A Comparative Study of TBM Penetration Rate Assessment Based on the Rock Mass Properties

In tunneling with TBMs, a reliable assessment of the TBM rate of penetration (RoP) is needed for planning, cost control or other decision making purposes. An incorrect estimate of the RoP could delay the project and induce unplanned costs, making the project less profitable. Thus, extensive studies with the aim of estimating TBM's performance have been conducted in the last three decades. As a result, several empirical equations and models have been developed for different tunneling situations. The purpose of this study is to propose empirical models capable of assessing the RoP of TBM and to critically compare them. Two approaches were investigated on the basis of the rock mass parameters including the uniaxial compressive strength (UCS), intact rock brittleness (BI) alpha angle (a) the distance between planes of weakness (DPW). Datasets from the Queens Water Tunnel No. 3 project, New York City, were compiled and used to establish the models. On one hand, four (4) candidate models were proposed and the Bayesian inference approach was implemented to identify the most suitable among the candidates. The models were computed in WinBUGS software which employs the Bayesian analysis of complex statistical models. Next the models were ranked on the basis of the deviance information criterion (DIC) values taking into account both their fit and complexity. On the other hand, Multi-Layer Perceptron network a well-known approach used in rock engineering to map complex correlation between dependent and independent variables, was employed to predict the RoP. Both methods were validated and compared. The overall results were in good agreement with the field observations. In addition, the Bayesian-based models showed more flexibility in terms of probabilistic interpretation of the results.