Acta Geotechnica最新文献

The spatiotemporal characteristics of a rockburst, such as the distance from the tunnel face, are critical factors related to early warning and control. Therefore, by using the data from over 100 immediate strain rockbursts (ISRs) in three open tunnel boring machine (TBM) granite tunnels, the relationships among their occurrence locations and TBM shield, their impact and control measures are statistically analyzed. The ISRs in open TBM tunnels are categorized into shield area ISRs (SA-ISRs) and main beam area ISRs (MBA-ISRs). The differences in the spatiotemporal characteristics, rockburst pit evolution characteristics and microseismic (MS) activity laws of these two types of ISRs are further analyzed. IS-ISRs occur earlier, and mainly form V-type pits without expansion. MBA-ISRs occur later, with a high proportion of fossa-type pits with more obvious expansion. MS nucleation in the SA-ISR area is high after excavation, with MS activity increasing rapidly and peaking. In contrast, the MS events in the MBA-ISR area are scattered, and MS activity is weak during excavation, gradually increases over time and continues to accumulate in space. On this basis, the influence mechanism of stress level, lithology, structural planes, and construction factors on the spatiotemporal characteristics of ISRs is studied, with the overall stress level identified as the main factor. When the stress level is high, the degree of energy accumulation increases after excavation, making it easier for SA-ISR to occur. Conversely, the degree of energy accumulation after excavation is lower. However, due to the influence of the nearby steep structural plane, energy continues to accumulates during the stress adjustment process in this area, resulting in a delay in MBA-ISR.

This study investigates the thermo-hydro-mechanical (THM) behavior of argillaceous formations, particularly the Callovo–Oxfordian (COx) claystone, over extended timescales to evaluate the long-term safety of radioactive waste repositories. Numerical simulations were performed as part of a benchmark exercise to study the response of the COx formation under heating scenarios representative of high-level radioactive waste disposal. Six modeling teams from various institutions participated in this benchmark, using various numerical codes, providing valuable information on the evolution of temperature, pore water pressure, and stresses within the repository environment, particularly around the disposal cells. The results highlight that the COx formation exhibits significant thermal pressurization and stress relaxation because of its low permeability, whereas the excavation damaged zone (EDZ) remains confined to the near field and does not extend significantly under the thermal load considered. The study demonstrates the robustness of numerical tools for repository safety assessments and emphasizes the importance of validated THM formulations to ensure long-term containment of radioactive waste.

When shield tunnelling in unsaturated sandy ground (USG), the tunnel face is inevitably subjected to the combined effects of unloading and cutterhead vibration (CEUV), which adversely affects ground stability. To investigate the underlying mechanical mechanisms, a tunnel face unloading (TFU) apparatus was developed, and a series of physical model tests were conducted. The results indicate that the longitudinal acceleration amplitude induced by cutterhead vibration attenuates exponentially in the ground due to the energy dissipation. The TFU causes a chimney-like global failure in the dry sandy ground (DSG), but produces a localized failure with a cavity above it in the USG. Under vibration, the loosening zone in DSG expands in width, while it enlarges both in height and width in USG. The apparent cohesion enhances the tunnel face stability in the USG and facilitates the formation of the self-stabilized arch (SSA), as reflected in stress evolution. Nevertheless, the vibration weakens the soil arching effect, causing an increase in the limit support pressure. Via comparison with previous model tests and numerical simulations, the experimental results are well validated. The formation and destruction of the SSA and the increase of vertical earth pressure under CEUV are theoretically explained by the improved multi-arch model. In addition, the hysteretic failure of cavities in USG poses significant risks to tunnel engineering. Non-destructive physical prospecting methods are recommended to assist in shield tunnelling control and ground remediation.

