Underground Space最新文献

Micro-disturbance grouting is a recovery technique to reduce the excessive deformation of operational shield tunnels in urban areas. The grout mass behaves as a fluid in the ground before hardening to form a grout–soil mixture, which highlights the necessity of using fluid–solid coupling method in the simulation of grouting process. Within a discrete element modeling environment, this paper proposes a novel fluid-solid coupling method based on the pore density flow calculation. To demonstrate the effectiveness of this method, it is applied to numerical simulation of micro-disturbance grouting process for treatment of large transverse deformation of a shield tunnel in Shanghai Metro, China. The simulation results reveal the mechanism of recovering tunnel convergence by micro-disturbance grouting in terms of compaction and fracture of soil, energy analysis during grouting, and mechanical response of soil-tunnel interaction system. Furthermore, the influence of the three main grouting parameters (i.e., grouting pressure, grouting distance, and grouting height) on tunnel deformation recovery efficiency is evaluated through parametric analysis. In order to efficiently recover large transverse deformation of shield tunnel in Shanghai Metro, it is suggested that the grouting pressure should be about 0.55 MPa, the grouting height should be in the range of 6.2–7.0 m, and the grouting distance should be in the range of 3.0–3.6 m. The results provide a valuable reference for grouting treatment projects of over-deformed shield tunnel in soft soil areas.

The Sichuan-Xizang Railway is a global challenge, surpassing other known railway projects in terms of geological and topographical complexity. This paper presents an approach for rapidly profiling rock mass quality underneath tunnel face for the ongoing construction of the Sichuan-Xizang Railway. It adopts the time-series method and carries out the quantitative analysis of the rock mass quality using the depth-series measurement-while-drilling (MWD) data associated with drilling of blastholes. A tunnel face with 15 blastholes is examined for illustration. The results include identification of the boundary of homogeneous geomaterial by plotting the blasthole depth against the net drilling time, as well as quantification of rock mass quality through the recalculation of the new specific energy. The new specific energy profile is compared and highly consistent with laboratory test, manual logging and tunnel seismic prediction results. This consistency can enhance the blasthole pattern design and facilitate the dynamic determination of charge placement and amount. This paper highlights the importance of digital monitoring during blasthole drilling for rapidly profiling rock mass quality underneath and ahead of tunnel face. It upgrades the MWD technique for rapid profiling rock mass quality in drilling and blasting tunnels.

Research on automation and intelligent operation of tunnel boring machine (TBM) is receiving more and more attention, benefiting from the increasing construction data. However, most studies on TBM operations optimization were trained by the labels of human drivers’ decisions, which were subjective and stochastic. As a result, the control parameters suggested by these models could hardly surpass the performance of a human driver, even the possibility of subjective incorrect decisions. Considering that the geomechanical feedback to TBM under drivers’ actions is objective, in this paper, a transformer-based model called the geological response for tunnel boring machine (GRTBM), is proposed to learn the relationship between operation-adjust and TBM monitoring changes. Additionally, with the model-based offline reinforcement learning, this paper provided a novel approach to optimizing the TBM excavation operations. The decision processes, recorded in the Yin-song TBM project for a waterway tunnel in Jilin Province of China, were used for the validation of the model. By adopting an implicit perception of geological conditions in the GRTBM model, the suggested method achieved the desired state within a single action, greatly outperformed the practical adjustments where 500 s were taken, revealing the fact that the proposed model has the potential to surpass the capability of human beings.

Mechanical softening behaviors of shale in CO₂-water–rock interaction are critical for shale gas exploitation and CO₂ sequestration. This work investigated the cross-scale mechanical softening of shale triggered by CO₂-water–rock interaction. Initially, the mechanical softening of shale following 30 d of exposure to CO₂ and water was assessed at the rock-forming mineral scale using nanoindentation. The mechanical alterations of rock-forming minerals, including quartz, muscovite, chlorite, and kaolinite, were analyzed and compared. Subsequently, an accurate grain-based modeling (AGBM) was proposed to upscale the nanoindentation results. Numerical models were generated based on the real microstructure of shale derived from TESCAN integrated minerals analyzer (TIMA) digital images. Mechanical parameters of shale minerals determined by nanoindentation served as input material properties for AGBMs. Finally, numerical simulations of uniaxial compression tests were conducted to investigate the impact of mineral softening on the macroscopic Young’s modulus and uniaxial compressive strength (UCS) of shale. The results present direct evidence of shale mineral softening during CO₂-water–rock interaction and explore its influence on the upscale mechanical properties of shale. This paper offers a microscopic perspective for comprehending CO₂-water-shale interactions and contributes to the development of a cross-scale mechanical model for shale.

