Search Results (1,247)

Accurate reconstruction of train collision accidents is essential for understanding impact conditions, assessing crashworthiness, and supporting safety improvements. This study proposes a surrogate-based optimization framework for reconstructing structural damage in train collisions from post-accident observations. The pre-impact kinematic state, expressed by a six-dimensional vector of relative offsets, rotations, and impact velocity, is formulated as an inverse problem in which a Sum of Squared Relative Deviations (SSRD) between measured and simulated residual deformations serves as the objective function. A reduced two-vehicle finite element (FE) model is developed to capture the dominant impact dynamics, an Optimal Latin Hypercube Design is used to sample the parameter space, and a Kriging surrogate model is constructed to approximate the response. A simulated annealing algorithm is applied to search for the global minimum. The framework is demonstrated on a real high-speed rear-end collision of electric multiple units. The Kriging model achieves a coefficient of determination of about 0.85, and the optimized kinematic state yields FE-predicted residual deformations that agree with field measurements at key locations to within about 5%. The results show that the method can efficiently reconstruct physically plausible collision scenarios and provide insight into parameter sensitivity and identifiability for railway safety analysis. Full article

Rolling contact fatigue and wear of wheel–rail systems are critical factors affecting the safety of high-speed railways and have long been key research topics in materials science. This paper reviews the theoretical foundations of wheel–rail rolling contact fatigue, introduces representative experimental methods for studying rolling contact fatigue, and discusses the stress–strain problems in wheel–rail contact. Additionally, it provides a detailed overview of the emerging computational simulation approach for rolling contact fatigue wear, summarizes commonly used simulation software and their respective characteristics, and analyzes material factors influencing rolling contact fatigue simulations in wheel–rail steels. Finally, based on the classification of rolling contact fatigue algorithms, various measures are proposed to enhance rapid and accurate detection and evaluation. Full article

Polyester yarn bundle geogrids are widely used materials in flexible retaining structures due to their high toughness and high-strength mechanical properties. To investigate the mechanical characteristics and the interfacial mechanical properties of these geogrids, a series of pull-out tests were conducted under different pull-out rates and filling water contents. Based on the test results, a DEM-FDM coupled numerical model for pull-out behavior was established to analyze the pull-out deformation behavior of the geogrids. Combined with the theoretical analysis of the load-bearing characteristics of the geogrids, the reinforcement mechanism of polyester yarn bundle geogrids was revealed. The results show that there exists a critical pull-out rate of 1 mm/min that maximizes the pull-out resistance; the interface friction angle decreases with an increase in pull-out rate, while the interface cohesion shows an opposite trend. The filling water content presents a more significant weakening effect on the soil–geogrid interface strength under low stress, resulting in a strain-softening type of pull-out curve. Unlike fine-ribbed plastic geogrids, the sliding frictional resistance of polyester yarn bundle geogrids accounts for 80% of the total pull-out resistance during the pull-out process. The mechanical interlocking force, which arises from the bulges on the mid-section of transverse ribs and the downward bending of longitudinal rib edges, is subject to dynamic changes in the course of the pull-out process. The geogrid exhibits overall shear failure under low normal stress (${\sigma }_n<$ 200 kPa) and penetration shear failure under high normal stress (${\sigma }_n\ge$ 200 kPa). In practical engineering installation, polyester yarn bundle geogrids should be placed as parallel as possible to maximize the frictional resistance with filled soil and should take care of the geogrid joints for enhanced durability of the geogrids. Full article

To address the problem of the shortage of delivery drivers in the transportation sectors in Japan, this study explores the potential of the crowdshipping concept through the utilization of Shinkansen trains. This concept allows the passengers of the Shinkansen to transport parcels during their journey in exchange for monetary rewards. This allows the logistics companies to shift some of their long-distance shipments from trucks to high-speed rail, reducing delivery costs and greenhouse gas emissions. We formulate a cooperative game with side payments to evaluate the profitability of the scheme and design fair profit-sharing rules among the logistics company, the railway operator, and participating passengers. We use game-theoretic solution concepts, such as the Shapley value and nucleolus, to accomplish this. Numerical experiments using Sagawa Express and JR Central data suggest that under high passenger participation rates, a substantial portion of parcels on the Tokyo–Osaka corridor could be handled via crowdshipping, maintaining or improving profitability for all stakeholders while reducing CO₂ emissions relative to conventional truck-based delivery. Full article

