UBC Theses and Dissertations

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UBC Theses and Dissertations

Numerical analysis of the geomechanical interaction between open pit and cave mining using the hybrid finite-discrete element method Shapka-Fels, Tiara


Transitioning from previous or current surface (open pit) mining to underground mass mining (caving) allows operators to extend mine life and to maintain economical production of low-grade ore bodies. The application of advanced numerical models is essential to adequately analyze and design different geotechnical aspects of open pit-to-cave transitions. This thesis offers a critical assessment of numerical methods centered around the hypothesis that a model cannot perfectly imitate reality. Therefore, the numerical modelling of large-scale mining projects requires the real problem to be idealized and simplified. It is in this simplification process that limitations arise. The objective of this research is to investigate the role of numerical analysis applied to pit-to-cave transition, and to develop models to understand the geomechanical interaction between open pit and cave mining based on different geological and mine design variables. This thesis uses primarily conceptual models, with special consideration of the planned caving operation at the Red Chris Operations in northern British Columbia. Results from hybrid continuum-discontinuum models highlight the effects of uncertainty and variability of geological materials and structural geology. Modifying discontinuous features results in significant changes to overall caving behaviour and interaction with the open pit. Overall, both conceptual models and the Red Chris case study have emphasized the need for a whole suite of models to understand outcomes. With proper use, numerical analysis can provide insight for the identification of critical scenarios which may impact future design and operations. The results demonstrate that forward modelling should be performed in the context of a risk-based approach, with numerical models as investigative tools to assess risk and evaluate the impact of different unknowns, thus classifying modelling outputs in terms of expected consequences.

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