Oscillation behaviors of burning aluminum droplet and flame in solid propellant combustion

The burning aluminum droplets in composite solid propellants generated from merging and micro-explosion present complicated oscillations. It is essential to characterize this oscillatory process, while it is challenging for the oscillation frequency ranging from several to tens of kHz in a micron-scale region. The oscillation behaviors of micron-sized burning aluminum droplets have been experimentally investigated via high-speed microscopic imaging up to 75 kHz. The dynamical series images of oscillating aluminum droplets are processed with an artificial intelligence (AI) image segmentation algorithm and analyzed with proper orthogonal decomposition (POD). It is observed that the droplet oscillates in the multimode as a result of surface tension reduction upon merging on the burning surface, and the oscillation rapidly transforms to an eigenmode with a prolate/oblate ellipsoid shape. The droplet oscillation triggers the forced oscillation of the enveloping flame with the same frequency and a certain phase lag. A high-frequency wavy regime with a frequency of up to 96 kHz on the tail flame is observed, which is supposed to originate from the instability of the flame flow over the droplet. This work provides a comprehensive insight into the oscillation behaviors of burning aluminum droplets thereby bridging the gap between the burning behaviors on the surface and in the gaseous atmosphere. Novelty and significance statement This study furthers the previous understanding of the oscillation behaviors of aluminum droplet combustion near the burning surface in solid propellants. Aluminum has been widely applied in propellant while elucidating the underlying mechanisms governing its combustion process remains challenging. Oscillation stands as one of the essential factors in combustion. Therefore, this study revealed the oscillation behaviors of aluminum droplets in propellants through a high-speed microscopic imaging system up to 75 kHz. The droplet oscillation and its interaction with flame oscillation were quantitatively analyzed over a time series by segmenting the detailed structures of aluminum with an artificial intelligence image segmentation algorithm. The underlying mechanisms of droplet and flame oscillations as well as their interactions were elucidated. These comprehensive insights contributed to bridging the gap between the burning behaviors on the surface and in the gaseous atmosphere and facilitated the understanding of the intrinsic mechanisms of propellant combustion.