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Cartes Melo, Ignacio Alberto

University of British Columbia

Rock mass characterization is fundamental in underground mining and geotechnical engineering, particularly for stope stability design. Traditional classification methods such as Rock Quality Designation (RQD), Rock Mass Rating (RMR), and the Q-system have been widely used to assess rock mass properties. However, these methodologies rely on qualitative and empirical assessments, which may not fully capture the inherent variability of rock masses. This research aims to improve the spatial resolution of Uniaxial Compressive Strength (UCS) measurements and integrate advanced numerical modelling techniques for more reliable stope stability predictions. A comprehensive data acquisition campaign was conducted, incorporating both laboratory testing and in-situ measurements. Probabilistic and numerical modelling approaches, including Monte Carlo simulations and finite element analysis, were employed to refine stability assessments. The results demonstrate that an improved UCS spatial resolution enhances the variability in rock mass, allowing for better prediction of potential failure zones and more efficient support design. The findings of this study highlight the need for a paradigm shift in rock mass characterization, moving from empirical classification toward a more mechanistic understanding of rock behaviour. Future research should focus on bridging the gap between traditional classification systems and advanced numerical models. This research contributes to a different perspective on evaluating the stability of underground mining operations.

Text

2025-04-28

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/90872

Mining Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/