Journal of Rock Mechanics and Geotechnical Engineering最新文献

Enzyme-induced carbonate precipitation (EICP) is an emanating, eco-friendly and potentially sound technique that has presented promise in various geotechnical applications. However, the durability and microscopic characteristics of EICP-treated specimens against the impact of drying-wetting (D-W) cycles is under-explored yet. This study investigates the evolution of mechanical behavior and pore characteristics of EICP-treated sea sand subjected to D-W cycles. The uniaxial compressive strength (UCS) tests, synchrotron radiation micro-computed tomography (micro-CT), and three-dimensional (3D) reconstruction of CT images were performed to study the multiscale evolution characteristics of EICP-reinforced sea sand under the effect of D-W cycles. The potential correlations between microstructure characteristics and macro-mechanical property deterioration were investigated using gray relational analysis (GRA). Results showed that the UCS of EICP-treated specimens decreases by 63.7% after 15 D-W cycles. The proportion of mesopores gradually decreases whereas the proportion of macropores increases due to the exfoliated calcium carbonate with increasing number of D-W cycles. The microstructure in EICP-reinforced sea sand was gradually disintegrated, resulting in increasing pore size and development of pore shape from ellipsoidal to columnar and branched. The gray relational degree suggested that the weight loss rate and UCS deterioration were attributed to the development of branched pores with a size of 100–1000 μm under the action of D-W cycles. Overall, the results in this study provide a useful guidancee for the long-term stability and evolution characteristics of EICP-reinforced sea sand under D-W weathering conditions.

To investigate the mechanism of rockburst prevention by spraying water onto the surrounding rocks, 15 experiments are performed considering different water absorption levels on a single face. High-speed photography and acoustic emission (AE) system are used to monitor the rockburst process. The effect of water on sandstone rockburst and the prevention mechanism of water on sandstone rockburst are analyzed from the perspective of energy and failure mode. The results show that the higher the absorption degree, the lower the intensity of the rockburst after absorbing water on single side of sandstone. This is reflected in the fact that with the increase in the water absorption level, the ejection velocity of rockburst fragments is smaller, the depth of the rockburst pit is shallower, and the AE energy is smaller. Under the water absorption level of 100%, the magnitude of rockburst intensity changes from medium to slight. The prevention mechanism of water on sandstone rockburst is that water reduces the capacity of sandstone to store strain energy and accelerates the expansion of shear cracks, which is not conducive to the occurrence of plate cracking before rockburst, and destroys the conditions for rockburst incubation.

The technology of tunnel boring machine (TBM) has been widely applied for underground construction worldwide; however, how to ensure the TBM tunneling process safe and efficient remains a major concern. Advance rate is a key parameter of TBM operation and reflects the TBM-ground interaction, for which a reliable prediction helps optimize the TBM performance. Here, we develop a hybrid neural network model, called Attention-ResNet-LSTM, for accurate prediction of the TBM advance rate. A database including geological properties and TBM operational parameters from the Yangtze River Natural Gas Pipeline Project is used to train and test this deep learning model. The evolutionary polynomial regression method is adopted to aid the selection of input parameters. The results of numerical experiments show that our Attention-ResNet-LSTM model outperforms other commonly-used intelligent models with a lower root mean square error and a lower mean absolute percentage error. Further, parametric analyses are conducted to explore the effects of the sequence length of historical data and the model architecture on the prediction accuracy. A correlation analysis between the input and output parameters is also implemented to provide guidance for adjusting relevant TBM operational parameters. The performance of our hybrid intelligent model is demonstrated in a case study of TBM tunneling through a complex ground with variable strata. Finally, data collected from the Baimang River Tunnel Project in Shenzhen of China are used to further test the generalization of our model. The results indicate that, compared to the conventional ResNet-LSTM model, our model has a better predictive capability for scenarios with unknown datasets due to its self-adaptive characteristic.

This study focuses on the analytical prediction of subsurface settlement induced by shield tunnelling in sandy cobble stratum considering the volumetric deformation modes of the soil above the tunnel crown. A series of numerical analyses is performed to examine the effects of cover depth ratio (C/D), tunnel volume loss rate (η_t) and volumetric block proportion (VBP) on the characteristics of subsurface settlement trough and soil volume loss. Considering the ground loss variation with depth, three modes are deduced from the volumetric deformation responses of the soil above the tunnel crown. Then, analytical solutions to predict subsurface settlement for each mode are presented using stochastic medium theory. The influences of C/D, η_t and VBP on the key parameters (i.e. B and N) in the analytical expressions are discussed to determine the fitting formulae of B and N. Finally, the proposed analytical solutions are validated by the comparisons with the results of model test and numerical simulation. Results show that the fitting formulae provide a convenient and reliable way to evaluate the key parameters. Besides, the analytical solutions are reasonable and available in predicting the subsurface settlement induced by shield tunnelling in sandy cobble stratum.

