A process intensification synthesis framework for the design of extractive separation systems with material selection. Issue 4 (15th June 2021)

• Record Type: Journal Article
• Authors: Tian, Yuhe; Pistikopoulos, Efstratios N.
• Other Names: Grieco William J. guestEditor.
• Is Part Of: Journal of advanced manufacturing and processing. Volume 3:Issue 4(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-06-15
• Subjects: extractive separation -- integrated solvent selection and process design -- process synthesis intensification -- superstructure optimization -- ethanol‐water separation; Chemical engineering -- Periodicals; Manufacturing processes -- Technological innovations -- Periodicals; Manufacturing processes; Electronic journals; Periodicals; 660
• DOI: 10.1002/amp2.10097
• Languages: English
• ISSNs: 2637-403X

Abstract

Abstract: In this work, we present a systematic approach for solvent selection and process intensification synthesis based on the Generalized Modular Representation Framework (GMF). GMF is a bottom‐up process synthesis strategy which leverages mass and/or heat transfer building blocks to represent chemical equipment and flowsheets. Thus, conventional and/or intensified process solutions can be generated to obtain optimal process design(s) without a pre‐postulation of equipment or flowsheet configurations. To address the challenge of module dimensionality estimation for capital cost correlation, orthogonal collocation is coupled to enhance GMF intra‐module representation. Material selection is achieved by incorporating physical property models (e.g., NRTL) in GMF model formulation to describe the nonideal liquid mixture behaviors and to assess solvent performance in facilitating separation. In this context, solvent selection and process intensification synthesis are simultaneously addressed within a superstructure‐based optimization formulation. The proposed approach is demonstrated on two case studies for ethanol‐water extractive separation, with two sets of solvents evaluated: (a) ethylene glycol versus methanol to obtain 99 mol% ethanol, and (b) ethylene glycol versus 1‐ethyl‐3‐methyl‐imidazolium acetate ([EMIM][OAc]) to obtain 99.8 mol% ethanol and 99 mol% water. Abstract : We present a systematic approach for simultaneous solvent selection and process intensification synthesis based on the Generalized Modular Representation Framework. A bottom‐up process synthesis approach is introduced to maximize separation driving forces while explicitly accounting for solvent impacts. The proposed strategy is showcased via a representative ethanol‐water extractive separation case study comparing novel ionic liquid solvents versus conventional ethylene glycol solvent.