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Hard rock tunnel boring machines (TBMs) are increasingly widely used in tunnel construction today; however, TBMs are deeply buried underground and have a low perception of the underground surrounding rock conditions and excavation parameters. In order to ensure the safety of TBM digging, this paper describes the research carried out relating to the accurate prediction of TBM digging parameters and the precise prediction of tunnel surrounding rock grades. Based on the on-site excavation parameters and geological data of a certain water diversion project in Xinjiang, the thrust, torque, rotational speed, net excavation speed, construction speed, and excavation specific energy of the stable section of TBM excavation are selected as the input parameters for the model. A convolutional neural network optimized–long short-term time series prediction model (CNN-LSTM model) is established to predict the excavation parameters under various levels of surrounding rock conditions. The research results indicate that the CNN-LSTM model has a high prediction accuracy, with most data having a relative prediction error rate (Er) within 10%, root mean square error (RMSE) within 5%, mean absolute percentage error (MAPE) within 10%, and goodness of fit (R2) above 0.9. The model can assist in parameter setting, engineering planning and disposal of high-risk holes in the TBM digging process, and improve the safety level of TBM digging.

Evaluating critical face pressure with high accuracy is an important topic for shield tunneling. The existing research focuses more on the influence of complex geological conditions or environmental factors, and there are few reports on the influence of tunnel shape on critical face pressure. In reality, the tunnel shape has a significant impact on the deformation zone in front of the tunnel face, which may lead to non-negligible differences in shield pressure. To fill this gap, an efficient analytical approach is proposed to estimate the critical face pressure considering different tunnel shapes in the framework of limit analysis. As earthquakes are potential threats to the tunnel face stability in seismically active regions, the seismic effect is also taken into account with the help of the pseudo-static method. Several cases with the same area but different tunnel shapes are investigated using the limit analysis method. A comparison with static analysis is given to highlight the influence of seismic forces on the tunnel face stability. The results show that the critical face pressures increase by 15.3% when the tunnel face shape changes from rectangular to circular, and by 23.5% when the horizontal seismic coefficient varies from 0 to 0.1. A further validation with a 3D finite difference method is performed with respect to four typical tunnel shapes considered in this study. Lastly, several stability charts are provided for a quick estimation of the critical tunnel face pressure subjected to seismic forces. It is concluded that the proposed method can be applied to a tunnel stability assessment of various cross-sections and is highly efficient compared with numerical simulations.