Determination and Scale-up of Specific Rate of Grinding of Placer Iron Ore of Sangan

Nowadays different methods are being applied to improve scientists’ knowlage regarding the concept and mechanism of processes. One of these methods is mathematical modeling of processes, which is supposed to define and determine the parameters affecting the process. In mineral processing, the specific rate of grinding is one of the most important parameters for modeling and simulation of grinding circuits. Since high percent of energy is often consumed by the comminution circuit in a mineral processing plant, thus it needs to be properly investigated. The rate vareis with changing of the grinding conditions and the equipments selected for a specific task. There are several parameters affecting on the efficiency, effectiveness and on the model to be developed for energy consumption in a grinding circuit, the optimization of which should be conducted through a suitable modeling and simulation process. The material of this investigation was provided from the Sangan placer iron ore deposit, located 1000 km far from Tehran(Iran). This study aimed to investigate the effect of mills and balls diameter, ball and powder filling of the mill and rotational speed on grinding kinetics. Breakage distribution function of the placer iron ore of Sangan with a 10-millimeter maximum particle size was determined in the laboratory by a 200 millimeter mill. Values of the laboratory selection function were scaled up for a pilot mill with a diameter of 1200 millimeter. Austin's equations were used as a basis for the scale-up process. For validation of the models and checking the correctness of the scale-up process, BMCS simulator v. 1.3 was used for prediction of particle size distribution of the pilot mill discharge. The simulation results were found to be in a good agreement with the pilot test measured data. The good agreement between the discharge measured and the predicted particle size distributions confirms validity of the scale-up relationships and procedure. Therefore, the scaled-up selection function can be used confidently for design goals.