## 1 Introduction  
In most aspects of deep surface and underground excavations, the focus of geological and geotechnical investigations is on understanding rock mass properties, including the mechanical properties of intact rock and discontinuities as well as the geometry and orientation of discontinuities. These conditions are evaluated according to the size of the excavation, its geometry, and available rock mass data. Individual components of rock mass classification systems define intact rock and discontinuity characteristics as well as the orientation of discontinuities relative to an excavation and fracture frequency. Special care is required to avoid sample bias, and in most cases, discontinuity (e.g., joint) lengths can be crudely estimated by observing the discontinuity trace lengths on surface exposures [1]. The parameters of the rock mass classification systems must reflect actual ground conditions and consider their effect on the stability of the proposed excavation. In this study, the mechanical response of the rock mass forms an essential part of understanding the behaviour of the granite host rock at a deep underground radioactive waste disposal site (Hungary). Similarly, understanding rock mass parameters is key to assessing the stability of deep rock slope excavations at a large open pit gold mine in Australia. Scale effects, anisotropy, and confining stresses influence the rock mechanical problems, especially in geomechanics simulations [2, 3]. Modelling requires geometric data regarding fracture size distribution, spatial density, and orientation. Afterwards, simulated models are available to understand features of the fractured rock body concerning hydrodynamic behaviour (e.g., connectivity, porosity, and permeability) [4] and mechanical behavior (i.e., shear strength of fractures, elastic parameters of rock mass). Rock masses can be described using standardized descriptors and quantitative parameters associated with those descriptors, as engineers feel more confident with numbers. In this context, rock mass classification systems represent an attempt to \"put numbers to geology\" [5]. Various rock mass classifications have appeared since the beginning of the 20 th century. Some of these include the classification system of [PERSON] [6], of [PERSON] [7], the RQD [8], the RSR [9], the RMR [10], Q-system [11], GSI [12], RMi [13], and some recent ones such as the Rock Mass Fabric Indices (F) [14] and the Rock Mass Quality Index [15]. At this point, it should be mentioned that RMR and the Q-system have been the most widely used methods ([PERSON] [16]; [PERSON] and [PERSON] [17]; [PERSON] et al. [18]). However, other classifications such as RMi and GSI have been attracting more interest in recent years. The Rock Mass Rating (RMR) classification system was developed by [PERSON] [10] in 1973, and after several modifications, the 1989 version is the most used in rock engineering practice [19]. This classification system has been refined over several years, and its characterization method has been revised from its creation onward. The last modification of this classification system was introduced in 2014 [20]. The Geological Strength Index (GSI) system is widely used for estimating the strength reduction from an intact rock to a rock mass, introduced by [PERSON] [12] in 1994. It is a unique rock mass classification system used as part of the Hoek-Brown failure criterion for estimating the strength and stiffness of a rock mass [21; 22]. Accurate estimation of the GSI is important for subsequent calculations [23; 24]. As in other rock mass classifications, all the GSI-based equations are highly sensitive to their respective input parameters [25]. Figure 1 presents a chart for estimating GSI for jointed rock masses in the field. For practical engineering application, the Hoek-Brown failure criterion should only be applied when the potential for structurally controlled failures has been eliminated, as it treats the rock mass as an isotropic material.