Prediction of hydrate formation conditions to separate carbon dioxide from fuel gas mixture in the presence of various promoters

In this study estimation of hydrate formation conditions to separate carbon dioxide (CO₂) from fuel gas mixture (CO₂+H₂) was investigated in the presence of promoters such as tetra-n-butylammonium bromide (TBAB), tetra-n-butylammonium fluoride (TBAF), and tetra-n-butyl ammonium nitrate (TBANO₃). The emission of CO₂ from the combustion of fuels has been considered as the dominant contributor to global warming and environmental problems. Separation of CO₂ from fuel gas can be an effective factor to prevent many of environmental impacts. Gas hydrate process is a novel method to separate and storage some gasses. In this communication, a feed-forward artificial neural network algorithm has been developed. To develop this algorithm, the experimental data reported in the literature for hydrate formation conditions in the fuel gas system with different concentrations of promoters in aqueous phase have been used. Finally, experimental data compared with estimated data and with calculation of efficiency coefficient, mean squared error, and mean absolute error show that the experimental data and predicted data are in acceptable agreement which demonstrate the reliability of this algorithm as a predictive tool.