Abstract
In contrast to many disciplines, the approach to design in rock engineering remains largely inductive: observations, experience and engineering judgment are used to infer the behavior of a problem that cannot be constrained due to the nature of geological/geotechnical materials. Most of the rock mass classification systems used for rock engineering design purposes were developed in the 1960s and 1970s; since then no major updates have been proposed to reflect modern data collection tools and modelling procedures. Furthermore, engineers have attempted to apply existing classification systems in the context of a probabilistic design approach despite most of those systems being based on qualitative and semi-quantitative measurements. In this paper, we use a discrete fracture network (DFN) approach to introduce the first component of a new quantitative classification system that can capture rock mass scale, anisotropic effects; and better reflects the degree of connectivity of the natural fracture network. A new network connectivity index (NCI) is introduced that uses areal fracture intensity and density, and intersection density to provide a quantitative description of rock mass blockiness.
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Acknowledgements
The author would like to acknowledge the financial support through the Natural Sciences and Engineering Research Council of Canada (NSERC) grants hold by Dr. Davide Elmo.
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Elmo, D., Yang, B., Stead, D., Rogers, S. (2021). A Discrete Fracture Network Approach to Rock Mass Classification. In: Barla, M., Di Donna, A., Sterpi, D. (eds) Challenges and Innovations in Geomechanics. IACMAG 2021. Lecture Notes in Civil Engineering, vol 125. Springer, Cham. https://doi.org/10.1007/978-3-030-64514-4_92
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