Generalized optimization-based synthesis of membrane systems for multicomponent gas mixture separation

•Proposed superstructure-based optimization approach for membrane systems synthesis.•Developed new physics-based surrogate models describing permeation of multicomponent mixtures.•General problem, with variable inlet flows and recycle streams, considered.•Approach applied to address different types...

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Bibliographic Details
Published in:Chemical engineering science Vol. 252; no. C; p. 117482
Main Authors: Taifan, Garry S.P., Maravelias, Christos T.
Format: Journal Article
Language:English
Published: United Kingdom Elsevier Ltd 28.04.2022
Elsevier
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ISSN:0009-2509, 1873-4405
Online Access:Get full text
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Summary:•Proposed superstructure-based optimization approach for membrane systems synthesis.•Developed new physics-based surrogate models describing permeation of multicomponent mixtures.•General problem, with variable inlet flows and recycle streams, considered.•Approach applied to address different types of mixture and problems. Synthesizing a membrane system to separate multicomponent gas mixture is challenging due to the combinatorial number of feasible configurations and the difficulties in describing the multicomponent permeators. We present a mixed-integer nonlinear programming (MINLP) model for synthesizing membrane systems for multicomponent gas mixture separation. The approach employs a richly connected superstructure to represent numerous potential system configurations, and different physics-based surrogate permeator models, such as countercurrent flow or crossflow, to be used in each stage. Moreover, to describe realistic systems, pressure drop equations can be included. We also present solution methods to accelerate the solution process. Through a case study of natural gas sweetening, we demonstrate that the proposed approach is able to obtain good solutions using an off-the-shelf global optimization solver. Finally, we expand the conventional membrane system synthesis problem by introducing feed variability in our model through a case study of an integrated reactor-separation system.
Bibliography:SC0018409
USDOE Office of Science (SC), Biological and Environmental Research (BER)
ISSN:0009-2509
1873-4405
DOI:10.1016/j.ces.2022.117482