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This paper proposes an efficient method for quantifying the stratigraphic uncertainties and modeling the geological formations based on boreholes. Two Markov chains are used to describe the soil transitions along different directions, and the transition probability matrices (TPMs) of the Markov chains are analytically expressed by copulas. This copula expression is efficient since it can represent a large TPM by a few unknown parameters. Due to the analytical expression of the TPMs, the likelihood function of the Markov chain model is given in an explicit form. The estimation of the TPMs is then re-casted as a multi-objective constrained optimization problem that aims to maximize the likelihoods of two independent Markov chains subject to a set of parameter constraints. Unlike the method which determines the TPMs by counting the number of transitions between soil types, the proposed method is more statistically sound. Moreover, a random path sampling method is presented to avoid the directional effect problem in simulations. The soil type at a location is inferred from its nearest known neighbors along the cardinal directions. A general form of the conditional probability, based on Pickard's theorem and Bayes rule, is presented for the soil type generation. The proposed stratigraphic characterization and simulation method is applied to real borehole data collected from a construction site in Wuhan, China. It is illustrated that the proposed method is accurate in prediction and does not show an inclination during simulation.

Shield machine may deviate from its design axis during excavation due to the uncertainty of geological environment and the complexity of operation. This study therefore introduced a framework to predict the attitude and position of shield machine by combining long short-term memory (LSTM) model with attention mechanism. The data obtained from the Wuhan Rail Transit Line 6 project were utilized to verify the feasibility of the proposed method. By adding the attention mechanism into the LSTM model, the proposed model can focus more on parameters with higher weights. Sensitivity analysis based on Pearson correlation coefficient was conducted to improve the prediction efficiency and reduce the irrelevant input parameters. Compared with LSTM model, LSTM-attention model has higher accuracy. The mean value of coefficient of determination (R2) increases from 0.625 to 0.736, and the mean value of root mean square error (RMSE) decreases from 3.31 to 2.24. The proposed LSTM-attention model can provide an effective prediction for attitude and position of shield machine in practical tunneling engineering.

Through the active control of shield thrust system oil pressures, a synchronous shield tunnelling technology combining advancement and segment fabrication was proposed. The key to this technology was to completely exploit the additional stroke of the hydraulic jacks generated by the axial insertion of a key block to assemble the segments. Taking the tunnelling project of the Shanghai Airport Railway Link Line as a demonstration project, this paper uses a large model test platform for this synchronous technology. A single-ring construction process along a straight line was simulated, in which the theoretical external loads were implemented on the shield machine. The feasibility and reliability of this synchronous technology were evaluated considering the accuracy of total thrust force control, maintenance of tunnelling speed and shield postures and segment compression. The effectiveness of the redistribution principle for the missing thrust force due to the withdrawal of cylinders located in the segment fabrication region was discussed. Furthermore, some other interesting phenomena were observed in the practical application in addition to the model test. This technology primarily realizes synchronous assembly by improving the control of the propulsion system of conventional shield machines without any transformation of the shield machine’s primary structure, segment patterns or excavation method. The proposed method has good adaptability and a low construction cost, which will be beneficial for future long-distance tunnelling projects.