Title of article :
COMPARISON STUDY FOR THE SOLUBILITY PREDICTION OF PHENANTHRENE IN SUPERCRITICAL CO2 ENTRAINED WITH n-PENTANE WHEN USING EQUATION OF STATE AND ARTIFICIAL NEURAL NETWORKS
Author/Authors :
Karim, Abdul Mun’em Abbas University of Diyala - College of Engineering, Iraq , Mutlag, Ali Khudhair University of Diyala - College of Engineering, Iraq
From page :
81
To page :
90
Abstract :
The present work deals with the comparison study for the solubility prediction of phenanthrene in pure supercritical CO2 and supercritical CO2 entrained with n-pentane (n-C5) as a liquid solvent. The experimental data obtained from literatures for systems above are modeled by using two techniques:1. Peng-Robinson equation of state (PR- EOS). 2. Artificial Neural Networks (ANN). The results of two techniques showed that the ANN technique gives excellent agreement with the experimental data of the systems taken and the percentage of average absolute relative deviation (%AARD) ranges from 5.668×10-5 % to 2.089×10-3 % meanwhile the model when using PR- EOS gives good agreement with (%AARD) ranges from 3.34% to 8.67%.
Keywords :
Solubility , Phenanthrene , Supercritical CO2 , Entrainer , Peng , Robinson equation of state (PR , EOS) , Artificial Neural Networks (ANN)
Journal title :
Emirates Journal For Engineering Research
Journal title :
Emirates Journal For Engineering Research
Record number :
2596934
Link To Document :
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