Parameter estimation for modelling of organophilic pervaporation

Andras Jozsef Toth, Eniko Haaz, Szabolcs Solti, Nora Valentinyi, Anita Andre, Daniel Fozer, Tibor Nagy, P. Mizsey

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The work is motivated by an industrial environmental problem, which is ethanol removal from aqueous mixture. To complete this goal organophilic pervaporation of ethanol/water mixture through commercially available Sulzer PERVAP™ 4060 is investigated to obtain information about the removal of ethanol. The experimental results are obtained at different feed ethanol concentrations and temperatures. Our experimental data are evaluated with the semi-empirical pervaporation model (Valentínyi et al. 2013) of our improvement and it is found that the model can be applied also for this organophilic case. Linear and quadratic surfaces suiting (Model III) are also investigated in order to estimate partial permeate flux. The results of parameter estimation and modelling of the pervaporation show that the novel model that considers the concentration dependency of the transport coefficient (Model II) is also capable for the modelling of organophilic pervaporation and results in a better fit to the experimental data, than basic pervaporation model (Model I) and Model III.

Original languageEnglish
Title of host publicationComputer Aided Chemical Engineering
PublisherElsevier B.V.
Pages1287-1292
Number of pages6
ISBN (Print)9780444642356
DOIs
Publication statusPublished - Jan 1 2018

Publication series

NameComputer Aided Chemical Engineering
Volume43
ISSN (Print)1570-7946

Keywords

  • ethanol removal
  • model development
  • organophilic pervaporation
  • parameter estimation

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

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  • Cite this

    Toth, A. J., Haaz, E., Solti, S., Valentinyi, N., Andre, A., Fozer, D., Nagy, T., & Mizsey, P. (2018). Parameter estimation for modelling of organophilic pervaporation. In Computer Aided Chemical Engineering (pp. 1287-1292). (Computer Aided Chemical Engineering; Vol. 43). Elsevier B.V.. https://doi.org/10.1016/B978-0-444-64235-6.50226-6