Blend Prediction Model for Freezing Point of Jet Fuel Range Hydrocarbons

Sustainable aviation fuels are a near-term solution for aviation greenhouse gas emission reduction. To become a sustainable aviation fuel, a synthetic fuel derived from a renewable source must have specifications written into ASTM D7566 as an annex to regulate its quality. However, before a sustainable aviation fuel can be added, it must be thoroughly evaluated and approved by all stakeholders through an time and volume intensive, as well as expensive process described in ASTM D4054. For this reason, the prescreening process is being developed. Prescreening is a process to measure or predict, from very small sample volumes, key fuel properties that are crucial for operability of an aircraft. The intention of the prescreening process is to inform suppliers of possible risks to passing the evaluations of ASTM D4054. Freezing point is one of the critical safety stipulations that require fuel to remain in liquid state under severe weather conditions. Methods to predict the freezing point of hydrocarbon blends are scarce in current literature. These pre-existing blend prediction models are either not validated within the typical temperature range for jet fuel standards, or they contain an interaction coefficient which is only obtained experimentally. The goal of this study is to develop a blending rule to accurately predict the freezing point of combinations of jet fuel range hydrocarbons. To do so, blends of hydrocarbons with freezing points varying from one another were tested. Binary and ternary blends containing bicyclohexyl, cis-1,2-dimethylcyclohexane, and an alternative jet fuel (POSF 12968) were tested along with separate tests including binary and ternary blends of tridecane, cis-1,2-dimethylcyclohexane, and trans-decahydronaphthalene. The experimental values obtained were compared with linear predictive blending model results. A new model based on Gibbs free energy is reliable for neat molecules, however, is currently being developed to predict the freezing point of hydrocarbon blends.https://ecommons.udayton.edu/stander_posters/3755/thumbnail.jp