A prediction model of bubble size from experimental factors and fluid properties using multiple linear regression algorithm

Abstract

In a clean water test, the bubble diameter coming out through the circular diffusers was measured by photographic method and binary image analysis. Strong correlation was found between bubble diameter and superficial velocity. The depth of water has been added to existing experimental factors that include pore size and superficial velocity. By using dimensional analysis and multiple linear regression algorithm, a prediction model of bubble diameter was developed considering fluid properties and experimental factors including the depth of water. The developed model(EF-Model) was compared with the existing bubble diameter prediction models for the sample data. As a result of estimating the bubble diameter for the superficial velocity, the EF-Model has a lower RMSE and higher accuracy result than the existing models.