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Utilization of polymeric binders to agglomerate oxidized copper ore

Kiaei Kimia, Golpayegani Mohammad Hasan

Physicochemical Problems of Mineral Processing

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2023

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Vol. 59, iss. 6

art. no. 176682

EN

Permeability reduction is a major challenge in heap leaching, primarily caused by the accumulation of fines that move with the leaching agent, leading to the formation of dead zones and channeling within the heap. In the Aria copper beneficiation plant, the 0-2 mm fraction with a copper grade of 1.4% undergoes pre-separation prior to heap loading without further processing. This study investigated the potential of using the agglomeration method to improve permeability in the case of using the 0-2 mm fraction of ore. Mineral compounds, such as sodium silicate and calcium sulfate, and non-ionic, cationic, and anionic polymer compounds, were used in the agglomeration process. The strength of interparticle bonding was evaluated by measuring the fine migration percentage (FMP) in the soak test. The results revealed that agglomerates produced using non-ionic compounds had the highest bonding strength, with an FMP of 3.89%, the lowest of all the compounds tested. This enhanced bonding strength was attributed to the combined influence of hydrogen bonding forces and van der Waals forces.

2

Modelling the power draw of tumbling mills : a comprehensive review

Golpayegani Mohammad Hasan, Rezai Bahram

Physicochemical Problems of Mineral Processing

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2022

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Vol. 58, iss. 4

art. no. 151600

EN

Optimizing power consumption in grinding, the most consumed stage in the mining industry, plays an influential role in reducing operating costs. Obtaining an efficient model to predict tumbling mills' power consumption accurately took the attention of researchers, mineral processing engineers, and tumbling mill manufacturers. This article comprehensively reviews the published mill power models and the most critical studies on this topic since 1919. Furthermore, the employed approaches for modelling the tumbling mills' power draw, the incorporated parameters into the developed models, the models' performances in predicting the industrial mills' power draw, and the potential gaps in the available literature are discussed. Moreover, based on the shortages identified in this review, some recommendations have been made to enhance the modelling mill power draw.

3

Improvement of the accuracy of Hogg and Fuerstenau's model in predicting the power draw of ball mills based on determining the grinding media’s dynamic voidage

Golpayegani Mohammad Hasan, Rezai Bahram

Physicochemical Problems of Mineral Processing

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2022

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Vol. 58, iss. 6

art. no. 153380

EN

In the development of tumbling mills' power models, the voidage of grinding media is assumed to be static and equal to 40%. While the grinding media’s voidage is dynamic; and hence is varied by changing the operating parameters. In this paper, to improve the Hogg and Fuerstenau model's accuracy in predicting the ball mills' power draw, the grinding media's static and dynamic voidage was studied for Bond's proposed ball size distributions (BSD) for the ball mills' first filling. To this end, by scaling down balls to one-tenth of actual size, developing a novel method to measure the dynamic voidage, and employing the three-level factorial method, a separate empirical model was developed for determining the dynamic voidage of each Bond's BSD with respect to mill's fractional filling and rotating speed. Moreover, using the multiple regression method, a general empirical model was derived to determine the dynamic voidage of each supposed BSD based on calculating the mean absolute deviation of balls diameter (MAD). Results indicated that grinding media's dynamic voidage increases with an increase in rotating speed and a decrease in fractional filling and balls diameter's MAD. The maximum and minimum static and dynamic voidage occurred for the seventh and first Bond's BSDs. By employing an industrial database and analyzing the mean absolute percentage error (MAPE) of predicted ball mills' power draw, it was found that the Hogg and Fuerstenau model's accuracy enhances by calculating the load's bulk density based on the grinding media's dynamic voidage.