In order to evaluate the performance of deep geological disposal of radioactive waste, an underground research laboratory (URL) was constructed by Andra in the Callovo-Oxfordian (COx) claystone formation at the Meuse/Haute-Marne (MHM). The construction of URL induced the excavation damage of host formations, and the ventilation in the galleries desaturated the host formation close to the gallery wall. Moreover, it is expected that the mechanical behaviour of COx claystone is time-dependent. This study presents a constitutive model developed to describe the viscoplastic behaviour of unsaturated and damaged COx claystone. In this model, the unsaturation effect is considered by adopting the Bishop effective stress and the van Genuchten (VG) water retention model. In terms of the viscoplastic behaviour, the nonstationary flow surface (NSFS) theory for unsaturated soils is used with consideration of the coupled effects of strain rate and suction on the yield stress. A progressive hardening law is adopted. Meanwhile, a non-associated flow rule is used, which is similar to that in Barcelona basic model (BBM). In addition, to describe the damage effect induced by suction change and viscoplastic loading, a damage function is defined based on the crack volume proportion. This damage function contains two variables: unsaturated effective stress and viscoplastic volumetric strain, with the related parameters determined based on the mercury intrusion porosimetry (MIP) tests. For the model validation, different tests on COx claystone under different loading paths are simulated. Comparisons between experimental and simulated results indicated that the present model is able to well describe the viscoplastic behaviour of damaged COx claystone, including swelling/shrinkage, triaxial extension and compression, and triaxial creep.

The spatiotemporal distributions of microbes in soil by different methods could affect the efficacy of the microbes to reduce the soil hydraulic conductivity. In this study, the specimens of bio-mediated sands were prepared using three different methods, i.e. injecting, mixing, and pouring a given microbial solution onto compacted sand specimens. The hydraulic conductivity was measured by constant-head tests, while any soil microstructural changes due to addition of the microbes were observed by scanning electron microscope (SEM) and mercury intrusion porosimetry (MIP) tests. The amount of dextran concentration produced by microbes in each type of specimen was quantified by a refractometer. Results show that dextran production increased exponentially after 5–7 d of microbial settling with the supply of culture medium. The injection and mixing methods resulted in a similar amount and uniform distribution of dextran in the specimens. The pouring method, however, produced a nonuniform distribution, with a higher concentration near the specimen surface. As the supply of culture medium discontinued, the dextran content near the surface produced by the pouring method decreased dramatically due to high competition for nutrients with foreign colonies. Average dextran concentration was negatively and correlated with hydraulic conductivity of bio-mediated soils exponentially, due to the clogging of large soil pores by dextran. The hydraulic conductivity of the injection and mixing cases did not change significantly when the supply of culture medium was absent.

Jet grouting is one of the most popular soil improvement techniques, but its design usually involves great uncertainties that can lead to economic cost overruns in construction projects. The high dispersion in the properties of the improved material leads to designers assuming a conservative, arbitrary and unjustified strength, which is even sometimes subjected to the results of the test fields. The present paper presents an approach for prediction of the uniaxial compressive strength (UCS) of jet grouting columns based on the analysis of several machine learning algorithms on a database of 854 results mainly collected from different research papers. The selected machine learning model (extremely randomized trees) relates the soil type and various parameters of the technique to the value of the compressive strength. Despite the complex mechanism that surrounds the jet grouting process, evidenced by the high dispersion and low correlation of the variables studied, the trained model allows to optimally predict the values of compressive strength with a significant improvement with respect to the existing works. Consequently, this work proposes for the first time a reliable and easily applicable approach for estimation of the compressive strength of jet grouting columns.

Lime-treatment of clayey soil significantly increases its shear and tensile strengths. Consequently, the tensile strength of lime-treated soils deserves careful investigation because it may provide an appreciable benefit for the stability of earth structures. This study investigates the tensile and shear strengths of an untreated and lime-treated (3% of lime) plastic clay at different curing times (7 d, 56 d and 300 d), through triaxial tension and compression tests. Triaxial tension tests are performed using “diabolo-shaped” soil samples with reduced central section, such that the central part of the specimen can be under axial tension while both end-sections remain in axial compression. Consolidated undrained (CU) conditions with measurement of pore water pressure allow analyzing the failure conditions through effective stress and total stress approaches. The results of triaxial tension tests reveal that the failure occurs under tensile mode at low confining pressure while extensional shear failure mode is observed under higher confining pressure. Consequently, a classical Mohr-Coulomb shear failure criterion must be combined with a cut-off tensile strength criterion that is not affected by the confining pressure. When comparing shear failure under compression and tension, a slight anisotropy is observed.