Multi component modelling of an air classifier

This paper focusses on investigating the classification behaviours of the components having different densities and flow characteristics then developing preliminary model structure where these properties are considered. Such a study can improve the prediction accuracy of the existing models since material characteristics are of crucial importance. Within the scope of this study, laboratory scale experimental tests were undertaken on clinker, copper ore, magnetite and coal samples, at different operating conditions. The results concluded that, increasing the density decreased the cut size in the meantime increased the bypass of the classification operation. In addition, the sharpness and the fish hook parameters were found to be correlated with the flow characteristics of the material e.g., the higher the fluidity the higher the sharpness and the lower the fish-hook. As a conclusion of the study, the correlations presented in the paper were integrated into an existing air classifier model and preliminary multi component model structure for air classifiers was developed.