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A Discrete Fracture Network Approach to Rock Mass Classification
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.
A Discrete Fracture Network Approach to Rock Mass Classification
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.
A Discrete Fracture Network Approach to Rock Mass Classification
Lecture Notes in Civil Engineering
Barla, Marco (Herausgeber:in) / Di Donna, Alice (Herausgeber:in) / Sterpi, Donatella (Herausgeber:in) / Elmo, Davide (Autor:in) / Yang, B. (Autor:in) / Stead, Dean (Autor:in) / Rogers, S. (Autor:in)
International Conference of the International Association for Computer Methods and Advances in Geomechanics ; 2021 ; Turin, Italy
15.01.2021
8 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
A Discrete Fracture Network Approach to Rock Mass Classification
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