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...

Full description

Bibliographic Details
Main Authors: Saidina Amin, Nor Aishah, Istadi, Istadi
Format: Article
Published: Pergamon-Elsevier Science Ltd 2007
Subjects:
_version_ 1825910239190319104
author Saidina Amin, Nor Aishah
Istadi, Istadi
author_facet Saidina Amin, Nor Aishah
Istadi, Istadi
author_sort Saidina Amin, Nor Aishah
collection ePrints
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.
first_indexed 2024-03-05T18:14:07Z
format Article
id utm.eprints-8704
institution Universiti Teknologi Malaysia - ePrints
last_indexed 2024-03-05T18:14:07Z
publishDate 2007
publisher Pergamon-Elsevier Science Ltd
record_format dspace
spelling 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
work_keys_str_mv AT saidinaaminnoraishah modellingandoptimizationofcatalyticdielectricbarrierdischargeplasmareactorformethaneandcarbondioxideconversionusinghybridartificialneuralnetworkgeneticalgorithmtechnique
AT istadiistadi modellingandoptimizationofcatalyticdielectricbarrierdischargeplasmareactorformethaneandcarbondioxideconversionusinghybridartificialneuralnetworkgeneticalgorithmtechnique