There have been many railway construction projects in the loess region of China. Embankment is typically required for rail projects in these regions, since the railway basement is restricted by longitudinal slope requirements. However, there has been little study of the dynamic response of compacted loess embankment under moving train loading. The 2.5D finite element method was adopted to investigate this process and characterize the effects of train speed, height of embankment, and axle weight on the dynamic behavior of subgrade. A rectangular core zone of subgrade was determined, and a prediction model was established to evaluate the long-term settlement of embankment generated by moving train loading. The results showed that embankment height had negligible influence on the variation of dynamic stress. Decays of stress amplitude in both the vertical and horizontal directions slowed with increased train speed. Additionally, the dynamic stress increased linearly with the increase in axle weight due to the linear stress-strain relationship of soil. In the practical speed range (≤ 100 m/s), the dynamic influence depth increased with increasing speed in a range of 3–6 m. A core zone depth of 6 m reflects the effects of moving train loading, with a width of 4 m. For practical conditions (v ≤ 100 m/s), only slight settlement of embankment was observed (≤ 6 mm). However, it is difficult to achieve the same physical parameters used in the experiments (moisture content and compaction degree) in engineering practice. Further work should explore long-term dynamic settlement with relation to the degree of compaction of the embankment.

A screw pile is a special-shaped pile with several advantages, including good bearing capacity, economy, and rapid construction. The calculation of the screw piles’ ultimate bearing capacity in the individual bearing failure state remains controversial. To address the problems of an unclear failure mechanism and the pile–soil contact relationship in screw piles, we conducted large-scale direct shear tests using a partial amplification method. The variation law for soil stress and the failure pattern of soil around the screw teeth were analyzed. The bearing capacity of the screw shear plate with screw teeth was found to be significantly higher than that of the plane shear plate, while that of the screw pile first increased and then decreased with an increase in the screw pitch. The optimal screw pitch allowed the determination of the maximum bearing capacity. Furthermore, the optimal screw pitch was generally equal to the critical screw pitch, which distinguished the individual bearing failure from the cylindrical shearing failure. A new calculation method for the critical screw pitch and ultimate bearing capacity in the individual bearing failure state was presented, and its rationality was proved using the direct shear test results. The calculation of the critical screw pitch considers the shear strength of soil and the geometric parameters of the screw teeth, making it more widely applicable. These results can provide a theoretical basis for the subsequent design of screw piles.

To address the complex pile–soil interaction mechanisms in predicting the compressive bearing capacity of HSCM piles (Helix Stiffened Cement Mixing piles) in marine soft soil regions, this study proposes an intelligent prediction method based on a GA-BPNN (Genetic Algorithm-Optimized Back Propagation Neural Network). A high-quality database comprising 1243 data points was established through finite element numerical simulations. By integrating data preprocessing techniques and the GA-BPNN model, the study systematically investigated the influence of helical blade spacing H₁ and H₂, strength ratio C_ref/S_u, and diameter ratio D_sc/D_H on bearing capacity. The results demonstrate that the GA-BPNN model achieves a prediction accuracy of 99.07%, with a mean squared error (MSE) of 7.20 × 10⁻³ and a coefficient of determination R² of 0.990. SHAP value analysis reveals that the strength ratio and diameter ratio are the dominant factors, exhibiting nonlinear relationships with bearing capacity characterized by saturation effects and threshold-dependent behavior. Laboratory tests further confirm strong correlations between cement–soil strength C_ref, formed pile diameter D_sc, and bearing capacity. The findings indicate that the GA-BPNN model provides an efficient and accurate approach for predicting the bearing capacity of HSCM piles, offering a reliable basis for engineering parameter optimization.

Surcharge loading compromises the original stress state of soil strata, generating detrimental additional stresses on the tunnel that critically threaten operational safety. Given this, the tunnel is equated to the Timoshenko beam resting on the three-parameter Kerr foundation model for this study. The theoretical models of the existing shield tunnel structural response under surcharge, considering and ignoring the impact of lateral soil, are proposed and solved using finite difference method. On this basis, the parameter sensitivity analysis is conducted. Finally, the prediction formula for the vertical deformation of the existing tunnel under surcharge is developed. The results show that the calculation results obtained by proposed theoretical models match well with the observation results from the finite-element method, existing analytical method, and field-measured data. In particular, the theoretical model considering the impact of lateral soil has higher calculation accuracy. Meanwhile, the parameter analysis shows that an increase in the area and amount of the surcharge causes increasing the tunnel longitudinal displacement. Conversely, increasing the elastic modulus of soil, the tunnel buried depth and the distance between the tunnel axis and the loading center decreases the tunnel longitudinal displacement. The proposed prediction formula has sufficient engineering accuracy and can serve as a valuable tool for quickly calculating the existing tunnel longitudinal deformation under surcharge.