Probabilistic Analysis of TBM Advance Rate Prediction Models

The overall purpose of this study is to use probabilistic methods for the estimation of the advanced rate of full-face tunnel boring machines. To collect appropriate input parameters, Monte Carlo Simulation was utilized. Then, the calculation phase was conducted applying established models on input data and probability density functions of output data were obtained. The results show that the average advance rates calculated by QTBM and CSM models were closer to the average value of the actual advance rates. In addition, using probabilistic methods in combination with TBM prediction models helps to estimate the range of advance rates more confidently.