title: Correlations to predict droplet size in ultrasonic atomisation.
abstract: In conventional two fluid nozzles, the high velocity air imparts its energy to the liquid and disrupts the liquid sheet into droplets. If the energy for liquid sheet fragmentation can be supplied by the use of ultrasonic energy, finer droplets with high sphericity and uniform size distribution can be achieved. The other advantage of ultrasound induced atomisation process is the lower momentum associated with ejected droplets compared to the momentum carried by the droplets formed using conventional nozzles. This has advantage in coating and granulation processes. An ultrasonic probe sonicator was designed with a facility for liquid feed arrangement and was used to atomise the liquid into droplets. An ingenious method of droplet measurement was attempted by capturing the droplets on a filter paper (size variation with regard to wicking was uniform in all cases) and these are subjected to image analysis to obtain the droplet sizes. This procedure was evaluated by high-speed photography of droplets ejected at one particular experimental condition and these were image analysed. The correlations proposed in the literature to predict droplet sizes using ultrasound do not take into account all the relevant parameters. In this work, a truly universal correlation is proposed which accounts for the effects of physico-chemical properties of the liquid (flow rate, viscosity, density and surface tension), and ultrasonic properties like amplitude, frequency and the area of vibrating surface. The significant contribution of this work is to define dimensionless numbers incorporating ultrasonic parameters, taking cue from the conventional numbers that define the significance of different forces involved in droplet formation. The universal correlations proposed are robust and can be used for designing ultrasonic atomisers for different applications. Among the correlations proposed here, those ones that are based on the dimensionless numbers and Davies approach predict droplet sizes within acceptable limits of deviation. Also, an empirical correlation from experimental data has been proposed in this work.
authors: Hindustan Lever Research Centre, Whitefield, Bangalore, India. rajan.raghavachari@unilever.com
authors: R
authors: R
authors: Rajan
authors: A B
authors: AB
authors: Pandit
mesh_terms: D006801:Humans; D009330:Nebulizers and Vaporizers; D010316:Particle Size; D013010:Sonication; D014835:Volatilization