Although rock-mass rating (RMR) and tunneling quality index (Q) systems are used in different rock engineering projects as empirical design tools, their application in tunnel design is widely accepted as these systems were developed and updated for this purpose specifically. This paper reviews the work conducted by various researchers since the development of these two systems with respect to tunneling only. Compared to other empirical classification systems, these systems received international acceptance and are still used as empirical design tools in tunneling due to their continuous updates in the form of characterization and support. As the primary output of these systems is the initial support design for tunnel, however, their use in the calculation for rock-mass properties is an essential contribution of these systems in rock engineering design. Essential for the tunnel design, these rock-mass properties include the modulus of deformation, strength, Poisson’s ratio, Mohr-Coulomb parameters and Hoek-Brown constants. Other application for tunneling include the stand-up time and rock load. The uses and limitations of these systems as empirical tunnel design tools are also included in this review article for better results. Research to date indicates that if the ground behavior is also taken into account, the application of these empirical systems will be more beneficial to the preliminary design of tunnels.

Uniaxial compressive strength (UCS) and the static Young’s modulus (E_s) are fundamental parameters for the effective design of engineering structures in a rock mass environment. Determining these two parameters in the laboratory is time-consuming and costly, and the results may be inappropriate if the testing process is not properly executed. Therefore, most researchers prefer alternative methods to estimate these two parameters. This work evaluates the thermal effect on the physical, chemical, and mechanical properties of marble rock, and proposes a prediction model for UCS and E_S using multi-linear regression (MLR), artificial neural networks (ANNs), random forest (RF), and k-nearest neighbor. The temperature (T), P-wave velocity (P_V), porosity (η), density (ρ), and dynamic Young’s modulus (E_d) were taken as input variables for the development of predictive models based on MLR, ANN, RF, and KNN. Moreover, the performance of the developed models was evaluated using the coefficient of determination (R²) and mean square error (MSE). The thermal effect results unveiled that, with increasing temperature, the UCS, E_S, P_V, and density decrease while the porosity increases. Furthermore, ES and UCS prediction models have an R² of 0.81 and 0.90 for MLR, respectively, and 0.85 and 0.95 for ANNs, respectively, while KNN and RF have given the R² value of 0.94 and 0.97 for both E_S and UCS. It is observed from the statistical analysis that P-waves and temperature show a strong correlation under the thermal effect in the prediction model of UCS and E_S. Based on predictive performance, the RF model is proposed as the best model for predicting UCS and E_S under thermal conditions.

Rockburst is a hazardous phenomenon in deep tunnels influenced by geological structural planes like faults, joints, and shear planes. Small-scale shear-plane-like structures have damaging impact on the boundaries of the tunnel, which act as barrier and accumulate high stresses. A shear plane combined with high stress conditions is very dangerous in deep excavations. Such a shear plane exposed in the side wall of the right headrace tunnel in the Neelum-Jehlum Hydropower Project. This project is constructed in the tectonically active Himalayas under high stress conditions. The influence of a shear zone on rockburst occurrence near the tunnel is studied. The FLAC^3D explicit code simulated the shear zone in the right tunnel, revealing that the stresses are concentrated near the shear zone, while no such stress concentration is present in the left tunnel. The Rock mass got displaced near this shear zone. Modeling results confirm that the presence of shear zone in side wall of the right tunnel has a major influence on rockburst occurrence. A shear slip along this plane released huge amounts of accumulated energy, causing human fatalities and property damage. A comparison of numerical simulation with empirical rockburst criteria validates the actual conditions and help us to understand the phenomenon of stress concentration near the shear zone and its impact during deep tunneling.

The primary output of the rock mass rating (RMR) and tunneling quality index (Q) system is a preliminary tunnel support design, as these methods are empirically developed and updated for this purpose. In this study, these internationally accepted design tools are evaluated to improve results for tunnel support design. The rating system is simplified and improved for some parameters through the use of equations to replace the discrete/lump characterization with a continuous rating. Recent developments in characterization and support are used in proposing the back analysis approach of rock mass quality calculation from tunnel span and installed support. This approach is used for two tunnel projects which experience high stresses. Approximately 90% of the tunnel sections show that actual supports have rock bolt spacing and shotcrete thickness which are heavier than those indicated by RMR₈₉, indicating a system limitation. Another assessment using RMR₁₄ indicates that its rating is higher than that of RMR₈₉. A strong correlation exists between them, as supported by the literature and data from analyses of 462 tunnel sections. Despite its new version, RMR₈₉ still preserves its importance. Evaluating the different correlations between RMR and Q through published data indicates that the rock mass fabric index gives comparatively better results.

Rockburst is an unstable failure of a rock mass which is influenced by many factors. During deep excavations, the presence of nearby geological structures such as minor faults, joints, and shear zones increases the likelihood of rockburst occurrence. A shear zone has been observed in the headrace tunnel in the Neelum Jhelum Hydropower Project, Pakistan, which has played an important role in major rockburst events in the project’s history. A rockburst is a seismic event that involves the release of a great amount of energy as the dynamic wave radiated from the seismic source reaches the excavation boundary. In this paper, the FLAC 2D explicit numerical code has been used to simulate the dynamic phenomenon of rockburst near the shear zone in a headrace tunnel. The behavior of the rock mass around the tunnel has been studied under both static and dynamic loading. According to modeling results, rockburst significantly affected the upper left quadrant of the tunnel similar to the actual failure profile with a depth of approximately 5 m. The dynamic impact of rockburst has also affected the loading conditions of the support system in the adjacent tunnel. This study elucidates one of the most important rockburst controlling factors through numerical analysis and recommends yielding support measures that can withstand the dynamic impacts of rockburst in deep, hard rock tunnels.

Empirical classification systems do not provide details of the factors that affect the performance of fully grouted rock bolts, as they are based on average values. Fully grouted rock-bolt patterns during tunnel-support design are a part of the composite support, and they are functions of rock-mass quality and tunnel span. Various fully grouted rock bolts are used in situ in different environments, along with other tunnel-support materials in static and dynamic environments during tunnel construction. The rock-bolt performances are evaluated through pull-out tests that follow ASTM standards. Several field pull-out tests were conducted on cement and resin grouted rock bolts. Under groundwater flow conditions, inflated steel tube rock bolts were tested and the results were compared with fully grouted rock bolts. Based on field experiments and previous studies, the factors that affect rock bolt performances are divided into five groups with respective sub-factors. Natural parameters cannot be controlled to ensure safety, economy, and stability in tunnels. The controllable factors, too, can be varied only within a practical range. In conclusion, the factors investigated here should be considered with the empirical support pattern of rock-mass classification systems for safe and economical design.