Nanofluid fuel has garnered significant attention due to its potential to enhance combustion characteristics, energy density, and ignition properties. The study comprehensively examined the effects of aluminum nanoparticles with diverse sizes (50 nm, 100 nm, 200 nm, 500 nm, 1 μm) and concentrations (2.5 wt%, 5.0 wt%, 7.5 wt%) on the ignition and combustion characteristics of nanofluid fuel droplets, utilizing a mechanically mixed aluminum-based nanofluid fuel solution that incorporated kerosene, aluminum particles, and the surfactant oleic acid. The combustion process of the nanofluid fuel droplets encompasses phases of ignition, steady combustion, micro-explosion, and agglomerate reaction. The surface temperature of the nanofluid fuel droplets consistently exceeded that of a pure kerosene droplet, with temperature elevations correlating positively with particle concentration but not with the particle size. The surface temperature of nanofluid fuel droplets containing 7.5 wt% aluminum particles is approximately 205°C. The incorporation of oleic acid into pure kerosene prolongs the ignition delay from 0.317 s to 0.333 s. The combustion rate of the nanofluid fuel droplets escalates upon the addition of aluminum particles, with the rate escalating in tandem with the diameter and concentration of the aluminum particles. Nanofluid fuel droplets containing 5.0 wt% aluminum and 5.0 wt% oleic acid particles exhibit a combustion rate akin to that of pure kerosene droplets, with rates of 0.596 and 0.604 mm2 s−1, respectively. Concurrently, the ignition delay for nanofluid fuel droplets is longer than that of pure kerosene, yet it exhibits insensitivity to particle size. The ignition delay for nanofluid fuel droplets with the addition of 7.5 wt% aluminum particles is approximately 1.5 times that of kerosene. Nanofluid fuel droplets devoid of oleic acid yield divergent results due to particle agglomeration effects. Subsequently, as particle size increased, the surface of combustion residue develops more pronounced bulges, becoming more prone to rupture. Ultimately, a kinetic prediction model is proposed, accounting for the inhomogeneous properties within the droplet. The root mean squared errors for ignition delay time, combustion rate, and steady surface temperature are all below 8 %, indicating a strong correlation between model predictions and experimental data. This research could help accelerate the adoption of aluminum-based nanofluid fuel.
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