The knowledge of rock masses behaviour is an important information in various fields such as civil engineering, land use planning and hazard/risk zoning. Different rock mass classification methods, initially aimed at assisting underground excavations (Hoek, 2007), are widely used nowadays for preliminary design procedures (Bieniawski, 1989; Hoek, 2007), like the RMR (Bieniawski, 1976) and the Q (Barton et al., 1974) and their modifications. These methods incorporate geological, geomechanical and geometric parameters in order to obtain a quantitative estimation of the rock mass quality, but, on the other hand, their implementation is time-consuming. Despite the dominance of these two methods, further rock mass classifications systems have been proposed in the last decades and, among these, the Geological Strength Index (GSI) classification system is currently widely used as it allows to estimate the strength of rock mass through empirical semiquantitative evaluation (Hoek, 1994; Cai et al., 2004), based on both rock mass structure and condition of the joints (Hoek et al., 1995). Estimating the GSI is straightforward and fast, but it comes at the cost of a certain degree of subjectivity. Moreover, the index does not adequately account for the lithology of the rock mass matrix. Hence, for the above reasons, these classification methods are not fully suitable to collect rock mass data over wide scale areas for engineering geological mapping. The Rock mass Quality Index (RQI, Disperati et al., 2016; Mammoliti et al., 2018) is a rock mass classification system developed for cartographic purposes and it is based on the systematic fieldwork measurement and processing of sets of the Schmidt hammer rebound values (R). Each representative rock mass outcrop is analysed by collecting ca. 20 R values at the 15-25 nodes of a regular grid conceived to investigate the typical features of the rock mass. This allows to perform statistical analyses and to calculate the RQI, a quantitative indicator of the global strength and quality of the rock mass. In the last decade, a dataset of ca 1100 outcrops sites spreading over a large area (ca. 12000 km2) were acquired in Tuscany (Italy), according to different lithology, weathering, jointing conditions. The dataset consists of both RQI measurements and GSI estimations for the main different lithological groups (flysch, limestones, marls, magmatic rocks and schists) of the Northern Apennines (Italy), as well as the laboratory determinations of the Slake Durability Index (Id2; Franklin & Chandra, 1974) obtained by testing representative outcrop rock samples. The large dataset has allowed to analyse the correlation among RQI, GSI and Id2 and to perform an in-depth critical analysis of the relationships among RQI, lithology, rock mass structure, as well as the suitability of the RQI as reference index for engineering geological mapping of near-surface rock mass quality.

D'Addario, E., Disperati, L., Lombardi, G., Marzini, L. (2022). The Rock Mass Quality Index (RQI): a quantitative tool for the quality evaluation of near-surface rock masses. In EGU General Assembly 2022. Gottingen : Copernicus GmbH [10.5194/egusphere-egu22-7779].

The Rock Mass Quality Index (RQI): a quantitative tool for the quality evaluation of near-surface rock masses

D'Addario, Enrico
;
Disperati, Leonardo;Marzini, Lorenzo
2022

Abstract

The knowledge of rock masses behaviour is an important information in various fields such as civil engineering, land use planning and hazard/risk zoning. Different rock mass classification methods, initially aimed at assisting underground excavations (Hoek, 2007), are widely used nowadays for preliminary design procedures (Bieniawski, 1989; Hoek, 2007), like the RMR (Bieniawski, 1976) and the Q (Barton et al., 1974) and their modifications. These methods incorporate geological, geomechanical and geometric parameters in order to obtain a quantitative estimation of the rock mass quality, but, on the other hand, their implementation is time-consuming. Despite the dominance of these two methods, further rock mass classifications systems have been proposed in the last decades and, among these, the Geological Strength Index (GSI) classification system is currently widely used as it allows to estimate the strength of rock mass through empirical semiquantitative evaluation (Hoek, 1994; Cai et al., 2004), based on both rock mass structure and condition of the joints (Hoek et al., 1995). Estimating the GSI is straightforward and fast, but it comes at the cost of a certain degree of subjectivity. Moreover, the index does not adequately account for the lithology of the rock mass matrix. Hence, for the above reasons, these classification methods are not fully suitable to collect rock mass data over wide scale areas for engineering geological mapping. The Rock mass Quality Index (RQI, Disperati et al., 2016; Mammoliti et al., 2018) is a rock mass classification system developed for cartographic purposes and it is based on the systematic fieldwork measurement and processing of sets of the Schmidt hammer rebound values (R). Each representative rock mass outcrop is analysed by collecting ca. 20 R values at the 15-25 nodes of a regular grid conceived to investigate the typical features of the rock mass. This allows to perform statistical analyses and to calculate the RQI, a quantitative indicator of the global strength and quality of the rock mass. In the last decade, a dataset of ca 1100 outcrops sites spreading over a large area (ca. 12000 km2) were acquired in Tuscany (Italy), according to different lithology, weathering, jointing conditions. The dataset consists of both RQI measurements and GSI estimations for the main different lithological groups (flysch, limestones, marls, magmatic rocks and schists) of the Northern Apennines (Italy), as well as the laboratory determinations of the Slake Durability Index (Id2; Franklin & Chandra, 1974) obtained by testing representative outcrop rock samples. The large dataset has allowed to analyse the correlation among RQI, GSI and Id2 and to perform an in-depth critical analysis of the relationships among RQI, lithology, rock mass structure, as well as the suitability of the RQI as reference index for engineering geological mapping of near-surface rock mass quality.
D'Addario, E., Disperati, L., Lombardi, G., Marzini, L. (2022). The Rock Mass Quality Index (RQI): a quantitative tool for the quality evaluation of near-surface rock masses. In EGU General Assembly 2022. Gottingen : Copernicus GmbH [10.5194/egusphere-egu22-7779].
File in questo prodotto:
File Dimensione Formato  
EGU22-7779-print.pdf

accesso aperto

Tipologia: PDF editoriale
Licenza: Creative commons
Dimensione 291.77 kB
Formato Adobe PDF
291.77 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11365/1214954