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A framework for synthesizing the optimal separation process of azeotropic mixtures
Author(s) -
Yang Xiao,
Dong HongGuang,
Grossmann Ignacio E.
Publication year - 2012
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.12677
Subject(s) - superstructure , ternary operation , process (computing) , heuristic , mixing (physics) , computer science , state space , separation (statistics) , algorithm , space (punctuation) , work (physics) , basis (linear algebra) , process engineering , mathematical optimization , mathematics , engineering , mechanical engineering , physics , statistics , structural engineering , quantum mechanics , machine learning , programming language , operating system , geometry
In this work, a systematic framework is introduced to synthesize the optimal separation process of azeotropic mixtures. The proposed framework, which can handle an arbitrary number of components, consists of two main steps: a system analysis and a state‐space superstructure algorithm. The system analysis is composed of some equation‐oriented algorithms to supply basic information for the superstructure, including structure of the composition space, existence of unchangeable points and candidate operations. It is shown that the proposed superstructure featuring multistream mixing is superior to previous ones because it significantly expands the feasible area. Moreover, detailed design parameters such as number of stages and reflux ratio are derived. Additionally, flowsheet feasibility test rules are constructed to facilitate the analysis of the process, and are able to be used as heuristic methods to guide the design of ternary or quaternary systems. Three industrial cases are presented to illustrate the proposed framework. © 2011 American Institute of Chemical Engineers AIChE J, 2012