Determination of Cetane Numbers Via Chemical Kinetic Mechanism

Minimizing global warming is a major task of todays' society. For air transport, sustainable aviation fuels (SAF) produced from renewable sources are a promising key solution. While electric flight is intriguing for short distances, SAF are required for mid- and long-distance flights and in addition, enable fuel design strategies to minimize environmental effects. The qualification and approval for SAF are standardized in the ASTM D4054, which include fuel properties as an essential part. Among others, lean blow-out (LBO) limits are a key performance parameter. The experimental determination of LBO is very time-consuming and cost-effective. The LBO of a specified engine is highly dependent on the fuel properties affecting evaporation, mixing, and ignitability. Therefore, prediction tools are desired to identify early promising SAF for decreasing the certification cost. Due to the correlation between LBO and derived cetane numbers (DCN), a tool for the prediction of the DCN is presented in this study. The DCN model uses chemical kinetic ignition delay time (IDT), simulated in a constant volume combustion chamber based on the ASTM D6890 standard, and seven representative physical properties of a fuel. A high agreement of the predicted DCN to the literature DCN with root-mean-square errors of 4.7 and correlation coefficients of 0.95 was found.