Due to multiple factors influencing the construction safety of TBM hydraulic tunnels, risk assessment is a critical point of a construction management plan to avoid possible risks. In this paper, a safety-risk evaluation index system of TBM construction for hydraulic tunnels is built based on the identification and analysis of possible sources of risk in techniques, geologic, equipment, management, and accidents. Considering the influence of factors such as the experience level and the expertise of decision makers, a combination assignment method of index weights is proposed based on binary semantics. On the basis of a fuzzy normal distribution used as the subordinate function distribution of fuzzy evaluation levels, the subordinate function distribution of fuzzy evaluation levels under multi-level intersection situations is introduced, and a comprehensive evaluation model of safety risks for TBM tunnel construction is built. The validity and practicality of the evaluation model is examined with the combination of a long-distance water conveyance tunnel project. Results show that the construction safety-risk of the TBM hydraulic tunnel project belongs to the middle-high level, and the safety accident risk belongs to the low level. The study provides guidance of evaluation and control of risks for this tunneling construction being successfully completed.

The misalignment of segments in installation is a common issue in the construction of TBM tunnels. This raises a question of whether misalignment affects the operation safety of a hydraulic TBM tunnel. Using a water transfer engineering project as an example, this paper built a three-dimensional finite element model composited with segment, grout layer and surrounding rock for the numerical analysis of the behavior of single-directionally misaligned segments. The crown or invert segment was separately misaligned towards to the center of segment ring in a value of 5 mm, 10 mm, 20 mm, 30 mm or 40 mm. The strength grade of the segment concrete was C50. A weaker surrounding rock composed of V-class rock was considered for the tunnel. The results indicate that the misalignment of the crown or invert segment, respectively, creates the tensile stress in the inner surface of the corresponding segment, the tensile stress will be over the limit of C50 concrete when the misalignment is over 30 mm, indicating a risk of concrete cracking. The contact surfaces of the segment ring basically remain in compression, and the locating pins between the segment rings exhibit an evident increase in tensile stress at misaligned positions. The key points that can be obtained from this study are that a special supervision is needed to ensure the accuracy of segment installation, and strengthening measures are needed for existing misaligned segments.

The accurate prediction of tunneling speed in tunnel boring machine (TBM) construction is the basis for the timely adjustment of the operating parameters of TBM equipment to ensure safe and efficient tunneling. In this paper, a multi-step prediction model of TBM tunneling speed based on the EWT-ICEEMDAN-SSA-LSTM hybrid model is proposed. Firstly, four datasets were selected under different geological conditions, and the original data were preprocessed using the binary discriminant function and the $3\sigma$ principle; secondly, the preprocessed data were decomposed using the empirical wavelet variation (EWT) to obtain several subseries and residual series; then, Intrinsic Computing Expressive Empirical Mode Decomposition With Adaptive Noise (ICEEMDAN) was used to perform further decomposition on residual sequences. Finally, several subsequences were fed into a Long Short-Term Memory (LSTM) network optimized by the Sparrow Search Algorithm (SSA) for multi-step training and prediction, and the predicted results of each subsequence were added up to obtain the final result. A comparison with existing models showed that the performance of the prediction method proposed in this paper is superior to other models. Of the four datasets, the average accuracy from the first step prediction to the fifth step prediction reached 99.06%, 98.99%, 99.07%, and 99.03%, respectively, indicating that the proposed method has high multi-step prediction performance and generalization ability. In this sense, this paper provides a reference for other projects.

Pea-gravel grouting, which fills the gap between the lining of tunnels and the surrounding rock, is crucial for the structural stability and waterproofing of water delivery TBM tunnels. However, it is prone to defects due to complex construction conditions and geological factors. To provide practical insights for engineers to evaluate grouting quality and take appropriate remedial action during TBM tunnel construction, this paper assesses four types of pea-gravel grouting defects, including local cavities, less density, rich rock powder and rich cement slurry. Detailed numerical simulation models comprising segment lining, pea-gravel grouting and surrounding rock were built using the 3D finite element method to analyze the displacement and stress of the segments at the transition zone between different classes of surrounding rocks, labeled V–IV, V–III and IV–III. The results indicate that a local cavity defect has the greatest impact on the loading response of segment lining, followed by less density, rich rock powder and rich cement slurry defects. Their impact will weaken with better self-support of the surrounding rocks in the order of V–IV, V–III and IV–III. The tensile stress of segment lining is within the limit of concrete cracking for combinations of all four defects when the surrounding rock is of the class IV–III, and it is within this limit for two-defect combinations when the surrounding rock is of classes V–III and V–IV. When three defects or all four defects are present in the pea-gravel grouting, the possibility of segment concrete cracking increases from the transition zone of class V–III surrounding rock to the transition zone of class V–IV surrounding rock.