was predicted. In this study, a novel multi-scale model for describing the liquid distribution on the perforated structured packing sheet is proposed. The large scale model is a mechanistic model, using liquid split coefficients as model parameters derived from a 3D volume of fluid (VOF) simulation within the representative units. The model can theoretically adapt to vary working conditions; and the liquid distribution of all the packing layer/tower can be given. Five types of flow patterns are discussed according to the simulation results. The influence of gas flow and openings on liquid flow are also discussed. This proposed model can supply a deep insight into the mechanism of the liquid distribution inside the packing tower and help understanding the details of inter-phase behavior which are hardly available by experiment.

In this paper, an evolutionary approach, improved CAMD based on the hybrid gene algorithm and simulated annealing algorithm (GASA), is developed. The new approach combines the feature of GA and SA, avoiding the problem of prematurity. With a new category strategy of candidate groups from the Mod UNIFAC group database adopted, a repair operator is introduced to guarantee the integrity of randomly generated molecules and thus the search of straight chain alkane as well as cyclane solutions can be performed together. The properties of molecules are obtained by the group contribution method. An example of extractive solvent selection for a methanol‐methyl acetate system has been illustrated in detail to further explain the method. The stability as well as other properties of the molecules which the authors think important is considered in the fitness function. Results of the example show that the fitness ranking values are better than those in the literature. The CAMD method in this paper can be used in practical chemical processes.