Chemical mechanism development and reduction for combustion of NH3/H2/CH4 mixtures

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title = "Chemical mechanism development and reduction for combustion of NH3/H2/CH4 mixtures",
abstract = "To achieve a reduced chemical model for comprehensive prediction of ammonia/hydrogen/methane mixture combustion, a detailed chemical mechanism with 128 species and 957 reactions was first assembled using models from literature. Directed relation graph with error propagation (DRGEP) with sensitivity analysis reduction method was then used to obtain compact reaction models. The studied reduction conditions cover ɸ = 0.5–2.0, temperature 1000–2000 K, and pressure 0.1–5 MPa. Finally, two reduced models have been obtained: 28 species and 213 reactions for ammonia/hydrogen and 51 species and 420 reactions for ammonia/hydrogen/methane. Ignition delay times and laminar burning velocities for single component and fuel mixtures predicted using the detailed and reduced mechanisms were compared with available experiments. Results showed that both detailed and reduced mechanisms performed fairly well for ignition delays, while over-predicted laminar burning velocity at fuel-rich conditions for single ammonia fuel and mixtures. The 51 species reduced mechanism was also tested in non-premixed coflow hydrogen/methane jet flames, while 1%–50% mole ammonia were added to the fuel stream. Modelling results showed that this 51-species mechanism was suitable for CFD modelling, and the speedup factor was over 5 when using the reduced mechanism with different codes. The flame structure, as well as NO and NO2 formation was studied. High NO concentrations were found in high-temperature region near the stoichiometric zone, while NO2 was dominant in the lean flame zone. Reaction flux analysis was performed to better understand NH3 oxidation and NOx emissions at low- and high-temperature conditions.",
keywords = "Ammonia, Ammonia-hydrogen-methane, Chemical model, Mechanism reduction, NO emissions, Nonpremixed flame",
author = "Rui Li and Konnov, {Alexander A.} and Guoqiang He and Fei Qin and Duo Zhang",
year = "2019",
doi = "10.1016/j.fuel.2019.116059",
language = "English",
volume = "257",
journal = "Fuel",
issn = "1873-7153",
publisher = "Elsevier",