Estimating mutual solubility of a CO2 in NaCl aqueous solution system using connectionist approaches

被引:2
作者
Raji, Mojtaba [1 ]
Dashti, Amir [1 ]
Ghafoori, Samira [2 ,3 ]
Bahadori, Alireza [4 ]
Chau, Kwok-Wing [5 ]
机构
[1] Univ Kashan, Dept Engn, Separat Proc Res Grp SPRG, Kashan, Iran
[2] Ryerson Univ, Dept Chem Engn, Toronto, ON, Canada
[3] Australian Coll Kuwait, Dept Petr Engn, Safat, Kuwait
[4] Southern Cross Univ, Sch Environm Sci & Engn, Lismore, NSW, Australia
[5] Hong Kong Polytech Univ, Dept Civil & Environm Engn, Kowloon, Hong Kong, Peoples R China
关键词
Artificial neural networks; carbon dioxide sequestration; genetic programming; modeling; NaCl; CARBON-DIOXIDE; IMPROVED MODEL; SODIUM-CHLORIDE; HIGH-PRESSURE; CAPTURE; SEQUESTRATION; 100-DEGREES-C; ABSORPTION; MIXTURES; BRINE;
D O I
10.1080/10916466.2022.2043368
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Expert models of GP, MLP-ANNs and LSSVM were used to evaluate CO2 solubility in NaCl aqueous solution. Temperature, pressure, and molarity of NaCl aqueous solution were considered as the inputs of the model and CO2 (mole/kg) solubility in NaCl solutions was the models output. The proposed GP, LSSVM, and ANNs models are verified by comparing their results with extensive experimental data for CO2-NaCl solutions solubility from open literature. LSSVM modeling approach can be applied to model the system with satisfactory precision. Meanwhile, using the AI models precise predictions are provided without applying complicated thermodynamic principles.
引用
收藏
页码:2429 / 2449
页数:21
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