Hydrate phase equilibria for hydrogen+water and hydrogen+tetrahydrofuran+water systems: Predictions of dissociation conditions using an artificial neural network algorithm

In this communication, a mathematical model based on feed-forward artificial neural network algorithm is presented, which can estimate hydrate dissociation conditions for the hydrogen+water and hydrogen+tetrahydrofuran+water systems. To develop this algorithm, the experimental data for the hydrate dissociation conditions of the latter two systems with different concentrations of tetrahydrofuran in aqueous phase below its stoichiometric concentration (i.e., ≃0.059) have been used. Independent experimental data (not used in training and developing this algorithm) have been employed to examine the reliability of this method. It is shown the agreement between the predictions and the experimental data is acceptable demonstrating the reliability of this algorithm as a predictive tool.