Abstract

The use of TBMs in the tunnel industry has undergone a continuous growth over the last years, with application in ever expanding ranges of geotechnical conditions. Nevertheless, the feedback from completed projects with respect to the use of machine data for assessing geotechnical conditions are not common: there are only a few attempts to correlate machine data with geotechnical conditions during excavation and in most cases the use of machine data is related to assessment of TBM performance for prediction of advance rate. The analysis of TBM parameters may represent an interesting tool for monitoring of geotechnical conditions at the tunnel face and early detection of adverse face conditions. This work presents the feedback from the Tunnel 4, a 6.4 km long water transfer tunnel excavated by double shield TBM in the Philippines. The machine data have been analysed for identification of most sensitive parameters to geomechanical properties of the rock mass. In this respect, the use of specific-excavation parameters provides best results for assessing geotechnical conditions during excavation. Specific energy and Field Penetration Index displayed a good correlation with RMR values. The combined use of Net Advance Rate and Drillability Index allows to highlight how unstable face conditions and / or tough rock can influence the TBM advance.

Introduction

The use of Tunnel Boring Machines (TBMs) in the tunnel industry has undergone a continuous growth over the last years and improvements in technical features (e.g. cutter-head size, value of machine torque and thrust) allowed the use of TBMs in always wider range of geological and geotechnical context. Despite of such increase in the application of TBM, there is a poor feedback from completed projects with respect to the use of machine data for assessing geological and geotechnical conditions at the tunnel face, namely in the frame of hard rock excavation. In most of cases, the analysis of machine data is related to assessment of TBM performance, i.e. as a tool for prediction of advance rate. As a matter of fact, TBM is not a flexible method of excavation and a reliable assessment of geotechnical conditions along the tunnel alignment is a key-aspect for successful application of mechanized excavation. The choice whether using a TBM or not is therefore crucial in terms of project planning and cost estimation and this choice is often based on the expected TBM’s rate of advance. In this respect, the most recognized TBM performance prediction models correspond to the CSM (Colorado School of Mines) model (e.g. [1-2]) and to the NTNU (Norwegian University of Science and Technology) model (e.g. [3-4]) and adjustments factors for these two models are continuously suggested (see e.g. review in [5]). On the other hand, there are only a few feedbacks from completed TBM projects about correlation between machine data and encountered geotechnical conditions. Bieniawski et al. [6] suggested the use of specific energy of excavation for detecting changes in tunnelling ground conditions, based on the good correlation between this parameter and the Rock Mass Rating (RMR). Alber [7] indicates a good relationship between specific penetration and rock mass conditions such as uniaxial compressive strength (UCS) and spacing of discontinuities. Hassanpour et al. [5] highlight the correlation between some rock mass parameters (RQD, UCS) and the Field Penetration Index.

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