Mineral Processing
M. Noori; R. Dehghan
Abstract
In the Tabas coal preparation plant (SE Iran), -50 + 6 mm raw coal was treated in a 700 mm two-stage two-density Tri-Flo dynamic dense medium separator. In order to study the circuit performance and to evaluate the separator efficiency, 32 mm cubic density tracers were used in the range of 1.28-2.1 g/cm3 ...
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In the Tabas coal preparation plant (SE Iran), -50 + 6 mm raw coal was treated in a 700 mm two-stage two-density Tri-Flo dynamic dense medium separator. In order to study the circuit performance and to evaluate the separator efficiency, 32 mm cubic density tracers were used in the range of 1.28-2.1 g/cm3 and under different operational conditions. The performance of Tri-Flo was evaluated in a rapid manner, and an acceptable partitioning performance was observed under the process regime; the misplacements were in the normal range. Contrary to the dense media cyclones where the cut point shift (CPS) is usually positive, the results of this work showed that CPS was negative in both stages of the Tri-Flo separator. The Ecart probable value for the first stage of the separator (Epf = 0.023) was rather greater than the second stage (Eps = 0.018), representing the higher performance achieved in the second stage. In addition, the Tri-Flo operational parameters were found to be adjustable on the basis of raw coal specifications in order to reach good metallurgical results. Therefore, the optimum operational feed capacities of the Tri-Flo separator were determined to be in the range of 80-140 t/h, depending on the type of raw coal.
Hamid Khoshdast
Abstract
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 ...
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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.
