Development of Artificial Intelligence Methods for Determination of Methane Solubility in Aqueous Systems. (12th July 2022)

• Record Type: Journal Article
• Authors: Zhao, Yi; Li, Yinsen; Li, Zhimin; Pang, Yanping; Han, Linbo; Zhang, Hao; Yu, Li; Alruyemi, Issam
• Other Names: Narayanasamy Selvaraju Academic Editor.
• Is Part Of: International journal of chemical engineering. Volume 2022(2022)
• Publication Date: 2022-07-12
• Subjects: Chemical engineering -- Periodicals; Chemical engineering; Electronic journals; Periodicals; 660
• DOI: 10.1155/2022/6387408
• Languages: English
• ISSNs: 1687-806X

Abstract

Abstract : Accurate determinations of water (H2 O) content in natural gases especially in the methane (CH4 ) phase are highly important for chemical engineers dealing with natural gas processes. To this end, development of a high performance model is necessary. Due to importance of the solubility of methane in the aqueous solutions for natural gas industries, two novel models based on the Decision Tree (DT) and Adaptive Neuro-Fuzzy Interference System (ANFIS) have been employed. To this end, a total number of 204 real methane solubility points in aqueous solution containing NaCl under different pressure and temperature conditions have been gathered. The comparisons between predicted solubility values and experimental data points have been conducted in visual and mathematical approaches. The R 2 values of 1 for training and testing phases express the great ability of proposed models in calculation of methane solubility in pure water systems.