Corresponding States Method for Estimation of Upper Flammability Limit Temperature of Chemical Compounds
The accuracy and predictability of predictive methods to determine the flammability characteristics of chemical compounds are of drastic significance in the chemical industry. This work aims at continuing application of the gene expression programming (GEP) mathematical strategy to modify the existing thermophysical properties correlations available in the literature to pursue the following objectives: optimization of the number of independent parameters, amplification of the generality, and improvement of the accuracy and predictability. This work deals with presenting a simple corresponding states model to predict the upper flammability limit temperature of 1462 organic compounds from 76 chemical families. The parameters of the correlation include the critical temperature and the acentric factor of the compounds. The obtained statistical parameters including average absolute relative deviation of the results from DIPPR 801 database values (1.7, 1.8, 1.7% for training, optimization, and prediction sets, ...
Empirical Method for Representing the Flash-Point Temperature of Pure Compounds
Flash point temperature is one of the most-widely used physical properties for the evaluation of the flammability hazard of combustible liquids. In this communication, an empirical method involving normal boiling-point temperature and number of carbon atoms of the pure compounds is presented for accurate representation of the flash-point temperature of pure substances. A total of 1471 pure compounds belonging to 77 chemical families were used to develop a general correlation. The global absolute average deviation of the model results from experimental values is 2.4%. A successful comparison is finally made with respect to some of the methods proposed in the literature, which apply a similar approach for calculation of the flash-point temperature of pure compounds.
Prediction of standard chemical exergy by a three descriptors QSPR model
A new quantitative structure–property relationship (QSPR) three parameter correlation (R2 = 0.9977) of standard chemical exergy for a diverse set of 134 organic substances was developed by application of a genetic algorithm search. The descriptors are all calculated directly from the molecular structure, and the approach given is applicable, in principle, to all organic substances of regular structure. The application of the genetic algorithm in comparison with stepwise multi-variate linear regression (MLR) shows some advantages in required time for solving and in precision.