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Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algorithm technique

Saidina Amin, Nor Aishah and Istadi, Istadi (2007) Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algorithm technique. Chemical Engineering Sciences, 62 (23). pp. 6568-6581. ISSN 0009-2509

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Official URL: http://dx.doi.org/10.1016/j.ces.2007.07.066

Abstract

A hybrid artificial neural network-genetic algorithm (ANN-GA) was developed to model, simulate and optimize the catalytic-dielectric barrier discharge plasma reactor. Effects of CH4/CO2 feed ratio, total feed flow rate, discharge voltage and reactor wall temperature on the performance of the reactor was investigated by the ANN-based model simulation. Pareto optimal solutions and the corresponding optimal operating parameter range based on multi-objective scan be suggested for two cases, i.e., simultaneous maximization of CH4 conversion and C2+ selectivity (Case 1), and H-2 selectivity and H-2/CO ratio (Case 2). It can be concluded that the hybrid catalytic-dielectric barrier discharge plasma reactor is potential for co-generation of synthesis gas and higher hydrocarbons from methane and carbon dioxide and performed better than the conventional fixed-bed reactor with respect to CH4 conversion, C2+ yield and H-2 selectivity.

Item Type:Article
Uncontrolled Keywords:higher hydrocarbons; greenhouse gases; zeolite; benzene
Subjects:T Technology > TP Chemical technology
Divisions:Chemical and Natural Resources Engineering (Formerly known)
ID Code:8704
Deposited By:INVALID USER
Deposited On:08 May 2009 01:56
Last Modified:08 May 2009 01:56

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