Rock mass redefined: integrating discrete fracture network models and rock mass classification systems

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In 1963 Karl Terzaghi, the father of modern geotechnical engineering, wrote “we are overstepping the limits of our ability to predict the consequences of our actions”. 55 years later, rock engineering design still depends on empirical methods, whereby observations are used to reach conclusions and generate theories. What makes rock engineering design challenging is the presence of physical discontinuities in the form of joints, bedding planes, and faults, which may affect the stability of slopes, underground excavations, and dam foundations. Several classification systems exist to quantify the quality of the rock mass and account for the effects of those discontinuities. However, most of those classification systems were developed in the 1960s-1970s, at a time when the scale of rock engineering projects was much limited. As large open pit operations are approaching their economic limits and mines are being developed deeper underground, a new approach to design is required that is not limited by a subjective interpretation of empirical tables and qualitative assessments of rock mass properties. We believe our research can contribute to reduce the degree of occurrence of “unforeseeable” events, by providing a better understanding of geological variability and the relationship between rock mass behaviour and intensity/nature of the discontinuities. Integrating conventional discontinuities mapping with new long-range remote sensing techniques for resource geotechnics and natural hazard investigations, discrete fracture network (DFN) methods have increasingly become an effective tool to assist with rock engineering design. Coupled with advanced numerical analyses, DFN-based rock engineering can support more efficient mine design and improve operational safety. My research group has introduced a new method that analyse the properties of DFN models, and provides a measure of the network connectivity, which is the key element for implementing a DFN-based approach to rock mass classification and design. Several geotechnical consulting companies in Canada are now using DFN methods for rock engineering design. In this application, we propose a research program to advance and update rock mass classification systems, removing qualitative measurements, and focusing on the use of new technologies to map key geological parameters that are more appropriate for statistical analysis (e.g. fracture frequency and blocks volumes). This is a key requirement if we want rock engineering to evolve and to support modern design frameworks such as the analysis of probability of failure and risk assessment. To meet these objectives, the proposal will seek funding for 5 Highly Qualified Personnel (HQP). The research will have a significant impact with respect to improving the design of engineered slopes and underground excavations, and increasing the use of DFN tools and probability methods in rock engineering design.