Droplet size distribution in a swirl airstream using in-line holography technique

TL;DR

This study examines how swirling airflows affect droplet breakup and satellite droplet size distribution using advanced holography techniques, revealing different breakup phenomena and size distributions at varying swirl strengths.

Contribution

It introduces a combined experimental and analytical approach to understand droplet breakup mechanisms under swirl conditions, with new insights into size distribution patterns.

Findings

High swirl produces smaller satellite droplets.

Droplet size distribution is bi-modal or multi-modal depending on swirl strength.

Analytical model accurately predicts size distribution modes at high swirl.

Abstract

We investigate the morphology and size distribution of satellite droplets resulting from the interaction of a freely falling water droplet with a swirling airstream of different strengths by employing shadowgraphy and deep-learning-based digital in-line holography techniques. We found that the droplet exhibits vibrational, retracting bag and normal breakup phenomena for the no swirl, low and high swirl strengths for the same aerodynamic field. In the high swirl scenario, the disintegrations of the nodes, rim, and bag-film contribute to the number mean diameter, resulting in smaller satellite droplets. In contrast, in the low swirl case, the breakup of the rim and nodes only contributes to the size distribution, resulting in larger droplets. The temporal variation of the Sauter mean diameter reveals that for a given aerodynamic force, a high swirl strength produces more surface area and surface energy than a low swirl strength. The theoretical prediction of the number-mean probability density of tiny satellite droplets under swirl conditions agrees with experimental data. However, for the low swirl, the predictions differ from the experimental results, particularly due to the presence of large satellite droplets. Our results reveal that the volume-weighted droplet size distribution exhibits two (bi-modal) and three (multi-model) peaks for low and high swirl strengths, respectively. The analytical model that takes into account various mechanisms, such as the nodes, rim, and bag breakups, accurately predicts the shape and characteristic sizes of each mode for the case of high swirl strength.