Prediction of Bubble Generation Based on Acoustic Emission

Abstract

The noise associated with gas discharged from a submerged nozzle is of great interest to many industries because of its important applications. For example, it can be used to size bubbles and to detect gas flow rate. However, the physics associated with the acoustic emission due to bubble formation is complex, particularly when a large number of bubbles are involved, and has not been fully understood. In this study, the dynamics of the bubble formation from a submerged nozzle has been studied experimentally using the Particle Droplet Image Analysis technique. An improved model for prediction of the bubble generation rate and size distribution based on acoustic emission is presented. The experimental study is carried out in a large water tank, of dimensions 10 m \(\times \) 10 m \(\times \) 6 m, using multiple hydrophones. The water tank is carefully calibrated in order to provide free-field measurements. The predicted bubble generation rate and size distribution have been compared with the experimental data. It has been found that the predicted results are in good agreement with the experimental measurement, implying that an accurate prediction of acoustic emission associated with a bubbling plume from a submerged nozzle can be achieved by using the model.