Genetic programming (GP) approach for prediction of supercritical CO2 thermal conductivity

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Rostami:2017:CERD,

• author = "Alireza Rostami and Milad Arabloo and Hojatollah Ebadi",
• title = "Genetic programming (GP) approach for prediction of supercritical {CO2} thermal conductivity",
• journal = "Chemical Engineering Research and Design",
• volume = "122",
• pages = "164--175",
• year = "2017",
• ISSN = "0263-8762",
• DOI = "doi:10.1016/j.cherd.2017.02.028",
• URL = "http://www.sciencedirect.com/science/article/pii/S0263876217301247",
• abstract = "Gas thermal conductivity is one of the thermophysical properties that inevitably enters into mathematical models of real systems used in the design of chemical engineering processes or in the gas industry. In this study, via implementing a powerful and newly applied equation generator algorithm known as, genetic programming (GP) mathematical strategy, a novel correlation for estimation of supercritical CO2 thermal conductivity is established. The proposed correlation is developed and validated based on a comprehensive databank of 752 thermal conductivity datasets from open literature. By using various statistical quality measures, the result of the proposed GP model was compared with commonly used literature models. As a result, the proposed GP model gives the best fit and satisfactory agreement with the target data with an average absolute relative error of 2.31percent and R2 = 0.997. A parametric sensitivity analysis showed that pressure and density of the CO2 gas stream have considerable impact on the thermal conductivity at supercritical condition. The results of this study can be of enormous practical worth for scientist and expertise in order to efficiently compute the thermal conductivity in any supercritical industry involving CO2.",
• keywords = "genetic algorithms, genetic programming, Supercritical CO2 thermal conductivity, Empirical correlation, Comprehensive error analysis",

}

Genetic Programming entries for Ali Reza Rezghi Rostami Milad Arabloo Hojatollah Ebadi

Citations