Experimental Study and Mathematical Modeling of Solubility of CO2 in Water: Application of Artificial Neural Network and Genetic Algorithm

被引：9

作者：

Ghasemian, Naser ^{[1
]}

Kalbasi, Mansour ^{[1
]}

Pazuki, Gholamreza ^{[1
]}

机构：

[1] Amirkabir Univ Technol, Dept Chem Engn, Tehran Polytech, Tehran, Iran

来源：

JOURNAL OF DISPERSION SCIENCE AND TECHNOLOGY | 2013年 / 34卷 / 03期

关键词：

Artificial neural network; carbon dioxide; equations of state; genetic algorithm; mixture combining rules; water; CARBON-DIOXIDE-WATER; THERMODYNAMIC PROPERTIES; PHASE-EQUILIBRIA; SYSTEMS; PREDICTION;

D O I：

10.1080/01932691.2012.667293

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

The solubility of carbon dioxide in water is measured at 278.15348.15K and 0.11MPa. The experimental data are compared with those obtained from equations of state such as van der Waals, Redlikh-Kwong, Soave- Redlikh-Kwong, Peng-Robinson coupled with two mixing rules van der Waals and Wong Sandler equations. Also, the solubility of carbon dioxide in water is modeled using the artificial neural network system and optimized with genetic algorithm method. The results show that the artificial neural network system can accurately predict the solubility of carbon dioxide in water than the other equations of state.

引用

页码：347 / 355

页数：9

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