Fabrication modeling of industrial CO2 ionic liquids absorber by artificial neural networks

Abdollahi, Y. and Sairi, N.A. and Aroua, M.K. and Masoumi, H.R.F. and Jahangirian, H. and Alias, Y. (2015) Fabrication modeling of industrial CO2 ionic liquids absorber by artificial neural networks. Journal of Industrial and Engineering Chemistry, 25. pp. 168-175. ISSN 1226-086X, DOI https://doi.org/10.1016/j.jiec.2014.10.029.

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Abstract

The fabrication of industrial CO2 blended solution absorber was modeled by artificial neutral network. First the generated model had been statistically evaluated and then its ability of prediction was confirmed by validation test. The validated model was used to predict the desirable density and relative importance of the fabrication's effective variables. In conclusion, the importance included xH2O, 36.18%, xgua, 25.37%, xMDEA, 25.34% and temperature, 13.11% which showed none of them is negligible as well as the density (g cm(-3)) was validated by further experiment that showed the actual density, 1.101, was quite close to the predicted value, 1.017. (C) 2014 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.

Item Type: Article
Funders: University of Malaya RP006F-13SUS, University of Malaya PR007D-13AET
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Uncontrolled Keywords: Optimization, co2 capture, separation, greenhouse gases, ionic liquid, carbon-dioxide, n-methyldiethanolamine, solubilities, mixtures, density, systems, designs,
Subjects: T Technology > T Technology (General)
T Technology > TP Chemical technology
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 14 Apr 2016 06:52
Last Modified: 21 Mar 2019 06:55
URI: http://eprints.um.edu.my/id/eprint/15763

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