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The modified rock mass classification system for TBM tunnels and tunneling was proposed to assess rock mass quality, rock mass boreability, and TBM construction suitability. However, the section concerning the impact of adverse geological conditions on TBM utilization was not yet finalized. In this study, the classification system was upgraded to the stressed hard rock tunnels by adding the coefficient. A database comprising 551 instances of rockbursts and their corresponding TBM performance data was compiled from the Yinhan Water Conveyance Tunnel in China. The characteristics of rockbursts occurring in the tunnel excavated by TBM and their formation mechanisms were introduced. The depth of damage to the tunnel wall was used as the assessment index for the intensity grade of rockbursts. Quantitative relationships were established between the intensity grade of rockbursts and TBM performance parameters for the first time. As the intensity grade of rockbursts increased, there was a substantial reduction in TBM utilization, while the penetration rate exhibited no significant changes. The reduction coefficient β A for TBM utilization at the rockburst intensity grades, namely minor damage, moderate damage, and severe damage, was determined to be 0.88, 0.60, and 0.39 respectively. These coefficients were subsequently integrated into the classification system. Finally, a simple case was presented to illustrate the applicability of the rockburst reduction coefficient β A and the upgraded system. • The database was established with different grades of rockburst data. • Rockburst impact on rock mass boreability, stability, and TBM process was analyzed. • The quantitative relationships between rockburst and TBM parameters were obtained. • The rockburst reduction coefficient β A on TBM utilization was determined. [ABSTRACT FROM AUTHOR]

The Rock Quality Designation (RQD) index is defined as the percentage of the borehole core or scanline that consists of intact lengths ≥0.1 m, and has been widely used as an engineering measure of the jointing degree of a rock mass. The directivity of RQD, which means the value of the RQD obtained from drilling cores or scanlines with different orientations can be different for a given site, is usually regarded as a drawback by researchers and engineers. This study presents a new perspective for the directivity of RQD: the directivity of RQD should be regarded as an advantage of the index because it essentially reflects the anisotropy of rock masses. Because a smaller value of the RQD index implies a better reproduction of the different jointing degrees of different rock masses, its minimum value is selected as the representative RQD (RQD r ), and its corresponding direction is called as the representative direction of RQD. In this study, to obtain the RQD r and its representative direction, theoretical formulas are derived to calculate the RQD in any direction based on some known RQDs in different directions. The proposed formulas consider the variance of the discontinuity orientations and sizes for a discontinuity set, use the traditional concept of RQD, and possess the associated simplicity; they only require sampling a few additional discontinuity orientations. Therefore, the proposed approach is easy to understand and apply in engineering practices. An anisotropy index of jointing degree ( AI jd ) is defined to quantitatively describe the anisotropy of jointing degree for rock masses. The range of AI jd is from 0 to 100, and the larger value of AI jd reflects stronger anisotropy of jointing degree of a rock mass. In this study, a hypothetical three-dimensional discontinuity network is constructed by performing Monte Carlo simulations, based on which the generated data are analyzed to validate the proposed method. The comparison between the calculated and actual values of the RQD shows that (a) the difference between the calculated and actual values of the RQD is <4 for >86.0% of the 1368 scanlines examined with respect to 12 scanline groups, except SG4–1 group, for which the proportion is 66.2%; (b) the difference between the calculated and actual values of the RQD is <6 for >96.2% of the 1368 scanlines examined with respect to 12 scanline groups, except SG4–1, for which the proportion is 86.7%; and (c) the proposed method of calculating the RQD in any direction based on some known RQDs in different directions is satisfactory. In addition, the comparisons show that the calculated RQD r and representative direction exhibit a good agreement with the actual results, and hence, the proposed method for this purpose is satisfactory. Moreover, an actual rock mass of a slope around the Qingshan Lake National Forest Park in China is investigated, and the results show that the proposed method is valid for that rock mass. [ABSTRACT FROM AUTHOR]

