Threshold Sooting Index of Sustainable Aviation Fuel Candidates from Composition Input Alone: Progress toward Uncertainty Quantification

A quantitative structure-property relationship model has been developed to predict the threshold sooting index (TSI) of arbitrary mixtures of aliphatic and aromatic hydrocarbons of known composition. The model employs contributions from eight molecular fragments plus a global shift and a penalty factor for naphthenic compounds. For each coefficient, the contributions were determined by a constrained regression to data from five different experimental campaigns, which were stitched together by setting the TSI of methylcyclohexane to 5 and the TSI of 1-methylnaphthalene to 100. Unique to this study; the TSI of 1,3,5-trimethylbenzene was restricted to the range of 54.7 and 63.1, which significantly constrains uncertainty. Within the composite training dataset, which contained 65 molecules and 124 data points, including simple mixtures, the model was found to match 95% of the data within 8.9 TSI. Validation of the model against n-butylcyclohexane, dimethylcyclooctane, and a six-component surrogate jet fuel shows prediction to be well within the 95-percentile confidence band of the experiment. This model is the first to integrate the linear blending rule for the TSI with a linear quantitative structure-property relationship model for the TSI, and the first time that referee controls have been applied to ensure that all datasets, experimental and modeled, are normalized to the same scale.

Automated summary

A quantitative structure-property relationship model has been developed to predict the threshold sooting index (TSI) of arbitrary mixtures of aliphatic and aromatic hydrocarbons. The model utilizes molecular fragments, a global shift, and a penalty factor to make predictions. The model has been validated and found to accurately predict TSI values.