This study introduces a mesoscale modeling methodology for polyurethane-solidified ballast beds (PSBBs) that eliminates reliance on X-ray computed tomography (XCT) and addresses constraints in specimen size, capital cost, and post-processing complexity. The approach couples the Discrete Element Method (DEM) with the Finite Element Method (FEM). A high-fidelity discrete-element geometry is reconstructed from three-dimensional laser scans of ballast particles. The virtual-ray casting algorithm is then employed to identify the spatial distribution of ballast and polyurethane and map this information onto the finite-element mesh, enabling heterogeneous material reconstruction at the mesoscale. The accuracy of the model and mesh convergence are validated through comparisons with laboratory uniaxial compression tests, determining the optimal mesh size to be 0.4 times the minimum particle size (0.4 D_min). Based on this, a parametric study on the effect of sleeper width on ballast bed mechanical responses is conducted, revealing that when the sleeper width is no less than 0.73 times the ballast bed width (0.73 W_b) an optimal balance between stress diffusion and displacement control is achieved. This method demonstrates excellent cross-material applicability and can be extended to mesoscale modeling and performance evaluation of other multiphase particle–binder composite systems. Full article

The geometric precision of ballastless tracks critically determines the performance and safety of high-speed railways. Traditional manual fine adjustment methods remain labor-intensive, iterative, and sensitive to human expertise, making it difficult to achieve sub-millimeter accuracy and global consistency. To address these challenges, this paper proposes a virtual-model–enabled pre-adjustment framework for high-speed ballastless track construction. The framework integrates a dual-frame SLAM-based and multi-sensor measurement system based on RC-SLAM principles and a local attitude compensation model, enabling accurate 3D mapping and reconstruction of long-track segments under extended-range and GNSS-denied conditions typical of linear infrastructure scenarios. A constraint-based global optimization algorithm is further developed to transform empirical fine adjustment into a computable geometric control problem, generating executable adjustment configurations with engineering feasibility. Field validation on a 1 km railway section demonstrates that the proposed method achieves sub-millimeter measurement accuracy, improves adjustment efficiency by over eight times compared with manual operations, and reduces material waste by $2800–$7000 per kilometer. This paper demonstrates a previously unexplored execution-level workflow for long-rail fine adjustment, establishing a closed-loop paradigm from measurement to predictive optimization and paving the way for SLAM-driven, simulation-based, and multi-sensor–integrated precision control in next-generation railway construction. Full article

Periodically supported beams are widely employed in engineering structures, where effective control of low-frequency vibration and noise is often required. To achieve broadband elastic wave manipulation, an inertial amplification (IA) mechanism was introduced to generate low-frequency and ultra-wide bandgaps. Based on the Timoshenko beam theory, analytical models for flexural wave propagation in periodically supported beams with IA structures were established using the generalized state transfer matrix method and the Floquet transform method, respectively. The validity of the analytical models was verified by vibration transmission analysis using a finite element model. The results demonstrate that the Floquet transform method enables rapid and accurate solution of the wave model. The introduction of the IA mechanism can generate low-frequency bandgaps, which are most sensitive to the amplification angle and amplification mass. The bandgap formation mechanism arises from the modulation of Bragg scattering in the periodically supported beam by the IA structure. This modulation causes the standing wave mode frequencies to shift to lower frequencies, thereby widening the bandgaps. Furthermore, hybrid IA structure configuration can achieve broader bandgaps, facilitating elastic wave control in the ultra-wide low-frequency range. These findings provide valuable insights for low-frequency vibration and noise attenuation in engineering structures. Full article

Dense and complex underground structures impose stringent requirements on shield tunneling. In the close-proximity construction of super-large-diameter shield tunnels, challenges may arise, including adverse impacts on the normal operation of existing structures, as well as difficulties in ensuring the bearing capacity and deformation control of these structures during excavation. This study, based on the stratigraphic conditions of the Chengdu area, employs FLAC3D 7.0 version software to simulate the section where the Shuanghua Road Tunnel underpasses both Metro Line 10 and the Chengdu-Guiyang High-Speed Railway. The main conclusions are as follows: (1) Tunnel underpassing induces uneven settlement in the metro tunnel, with a maximum settlement reaching 47.7 mm. The settlement trough exhibits a twin-peak morphology during dual-line construction. When a single super-large-diameter tunnel line crosses the existing structural cluster, the maximum settlement is located directly above the crossing point. During dual-line crossing, the maximum settlement shifts towards the midpoint between the two new tunnel lines. (2) As the left line of the new tunnel approaches the existing structure, the cross-sectional deformation of the existing structure is “pulled” towards the direction of the excavated new tunnel. After the new left line moves away, the cross-sectional deformation gradually recovers to a bilaterally symmetrical state. (3) The tunnel cross-section undergoes dynamic “compression-tension” convergence changes during the construction process, with a maximum longitudinal tensile convergence of −1.28 mm. (4) During the underpassing of the existing structural cluster by the super-large-diameter tunnel, the maximum torsion angle is approximately −0.016°, occurring at the moment when the shield machine head first passes directly beneath, located directly above the new tunnel. The torsion angle of the existing structure is greatest during the first underpassing event, and the maximum torsion angle during the second underpassing is lower than that during the first. This study reveals the composite deformation mode of “settlement-convergence-torsion” during the underpassing of existing structural clusters by super-large-diameter shield tunnels, providing a theoretical basis for risk control in similar adjacent engineering projects. Full article

