Development of a bulk ore sorting model for ore sortability assessment—Part II: Model validation and optimisation. (1st October 2021)

• Record Type: Journal Article
• Authors: Li, Genzhuang; Klein, Bern; He, Chen; Yan, Zengxin; Sun, Chunbao; Kou, Jue
• Is Part Of: Minerals engineering. Volume 172(2021)
• Publication Date: 2021-10-01
• Subjects: Bulk ore sorting -- Fractal -- Multifractal -- Ore Sortability -- Block cave mine; Mines and mineral resources -- Periodicals; Ressources minérales -- Périodiques; Mines and mineral resources; Periodicals; Electronic journals; 622
• DOI: 10.1016/j.mineng.2021.107143
• Languages: English
• ISSNs: 0892-6875

Abstract

Highlights: The developed fractal model was validated on mine production data. The multifractal model was proposed for bulk ore sortability assessment. The multifractal model was more accurate in predicting the sorting results and assessing ore sortability. Abstract: A previous study demonstrated the theoretical development of a model for assessing bulk ore sortability. However, the model has not been validated with many cases. In this study, the developed model was validated using the production data from 232 draw points in a block cave copper mine. For each draw point, sorting results and mine economics were predicted using fractal modelling and compared with results based on actual data analysis. The statistical error was measured for the fractal model predictions of feed grade, mass yield, pre-concentrate grade, metal recovery, and NSR with and without bulk ore sorting. An optimised approach was developed using multifractal modelling; two sets of fractal parameters were determined to characterise the metal distribution in high- and low-grade ranges. The results showed that the multifractal model was more accurate than the fractal model in predicting the sorting results and assessing ore sortability.