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Home Publications Journals Specific Energy of TBM's, Rock Mechanics & Rock Engineering, 41: 797–834, 2008

Specific Energy of TBM's, Rock Mechanics & Rock Engineering, 41: 797–834, 2008

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A spatial estimation model for continuous rock mass characterization from the specific energy of a TBM

G. Exadaktylos1, M. Stavropoulou2, G. Xiroudakis1, M. de Broissia3 and H. Schwarz4

1 Department of Mineral Resources Engineering, Technical University of Crete,

Chania, Greece, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

2 Department of Dynamic, Tectonic and Applied Geology, Faculty of Geology,

University of Athens, Greece, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

3Challenger – BOUYGUES TP1, avenue Eugène Freyssinet – Guyancourt,

F-78061 Saint-Quentin-en-Yvelines cedex, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

4GISA Gestió d´Infraestructures, S. A. ISA,   This e-mail address is being protected from spambots. You need JavaScript enabled to view it

 

 

Summary

 

Basic principles of the theory of rock cutting with rolling disc cutters are used to appropriately reduce Tunnel Boring Machine (TBM) logged data and compute the Specific Energy (SE) of rock cutting as a function of geometry of the cutterhead and operational parameters. A computational code written in Fortran 77 is used to perform Kriging predictions in a regular or irregular grid in 1D, 2D or 3D space based on sampled data referring to rock mass classification indices or TBM related parameters. This code is used here for three purposes, namely: (1) to filter raw data in order to establish a good correlation between SE and Rock Mass Rating (RMR) (or tunnelling quality index Q) along the chainage of the tunnel, (2) to make prediction of RMR, Q or SE along the chainage of the tunnel from boreholes at the exploration phase and design stage of the tunnel, and (3) to make predictions of SE and RMR or Q ahead of the tunnel’s face during excavation of the tunnel based on SE estimations during excavation. The above tools are the basic constituents of an algorithm to continuously update the geotechnical model of the rock mass based on logged TBM data. Several  cases were considered to illustrate the proposed methodology, namely: (a) data from a system of twin tunnels in Hong Kong, (b) data from three tunnels excavated in Northern Italy, and (c) data from the section Singuerlin-Esglesias of the Metro L9 tunnel in Barcelona.

 

Keywords: Rock cutting, Geostatistics, Kriging, TBM, RMR, Q, Specific Energy