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

• Published in: Chemical engineering science Vol. 62; no. 23; pp. 6568 - 6581
• Main Authors: Istadi, I., Amin, Nor Aishah Saidina
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.12.2007; Elsevier
• Subjects: ANN-GA; Applied sciences; Catalysis; Catalytic reactions; Chemical engineering; Chemical reactors; Chemistry; Exact sciences and technology; General and physical chemistry; Numerical analysis; Optimization; Pareto optimal solution; Plasma reactor; Reaction engineering; Reactors; Theory of reactions, general kinetics. Catalysis. Nomenclature, chemical documentation, computer chemistry; Numerical analysis; Plasma reactor; Pareto optimal solution; Chemical reactors; ANN-GA; Optimization; Reaction engineering; Catalytic reaction; Cogeneration; Dielectric materials; Carbon dioxide; Fixed bed reactor; Non thermal plasma; Neural network; Non equilibrium plasma; Synthesis gas; Modeling; Electric discharge; Operating conditions; Chemical reactor; Genetic algorithm; Numerical simulation
• ISSN: 0009-2509; 1873-4405
• DOI: 10.1016/j.ces.2007.07.066

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 CH 4 / CO 2 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-objectives can be suggested for two cases, i.e., simultaneous maximization of CH 4 conversion and C 2 + 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 CH 4 conversion, C 2 + yield and H 2 selectivity.