The electrical resistivity and acoustic properties of marine sediments are essential for understanding their physical and mechanical behavior. Over recent decades, significant advancements have been made in both in situ and laboratory measurement techniques, alongside theoretical models, to establish correlations between these geophysical parameters and sediment properties such as porosity, saturation, and consolidation degree. However, a comprehensive comparison of the advantages, limitations, and applicability of different measurement methods remains underexplored, particularly in complex scenarios such as gas hydrate-bearing sediments. This review provides an in-depth synthesis of recent developments in in situ and laboratory testing technologies for assessing the resistivity and acoustic characteristics of marine sediments. Special emphasis is placed on the latest advances in acoustic measurements during gas hydrate formation and decomposition. The review highlights key challenges, including (1) limited vertical resolution in in situ resistivity measurements due to probe geometry; (2) errors arising from electrode polarization and poor soil–electrode contact; and (3) discrepancies in theoretical models linking geophysical parameters to sediment properties. To address these challenges, future research directions are proposed, focusing on optimizing electrode array designs for high-resolution resistivity measurements and developing non-destructive acoustic techniques for deep-sea sediments. This work offers a critical reference for marine geophysics and offshore engineering researchers, aiding the selection and development of testing technologies for effective marine sediment characterization. Full article

In high-speed railways, the reliability of jointless track circuits largely hinges on the operational integrity of compensation capacitors. These capacitors are periodically installed along the track to mitigate rail inductive impedance and stabilize signal transmission. The induced voltage response, referred to as the compensation-capacitor signal, serves as a critical diagnostic indicator of circuit health. Yet it is often distorted by electromagnetic interference and structural resonance, posing significant challenges for robust feature extraction. To address this challenge, we propose a Disturbance-Robust Feature Distillation (DRFD) framework that performs multi-perspective modeling and validation of robust features. The framework formulates a unified multi-objective optimization model that jointly considers statistical significance, environmental stability, and structural separability. These objectives are harmonized through an adaptive Bayesian weighting mechanism, enabling automatic identification of disturbance-resistant and discriminative features under complex operating conditions. Experimental evaluations on real-world datasets collected at a 100 kHz sampling rate from roadbed, tunnel, and bridge environments demonstrate that the DRFD framework achieves 96.2% accuracy and 95.4% F1-score, outperforming the best-performing baseline by 4.2–7.8% in accuracy and 6.5% in F1-score. Moreover, the framework achieves the lowest cross-condition relative variance (RV < 0.015), confirming its high robustness against electromagnetic and structural disturbances. The extracted core features—Root Mean Square (RMS), Peak Factor (PF), and Center Frequency (CF)—faithfully capture the intrinsic electromagnetic behaviors of compensation capacitors, thus linking statistical robustness with physical interpretability for enhanced reliability assessment of railway signal systems. Full article

A comfortable, reliable, safe and environmentally friendly high-speed train journey that saves time and offers an unforgettable experience for passengers is not a dream. Passengers can enjoy panoramic views, delicious cuisine and use their mobile devices without restrictions. High-speed trains, powered by environmentally friendly methods, are a sustainable form of transport, reducing harmful emissions. Integrating intelligent control and management into railway networks has the capacity to increase efficiency and improve reliability and safety, as well as reduce development and maintenance costs. Future intelligent railway network architectures are expected to focus on integrated, multi-layered systems that deeply embed artificial intelligence (AI), the Internet of Things (IoT) and advanced communication technologies (5G/6G) to ensure intelligent operation, improved reliability and increased safety. Distributed intelligent control in railways refers to an advanced approach in which decision-making capabilities are distributed across network components (trains, stations, track sections, control centers) rather than being concentrated in a single central location. The recent advances in AI in railways are associated with numerous scientific papers that enable intelligent traffic management, automatic train control, and predictive maintenance, with each of the proposed intelligent solutions being evaluated in terms of key performance indicators such as latency, reliability, and accuracy. This study focuses on how different intelligent solutions in railways can be implemented in network components based on the requirements for real-time control, near-real-time control, and non-real-time operation. The analysis of related works is focused on the proposed intelligent railway frameworks and architectures. The description of typical use cases for implementing intelligent control aims to summarize latency requirements and the possible distribution of control logic between network components, taking into account time constraints. The considered use case of automatic train protection aims to evaluate the added latency of communication. The requirements for the nodes that host and execute the control logic are identified. Full article