In this paper, a seismic and vibration reduction measure of subway station is developed by setting a segmented isolation layer between the sidewall of structure and the diaphragm wall. The segmented isolation layer consists of a rigid layer and a flexible layer. The rigid layer is installed at the joint section between the structural sidewall and slab, and the flexible layer is installed at the remaining sections. A diaphragm wall-segmented isolation layer-subway station structure system is constructed. Seismic and vibration control performance of the diaphragm wall-segmented isolation layer-subway station structure system is evaluated by the detailed numerical analysis. Firstly, a three-dimensional nonlinear time-history analysis is carried out to study the seismic response of the station structure by considering the effect of different earthquake motions and stiffness of segmented isolation layer. Subsequently, the vibration response of site under training loading is also studied by considering the influence of different train velocities and stiffness of the segmented isolation layer. Numerical results demonstrate that the diaphragm wall-segmented isolation layer-subway station structure system can not only effectively reduce the lateral deformation of station structure, but also reduce the tensile damage of the roof slab. On the other hand, the developed reduction measure can also significantly reduce the vertical peak displacements of site under training loading.

Since the classical element model cannot describe the nonlinear characteristics of rock during the entire compressive creep process, nonlinear elements and creep damage are generally introduced in the model to resolve this issue. However, several previous studies have reckoned that creep damage in rock only occurs in the accelerated creep stage and is only described by the Weibull distribution. Nevertheless, the creep damage mechanism of rocks is still not clearly understood. In this study, a reasonable representation of the damage variables of solid materials is presented. Specifically, based on the Gurson damage model, the damage state functions reflecting the constant creep stage and accelerated creep stage of rock are established. Further, the one-dimensional and three-dimensional creep damage constitutive equations of rock are derived by modifying the Nishihara model. Finally, the creep-acoustic emission tests of phyllite under different confining pressures are conducted to examine the creep damage characteristics of phyllite. And the proposed constitutive model is verified by analyzing the results of creep tests performed on saturated phyllite. Overall, this study reveals the relationship between the creep characteristics of rocks and the corresponding damage evolution pattern, which bridges the gap between the traditional theory and the quantitative analysis of rock creep and its damage pattern.

Double-arch tunnels, as one of the popular forms of tunnels, might be exposed to boiling liquid expanding vapour explosions (BLEVEs) associated with transported liquified petroleum gas (LPG), which could cause damage to the tunnel and even catastrophic collapse of the tunnel in extreme cases. However, very limited study has investigated the performance of double-arch tunnels when exposed to internal BLEVEs and in most analyses of tunnel responses to accidental explosions. The TNT-equivalence method was used to approximate the explosion load, which may lead to inaccurate tunnel response predictions. This study numerically investigates the response of typical double-arch tunnels to an internal BLEVE resulting from the instantaneous rupture of a 20 m³ LPG tank. Effects of various factors, including in-situ stresses, BLEVE locations, and lining configurations on tunnel responses are examined. The results show that the double-arch tunnels at their early-operation ages are more vulnerable to severe damage when exposed to the BLEVE due to the low action of in-situ stress of rock mass on the response of early-age tunnels. It is also found that directing the LPG tank to different driving lanes inside tunnels can affect the BLEVE-induced tunnel response more significantly than varying the configurations of tunnel lining. Moreover, installing section-steel arches in the mid-wall can effectively improve the blast resistance of the double-arch tunnels against the internal BLEVE. In addition, the prediction models based on multi-variate nonlinear regressions and machine learning methods are developed to predict the BLEVE-induced damage levels of the double-arch tunnels without and with section-steel arches.

Many empirical and analytical methods have been proposed to predict fracturing pressure in cohesive soils. Most of them take into account three to four specific influencing factors and rely on the assumption of a failure mode. In this study, a novel data-mining approach based on the XGBoost algorithm is investigated for predicting fracture initiation in cohesive soils. This has the advantage of handling multiple influencing factors simultaneously, without pre-determining a failure mode. A dataset of 416 samples consisting of 14 distinct features was herein collected from past studies, and used for developing a regressor and a classifier model for fracturing pressure prediction and failure mode classification respectively. The results show that the intrinsic characteristics of the soil govern the failure mode while the fracturing pressure is more sensitive to the stress state. The XGBoost-based model was also tested against conventional approaches, as well as a similar machine learning algorithm namely random forest model. Additionally, several large-scale triaxial fracturing tests and an in-situ case study were carried out to further verify the generalization ability and applicability of the proposed data mining approach, and the results indicate a superior performance of the XGBoost model.