The environmental impact and the dependence upon fossil fuels in the aeronautical sector have promoted the demand for alternative and greener fuels. The implementation of alternative fuels is one of the main challenges for this sector in the near future. A possible short-term solution might be the blending of biofuels with jet fuel, which would allow for the use of greener fuels and a reduction in the greenhouse gases and pollutant emissions without significant changes in the existing fleets of the companies, with the purpose to develop a "drop-in" fuel. In this context, this work examines the combustion characteristics of single droplets of Jet A-1 (JF), hydroprocessed vegetable oil (NExBTL), and their mixtures in a drop-tube furnace (DTF). The objective of this work is to evaluate the influence of the mixture composition on the fuel characteristics. Droplets with diameters of 155 ± 5 μm, produced by a commercial droplet generator, were injected into the DTF, whose wall temperature and oxygen concentration were controlled. Experiments were conducted for three temperatures (900, 1000, and 1100 °C). The combustion of droplets was evaluated through the images obtained with a high-speed camera coupled with a high magnification lens and an edge detection algorithm. From the images allowed for the analysis of droplet combustion, data are reported for the temporal evolution of droplet sizes and burning rates. The results revealed that the mixtures followed the D 2 law, except the mixture with 75% JF for a DTF wall temperature of 1100 °C. The 75% JF mixture did not follow the D 2 law as a result of the occurrence of puffing and microexplosions, which enhanced the burning rates. Additionally, it was observed that the mixtures with a higher content of JF present brighter flames and higher burning rates.
Ammonia (NH3) is an inorganic substance considered as a promising fuel for power sector decarbonization. As a result of the absence of carbon in its structure, ammonia is capable of producing energy with zero CO2 emissions when burned. However, the combustion of NH3 presents several challenges as a result of its low reactivity and low flame speed as well as the formation of large quantities of nitrogen oxides (NO x ) and frequent ammonia slip. A suggested solution for gas turbines is the use of rich-to-lean approaches, with a fuel-rich first-stage combustion, which mitigates NO x formation, followed by a lean phase for the oxidation of the remaining reactants, improving combustion efficiency. To help assess this concept, the present work investigates experimentally and computationally the combustion of ammonia/air mixtures, enriched by hydrogen (H2) for enhanced burning characteristics, in a swirl and bluff-body stabilized burner, at stoichiometric to fuel-rich conditions. Stability tests were performed for a fixed thermal input (2.8 kW), and flames of fuel/air equivalence ratios of 1.0, 1.1, and 1.2, with molar fractions of ammonia in fuel of 0.7 and 0.8, were studied. Temperature profiles along the combustor axis were measured, and flue gas measurements for NO x emissions and unburned NH3 and H2 concentrations were performed for the six studied flames. Computational simulations were performed using a chemical reactor network coupled with recent kinetic mechanisms to compare species trends and further understand the NO x formation and NH3 conversion into hydrogen, through rate of production analyses. It was found that the present laboratory combustor performed well in terms of flame stability, also generating low levels of NO x emissions in all fuel-rich conditions. H2 was detected in high concentrations in the flue gas, partially originated from ammonia dissociation, and is followed by high unburned ammonia emissions. Both H2 and NH3 emissions increase with the equivalence ratio. A secondary, spontaneous diffusion flame was observed above the combustor, proving that the flue gas may subsequently be burned. Higher fractions of hydrogen in the fuel generate more unburned ammonia but also higher H2 concentrations in the flue gas. The predictions based on a reactor network model coupled with the evaluated kinetic mechanisms presented good agreement with the experimentally observed species trends and fair agreement with species values.
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