Assessing TBM performance in heterogeneous rock masses

A major challenge that TBM performance is requested to deal with for a successful and effective progress is tunnelling through lithologically and geomechanically heterogeneous rock masses. Such heterogeneous environments are common and recent tunnel examples in the UK include the Hinckley Point C offshore cooling tunnels being driven through interbedded carbonaceous mudstone/shales and argillaceous limestone and the Anglo American’s Woodsmith Mine Mineral Transport System tunnel in Redcar Mudstone with beds of ironstone. This inherent geological heterogeneity leads to difficult tunnelling conditions that initially stem from predicting a sound and representative ground model that can be used to preliminary assess the TBM performance. In this work, an exhaustive review of existing TBM Penetration Rate (PR) methods identified that no models address the issue of parameter selection for heterogeneous rock masses comprising layers with different rock strengths. Consequently, new approaches are required for estimating rock mass behaviour and machine performance in such environments. In the presented work the Blue Lias Formation (BLI), which is characterised by its layered rock mass, comprising very strong limestone, interbedded with weak mudstone and shales, is investigated. BLI formation is considered herein being a representative example of lithological heterogeneity. Based on the fieldwork carried out in three localities in the Bristol Channel Basin (S. Wales and Somerset), geological models are produced based on which a geotechnical model is developed, and four ground types are determined. Implications of the current findings for TBM performance are assessed, including faulting, groundwater inflow and excavation stability with a particular focus on both PR and advance rate. A modified approach using the existing empirical models is proposed, developed and presented in this paper that can be used as a guide to determine TBM performance in heterogeneous rock masses reducing the risk of cost and time overruns.