Underground Space最新文献

This paper concentrates on the sensitivity and dynamic simulation of randomly distributed karst cave groups on tunnel stability and connectivity extended ratio based on water–rock interaction using a novel contact dynamic method (CDM). The concept of karst cave group connectivity extended ratio during tunneling and water inrush is proposed. The effects of cave shape and spatial distribution on Qiyueshan tunnel are investigated. Tunnel deformation and damage index, and connectivity extended ratio with uniform random karst cave groups are evaluated. The results demonstrate that the connectivity extended ratio is verified as a crucial judgment in predicting the safe distance and assessing the stability of the tunnel with the karst cave group. CDM model captures the fracture propagation and contact behavior of rock mass, surface flow, as well as the bidirectional water–rock interaction during the water inrush of Qiyueshan tunnel with multiple caves. A larger cave radius and smaller minimum distance between the cave and tunnel increase the deformation and damage index of the surrounding rock. When the cave radius and cave area ratio increase, the failure pattern shifts from overall to local failure. These findings potentially have broad applications in various surface and subsurface scenarios involving water–rock interactions.

Discontinuity is critical for strength, deformability, and permeability of rock mass. Set information is one of the essential discontinuity characteristics and is usually accessed by orientation grouping. Traditional methods of identifying optimal discontinuity set numbers are usually achieved by clustering validity indexes, which mainly relies on the aggregation and dispersion of clusters and leads to the inaccuracy and instability of evaluation. This paper proposes a new method of Fisher mixed evaluation (FME) to identify optimal group numbers of rock mass discontinuity orientation. In FME, orientation distribution is regarded as the superposition of Fisher mixed distributions. Optimal grouping results are identified by considering the fitting accuracy of Fisher mixed distributions, the probability monopoly and central location significance of independent Fisher centers. A Halley-Expectation-Maximization (EM) algorithm is derived to achieve an automatic fitting of Fisher mixed distribution. Three real rock discontinuity models combined with three orientation clustering algorithms are adopted for discontinuity grouping. Four clustering validity indexes are used to automatically identify optimal group numbers for comparison. The results show that FME is more accurate and robust than the other clustering validity indexes in optimal discontinuity group number identification for different rock models and orientation clustering algorithms.

Shipwreck salvage is a risky, time-consuming, and expensive process. Although there are many sunken ships along coastlines and in the open seas, the salvage process of a sunken ship has rarely been reported. The integrated salvage of the “Yangtze River Estuary II” shipwreck used a novel method with 22 closely locked curved rectangular pipes to form a watertight base that wrapped the shipwreck inside. The basing was lifted out of the water using a powerful crane situated on an engineering ship. For the first time, the tunneling method was used in a shipwreck salvage project, significantly reducing the disturbance to the shipwreck and its stowage, thereby preserving the original state and integrity of the shipwreck to the greatest extent. In this study, the basic concepts of the salvage method and process are explained. Solutions to critical issues in the new salvage method are provided, including jacking force prediction and major considerations for the structural design of the salvage system. The design of the salvage system and salvage process of the “Yangtze River Estuary II” shipwreck are introduced. The monitored jacking force, pipe deformation, and observed water-tightness verified that the proposed method was effective and efficient. Other possible application scenarios for the proposed method are presented at the end.

High-pressure waterjet-assisted tunnel boring machine (WTBM) is an efficient method for improving the tunneling performance of a tunnel boring machine (TBM) and reducing the wear of its disc cutters in hard rock with high geostresses. Confining pressure directly affects the efficiency of rock breaking and the configuration of the disc cutters. In this study, we evaluated the effect of confining pressure on WTBM rock breaking by developing a self-designed and manufactured experimental system, including confining pressure loading, TBM disc-cutter penetration, and high-pressure waterjet. The macro fracture, acoustic emission (AE), peak normal force drop, and specific energy (SE) were analyzed for four different confining pressures (10, 20, 30, and 35 MPa). The results showed that the cutting depth of the waterjet increased linearly as the waterjet pressure increased and decreased with the gradual increase in the nozzle moving speed. The expansion and development of cracks formed rock debris, and the size of the rock fragments decreased with an increase in confining pressure. When the waterjet pressure was 280 MPa, the nozzle moving velocity was 800 mm/min and the kerf space was 75 mm, which indicated that the confining pressure, which was 23.16 MPa, minimized the cutting SE under this condition. However, regardless of the confining pressure, the maximum normal force of WTBM was less than that of a TBM, whereas the SE of WTBM was less than that of complete TBM cutting mode (CTCM). The average force drop and average drop rate of SE were approximately 25%, and 80%, respectively. The results of this study can inspire the design and mechanism of a TBM assisted by a high-pressure waterjet.

