Search Results (6)

As shield tunnels increase, managing shield muck strains construction and the environment. To mitigate this problem, shield muck replaced bentonite in silty clay to improve synchronous grouting slurry. Initially, the physical attributes and microstructural composition of shield muck were obtained, alongside an analysis of the effects of the muck content, particle size, and general influencing factors on the slurry properties through standardized tests and regression models. Subsequently, leveraging three-dimensional response surface methodology, admixture interactions and multiple factor impacts on the slurry were explored. Finally, utilizing the SQP optimization technique, an optimal slurry blend ratio tailored for actual project needs was derived for improved muck slurry. The findings reveal with the decreasing bleeding rates as the muck content rises, the particle size diminishes. An inverse relationship exists between the muck content and slurry fluidity. At soil–binder ratios below 0.6, a decrease in the soil–binder ratio intensifies the influence of the water–binder ratio on the slurry density, bleeding rate, and setting time. The fly flash–cement ratio inversely correlates with the slurry bleeding rate, while the ratio greater than 0.6 is positively correlated. For muck particle sizes under 0.2 mm, the fly flash–cement ratio inversely impacts the density, while over 0.2 mm, it correlates positively. The optimal proportion for silty clay stratum synchronous grouting slurry, substituting muck for bentonite, includes a water–binder ratio of 0.559, binder–sand ratio of 0.684, fly flash–cement ratio of 2.080, soil–binder ratio of 0.253, particle size under 0.075 mm, and water-reducing admixture of 0.06. Full article

The high permeability of gravel sand increases the risk of water spewing from the screw conveyor during earth pressure balance (EPB) shield tunnelling. The effectiveness of soil conditioning is a key factor affecting EPB shield tunnelling and construction safety. In this paper, using polymer, a foaming agent, and bentonite slurry as conditioning additives, the permeability coefficient tests of conditioned gravel sand are carried out under different injection conditions based on the factorial experiment design. The interactions between different concentrations of conditioning additives are analyzed. A prediction model for soil conditioning during shield tunneling based on particle swarm optimization (PSO) and relevance vector machine (RVM) algorithms is proposed to accurately and efficiently obtain the soil conditioning parameters in the water-rich gravel sand layer. The experimental results indicate that the improvement effect of the foaming agent on the permeability of the conditioned gravel sand gradually diminishes with the growing concentration of bentonite slurry. Under conditions of high polymer concentration, further increasing the concentration of bentonite slurry and foaming agent has a weak impact on the permeability coefficient when the concentration of bentonite slurry exceeds 10%. The significance of main effects, first-order interactions, and second-order interaction on the permeability of conditioned gravel sand are as follows: polymer concentration (A) > foaming agent concentration (B) > bentonite slurry concentration (C) > first-order interactions (A × B, A × C, B × C) > second-order interaction (A × B × C). The first-order interaction mainly manifests as a synergistic effect, while the second-order interaction primarily exhibits an antagonistic effect. Case studies show that the maximum relative error between predicted and experimental values is less than 3%. A field application of shield tunneling demonstrates the good performance of real-time optimization of soil conditioning parameters based on the PSO–RVM algorithm. This research provides a new method for evaluating the effectiveness of soil conditioning in the water-rich gravel sand layer. Full article

The rapid and accurate control of air chamber pressure in slurry pressure balance (SPB) shield tunneling machines is crucial for establishing the balance between slurry pressure and soil and water pressure, ensuring the stability of the support face. A novel air chamber pressure control method based on nonlinear adaptive robust control (ARC) and using a pneumatic proportional three-way pressure-reducing valve is proposed in this paper. Firstly, an electric proportional control system for the air chamber pressure is developed. Secondly, a nonlinear state space model for the air chamber pressure regulation process is established. Utilizing experimental data from the SPB shield tunneling machine test bench, nonlinear adaptive identification is conducted through the nonlinear recursive least square algorithm. The results demonstrate the model’s effectiveness and accuracy. Then, a nonlinear ARC for air chamber pressure is designed based on the backstepping method, and its Lyapunov stability is proved. Finally, the feasibility and effectiveness of the controller designed in this paper is verified through simulation and experiments. The results demonstrate that the developed control system can compensate for the nonlinearity and disturbance in the air chamber pressure regulation process. It can achieve good transient and steady-state performance and has good robustness against uncertainty. Full article

