| Autor: |
Yi Zhao, Yinsen Li, Zhimin Li, Yanping Pang, Linbo Han, Hao Zhang, Li Yu, Issam Alruyemi |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
International Journal of Chemical Engineering, Vol 2022 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1687-8078 |
| DOI: |
10.1155/2022/6387408 |
| Popis: |
Accurate determinations of water (H2O) 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 R2 values of 1 for training and testing phases express the great ability of proposed models in calculation of methane solubility in pure water systems. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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