The aim of this study is to provide a sound support design for a large-scale underground water-sealed oil storage facility in China. The lithology of this study area consists of reddish-gray, medium-coarse grained granites interpenetrated by diabase, amphibole dioritic porphyrite and aplite. In order to obtain the geotechnical properties of intact rocks and rock masses, detailed field and laboratory studies were carried out. Rock masses at three sites were characterized in terms of Rock Mass Rating (RMR), Rock Mass Quality ( Q -system) and Geological Strength Index (GSI), and then rock mass properties of underground caverns were estimated, accordingly. The support systems obtained from empirical methods were analyzed using FLAC3D commercial software considering the effect of the water curtain system. The maximum thickness of plastic zones and the maximum total displacement occurred around underground caverns after installing the support systems suggested by the empirical methods were compared to the unsupported case. The results show that more reliable support design could be obtained by using both empirical rock mass classifications and numerical analysis method. [ABSTRACT FROM AUTHOR]

• Simple estimating equations of TBM penetration rate were set up. • A comprehensive database including 115 sets of data was compiled. • The independent variables were derived from rock mass classification parameters. Establishing a suitable TBM performance prediction model is benefit to the machine type selection, project scheduling and budgeting. Some regression equations using rock mass classification parameters had already been set up based on TBM tunneling database, some of which were small. Besides, most of existing equations involved field penetration index (FPI) or the cutter force. Once apply these equations, how to determine the cutter load is a problem. The cutter thrust force is affected by various factors, the most important of which is the ground conditions. To make a straightforward estimation of penetration rate at planning phase, some simple regression equations merely using rock mass classification parameters were set up based on 115 tunnel sections sourced from three TBM job sites. TBM penetration rate (mm/rev) was employed as the prediction result. It is a comprehensive value including the rock mass condition and the experiences of TBM operators in the projects used for this study, since TBM operators would adjust the thrust force with the changing rock masses to get an acceptable penetration rate on site. The datasets in the database indicated the intrinsic relationship among the rock mass condition, the needed thrust force and the obtained penetration rate. Five rock mass classification systems including RMR, Q, GSI, HC and BQ were covered, the latter two are widely used in China. The input rock mass classification parameters were categorized into three types, which respectively are final ratings, estimated rock mass properties, and partial ratings or corresponding original values. Generally, the multivariate equations using partial ratings have the best correlation with TBM penetration rate. The strength of intact rock, integrity of rock mass and joint condition are proved to be the most critical factors in the estimation of TBM penetration rate. The established equations reflect the statistical relationship between the rock mass and penetration rate with the requisite of the normal TBM tunneling data in various rock masses, and can be easily applied in the planning phase of a TBM tunneling project. [ABSTRACT FROM AUTHOR]

• A modified Bayesian sequential updating approach is proposed to estimate GSI. • Multi-source information can be integrated in the approach. • GSI can be estimated using limited data based on various rock mass classifications. • Evaluated probabilistic characteristics of the GSI agree with the observed GSI data. • Rational result is achieved by taking model uncertainties as random normal variables. Explicit determination of geotechnical parameters is an important but difficult task in rock engineering. Paradoxically, data are often limited even though data from multiple sources (e.g., different testing procedures, testing positions, and estimation models) are commonly available, and the integration of multi-source information for the determination of geotechnical parameters in a probabilistic context remains a great challenge. We have modified an existing Bayesian sequential updating approach and used it for the first time to estimate the geological strength index (GSI) of rock masses by integrating multi-source information in a way that considers prior information, multiple estimation models and probabilistic properties of model uncertainties. The argillaceous siltstone in Zigui County in the Three Gorges Reservoir region of China was used to quantitatively illustrate this method. Three data sets using rock mass rating (RMR)-, tunneling quality index (Q)-, and rock mass index (RMi)-based estimation models were sequentially incorporated into the Bayesian sequential updating framework, through which the information on the mean value and standard deviation of the GSI can be updated. Then a large number of equivalent GSI samples were generated through Markov chain Monte Carlo (MCMC) simulation for further statistical analysis. The results showed that the proposed Bayesian sequential updating approach can provide reasonable probabilistic estimates of the GSI, which compared well with observed data using the standard GSI chart. The Bayesian sequential updating approach is a promising tool for geotechnical parameter estimation and can combine large amounts of information, thereby effectively depicting the probabilistic characteristics of GSI. [ABSTRACT FROM AUTHOR]