Urban tunnelling can be highly challenging, especially in areas where limited ground settlements and environmental disturbance is required. Mechanised tunnelling is usually preferred in such ground environments, specifically Slurry or EPBM (Earth Pressure Balance Machine), depending on the ground properties. Being able to predict the anticipated tunnel behaviour at the preliminary stages of the project can be very beneficial in optimising not only the design, but also control the construction activities and completion times. In practice, the short-term excavation response and support performance focus primarily on design, since most site characterisation inputs are focused on material properties gained from short-term testing. Although the analysis of tunnelling is a three-dimensional (3D) problem, conventional approaches and design methods employed during the design and construction of underground openings are often based on the ground’s static response in two dimensions (2D). In this paper, an initial 2D model is generated in PLAXIS2D and RS2 (Rocscience) to test advanced constitutive models and compare transverse settlement profiles; subsequently, a complete 3D FEM numerical model in RS3 (Rocscience) was used to simulate an Earth Pressure Balance (EPB) excavation sequence. The 3D numerical model simulates the relevant EPB components such as face pressure, TBM shield, backfilling of the tail void (time-dependent hardening of the grout) and gradual segmental lining erections in the longitudinal direction. The presented numerical approach can be used by tunnel designers and engineers to predict the soil response in EPBM tunnelling. Full article

Clogging constitutes a significant obstacle to shield tunneling in mudstone soils. Previous research has focused on investigating the influence of soils and slurry properties on clogging, although little attention has been paid to the impact of tunneling parameters on clogging, and particularly early clogging warning during tunneling. This paper contributes to developing a real-time clogging early-warning approach, based on a self-updating machine learning method. The clogging judgment criteria are based on the statistical characteristics of whole-ring tunneling parameters. The paper proposes the use of random forest (RF) for a real-time self-updating early warning strategy for clogging. The performance of this approach is illustrated through its application to a slurry-pressure-balanced shield tunneling construction of Nanning metro line 1. Results show that the RF-based approach can predict clogging during a ring construction with only four minutes of tunneling data, with an accuracy of 95%. The RF model provided the best performance compared with the other machine learning methods. Furthermore, the RF model can realize an accurate clogging prediction in one ring, using less tunneling data with the self-updating mechanism. Full article

Soil conditioning is a key factor in increasing tunnel face stability and extraction efficiency of excavated soil when excavating tunnels using an earth pressure balance (EPB) shield tunnel boring machine (TBM). Weathered granite soil, which is abundant in the Korean Peninsula (also in Japan, Hong Kong, and Singapore), has different characteristics than sand and clay; it also has particle-crushing characteristics. Conditioning agents were mixed with weathered granite soils of different individual particle-size gradations, and three characteristics (workability, permeability, and compressibility) were evaluated to find an optimal conditioning method. The lower and upper bounds of the water content that are needed for a well-functioning EPB shield TBM were also proposed. Through a trial-and-error experimental analysis, it was confirmed that soil conditioning using foam only was possible when the water content was controlled within the allowable range, that is, between the upper and lower bounds; when water content exceeded the upper bound, soil conditioning with solidification agents was needed along with foam. By taking advantage of the particle-crushing characteristics of the weathered granite soil, it was feasible to adopt the EPB shield TBM even when the soil was extremely coarse and cohesionless by conditioning with polymer slurries along with foam. Finally, the application ranges of EPB shield TBM in weathered granite soil were proposed; the newly proposed ranges are wider and expanded to coarser zones compared with those proposed so far. Full article