Selection of Optimum Separation Sequence for Multicomponent Distillation

This paper considers the process of multicomponent distillation. It is shown that energy consumption (per mole of mixture being separated) depends monotonously on efficiency if the capacity is constant and separation is reversible. Authors suggest the technique for selection of distillation sequence for which the total energy consumption in the cascade of columns reaches its minimum. This sequence is determined by values of thermal coefficients. Coefficients themselves depend on temperatures in the reboiler and condenser. This paper offers the algorithm for the calculation of these coefficients.

CFD Modeling to Predict Mass Transfer in Multicomponent Mixtures

A novel three-dimensional computational fluid dynamics mass transfer (CMT) model in Eulerian–Eulerian frame work is deploys for investigating the concentration profiles, and trays efficiencies in multicomponent distillation columns. The proposed model is based on Maxwell Stefan equations, and CFD was employed as a powerful tool to model the hydrodynamics and mass transfer. The two phases are modelled as two interpenetrating phases with interphase momentum, heat and mass transfer. The Closure model is developed for mass interphase transfer rate in ternary mixtures. The predictability of the mass transfer behaviours of multicomponent can result in a more efficient and predictable design of distillation trays. Two non-ideal ternary mixtures were studied. The tray geometry and operating conditions are based on the experimental works of Kalbassi and the composition profiles, tray efficiencies, and point efficiencies of mixtures were presented. The obtained results were confirmed by the experimental data. The results indicate that the values of individual component tray efficiencies and point efficiencies for these multicomponent systems were considerably different which confirm the interactive nature of the mass transfer in multicomponent mixtures. These mixtures also illustrated different point efficiencies across the tray because of the composition dependency of these mixtures. The average relative error for the prediction of efficiencies is about 8 %, which indicates the accuracy of the model.