Evaluation of Thermal Conductivity of Gases at Atmospheric Pressure through a Corresponding States Method

In the present communication, we propose a corresponding states method for calculation/estimation of the vapor thermal conductivity of chemical compounds (mostly organic), applying the gene expression programming (GEP) algorithm. Around 16000 thermal conductivity data of gases at various temperatures from 100 to 1500 K. and atmospheric pressure related to about 1600 chemical compounds (mostly organic) are used for development and validation of the method. The quantities used in the corresponding states correlation include temperature, critical pressure, molecular weight, acentric factor, and normal boiling point. More than 14000 thermal conductivity data are randomly selected for developing (training + optimizing) the correlation, and about 1600 data are used for checking its prediction capability. The obtained statistical parameters including average absolute relative deviation of the results from the applied data (about 8%) show acceptable accuracy of the presented method. The most important features of the developed model are its simplicity, its wide range of applicability, and its validity based on the Leverage value test.