Abstract
To support our research and process modeling for liquid fuels, including blends, from petroleum and synthetic sources such as from biomass intermediates, we evaluated composition-based prediction methods and improved predictions for five key specification properties of petroleum-based and alternative aviation fuels, namely distillation temperatures (10 % distilled, t10, and final boiling point, tFBP), density, flash point, net heat of combustion, and freezing point. The types of fuels included were petroleum-based jet fuels, jet-fuel surrogate mixtures, synthetic blending components obtained from different sources, and blends of Jet A with many synthetic blending components. Expanded datasets to update associated parameters allowed significant improvements for one of the prediction methods used in earlier work, namely the Modified Weighted Average method published initially by Shi et al. By considering the importance of lighter compounds for flash points and heavier compounds for freezing points, the revised Modified Weighted Average method was further improved. For liquid density, the revised Modified Weighted Average method gave the best overall results. The revised Modified Weighted Average method, the American Society for Testing and Materials D7215 method, and the D7215 method modified by another group gave comparable results for flash point, while the revised Modified Weighted Average and D3338 methods gave the best results for net heat of combustion. Freezing point was well predicted using the revised Modified Weighted Average method and showed the most significant improvements over current predictions. Distillation temperature t10 was not well predicted, while tFBP was predicted with a mean absolute error comparable to experimental reproducibility.
| Original language | American English |
|---|---|
| Number of pages | 23 |
| Journal | Fuel |
| Volume | 423 |
| DOIs | |
| State | Published - 2026 |
NLR Publication Number
- NLR/JA-5100-89223
Keywords
- aviation fuel properties prediction
- distillation temperature prediction
- flash point prediction
- freezing point prediction
- liquid density prediction
- net heat of combustion prediction
- sustainable aviation fuels
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