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Keywords:

  • gene expression programming;
  • liquid thermal conductivity;
  • corresponding states;
  • reliable model;
  • prediction

In this communication, a general model for representation/presentation of the liquid thermal conductivity of chemical compounds (mostly organic) at 1 atm pressure for temperatures below normal boiling point and at saturation pressure for temperatures above the normal boiling point is developed using the Gene Expression Programming algorithm. Approximately 19,000 liquid thermal conductivity data at different temperatures related to 1636 chemical compounds collected from the DIPPR 801 database are used to obtain the model as well as to assess its predictive capability. The parameters of the model comprise temperature, acentric factor, critical pressure, normal boiling temperature, and molecular weight. Nearly 80% of the data set (15,221 data) is randomly assigned to develop the model equation, 10% of the data set (1902 data) is used to validate the model, and the remaining data (1902 data) were implemented to evaluate its predictive power. The average absolute relative deviation of the model results from the DIPPR 801 data is less than 9%. In terms of simplicity and wide range of applicability, this empirical model shows acceptable accuracy. © 2012 American Institute of Chemical Engineers AIChE J, 59: 1702–1708, 2013