(378n) Minimum Reflux Calculation for Multicomponent Azeotropic Distillation Using Shortcut Method

Authors: 
Jiang, Z., Purdue University
Chemical, pharmaceutical, and agrochemical industries are frequently involved with separation of multicomponent mixtures exhibiting one or more azeotropes using distillation. To design a distillation column that is cost-effective to build and energy efficient to operate, key parameters such as the minimum reflux ratio are generally required. Therefore, design engineers need to understand and be able to determine the minimum reflux condition of a distillation column when separating a multicomponent azeotropic mixture.

Despite its practical significance, this problem is challenging to solve. Most existing approaches rely on tray-by-tray calculations or iterative guessing of reflux ratio, which can be too computationally expensive and complex to implement. Here, we present a simple and easy-to-use shortcut method to analytically calculate the minimum reflux ratio of a distillation column for multicomponent homogeneous azeotropic mixture separations. We treat each azeotrope as a pseudocomponent after exploiting the physical and mathematical properties of azeotropes and applying the proper linear transformation. Such transformation preserves the mathematical simplicity of the resulting system and allows us to derive the minimum reflux condition for multicomponent homogenous azeotropic distillation.

Through case studies, we demonstrate the accuracy and effectiveness of our new approach. We show that the classic Underwood’s method used for ideal multicomponent distillation turns out to be a special case of this general approach. Compared to existing algorithmic approaches, our method does not require any tray-by-tray calculation and is iteration free. As a result, it can be easily incorporated into a global optimization framework that will allow industrial practitioners to, for the first time, quickly ranklist and identify a handful of attractive distillation configurations from the immense configuration search space.