Transportation fuels consist of a large number of hydrocarbon components and combust through an even larger number of intermediates. Detailed chemical kinetic models of these fuels typically consist of hundreds of species, and are computationally expensive to include directly in 3D CFD simulations. HyChem (Hybrid Chemistry) is a recently proposed modeling approach for high-temperature fuel oxidation based on the assumptions that fuel pyrolysis is fast compared to the subsequent oxidation of the small fragments, and that, although their proportions may differ, all fuels pyrolyse to similar sets of these fragment species. Fuel pyrolysis is hence modeled with a small set of lumped reactions, and oxidation is described by a compact C0-4 foundation chemistry core. The stoichiometric coefficients of the global pyrolysis reactions are determined to match experimental or detailed mechanism computational data, such as shock-tube pyrolysis products, ignition delays and laminar flame speeds. The model is then validated against key combustion properties, including ignition delays, laminar flame speeds and extinction strain rates. The resulting HyChem model is relatively small and computationally tractable for 3D CFD simulations in complex geometries. This paper applies the HEEDS optimization tool to find optimal pyrolysis reaction stoichiometric coefficients for high-temperature combustion of two fuels, namely Jet-A and n-heptane, using a 47 species mechanism. It was found that optimizing on experimental ignition delay and laminar flame speed targets yield better agreement for ignition delay times and flame speeds than optimizing on pyrolysis yield targets alone. For Jet-A, good agreement for ignition delays and flame speeds were obtained by using both ignition delay and flame speeds as targets. For n-heptane, a trade-off between ignition delay and flame speed was found, where increased target weights for ignition delay resulted in worse flame speed predictions, and visa-versa.

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