Treating sulfate saline soil with lime or cement can lead to significant ettringite-induced swelling, resulting in the deterioration of subgrade or foundation layers, particularly in the presence of excessive moisture. This study employed reactive MgO and ground granulated blast furnace slag (GGBS) to treat saline loess to mitigate this adverse swelling. Sodium sulfate saline loess with 4% salt content was stabilized by 8%, 10%, and 12% MgO-GGBS binder with MgO to GGBS ratios of 1:9, 2:8, and 3:7. The properties of the treated soil was assessed through linear swelling test, unconfined compressive strength (UCS), X-ray diffraction (XRD), derivative thermogravimetric analysis (DTG), and scanning electron microscopy (SEM) analysis. The results demonstrated that the UCS of saline loess stabilized with the MgO-GGBS binder increased gradually with the GGBS dosage and the curing time, and the MgO content of the binder exceeded 1% favored the hydration of GGBS and the strength development of cured saline soil. In addition, the linear swelling (%) and strength loss (%) of saline soil stabilized by the MgO-GGBS binder under immersion conditions decreased progressively with increasing MgO dosage. Saline loess cured with the MgO-GGBS binder containing 2% MgO exhibited the lowest linear swelling of 0.08%, while the strength of the cured soil with MgO dosages greater than 2% gradually increased under immersion. The optimal formulation for stabilizing saline loess with 4% salt content was 10% MgO-GGBS binder containing 2% MgO. XRD, DTG, and SEM analysis confirmed that the major secondary reaction products formed in the cured saline soil matrix by the MgO-GGBS binder containing more than 2% MgO included low crystallinity ettringite, S-AFm, Mg–Al–SO₄ LDHs, and MSH gel, which primarily contributed to the reduction in linear swelling of the cured soil. In contrast, the swelling of binder treated soil with less than 1.6% MgO was predominantly due to the formation of ettringite and its water-absorption expansion.

The stability of three-dimensional (3D) cylindrical tunnel vaults in soil strata subjected to a compound tension-shear failure is investigated based on the upper bound limit analysis. A failure mechanism for 3D cylindrical tunnel vaults reflecting the transition process from shallow to deep buried conditions, making the deep buried failure mechanisms a special case, is developed from the modified Mohr–Coulomb (MC) criterion with tension cut-off (TC). By deducing the energy balance equation, the expressions for three stability indices, i.e., the stability coefficient, the factor of safety (FoS) and critical required reinforcement strength, which can be used to quantify the tunnel vault stability, are derived. The optimal upper bound solution of stability indices is obtained using compiler optimization algorithms. The influences of 3D geometric characteristics and soil strength parameters with TC on the tunnel vault stability during the transition process from shallow to deep buried conditions of tunnel vault are revealed. Further, the stability charts for the 3D tunnel vault FoS under different parameters and for the critical reinforcement strength required to maintain the tunnel vault stability under different desired FoS are calculated and plotted. In practical engineering, the corresponding data can be acquired quickly by chart query, which provides a theoretical basis for the 3D preliminary design of cylindrical tunnels.

The concentrated solution sludge (CSS) produced by the immersion combustion evaporation process has extremely high soluble salt content. Ground-granulated blast-furnace slag (GGBS) and municipal solid waste incineration (MSWI) by-products geopolymer is adopted for solidification/stabilization (S/S) of CSS. A series of unconfined compressive strength (UCS) test, water immersion tests, microscopic observation tests and leaching toxicity tests were carried out on the solidified sludge to investigate the S/S effect and mechanism of the prepared geopolymer on CSS. Results show that the MSWI by-products can effectively promote the geopolymerization of precursors and improve the compressive strength and water stability of the solidified CSS. The leaching concentration of heavy metal and PCDD/Fs [polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs)] can satisfy the relevant standards of China. The geopolymeric gels generated by GGBS-based geopolymer can effectively cement and wrap the CSS particles, which is the S/S mechanism of the CSS solidified by the synthetic geopolymer. The energy consumption and carbon emissions of using this geopolymer for solidifying the CSS are much lower than those of using cement/MSWI by-products.

This study introduces a new and efficient methodology for the stability analysis of excavations, accounting for soil variability, by integrating an improved limit analysis (iLA) method with the Polynomial Chaos Kriging (PCK) and Monte Carlo Simulation (MCS) technique. First, the iLA method is proposed for deterministic analysis, incorporating factors such as the soil–wall interface, excavation geometry, and wall embedment depth. This approach allows for the estimation of the basal heave safety factor using the strength reduction method in combination with a bisection optimization technique. The accuracy and versatility of the proposed iLA method are demonstrated through comparisons with numerical simulations and four existing analytical methods. Next, the study introduces an active learning method, PCK–MCS, and integrates it with the iLA method to perform probabilistic analyses of excavation stability. The efficiency and effectiveness of the final integrated methodology, iLA–PCK–MCS, are validated through comparisons with established methods, including direct MCS, Subset Simulation, and Kriging- and Sparse Polynomial Chaos Expansion-based MCS. Finally, leveraging the computational efficiency of the iLA–PCK–MCS framework, a parametric study is conducted to provide insights into the effects of soil uncertainties, the soil–wall interface, and wall embedment depth on excavation stability. The methods presented in this study are expected to advance both deterministic and probabilistic analyses in excavation projects by offering a highly efficient and accurate tool for evaluating basal heave stability.

