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An improved method for predicting autoignition temperatures based on first principles
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DOI：10.1016/j.fuel.2022.124245.png)
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摘要
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Methods for predicting autoignition temperatures (AIT) have been historically inaccurate and are rarely based on the underlying physical phenomena leading to observed AIT. Previous attempts at predicting AIT have been developed based on Quantitative Structure-Property Relationships (QSPR) and additive group contribution methods. This work presents an improved method for predicting AIT based on the method originally developed by the late Dr. William H. Seaton. The method of Seaton is described in detail including its use of first principles to predict AIT. A comprehensively evaluated data set is used for a new regression of Seaton method parameters. Improvements on the model of Seaton and underlying principles are presented and discussed. Finally, an improved AIT prediction model and parameter sets based on Seaton's method are recommended.
Keyword:
Autoignition
Flammability
Safety
Prediction
First-principles
期刊
IF:
7.5
论文数:
3.9W
被引数:
16.7W
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