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Conference Proceedings

Seventh International Conference & Exhibition on Mass Mining (MassMin 2016)

Conference Proceedings

Seventh International Conference & Exhibition on Mass Mining (MassMin 2016)

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Experimental and Comminution Model Framework for Secondary Fragmentation Prediction in Block Caving

Block caving is the most economic underground methods for excavating massive orebodies, due to the high productivity and low production costs. The success of block caving operations depends on the fragmentation and draw control as large blocks decrease the equipment efficiency, inhibit the material flow and may lead to expensive secondary blasting. Even though ore handling system design, as well as overall economic results, both critically rely on secondary fragmentation, this parameter continues to be one of the least understood issues in the caving operations.This research focuses on the experimental study of secondary fragmentation, considering the impact of vertical pressures and material flow. Experiments using a load-haul-dump extraction system were conducted under laboratory conditions to quantify the influence of pressure and particle size on secondary fragmentation. Results demonstrate that increasing the vertical pressure (simulating deeper conditions) leads to higher fragmentation (smaller particle size) and greater fines generation during draw. The experimental results were applied to calibrate the developed mathematical model based on kinetic matrix. The acceptable accordance between the comminution model results and the reality showed that this method is convenient in predicting the secondary fragmentation in block caving.CITATION:Castro, R, Gmez, R, Casali, A and Hekmat, A, 2016. Experimental and comminution model framework for secondary fragmentation prediction in block caving, in Proceedings Seventh International Conference and Exhibition on Mass Mining (MassMin 2016), pp 175-182 (The Australasian Institute of Mining and Metallurgy: Melbourne).
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  • Published: 2016
  • PDF Size: 0.886 Mb.
  • Unique ID: P201602019

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