Abstract

This study presents two new reliable simple correlations for predicting flash point of kerosene hydrocarbons using multiple linear regression method. The methodology assumes that the flash point of kerosene fuels can be expressed as a function of elemental composition and several structural parameters. The proposed correlations have determination coefficients of 0.910 and 0.977. Also, the first model has root mean square deviation (RMSD) and the average absolute deviations (AAD) of 10.6 and 8.2 K, respectively, for 111 kerosene fuels with different molecular structures as training set. The RMSD and AAD for the second improved model are 5.39 and 4.33 K, respectively. The predictive power of two correlations is checked using a cross validation method. (R2 = 0.977, Q2Ext = 0.975, and Q2LMO = 0.979). Also, these correlations give good predictions for further 25 kerosene fuels as test set. The proposed model can also be applied for designing novel kerosene fuels.

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