Large-section special-shaped shield tunnels feature many advantages, such as versatility and a large space utilization rate in energy transmission and public transport; however, guaranteeing the quality of segments’ assembly is difficult. Based on the quasi-rectangular shield tunnel project of Hangzhou Line 9 in China, this study investigated the formation mechanism and control measures of lining segment assembly defects. By quantifying the manufacturing error and positioning error, a simulation program for segment assembly is developed to calculate the error. Furthermore, considering the relative accumulative error between the upper and lower T blocks, the finite element model of key blocks (T-LZ block) is established to perform mechanical analysis, based on which the relative error control standard of the key block under the corresponding working conditions is proposed. The results show that the assembly quality can be effectively improved by assembling the LZ block first and applying corresponding error control measures, and the displacement of the segment along the rZ direction should be carefully controlled during the construction. The error caused by normal assembly will not damage the LZ block, and the corresponding control standard under the action of multi-degree-of-freedom error (extreme case) is 9.8 mm. Using this method to predict the assembly quality of segments can provide a basis for actual construction control of segment assembly.

The rock mass rating (RMR) system plays a crucial role in geomechanics assessments for tunnel projects. However, conventional methods combining empirical and geostatistical approaches often yield inaccuracies, particularly in areas with weak strata such as faults and karst caves. To address these uncertainties and errors inherent in empirical techniques, we propose a progressive RMR prediction strategy based on the Bayesian framework. This strategy incorporates three key components: 1) Variogram modeling: utilizing observational data from the excavation face, we construct and update a variogram model to capture the spatial variability of RMR. 2) TSP-RMR statistic model: we integrate a TSP-RMR statistical model into the Bayesian sequential update process. 3) Bayesian maximum entropy (BME) integration: the BME method combines geological information obtained from tunnel surface excavation with tunnel seismic prediction (TSP) data, ultimately enhancing the RMR prediction accuracy. Our methodology is applied to the Laoying rock tunneling project in Yunnan Province, China. Our findings demonstrate that the fusion of soft data and geological interpretation significantly improves the accuracy of RMR predictions. At selected prediction points, the relative error of our method is less than 15% when compared to the traditional Kriging method. This approach holds substantial potential for advancing RMR estimation ahead of tunnel excavation, particularly when advanced geological forecast data are available.

The degradation of soil bonding, which can be described by the evolution of bond degradation variables, is essential in the constitutive modeling of cemented soils. A degradation variable with a value of 0/1.0 indicates that the applied stress is completely sustained by bonded particles/unbounded grains. The discrete element method (DEM) was used for cemented soils to analyze the bond degradation evolution and to evaluate the degradation variables at the contact scale. Numerical cemented soil samples with different bonding strengths were first prepared using an advanced contact model (CM). Constant stress ratio compression, one-dimensional compression, conventional triaxial tests (CTTs), and true triaxial tests (TTTs) were then implemented for the numerical samples. After that, the numerical results were adopted to investigate the evolution of the bond degradation variables B_N and B₀. In the triaxial tests, B₀ evolves to be near to or larger than B_N due to shearing, which indicates that shearing increases the bearing rate of bond contacts. Finally, an approximate stress-path-independent bond degradation variable B_σ was developed. The evolution of B_σ with the equivalent plastic strain can be effectively described by an exponential function and a hyperbolic function.

Mountain tunnel structures are subject to a variety of diseases with increasing service life. Earlier tunnels may need to be demolished and expanded because of the poor serving capacity. But few studies of tunnel demolition projects are available. Based on the demolition project of Huangmeishan Tunnel, this paper discusses the demolition scheme of the double-arch tunnel, calculates the stability of the slope, and investigates the defects and material performance in the tunnel. The water leakage in the tunnel mainly occurred at the mid-partition wall and the drainage pipe was clogged severely. The largest width of the crack detected is 15 mm. Material performance tests indicated that the concrete material strength exceeded the design values. In the loading test, the largest displacements of the tunnel arch and haunch were 1.73 and 1.32 mm, which verified the safety of heavy vehicles in construction. Finally, suggestions are given to avoid similar phenomena in other tunnels during the design, construction, and operation phase. The novelty of this study lies in its comprehensive analysis of a tunnel demolition project. The findings of this study contribute to enhancing the knowledge and understanding of tunnel demolition and support the safe and efficient execution of future demolition projects.

The materials involved in geotechnical engineering are objects of concern in granular mechanics. In order to study the influence of the sliding friction coefficient corresponding to different-sized elements in the discrete element method (DEM) on the simulation results, we establish a two-dimensional DEM model based on the experimental method to analyze a slope example. The correctness of the DEM model is verified by comparing the sliding surface of a finite element method (FEM) model and the DEM slope model. A sliding friction coefficient algorithm based on the experimental method is embedded into the DEM slope model and compared with the original model. The comparison results show that embedding the DEM model into the sliding friction coefficient algorithm leads to an increase in displacement. The reason for this is that the contact information between elements of different sizes has changed, but the displacement trend is the same. Different sliding friction coefficients should be set based on different-sized elements in the DEM, as they can improve simulation accuracy.