International Journal for Numerical and Analytical Methods in Geomechanics最新文献

Fractures are one of the most critical factors influencing the mechanical properties of rocks. To explore the quantitative description method of fracture networks in natural rock masses and achieve precise mathematical reconstruction of the stochastic distribution characteristics of natural fractures, the apparent fracture distribution characteristics of 499 fractures in 12 standard specimens were investigated. The results show that there is a significant correlation among the density, length, and dip angle of fractures in different directions. Based on this, a quantitative description method for fracture networks that considers the relationship between fracture density and orientation is proposed. Combined with the Fisher model, the probability density distribution function of natural fracture orientation density was established. Using this method, the equivalent numerical analysis model of rock specimens containing natural fractures was reconstructed on the RFPA platform, and numerical experiments of triaxial loading and unloading were performed on the reconstructed equivalent fractured rock numerical model. This method can quantitatively describe the geometric distribution characteristics of fractures in natural rocks. The modified Fisher model enables the visual reconstruction of natural fracture networks, offering an effective technical approach for building equivalent numerical analysis models of rocks with natural fractures. It is highly valuable for studying the coupled mechanical behavior of multi-physical fields in natural fractured rocks and provides an equivalent analysis method for visualizing and analyzing the damage process of natural fractured rocks.

This study proposes an efficient modeling approach for shield tunnel joints based on user-defined elements (UELs), which is applied to the analysis of transverse deformation in shield tunnels. The element stiffness matrix of longitudinal joints with irregular geometric configurations was derived under arbitrary loading conditions. The solution procedure of the stiffness matrix was then incorporated into the UEL algorithm framework. The developed element simultaneously accounts for the varying load state at longitudinal joints, geometric configurations of the joint, and material nonlinearity, as well as their coupling effect on the load-bearing capacity of the joint. Subsequently, the feasibility and accuracy of the UEL-based modeling approach were evaluated across multiple modeling scales. The results demonstrate that this element not only significantly simplifies the modeling process but also effectively captures the nonlinear characteristics of tunnel convergence deformation observed in practical engineering scenarios. In addition, the UEL-based modeling approach was employed to investigate the transverse deformation of shield tunnels subjected to an extreme surcharge–unloading–grouting rehabilitation sequence. Lining displacement–subgrade reaction and in situ stress state were appropriately incorporated into the numerical model. The effects of initial soil stiffness and the coefficient of earth pressure at rest on tunnel transverse deformation were quantitatively examined, along with the relationship between tunnel convergence and joint rotation. The results reveal a flag-shaped hysteresis in the moment-rotation response of tunnel joints under unloading and grouting, underscoring the importance of precisely capturing the multi-degree-of-freedom coupling in joint element for practical engineering applications.

Frequent occurrences of shield clogging during slurry shield tunneling emphasize the necessity of optimizing cutterhead scouring systems. Conventional studies largely rely on empirical design and simplified analyses, which fail to capture complex flow–solid interactions or enable quantitative optimization. To overcome these limitations, a computational fluid dynamics (CFD) model was developed to simulate jet flow formation in shield nozzles and the flow field in the cutterhead excavation zone. It allows to systematically investigate the effects of nozzle inlet velocity, slurry chamber pressure, and cutterhead rotation speed, promoting the optimization of nozzle geometry and arrangement. The optimized configuration has been validated in the Qingdao Second Submarine Tunnel. Results show that increasing inlet velocity enhances jet strength without altering the overall velocity distribution pattern. Cutterhead rotation generates a rotating flow field that intensifies scouring but causes jet deflection, while interference between central and adjacent nozzles limits the effective scouring area. By modifying the outlet geometry and eliminating ineffective main arm nozzles, both the effective scouring area ratio and scouring efficiency index were improved. The optimized configuration ensures stable and efficient advancement when the nozzle inlet velocity exceeds 4 m/s, effectively preventing shield clogging. This work provides a validated modeling framework and practical optimization strategy for enhancing slurry shield performance in complex geological conditions.

