Simulation-driven formulation of transportation fuel surrogates

A new strategy to formulate transportation fuels surrogates using model predictions of gas-phase combustion targets is explored. Given a selection of individual fuel components, a multi-component chemical mechanism describing their oxidation kinetics, and a database of experimental measurements for key combustion quantities such as ignition delay times and laminar burning velocities, the optimal fractional amount of each fuel is determined as the one yielding the smallest error between experiments and model predictions. The approach contrasts with current best practices, which select surrogate compositions by matching fuel-intrinsic quantities (e.g. average hydrogen-to-carbon ratio) or measured global combustion quantities (e.g. Octane or Cetane numbers) assuming that those quantities are correlated with the fuel composition through simple mixing functions. Using a previously studied three-component jet fuel surrogate containing n-dodecane, methyl-cyclohexane, and m-xylene as case study, this article investigates in a systematic manner how the surrogate composition affects model predictions for ignition delay time and laminar burning velocities over a wide range of temperature, pressure, and stoichiometry conditions, and compares the results to existing surrogate formulation techniques, providing new insights on how to define surrogates for simulation purposes. Finally,