Covered karst collapse is a key geotechnical hazard in infrastructure construction in karst regions of China. In particular, strata consisting of an overlying clay layer and an underlying sand layer are prone to abrupt collapse induced by sand leakage under construction disturbances, which poses serious risks to pile foundation safety. To clarify the disaster-forming mechanism and develop a quantitative analysis method, this study investigates the mechanical behaviour of the entire collapse process by combining theoretical analysis with numerical simulation. A continuous mechanical analysis framework is established that follows the sequence from sand layer leakage to cavity expansion and then clay layer instability. Within this framework, a calculation model for the angle of repose of the sand layer is proposed that considers seepage and confined pressure effects. Simultaneously accounting for the influence of the casing, stability models for overall and localised collapses are developed using limit equilibrium theory. A comprehensive safety factor criterion K_c based on the critical span (or radius) is then proposed, leading to a linked evaluation method that couples the potential span of the sand layer with the ultimate span of the clay layer. The results show that an increase in Δh/h significantly reduces the angle of repose of the sand layer; the mechanical mechanism is confirmed whereby an increase in the roof span leads to shear stress exceeding the soil’s shear strength, thus triggering instability; the proposed safety factor K_c can effectively predict both overall and localised collapse, and case verification demonstrates that the predicted spans match well with actual collapse dimensions. The results provide a theoretical and technical basis for risk prediction, as well as for the prevention and control of pile foundation construction in karst areas. Full article

To enhance line capacity in high-speed railways without new infrastructure, virtual coupling train sets (VCTSs) enable reduced inter-train distances via real-time communication and cooperative control. However, unknown disturbances and model uncertainties challenge VCTS performance, often causing chattering, slow convergence, and poor disturbance rejection. This paper proposes a novel finite-time extended state observer-based nonsingular terminal sliding mode (FTESO-NTSM) control strategy. The method integrates a nonsingular terminal sliding mode surface with a hyperbolic tangent-based reaching law to ensure fast convergence and chattering suppression, while a finite-time extended state observer estimates and compensates for lumped disturbances in real time. Lyapunov analysis rigorously proves finite-time stability. Numerical simulations under different initial statuses are conducted to validate the effectiveness of the proposed method. The results show that the maximum observation error achieves 0.0087 kN. The speed chattering magnitudes reach 0.00087 km/h, 0.0017 km/h, 0.0026 km/h, and 0.0034 km/h for the leading train and three followers, respectively. Furthermore, the convergence time of the followers is 56 s, 130 s, and 76 s, respectively. The results highlight that the proposed method can significantly improve line capacity and transportation efficiency. Full article

Feeder buses play an important role in supporting the accessibility of high-speed railway stations which leads to the improved efficiency of the transportation system. This paper proposes a new optimization technique for the design of feeder bus routes to the stations. It uses dynamic programming with a pulse algorithm seeking to maximize the number of serviced people considering the distance between the urban areas and high-speed railway station. The proposed algorithm was tested in a hypothetical network to find the optimum solutions and the running time needed. Moreover, the algorithm was applied to a real network as a case study in Aswan city, Egypt. Our results demonstrated significant improvements in the route design accuracy and efficiency. By applying the proposed algorithm, the potential demand values increased from 19.8% to 37.9% with a reasonable decrease in the running time compared to the literature. This research contributes to the advancement of transportation planning strategies by providing valuable insights into the optimization of feeder bus systems. The proposed model contributes to the scientific re-search and practical implementation by promoting a coordinated development of high-speed railway stations and urban areas. This may enhance the Egyptian high-speed railway technology, yielding substantial economic and social benefits. Full article

Reliable state estimation in railway environments presents significant challenges due to geometric degeneracy resulting from repetitive structural layouts and point cloud sparsity caused by high-speed motion. Conventional LiDAR-based SLAM systems frequently suffer from longitudinal drift and mapping artifacts when operating in such feature-scarce and dynamically complex scenarios. To address these limitations, this paper proposes SERail-SLAM, a robust semantic-enhanced multi-sensor fusion framework that tightly couples LiDAR odometry, inertial pre-integration, and GNSS constraints. Unlike traditional approaches that rely on rigid voxel grids or binary semantic masking, we introduce a Semantic-Enhanced Adaptive Voxel Map. By leveraging eigen-decomposition of local point distributions, this mapping strategy dynamically preserves fine-grained stable structures while compressing redundant planar surfaces, thereby enhancing spatial descriptiveness. Furthermore, to mitigate the impact of environmental noise and segmentation uncertainty, a confidence-aware filtering mechanism is developed. This method utilizes raw segmentation probabilities to adaptively weight input measurements, effectively distinguishing reliable landmarks from clutter. Finally, a category-weighted joint optimization scheme is implemented, where feature associations are constrained by semantic stability priors, ensuring globally consistent localization. Extensive experiments in real-world railway datasets demonstrate that the proposed system achieves superior accuracy and robustness compared to state-of-the-art geometric and semantic SLAM methods. Full article