Modelling and Optimization of Syngas Production from Methane Dry Reforming Over Ceria-Supported Cobalt Catalyst Using Artificial Neural Networks and Box–Behnken Design
In the present study, synthesis gas was produced from dry reforming of methane over ceria supported cobalt catalyst in a fixed bed stainless steel reactor. Artificial neural network (ANN) and Box Behnken design (BBD) were employed to investigate the effects of reactant partial pressures, reactant fe...
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| Format: | Article |
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Elsevier
2015
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| Online Access: | http://umpir.ump.edu.my/id/eprint/11581/ |
| _version_ | 1848819045379342336 |
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| author | Ayodele, Bamidele V. Cheng, C. K. |
| author_facet | Ayodele, Bamidele V. Cheng, C. K. |
| author_sort | Ayodele, Bamidele V. |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | In the present study, synthesis gas was produced from dry reforming of methane over ceria supported cobalt catalyst in a fixed bed stainless steel reactor. Artificial neural network (ANN) and Box Behnken design (BBD) were employed to investigate the effects of reactant partial pressures, reactant feed ratios, reaction temperature and their optimum conditions. Good agreement was shown between the predicted outputs from the ANN model and the experimental data. Optimum reactant feed ratio of 0.60 and CH4 partial pressure of 46.85 kPa were obtained at 728 °C with corresponding conversions of 74.84% and 76.49% for CH4 and CO2, respectively. |
| first_indexed | 2025-11-15T01:47:19Z |
| format | Article |
| id | ump-11581 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| last_indexed | 2025-11-15T01:47:19Z |
| publishDate | 2015 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-115812019-08-28T07:04:50Z http://umpir.ump.edu.my/id/eprint/11581/ Modelling and Optimization of Syngas Production from Methane Dry Reforming Over Ceria-Supported Cobalt Catalyst Using Artificial Neural Networks and Box–Behnken Design Ayodele, Bamidele V. Cheng, C. K. TP Chemical technology In the present study, synthesis gas was produced from dry reforming of methane over ceria supported cobalt catalyst in a fixed bed stainless steel reactor. Artificial neural network (ANN) and Box Behnken design (BBD) were employed to investigate the effects of reactant partial pressures, reactant feed ratios, reaction temperature and their optimum conditions. Good agreement was shown between the predicted outputs from the ANN model and the experimental data. Optimum reactant feed ratio of 0.60 and CH4 partial pressure of 46.85 kPa were obtained at 728 °C with corresponding conversions of 74.84% and 76.49% for CH4 and CO2, respectively. Elsevier 2015 Article PeerReviewed Ayodele, Bamidele V. and Cheng, C. K. (2015) Modelling and Optimization of Syngas Production from Methane Dry Reforming Over Ceria-Supported Cobalt Catalyst Using Artificial Neural Networks and Box–Behnken Design. Journal of Industrial and Engineering Chemistry, 32. pp. 246-258. ISSN 1226-086X. (Published) http://dx.doi.org/10.1016/j.jiec.2015.08.021 doi:10.1016/j.jiec.2015.08.021 |
| spellingShingle | TP Chemical technology Ayodele, Bamidele V. Cheng, C. K. Modelling and Optimization of Syngas Production from Methane Dry Reforming Over Ceria-Supported Cobalt Catalyst Using Artificial Neural Networks and Box–Behnken Design |
| title | Modelling and Optimization of Syngas Production from Methane Dry Reforming Over Ceria-Supported Cobalt Catalyst Using Artificial Neural Networks and Box–Behnken Design |
| title_full | Modelling and Optimization of Syngas Production from Methane Dry Reforming Over Ceria-Supported Cobalt Catalyst Using Artificial Neural Networks and Box–Behnken Design |
| title_fullStr | Modelling and Optimization of Syngas Production from Methane Dry Reforming Over Ceria-Supported Cobalt Catalyst Using Artificial Neural Networks and Box–Behnken Design |
| title_full_unstemmed | Modelling and Optimization of Syngas Production from Methane Dry Reforming Over Ceria-Supported Cobalt Catalyst Using Artificial Neural Networks and Box–Behnken Design |
| title_short | Modelling and Optimization of Syngas Production from Methane Dry Reforming Over Ceria-Supported Cobalt Catalyst Using Artificial Neural Networks and Box–Behnken Design |
| title_sort | modelling and optimization of syngas production from methane dry reforming over ceria-supported cobalt catalyst using artificial neural networks and box–behnken design |
| topic | TP Chemical technology |
| url | http://umpir.ump.edu.my/id/eprint/11581/ http://umpir.ump.edu.my/id/eprint/11581/ http://umpir.ump.edu.my/id/eprint/11581/ |