In large-diameter shield tunnels, applying the double-layer lining structure can improve the load-bearing properties and maintain the stability of segmental lining. The secondary lining thickness is a key parameter in the design of a double lining structure, which is worth being explored. Based on an actual large-diameter shield tunnel, loading model tests are carried out to investigate the effect of the secondary lining thickness on the mechanical behaviours of the double lining structure. The test results show that within the range of secondary lining thicknesses discussed, the load-bearing limit of the double-layer lining increases with growing secondary lining thickness. As a passive support, the secondary lining acts as an auxiliary load-bearing structure by contacting the segment. And changes in secondary lining thickness have a significant effect on the contact state between the segment and secondary lining, with both the contact pressure level and the contact area between the two varying. For double-layer lining structures in large-diameter shield tunnels, it is proposed that the stiffness of the secondary lining needs to be matched to the stiffness of the segment, as this allows them to have a coordinated deformation and a good joint load-bearing effect.

A novel coupled model integrating Elman-AdaBoost with adaptive mutation sparrow search algorithm (AM-SSA), called AMSSA-Elman-AdaBoost, is proposed for predicting the existing metro tunnel deformation induced by adjacent deep excavations in soft ground. The novelty is that the modified SSA proposes adaptive adjustment strategy to create a balance between the capacity of exploitation and exploration. In AM-SSA, firstly, the population is initialized by cat mapping chaotic sequences to improve the ergodicity and randomness of the individual sparrow, enhancing the global search ability. Then the individuals are adjusted by Tent chaotic disturbance and Cauchy mutation to avoid the population being too concentrated or scattered, expanding the local search ability. Finally, the adaptive producer-scrounger number adjustment formula is introduced to balance the ability to seek the global and local optimal. In addition, it leads to the improved algorithm achieving a better accuracy level and convergence speed compared with the original SSA. To demonstrate the effectiveness and reliability of AM-SSA, 23 classical benchmark functions and 25 IEEE Congress on Evolutionary Computation benchmark test functions (CEC2005), are employed as the numerical examples and investigated in comparison with some well-known optimization algorithms. The statistical results indicate the promising performance of AM-SSA in a variety of optimization with constrained and unknown search spaces. By utilizing the AdaBoost algorithm, multiple sets of weak AMSSA-Elman predictor functions are restructured into one strong predictor by successive iterations for the tunnel deformation prediction output. Additionally, the on-site monitoring data acquired from a deep excavation project in Ningbo, China, were selected as the training and testing sample. Meanwhile, the predictive outcomes are compared with those of other different optimization and machine learning techniques. In the end, the obtained results in this real-world geotechnical engineering field reveal the feasibility of the proposed hybrid algorithm model, illustrating its power and superiority in terms of computational efficiency, accuracy, stability, and robustness. More critically, by observing data in real time on daily basis, the structural safety associated with metro tunnels could be supervised, which enables decision-makers to take concrete control and protection measures.

