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Explorative tunnels are one of the best ways to assess the rock quality in the preliminary stage of a long tunnel excavation project: this strategy allows predictions for evaluating, with good accuracy, methods, costs, and technical problems related to the excavation of the main tunnel. The paper presents the first results of a study carried out on a 6.3 m diameter exploratory tunnel excavated in hard rock by TBM. A study of the data taken during the TBM's advancement is ongoing. The evaluation of the rock cutting efficiency, through the excavation specific energy (SE) is performed. A method for the evaluation of the grain size distribution of the muck produced during the excavation is proposed. The development of Matlab code to automatically analyze the machine acquired data in relation with the rock mass characteristics is reported in the paper.

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The intermediate linear cutting machine (ILCM) is a machine designed to work on an intermediate scale between the full- and the small-scale. The reduced scale involves several advantages compared to full-scale tests, especially in terms of sample supplying and transportation. On the other hand, it has an impact on the testing conditions, resulting in a limitation of the cutting penetration and spacing during the test, as well as in a smaller disc cutter. This affects most of the results, which cannot be directly used for the on-site machine performance prediction. However, some experimental results provided in the literature show that the optimal spacing/penetration ratio is not significantly affected by the changes involved. On this basis, the results obtained from ILCM tests should provide reliable information about the optimal cutting conditions of a tunnel boring machine in massive rock mass. The work performed included the development of some improvements of the testing rig, as well as a modified ILCM testing procedure, according to the one typically used in standard LCM tests. The results provide information about the attitude of the tested lithotypes to mechanical excavation by means of disc tools, including the optimal cutting conditions. Additional work was developed in terms of detailed characterisation of the rock samples involved and assessment of the size distribution of the debris produced during the ILCM tests. Nevertheless, further tests are necessary, in order to assess the consistency of the experimental procedure employed and to investigate the scale effect.

Tunnel boring machine (TBM) performance prediction is often a critical issue in the early stage of a tunnelling project, mainly due to the unpredictable nature of some important factors affecting the machine performance. In this regard, deterministic approaches are normally employed, providing results in terms of average values expected for the TBM performance. Stochastic approaches would offer improvement over deterministic methods, taking into account the parameter variability; however, their use is limited, since the level of information required is often not available. In this study, the data provided by the excavation of the Maddalena exploratory tunnel were used to predict the net and overall TBM performance for a 2.96 km section of the Mont Cenis base tunnel by using a stochastic approach. The preliminary design of the TBM cutterhead was carried out. A prediction model based on field penetration index, machine operating level and utilization factor was adopted. The variability of the parameters involved was analysed. A procedure to take into account the correlation between the input variables was described. The probability of occurrence of the outcomes was evaluated, and the total excavation time expected for the tunnel section analysed was calculated. Keywords Hard rock TBM performance prediction • Stochastic approach • Field penetration index • Monte Carlo method • TBM cutterhead design • Mont Cenis base tunnel Abbreviations MCBT gripper Section of the Mont Cenis base tunnel between pk 48 + 68 and pk 51 + 64 MET par Section of the Maddalena exploratory tunnel parallel to the axis of MCBT gripper * Marilena Cardu

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