Authors: Li, Y; Elmo, D

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DOI https://doi.org/10.36487/ACG_repo/2465_70

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Li, Y & Elmo, D 2024, 'Application of the network connectivity index on fragmentation assessment in cave mine design', in P Andrieux & D Cumming-Potvin (eds), Deep Mining 2024: Proceedings of the 10th International Conference on Deep and High Stress Mining, Australian Centre for Geomechanics, Perth, pp. 1091-1102, https://doi.org/10.36487/ACG_repo/2465_70

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Abstract:
Cave mine design relies on reasonable fragmentation assessment to optimise production efficiency and minimise operational costs. In the past decade the volumetric fracture intensity (P32) obtained from discrete fracture network (DFN) models has been widely used for fragmentation assessment in cave mine design. This paper examines the relationship between P32 and block sizes. The results show that P32 does not correlate well with key block size parameters D20, D50, and D80, which are sizes at 20, 50 and 80% mass passing, respectively. As an alternative, the network connectivity index 3D (NCI3D) is proposed as a geometric parameter to evaluate its correlation with block sizes. Results indicate that NCI3D exhibits stronger associations with D20, D50, and D80 compared to P32. Furthermore, NCI3D can be a computationally efficient alternative to the traditional DFNbased block formation approach for evaluating fragmentation characteristics in cave mine design. This parameter could be applied to mine-scale DFN models for assessing localised fragmentation within various locations of the orebody.

Keywords: network connectivity index, fracture intersection density, fracture, connectivity, discrete fracture network, fracture intensity, fragmentation assessment, cave mine

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