The present work focuses on developing a framework for accurate prediction of thermodynamic conditions for single-component hydrates, namely CH₄, CO₂, N₂, H₂S, and C₂H₆ (coded in MATLAB). For this purpose, an exhaustive approach is adopted by incorporating eight different equations of states, namely Peng–Robinson, van der Waals, Soave–Redlich–Kwong, Virial, Redlich–Kwong, Tsai-Teja, Patel, and Esmaeilzadeh–Roshanfekr, with the well-known van der Waals–Platteeuw model. Overall, for I – H – V phase region, the Virial and van der Waals equation of state gives the most accurate predictions with minimum AAD%. For L _w– H – V phase region, Peng–Robinson equation of state is found to yield the most accurate predictions with overall AAD of 3.36%. Also, genetic programming algorithm is adopted to develop a generalized correlation. Overall, the correlation yields quick estimation with an average deviation of less than 1%. The accurate estimation yields a minimal AAD of 0.32% for CH₄, 1.93% for C₂H₆, 0.77% for CO₂, 0.64% for H₂S, and 0.72% for N₂. The same correlation can be employed for fitting phase equilibrium data for other hydrates too. The tuning parameter, n , is to be used for fine adjustment to the phase equilibrium data. The findings of this study can help for a better understanding of phase equilibrium and cage occupancy behavior of different gas hydrates. The accuracy in phase equilibria is intimately related to industrial applications such as crude oil transportation, solid separation, and gas storage. To date, no single correlation is available in the literature that can accurately predict phase equilibria for multiple hydrate species. The novelty of the present work lies in both the accuracy and generalizability of the proposed correlation in predicting the phase equilibrium data. The genetic programming generalized correlation is convenient for performing quick equilibrium prediction for industrial applications.

中文翻译：

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CH ₄，C ₂ H ₆，CO ₂，H ₂ S和N ₂水合物的热力学模型及其 笼数的相关性

本工作着重于开发一种框架，用于准确预测单组分水合物（CH ₄，CO ₂，N ₂，H ₂ S和C ₂ H ₆（在MATLAB中编码））的热力学条件。为此，我们采用了详尽的方法，将八个不同的状态方程合并在一起，分别是：Peng–Robinson，van der Waals，Soave–Redlich–Kwong，Virial，Redlich–Kwong，Tsai-Teja，Patel和Esmaeilzadeh–Roshanfekr，著名的van der Waals–Platteeuw模型。总体而言，对于 I – H – V 在相区域内，Virial和van der Waals状态方程以最小的AAD％给出了最准确的预测。对于 L _w – H – V 相区域，Peng-Robinson状态方程可得出最准确的预测，总AAD为3.36％。另外，采用遗传编程算法来发展广义相关。总体而言，相关性可以快速估计平均偏差小于1％的情况。准确的估算得出CH ₄的最小AAD为0.32％，C ₂ H ₆的最小AAD为1.93 ％，CO ₂的最小AAD为0.77 ％，H ₂ S的最小AAD为0.64 ％，N ₂的最小AAD为0.72％。相同的相关性也可用于拟合其他水合物的相平衡数据。调整参数， n ，用于微调相平衡数据。这项研究的结果可以帮助更好地了解不同气体水合物的相平衡和笼式占用行为。相平衡的精度与工业应用（如原油运输，固体分离和储气）密切相关。迄今为止，文献中还没有单一的相关性可以准确预测多种水合物的相平衡。当前工作的新颖性在于在预测相平衡数据时所提出的相关性的准确性和可推广性。遗传程序化广义相关性便于进行工业应用的快速平衡预测。