4.7 Article

Performance prediction of hard rock TBM using Rock Mass Rating (RMR) system

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TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
卷 25, 期 4, 页码 333-345

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tust.2010.01.008

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TBM performance; Field Penetration Index (FPI); Rock Mass Rating (RMR) classification system

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RMR is a simple rock mass classification system and is often used for characterization and design purposes in preliminary stages of mining and civil engineering practices. However, the use of RMR in providing a precise predictive model of TBM field penetration index (FPI) is very limited due to the nature of the ratings (weights) assigned to the input parameters and their influence on the FPI. This limitation can be mitigated by using multivariate linear, non-linear and polynomial regression analyses of RMR input parameters. This approach was examined in mostly medium to hard sedimentary rocks in Zagros long tunnel in Western Iran. For this purpose, groundwater condition, because of its poor correlation with FPI, was excluded from determination of RMR and the subsequent analyses. Meanwhile, the angle between tunnel axis and discontinuity planes was included in the model as a substitution of the adjustment factor for discontinuity orientation in RMR. Comparison of measured FPIs with those predicted by the multi-linear, logarithmic and polynomial regression models showed good agreement with correlation coefficients of 0.87, 0.87 and 0.86, respectively. This highlights the potential of multivariate model of rock mass classifications in TBM performance prediction. However, the relationships obtained in this analysis should be considered valid only for geological settings similar to those of Zagros tunnel and more in depth study is required to extend the finding of this study to develop a universal model. This paper discusses previous works in this area, reviews the available data from Zagros tunnel project, methodology for analysis, and introduces a convenient empirical predictive model for TBM performance by using Rock Mass Rating (RMR) system. (C) 2010 Elsevier Ltd. All rights reserved.

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