Estimation of the dissociation conditions and storage capacities of various sH clathrate hydrate systems using effective deterministic frameworks

Abstract

Understanding gas hydrates potential for gas storage purposes has fascinated scientists for decades. Structure H clathrate hydrate through its capacity and ability of sH hydrate formers in decreasing the gas hydrates formation pressures, introduces itself as an appropriate alternative for gas storage and career aims. Hence, this communication is aimed at estimating the capacity and phase equilibria of methane, ethane, propane, carbon dioxide, hydrogen sulfide, nitrogen, hydrogen, argon, krypton, xenon, and methyl fluoride sH hydrates in the presence of different sH hydrate formers at below and above the freezing point of water. By developing the artificial neural network (ANN) model and extending thermodynamic-based framework these targets have been undertaken. The ANN approach correlates the hydrate dissociation conditions as a function of critical properties of hydrate formers. The thermodynamic approach employs a two-step hydrate formation mechanism using the modified version of Cubic-Plus-Association (CPA) equation of state associated with modified Huron-Vidal mixing rule (MHVI) accompanied by UNIFAC model. Findings reveal that the most accurate ANN model is obtained through tan-sigmoid transfer function with 12 neurons number. The average absolute relative deviation percent (AARD%) and correlation coefficient (R2) for the ANN approach are determined 0.09% and 0.9981 while the thermodynamic framework provides 0.07% and 0.9987, respectively. The capacity storage evaluation results indicate that the minimum and maximum storage volume percent for unit cell of various sH clathrate hydrate systems are 42 and 58, respectively.