Prediction of TBM penetration rate from brittleness indexes using multiple regression analysis

Abstract

One of the most important aspects in the excavation of tunnels with a Tunnel Boring Machine (TBM) is the reliable prediction of its penetration rate. This affects the planning and other decision making on the organization of the construction site of the tunneling project, and, therefore, total costs. In this study, raw data obtained from the experimental works of different researchers were used to establish the new statistical models for prediction of rock TBM penetration rate from brittleness indexes, B1, B2, and B3. For this, correlation between the TBM penetration rate with brittleness indexes statistically was investigated using multiple regression analyses. In these analyses, the TBM penetration rate was considered to be the dependent variable, which is dependent on the independent variables of the brittleness indexes. The validity of the predictive models was validated by statistical tests. The results showed that statistical models are in good accuracy for prediction of TBM penetration rate, and thus making a rapid assessment of the TBM performance.