In the longitudinal seismic deformation method for shield tunnels, one of the most commonly used is the longitudinal equivalent stiffness beam model (LES) for simulating the mechanical behavior of the lining. In this model, axial deformation and bending deformation are independent, so the equivalent stiffness is a constant value. However, the actual situation is that axial deformation and bending deformation occur simultaneously, which is not considered in LES. At present, we are not clear about the effect on the calculation results when axial deformation and bending deformation occur simultaneously. Therefore, in this paper, we improve the traditional LES by taking the relative deformation as a load and considering the coordinated deformation of axial and bending degrees of freedom. This improved model is called DNLES, and its neutral axis equations are an explicit expression. Then, we propose an iterative algorithm to solve the calculation model of the DNLES-based longitudinal seismic deformation method. Through a calculation example, we find that the internal forces based on LES are notably underestimated than those of DNLES in the compression bending zone, while are overestimated in the tension bending zone. When considering the combined effect, the maximum bending moment reached 13.7 times that of the LES model, and the axial pressure and tension were about 1.14 and 0.96 times, respectively. Further analysis reveals the coordinated deformation process in the axial and bending directions of the shield tunnel, which leads to a consequent change in equivalent stiffness. This explains why, in the longitudinal seismic deformation method, the traditional LES may result in unreasonable calculation results.

Ovaling deformation of circular tunnels has received great interest from the tunneling community because this mode of seismic-induced deformation is considered the most critical. However, there is growing evidence that other deformation modes can also be important and thus need to be considered in design. This study presents a new analytical solution to estimate axial bending (snaking), a mode of deformation caused by S-waves impinging on a tunnel parallel to the tunnel axis. The solution is developed using the soil-structure interaction approach with the assumption that the interface between the ground and the tunnel lining is frictionless (full-slip). Full dynamic numerical simulations are conducted to verify the new full-slip solution, together with the existing no-slip solution. Effects of dynamic amplification are also explored for both full-slip and no-slip interface conditions by changing the wavelength (or frequency) of the seismic input motions.

Over the last decades, an expansion of the underground network has been taking place to cope with the increasing amount of moving people and freight. As a consequence, it is of vital importance to guarantee the full functionality of the tunnel network by means of preventive maintenance and the monitoring of the tunnel lining state over time. A new method has been developed for the real-time prediction of the utilization level in tunnel segmental linings based on input monitoring data. The new concept is founded on a framework, which encompasses an offline and an online stage. In the former, the generation of feedforward neural networks is accomplished by employing synthetically produced data. Finite element simulations of the lining structure are conducted to analyze the structural response under multiple loading conditions. The scenarios are generated by assuming ranges of variation of the model input parameters to account for the uncertainty due to the not fully determined in situ conditions. Input and target quantities are identified to better assess the structural utilization of the lining. The latter phase consists in the application of the methodological framework on input monitored data, which allows for a real-time prediction of the physical quantities deployed for the estimation of the lining utilization. The approach is validated on a full-scale test of segmental lining, where the predicted quantities are compared with the actual measurements. Finally, it is investigated the influence of artificial noise added to the training data on the overall prediction performances and the benefits along with the limits of the concept are set out.

Parameters of foam penetration in earth pressure balance (EPB) shield tunnelling, such as permeability coefficients and penetration distances, significantly impact tunnel face stability. However, existing studies have faced inaccuracies in analysing these parameters due to imitations in experimental methods. This study addresses this issue by employing enhanced methods for a more precise analysis of foam penetration. Experiments involving three distinct sand types (coarse, medium, and fine) and three foam expansion ratios (FER) (10, 15, and 20) are conducted using a modified model test setup. Benefiting from a novel computer vision-based method, the model test outcomes unveil two distinct foam penetration paths: liquid migration (L_w) and bubble migration (L_f). Three penetration phases — namely, injection, blockage & drainage, and breakage — are identified based on L_w and L_f variations. The initial “injection” phase conforms to Darcy's law and is amenable to mathematical description. The foam with FER of 15 has the maximum viscosity and, hence the L_f and permeability in the penetration tests with FER of 15 are the lowest in the same sand. The bubble size distribution of foam with different FER shows minor differences. Nevertheless, the characteristics of foam penetration vary due to the distinct particle size distribution (PSD) of different sands. Foam penetration creates low-permeability layers in both medium and fine sands due to the larger bubble size of the foam compared to the estimated pore sizes of medium and fine sands. While the coarse sand results in a different situation due to its large pore size. The distinctive characteristics of foam penetration in different sand strata are notably shaped by FER, PSD, and pore size distributions. These insights shed light on the complex interactions during foam penetration at the tunnel face, contributing valuable knowledge to EPB shield tunnelling practices.