Composition Effects in Transcritical Turbulent Mixing of Sustainable Aviation Fuel Surrogates

Drop-in sustainable aviation fuels coupled with high overall pressure ratio gas turbine engines constitute a promising pathway toward near-term carbon neutrality in the aviation sector. Under typical high-power operating conditions, however, the pressure in the combustor exceeds the fuel’s critical pressure, so injection occurs in a transcritical regime. In this regime, the thermophysical and transport properties of the working fluid exhibit pronounced non-linear variations, which significantly influence the mixing processes. While the effects of pressure and temperature on transcritical injection are well established for cryogenic rocket propellants, substantial uncertainty persists regarding how surrogate fuel composition affects numerical predictions for sustainable aviation fuels. In this work, we first validate a numerical framework for representing transcritical, multicomponent aviation fuels by coupling OpenFOAM with Cantera. We then investigate the effect of the number of chemical species in SAF surrogates on turbulent transcritical mixing under aero-engine relevant conditions through the diffuse-interface large-eddy simulation approach. The study focuses on the alcohol-to-jet fuel POSF-11498, classified as a category C fuel within the National Jet Fuels Combustion Program. The results demonstrate that a two-component surrogate, designed to capture the dominant C12 and C16 highly branched iso-paraffins of POSF-11498, reproduces the behavior of a more detailed seven-component surrogate with no appreciable loss of accuracy, at less than half its computational cost. In contrast, a single-component representation departs appreciably from the multicomponent surrogates in the prediction of density, heat capacity and thermal conductivity. In all cases the mixing field itself is nearly surrogate-independent, so the composition sensitivity stems from the real-fluid thermophysical properties rather than from the mixing dynamics. The proposed numerical framework provides a versatile foundation for high-fidelity LES investigations of transcritical injection of sustainable aviation fuels.