Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algorithm technique
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...
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Pergamon-Elsevier Science Ltd
2007
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| Online Access: | http://eprints.utm.my/8704/ http://dx.doi.org/10.1016/j.ces.2007.07.066 |
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| author | Saidina Amin, Nor Aishah Istadi, Istadi |
| author_facet | Saidina Amin, Nor Aishah Istadi, Istadi |
| author_sort | Saidina Amin, Nor Aishah |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | 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. |
| format | Article |
| id | my.utm.eprints-8704 |
| institution | Universiti Teknologi Malaysia |
| publishDate | 2007 |
| publisher | Pergamon-Elsevier Science Ltd |
| record_format | eprints |
| spelling | my.utm.eprints-87042009-05-08T01:56:11Z http://eprints.utm.my/8704/ 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 Istadi, Istadi TP Chemical technology 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. Pergamon-Elsevier Science Ltd 2007 Article PeerReviewed 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 http://dx.doi.org/10.1016/j.ces.2007.07.066 10.1016/j.ces.2007.07.066 |
| spellingShingle | TP Chemical technology Saidina Amin, Nor Aishah Istadi, Istadi Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algorithm technique |
| title | Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algorithm technique |
| title_full | Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algorithm technique |
| title_fullStr | Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algorithm technique |
| title_full_unstemmed | Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algorithm technique |
| title_short | Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algorithm technique |
| title_sort | modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algorithm technique |
| topic | TP Chemical technology |
| url | http://eprints.utm.my/8704/ http://dx.doi.org/10.1016/j.ces.2007.07.066 |
| url_provider | http://eprints.utm.my/ |