This study presents a semi-analytical solution for modeling suspended sediment distribution in turbulent flows within ice-covered channels under unsteady, non-equilibrium conditions. The solution is derived using the generalized integral transform technique (GITT). Validation was performed against the cell-centered finite volume method and existing experimental data. The results confirm high accuracy, supported by error analysis. Optimized parameter values were obtained through a hybrid genetic and interior point algorithm. Several underlying phenomena of particle-turbulence interactions in ice-covered channels are explored. The focus is on the influence of key sediment transport parameters on the time-dependent evolution of vertical concentration profiles of suspended sediment particles. Key findings indicate that increasing the settling-velocity correction coefficient raises sediment concentration profiles over time. In contrast, greater ice-cover roughness reduces sediment suspension. Sensitivity analysis highlights the inverse of the Schmidt number as a critical factor. This novel application of GITT and variance-based sensitivity analysis (VBSA) provides a detailed solution library, and serves as a benchmark for numerical models.

A novel analytical approach based on the state-space method (SSM) is proposed to facilitate the rapid and accurate analysis of the mechanical behavior of pipe umbrellas in shallow-buried tunnels. First, a mechanical analysis model and its governing equations are developed based on the Winkler elastic foundation beam theory, incorporating key construction-related factors such as the lag effect of primary support, differential stress release in the surrounding rock, and the elasto-plastic behavior of the stratum. The governing equations are then transformed into a concise matrix form using the SSM and solved based on matrix theory and the continuity conditions between adjacent beam segments. Analytical solutions for deformation and internal forces at any cross-section of the pipe umbrella are derived under the nonlinear interactions among the pipe umbrella, surrounding rock, and primary support. The accuracy and applicability of the proposed method are verified through comparisons with existing field monitoring data, analytical solutions, and numerical simulation results from other researchers. On this basis, taking the Aketepu Tunnel as a case study, the influences of the surrounding rock stiffness ahead of the tunnel face, excavation footage, steel pipe diameter, and other factors on the deformation and internal forces of the pipe umbrella were investigated, and a recommended design scheme was proposed accordingly. The scheme was subsequently applied in the field, and monitoring results showed that the maximum deformations at two sections were 26.1 and 22.3 mm, respectively, both within the acceptable limits for surrounding rock deformation control.

Shield tunnels in soft clay are highly susceptible to long-term uplift and differential settlement. To precisely control these deformations, this study develops a novel anisotropic cavity expansion model integrated with Mindlin's solution, forming a coupled 2D/3D segment–soil interaction framework. Validated against field data from Fuzhou Metro Line 4, the model demonstrates superior accuracy over traditional isotropic approaches. The results quantitatively reveal that: (1) in single-ring grouting, increasing the grouting burial depth from 5 to 15 m reduces invert uplift by 28%; (2) in planar multi-hole grouting, symmetric-spacing sequences effectively control segment displacements within 5 mm; and (3) in longitudinal multi-ring grouting, symmetric injection reduces maximum stress fluctuations by 12.5% compared to staggered grouting under a 5% grouting volume. The study concludes that the anisotropic soil–grout interaction is the primary mechanism governing deformation, and the proposed model provides a foundation for optimizing grouting parameters to ensure tunnel stability.

Shield tunneling involves complex soil-structure interactions, thereby leading to a normally time-consuming and labor-intensive finite element calculation. A submodel based method for predicting segment uplift during tunnel construction is proposed in this study, which can effectively reduce the computational cost. It initially focuses on determination of the submodel boundary, where plastic dissipation energy and its associated coefficient of variation are selected as criteria. Compared to traditional boundary determination methods based on soil disturbance degree, the proposed approach demonstrates great advantages in accuracy. Finite element simulations of tunnel excavation are thereafter performed for both homogeneous and composite geological strata models, where the applicability of the submodeling technique as well as the rationality of plastic dissipation energy criteria are verified. Building upon the computationally enhanced segment uplift dataset (optimized via submodel-driven temporal efficiency framework), a rigorous benchmarking of machine learning architectures is finally implemented, among which the LSTM shows the best prediction performance, with an R² value of 0.9 and RMSE of 0.02, fully demonstrating the superiority of the proposed method in predicting tunnel segment uplift.