A preliminary phenomenological model of a flotation process in an L-150 Jameson cell wasdeveloped, in order to predict the metallurgical performance in a cleaner application. In this studythe feed was considered to be composed by chalcopyrite, molybdenite and gangue, which weredistributed in three size classes: +75 [μm], -75 +45 [μm] and -45 [μm].The overall flotation recovery was modelling using a multiphase approach, recognizing that theoverall flotation recovery is obtained from the interaction between three independent zones:downcomer zone, pulp zone and froth zone.The downcomer and pulp zone recoveries, were characterized using the general kinetic model forcontinuous flotation process, considering a first-order kinetic with rectangular distribution in bothcases, and a plug flow and perfect mixing regime to represent the downcomer and pulp zonehydrodynamics, respectively. The forth zone recovery was characterized using a semi-empiricalmodel as function of the principal variables that affect the cleaning zone operation.Furthermore, it was considered that the water recovery comes from the feed flow rate and the washwater flow rate. These were characterized using an exponential and lineal model, respectively, asfunction of the froth height, superficial air rate and superficial wash water rate. The gangue recoveryit was related directly to the water recovery from the feed flow rate by the entrainment factor.The metallurgical simulator was developed to show the effect of feed characteristics and the mainoperating variables on the recovery and concentrate grade. The model parameters were estimatedform previous industrial data for columns and mechanical cells, since at this time the results formetallurgical test in this Jameson cell were not available.Finally, the simulator was implemented online using the computational platform available in theProcess Control Laboratory. The operating variables are taken from the control and monitoringsystem, while the feed characteristics are created virtually. This simulator will allow the developmentof operational and control strategies to reduce the variability of the metallurgical performanceobtained, produced by the natural variability of the feed.
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