It is necessary to fully understand the settlement of high-speed railway subgrade induced by train loading to ensure the operation safety of high-speed trains. A 1:7 reduced-scale model test was designed to investigate the settlement of subgrade under two loading methods: continuous and intermittent cyclic loading. The testing results show that an increase in load amplitude enhances the load transmission effect to the bottom of the subgrade. After 105 cycles of continuous loading, the cumulative settlement of the subgrade at depth of 0, 20, and 40 cm directly below the loading range is 3.247, 1.05, and 0.09 mm, respectively, showing significant decreases with depth. A significant rebound can be observed when the applied load is removed during the intermittent loading process, which is quite different from the results under condition of continuous loading. Thus, the intermittent effect of train load on the cumulative deformation of the subgrade cannot be ignored. In addition, to better predict the cumulative settlement of the subgrade, a prediction method based on the state evolution model was proposed and used to quantitatively analyze the testing observations. Based on the state evolution model, the predicted cumulative strains at depths of 0, 20, and 40 cm were 1.218%, 0.457%, and 0.047%, respectively, which are in good agreement with the experimental results of 1.099%, 0.48%, and 0.045%, indicating that the theoretical model can accurately predict the cumulative strain of the subgrade caused by train load. Additionally, the parameters of the state evolution model can be updated in a timely manner by applying the updated monitoring data to enhance the prediction accuracy. The current work provides an alternative method for predicting the long-term cumulative settlement of subgrade induced by the train loading, and also a basis for the optimization of high-speed railway subgrade design.

The construction of high-speed railway in Southwest China must traverse extensive regions of red mudstone. However, due to the humid subtropical monsoon climate in Southwest region, the red mudstone is often exposed to a high-water content or saturated state for extended time, and the poor mechanical properties under such condition cannot satisfy the requirements of high-speed railway subgrade. This paper proposes the use of lime and cement to improve the saturated unconfined compression strength (UCS) of the red mudstone fill material. Comprehensive tests, including UCS tests and scanning electron microscopy, were conducted on cement-lime modified red mudstone. Results show that lime stabilisation can significantly enhance the UCS and elastic modulus with the increase of dry density and modifier content. For the specimens with 4% lime and 6% cement, both peak strength and elastic modulus of the modified samples are more than 10 times higher than those of the untreated ones. The modulus exhibits nonlinear degradation with the development of shear stress, but the degradation can be improved with the increase of dry density and modifier content. At 60% of initial tangent modulus, the corresponding stress for untreated soil, lime stabilised and cement-lime modified filler are 0.74, 0.92 and 0.99. As for the energy evolution, the increasing dry density can enhance elastic and dissipated energies through denser particle arrangements, while a higher modifier content raises total energy. When the cement content is 6%, the total energy is more than 8 times higher than that of the untreated material, reflecting increased brittleness to a sudden fracture. The improvements are attributed to the formation of acicular and platy hydration products, which can tighten the pore structure. The study underscores the importance of lime and cement in ensuring subgrade stability for high-speed railways in Southwest China's red bed regions.

Temperature changes may cause irregular soil uplift or thawing settlements in frozen soil areas, potentially affecting the safe operation of High-Speed Railways (HSR). Analyzing and predicting these deformation characteristics is thus critical. However, the conventional forecasting and analysis techniques rarely considered factors such as dynamic parameter variations, uncertainties, and measurement errors, which hinder accurate regional scale forecasting. To bridge this gap, this paper introduces a novel time-series coupling method, which integrates post-processing deformation from Interferometric Synthetic Aperture Radar (InSAR) with a frost heave model (FHM), facilitated by the ensemble Kalman filter (EnKF) assimilation algorithm. We obtained deformation observations along the HSR using Persistent Scatterer InSAR (PS-InSAR) technology in combination with time series post-processing techniques. Considering the causative factors for deformation, we structured the FHM. By integrating FHM with observational data using the EnKF algorithm achieved an efficient upgrade of the posterior distribution of model parameters. This integration significantly improves the predictive accuracy, it facilitates an efficient update to the posterior distribution of model parameters, leading to enhanced prediction accuracy of our model. Our experimental results indicate that the effectiveness of this approach, with observational data assimilation into FHM reducing the average Root Mean Square Error (RMSE) to a mere 0.247 mm. Concurrently, both the Normalized Reduction Error Index (NER) and the Assimilation Efficiency Factor (EFF) values surpassed 0.60 and 0.84 respectively. These underlines signify a successful update of our model parameters, which in turn elevates the accuracy of future deformation predictions, thereby promising safer railway operations.