An accurate model for prediction of autoignition temperature of pure compounds

作者：Gharagheizi Farhad^*

来源：Journal of Hazardous Materials, 2011, 189(1-2): 211-221.

DOI：10.1016/j.jhazmat.2011.02.014

• Autoignition temperature (AIT)
• Group contribution
• Artificial Neural Networks
• Combustion

Accurate prediction of pure compounds autoignition temperature (AIT) is of great importance. In this study, the Artificial Neural Network-Group Contribution (ANN-GC) method is applied to evaluate the AIT of pure compounds. 1025 pure compounds from various chemical families are investigated to propose a comprehensive and predictive model. The obtained results show the squared correlation coefficient of 0.984, root mean square error of 15.44 K, and average percent error of 1.6% for the experimental values.

• 出版日期2011-5-15