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
收藏
页码：347 / 355
页数：9
相关论文
共 50 条
  • [41] Optimization of CO2 injection and brine production well placement using a genetic algorithm and artificial neural network-based proxy model
    Musayev, Kudrat
    Shin, Hyundon
    Nguyen-Le, Viet
    INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, 2023, 127
  • [42] Application of Artificial Neural Network and Genetic Algorithm in Constructing Index System
    Peng, Dong
    Feng, Dai
    Song, Lu
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON PRODUCT INNOVATION MANAGEMENT, VOLS I AND II, 2008, : 1463 - 1467
  • [43] Phase equilibrium modeling for binary systems containing CO2 using artificial neural networks
    Atashrouz, S.
    Mirshekar, H.
    BULGARIAN CHEMICAL COMMUNICATIONS, 2014, 46 (01): : 104 - 116
  • [44] Modeling and optimization of biogas production on saw dust and other co-substrates using Artificial Neural network and Genetic Algorithm
    Kana, E. B. Gueguim
    Oloke, J. K.
    Lateef, A.
    Adesiyan, M. O.
    RENEWABLE ENERGY, 2012, 46 : 276 - 281
  • [45] Experimental and modeling study of CO2 solubility in formation brines at in-situ conditions
    Ji, Zemin
    Wang, Heng
    Wang, Mingyuan
    Lv, Weifeng
    Wang, Shouchuan
    Kou, Zuhao
    He, Chang
    Wang, Lei
    JOURNAL OF CLEANER PRODUCTION, 2024, 438
  • [46] Modeling particle size in the dispersion polymerization of styrene using artificial neural network and genetic algorithm
    Alireza Mahjub
    Colloid and Polymer Science, 2016, 294 : 1833 - 1843
  • [47] Modeling and Optimization of β-Cyclodextrin Production by Bacillus licheniformis using Artificial Neural Network and Genetic Algorithm
    Sanjari, Samaneh
    Naderifar, Abbas
    Pazuki, Gholamreza
    IRANIAN JOURNAL OF BIOTECHNOLOGY, 2013, 11 (04) : 223 - 232
  • [48] Modeling and optimization for microstructural properties of Al/SiC nanocomposite by artificial neural network and genetic algorithm
    Esmaeili, R.
    Dashtbayazi, M. R.
    EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (13) : 5817 - 5831
  • [49] Genetic Algorithm–Artificial Neural Network Modeling of Moisture and Oil Content of Pretreated Fried Mushroom
    Mohebbat Mohebbi
    Milad Fathi
    Fakhri Shahidi
    Food and Bioprocess Technology, 2011, 4 : 603 - 609
  • [50] Modeling and optimization of HVAC systems using artificial neural network and genetic algorithm
    Nabil Nassif
    Building Simulation, 2014, 7 : 237 - 245
12345