Why Engineers Should Not Attempt to Quantify GSI

Abstract

In the past decade, there has been an increasing trend of digitalizing rock engineering processes. However, this process has not been accompanied by a critical analysis of the very same empirical methods that many complex numerical and digital methods are founded upon. As engineers, we are taught to use and trust numbers. Indeed, we would not be able to define the factor of the safety of a structure without numbers. However, what happens when those numbers are nothing but numerical descriptions of qualitative assessments? In this paper we present a critical review of the many attempts presented in the literature to quantify GSI (geological strength index). To the authors’ knowledge, this paper represents the first time that all the different GSI tables and quantification methods that have been proposed over the past two decades are collated and compared critically. In our critique, we argue against the paradigm whereby the quantification process adds the experience factor for inexperienced engineers. Furthermore, we discuss the limitations of the notion that GSI quantification methods could transform subjectivity into objectivity since the parameters under considerations are not quantitative measurements. Relying on empirically defined quantitative equivalences raises important questions, particularly when these quantitative equivalences are being used to define so-called accurate rock mass classification input for design purposes.

Differential Energy Criterion for Brittle Fracture: Conceptualization and Application to the Analysis of Axial and Lateral Deformation in Uniaxial Compression of Rocks

“…The stress-strain relationship for the ideal and real material shown in Figure 5 as a straight line and a curved line, respectively. The tangent to the curve in Figure 5 passes through point 1 for which condition (19) holds. The abscissa of point 1 can be calculated by Formula (20), then calculate the highest value of the modulus of elasticity (18).…”

“…Using (19), we obtain two values of ε = ε le f t and ε = ε right , for the left and right branches, respectively:…”

“…The points with abscissa ( 20) and (21) determine, as indicated above, the largest prepeak and smallest post-peak moduli (Table 3). Thus, the points for which condition (19) is satisfied can referred to characteristic points on the stress-strain curve. The practical value of these modules lies, for example, in their application in justification of strength and fracture criteria for brittle materials [22].…”

“…As the literature review has shown, the development of strength and fracture criteria that take into account the influence of all material defects requires further research, which is especially important for rocks because their physical and mechanical properties are very variable [ 17 , 18 ]. Given that, in general, all models are to some extent approximate [ 19 ], and their areas of effective application may not coincide, it is advisable to complement the many known approaches and models of brittle fracture in order to reduce gaps in this area and improve understanding of the behavior of rocks and similar materials for sustainable development. Given this circumstance and the relevance of the problem [ 20 , 21 ], it is relevant to note that, along with the EMC and FMC mentioned above, a third approach is possible, in which the values of both the elastic modulus and strain of the virtual material are equal to the corresponding values for the real material, as briefly discussed in [ 22 ].…”

Geological Strength Index Relationships with the Q-System and Q-Slope

“…However, Winn et al [34] established a new GSI relationship by replacing RQD/2 with RQD/3 in the calculation of GSI2013, which provided substantially higher GSI values that did not correspond to the qualitative field values. Yang and Elmo [36] argue against the quantification paradigm for GSI determination without taking into account the constraints of the idea that GSI quantification approaches may convert subjectivity into objectivity since the parameters under consideration are not quantitative measurements. Yang and Elmo [36] argue against the quantification paradigm for GSI determination without taking into account the constraints of the idea that GSI quantification approaches may convert subjectivity into objectivity since the parameters under consideration are not quantitative measurements.…”