Document Type: Case Study


Mining Engineering Department, College of Mining and Industry, Shahid Bahonar University


A new parametric model was developed for predicting cut point of hydraulic classifiers. The model directly uses operating parameters including pulp flowrate, feed particle size characteristics, pulp solids content, solid density and particles retention time in the classification chamber and also covers uncontrollable errors using calibration constants. The model applicability was first verified using a bench scale classifier and then, validated at industrial scale for a coal classifier. Results showed that the new model can predict the cut point more precisely compared to the conventional Masliyah model, i.e. the accuracy values of 80% and 37% for the new and Masliyah models, respectively. Sensitivity study showed that the model was extremely sensitive to the particle size distribution of feed while being least sensitive to the particles retention time.