Simulation-driven formulation of transportation fuel surrogates

Abstract

An alternative way to formulate transportation fuel surrogates using model predictions of gas-phase combustion targets is explored and compared to conventional approaches. 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. Using a previously studied three-component jet fuel surrogate containing n-dodecane, methyl-cyclohexane, and m-xylene as a 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, an optimisation algorithm is described to accelerate the identification of optimal surrogate compositions in this context.

Keywords:

• Surrogate definition
• chemical kinetics
• ignition delay times
• laminar flame speeds
• jet fuel

Acknowledgements

The authors thank Dr Heinz Pitsch and Dr Sivaram Ambikasaran for valuable discussions on this work.

Supplemental data

The supplementary materials for this article can be accessed at https://krithikasivaram.github.io.

Additional information

Funding

The first author gratefully acknowledges support from the New Faculty Initiation Grant [project number MEE/15–16/845/NFIG] offered by the Indian Institute of Technology Madras.