ABSTRACT:

Rockmass characterization is an essential process for geotechnical engineering design, and most characterization programs are conducted entirely through the lens of classification systems like RQD, RMR, Q, and GSI. As underground excavations go deeper and as they encounter less routine geohazards, or as mining methods such as caving are adapted for unconventional orebody geologies, these classification systems tend to become less relevant. The authors believe that a more effective characterization approach should consider structures like joints, bedding, and foliations in a rockmass separately in order to both more accurately represent the strength of the rockmass and to better predict the behaviour and failure modes in an excavation. If structures like joints, bedding, and foliations are considered to be “interblock” structures, micro-defects within these blocks like veins, veinlets, and stockworks can be regarded as “intrablock” structures. These intrablock structures should also be considered in characterization since they can have a significant influence on rockmass strength.

1. INTRODUCTION

Rockmass characterization is an essential process for geotechnical engineering design, and classification systems have been developed to provide a structured methodology for use in a variety of geotechnical projects. In most cases, rockmass characterization programs are conducted entirely through the lens of classification systems like RQD, RMR, Q, and GSI, which were initially developed with certain geotechnical applications in mind. As underground excavations go deeper and as they encounter less routine geohazards, or as mining methods such as caving are adapted for unconventional orebody geologies, these classification systems tend to become less relevant. Q and RMR were originally developed as empirical classification systems as a direct input to support design for excavations. The advancement of numerical modelling has increased our ability to consider internal components of these systems separately rather than combined into a single value.

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