Various deep learning models are employed to predict landslide displacement. However, existing deep learning prediction models do not take into account the rich multi-scale information of external triggering factors from multiple sources and the impact of each influencing factor on the degree of triggered landslide displacements. Therefore, this work applies the variational mode decomposition (VMD) theory to decompose the “step” displacement of a landslide into trend displacement, periodic displacement, and stochastic displacement. A polynomial function is used to predict the trend displacement, VMD is used to calculate the high-frequency and low-frequency components of periodic displacement and random displacement, and the main trigger factors are determined by the grey correlation degree. Then, a hybrid deep learning model based on multi-scale convolutional neural networks (MCNN) and squeeze-and-excitation networks (SENet) combined with the gated recurrent unit (GRU), called MCNN-SE-GRU, is proposed to predict the periodic displacement and random displacement. In the model, the MCNN block is designed to extract three convolutional kernels of different scales to form receptive fields of different sizes and obtain global and local trigger factor characteristics. The SE block builds dependencies between channels by learning global and local information. By dynamically adjusting the weights of the channels of each feature, important features are reinforced, and non-important features are suppressed. Then, the GRU block is used for feature extraction of dependencies between temporal data. Finally, the feature fusion block is used to stitch the multi-featured vectors and linear regression is used to calculate the final displacement prediction values. Taking the Baijiabao Landslide in the Three Gorges of China as an example, data from two monitoring points with the maximum and minimum displacement changes were selected to reflect the sensitivity of model predictions and a comparative analysis was conducted with four mainstream models, four latest prediction models, and three different combinations of models. The results show that the root-mean-square error (RMSE) of MCNN-SE-GRU was 2.50 mm and 2.33 mm, respectively. Compared with the mainstream models, the prediction performance of MCNN-SE-GRU was at least improved by 66.44 % and 76.05%. Compared with the latest models, the prediction performance of MCNN-SE-GRU was at least enhanced by 23.31% and 11%. It has been verified that our method can effectively suppress the random fluctuations of the prediction results during the creeping period of landslide displacement and accurately predict when a steplike deformation occurs, providing a more effective means of predicting the risk warning during the intense deformation period of landslides.

Given the significant disparity in material properties between seabed soil and structural foundation, accurate description of the mechanical behavior at soil-structure interface is crucial. This study performed several cyclic interface shear tests to investigate the strength and deformation characteristics at the silty sand-steel interface under multiple boundary conditions. The shear strength, volumetric deformation, mobilized friction angle, and liquefaction trend at the interface were quantified. The increase in fines content transitions the soil skeleton from sand-sand contact to fine-sand, fine-fine contact, shifting the shear behavior from alternating dilation and contraction to dominant contraction. As the number of cycles increases, the differences in both cumulative and cyclic components of normal displacement across successive cycles diminish due to the degradation of interfacial restorability, accompanied by reduction in phase transformation stress. Tighter interaction of soil particles under high-stress condition enhances the liquefaction resistance, while increasing cyclic amplitude allows interfacial dilatancy to be more fully expressed, each contributing to a delayed onset of liquefaction. By introducing characteristic cycles that incorporate the effects of fines content, initial normal stress, and cyclic amplitude, an interface liquefaction formula is formulated to characterize the rapid liquefaction failure at the interface.

This study investigates the application of plastic optical fiber (POF) technology in geological engineering, especially for monitoring soil moisture at real-time during water infiltration. Characterized by high sensitivity and stability, POF sensors offer a new solution to accurate measurement of in-situ water contents at specific points in soils. In this study, a series of tests were first performed using a POF sensor to measure changes in light intensity with changes in the saturation degree of three types of soils with various densities. Moreover, soil column infiltration tests were conducted to simulate practical scenarios. As a result, it was confirmed that the change in light intensity detected by the POF sensor is linearly related to soil moisture. Additionally, it was found that the performance of the POF sensor allows for more detailed measurements at specific points than the widely used ECH2O EC5 soil moisture sensor. These features make the POF technology particularly useful for monitoring micro-changes in soil moisture, which are important for early landslide prediction. This study also presents significant potential for integrating the POF sensors into field applications, providing a reliable tool for disaster prevention and infrastructure safety.