Neuro Fuzzy Modeling of Oxidative Coupling of Methane over LSCF Perovskite Type Catalyst
Volume Title: 1
1Research Institute of Petroleum Industry, Tehran, Iran
2Process and Equipment Technology Development Division, Research Institute of Petroleum Industry
In the present study, neuro fuzzy technique was applied successfully to model oxidative coupling of methane (OCM) reaction over La0.6Sr0.4Co0.8Fe0.2O3-δ perovskite catalyst in the fixed bed micro reactor. In the developed models, reaction temperature and partial pressures of methane and oxygen at inlet stream were considered as input parameters. Three five layer neuro fuzzy models were designed separately to predict methane conversion, ethane selectivity and ethane formation rate as model outputs. To investigate the ability of the developed neuro fuzzy model in prediction of OCM reaction performance, the statistical parameters such as coefficient of determination (R2), root mean square error (RMSE) and mean relative error (MRE) were calculated and predicted values were compared with experimental data. The RMSE of the neuro fuzzy model in prediction of methane conversion, ethane formation rate and ethane selectivity were 0.1643, 0.8742 and 0.0493, respectively which indicate very good agreements between model predictions and experimental data.
Neuro Fuzzy Model; Oxidative Coupling of Methane; Perovskite Catalyst; selectivity; Formation Rate; conversion