Optimal design of gas permeation membrane & membrane adsorption hybrid systems

Ramagopal Uppaluri, Robin Smith, Patrick Linke, Antonis Kokossis

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This work presents systematic synthesis procedures able to develop robustly optimal process designs for gas permeation membrane and hybrid membrane systems. A superstructure representation is proposed for membrane permeator compartments (stages), pressure equipment such as feed compressors, permeate recycle compressors, product compressors and vacuum pumps and separators (adsorbers) to capture alternative separation options. Allocation of vacuum pumps is followed using generic methodology. Various flow patterns such as cross-flow, counter-current and co-current can be simultaneously considered in the synthesis framework. The proposed representation builds upon previous efforts in reaction/separation process synthesis and can consider a variety of structural and operational options. Such options emerge from a number of possible module and process layouts. This work employs stochastic optimisation techniques in the form of simulated annealing. Applications of the proposed methodology to different case studies will be presented. Examples include the separation of air, up-gradation of lean hydrogen hydro-cracking refinery stream and acid gas removal from natural gas streams using membrane and fixed bed adsorption networks.

Original languageEnglish
Title of host publicationComputer Aided Chemical Engineering
PublisherElsevier
Pages367-372
Number of pages6
EditionC
DOIs
Publication statusPublished - 1 Jan 2002

Publication series

NameComputer Aided Chemical Engineering
NumberC
Volume10
ISSN (Print)1570-7946

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ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

Cite this

Uppaluri, R., Smith, R., Linke, P., & Kokossis, A. (2002). Optimal design of gas permeation membrane & membrane adsorption hybrid systems. In Computer Aided Chemical Engineering (C ed., pp. 367-372). (Computer Aided Chemical Engineering; Vol. 10, No. C). Elsevier. https://doi.org/10.1016/S1570-7946(02)80089-X