Information-Probabilistic Approach to the Organization of a Binary Distillation Process

Abstract

A systematic approach to the optimal organization of a binary distillation process based on information theory is presented. This approach allows to formulate conditions for optimal function distribution for a complex process, when the feed stream is separated into several product streams. The results of computational experiments based on this approach and known thermodynamic approaches that involve the minimization of exergy losses and entropy production are compared using a numerical example that models the separation process for a methanol–water mixture. The results of computational experiments based on the information-probabilistic approach to the optimal organization of a binary distillation process agree with results obtained by using thermodynamic approaches, evidencing the applicability of the information approach in the context of its integration into the general algorithm of chemical engineering system design based on the information approach.