Development of Artificial Intelligence Methods for Determination of Methane Solubility in Aqueous Systems
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 t...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | International Journal of Chemical Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/6387408 |
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| _version_ | 1849409352269561856 |
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| author | Yi Zhao Yinsen Li Zhimin Li Yanping Pang Linbo Han Hao Zhang Li Yu Issam Alruyemi |
| author_facet | Yi Zhao Yinsen Li Zhimin Li Yanping Pang Linbo Han Hao Zhang Li Yu Issam Alruyemi |
| author_sort | Yi Zhao |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-75cec0d41d6d4851a23d5ab3f3d5edaf |
| institution | Kabale University |
| issn | 1687-8078 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Chemical Engineering |
| spelling | doaj-art-75cec0d41d6d4851a23d5ab3f3d5edaf2025-08-20T03:35:32ZengWileyInternational Journal of Chemical Engineering1687-80782022-01-01202210.1155/2022/6387408Development of Artificial Intelligence Methods for Determination of Methane Solubility in Aqueous SystemsYi Zhao0Yinsen Li1Zhimin Li2Yanping Pang3Linbo Han4Hao Zhang5Li Yu6Issam Alruyemi7Research Institute of Petroleum Engineering and TechnologyCollege of Health Science and Environmental EngineeringResearch Institute of Petroleum Engineering and TechnologyResearch Institute of Petroleum Engineering and TechnologyCollege of Health Science and Environmental EngineeringCollege of Health Science and Environmental EngineeringCollege of Health Science and Environmental EngineeringFouman Faculty of EngineeringAccurate 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.http://dx.doi.org/10.1155/2022/6387408 |
| spellingShingle | Yi Zhao Yinsen Li Zhimin Li Yanping Pang Linbo Han Hao Zhang Li Yu Issam Alruyemi Development of Artificial Intelligence Methods for Determination of Methane Solubility in Aqueous Systems International Journal of Chemical Engineering |
| title | Development of Artificial Intelligence Methods for Determination of Methane Solubility in Aqueous Systems |
| title_full | Development of Artificial Intelligence Methods for Determination of Methane Solubility in Aqueous Systems |
| title_fullStr | Development of Artificial Intelligence Methods for Determination of Methane Solubility in Aqueous Systems |
| title_full_unstemmed | Development of Artificial Intelligence Methods for Determination of Methane Solubility in Aqueous Systems |
| title_short | Development of Artificial Intelligence Methods for Determination of Methane Solubility in Aqueous Systems |
| title_sort | development of artificial intelligence methods for determination of methane solubility in aqueous systems |
| url | http://dx.doi.org/10.1155/2022/6387408 |
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