Applications in Energy and Combustion Science (Dec 2023)
A shock tube study of fuel concentration effect on high-pressure autoignition delay of ammonia
Abstract
Fulfilling the role of ammonia as a viable energy vector and clean alternative fuel for combustion systems requires an improved understanding of its fundamental chemical kinetics. In this work, autoignition delay time (IDT) measurements of ammonia/oxygen/argon (NH3/O2/Ar) mixtures behind reflected shock waves were reported at a temperature range of 1180–1941 K, a pressure range of 11–20 atm, and equivalence ratios of 0.5, 1.0, and 2.0. The effect of fuel concentration on the IDT was investigated for stoichiometric mixtures containing 1–22% NH3 by mole fraction. A combination of diagnostics, including pressure and chemiluminescence from excited hydroxyl radicals (OH*) near 307 nm at the sidewall and the endwall, and direct absorption of a diode laser emission near 2.2 μm, were used to provide a consistent determination of the autoignition event. The experimental data were compared with predictions by several kinetic models applicable to ammonia oxidation from literature to assess their performance. Large variations were observed among model predictions; the model by Mathieu and Petersen (2015) was found to produce the best agreement with the experimental data at low fuel concentrations, and the model by Mével et al. (2009) reproduced the experimental data the best at high fuel concentrations. However, none of these models is capable of accurate prediction of the IDT measurements across the entire range of fuel concentration investigated; most models shift from being over-reactive to under-reactive as the fuel concentration increases. Reaction path and sensitivity analyses performed with selected kinetic models revealed the importance of reactions related to NH3 and N2HX species in controlling the autoignition, especially at high fuel concentrations. The reliable shock tube IDT data from this study highlighting the fuel concentration effect could benefit the validation and refinement of kinetic models.
