Statistical distribution of residual fatigue life (RFL) of railway axles under given loading was computed using the Monte Carlo method by considering random variation of the selected input parameters. Experimental data for the EA4T railway axle steel, the loading spectrum, the press fit loading and the residual stress induced by surface hardening were considered in the crack propagation simulations. Usually, the material properties measured by tensile tests are considered to be the most informative source of material data. Under fatigue loading, however, the crack growth rates near the threshold are the most critical data. Two important influencing factors on these crack growth rates are presented: first, the air humidity and, second, the near-surface residual stress. The typical variation of these parameters in operation may change the RFL by one or two orders of magnitude. Experimentally obtained crack growth thresholds and residual stress profiles are highly affected by the used methodology. Therefore, the obtained input data may be located anywhere within a large scatter, while the experimenters are completely unaware of it. This can lead to dangerously non-conservative situations, e.g. when the thresholds are measured in a laboratory under humid air conditions and then applied to predictions of RFLs of axles operated in winter in low air humidity. This is significant for the topic of inspection interval optimisation. The results of experiments done on real 1:1 railway axles were close to the most frequent value found in the histogram of the numerically computed RFLs.

The characterization of track irregularities is crucial in railway dynamics, as track irregularities are the primary source of internal excitation in railway systems. In this paper, three mathematical models are proposed to characterize the track irregularities under different circumstances. The first model is a novel explicit track spectrum function, which performs better in reflecting the inherent periodic components of track irregularities than the existing track spectra. On this foundation, the second model, a parameterized track spectrum random model, is proposed to represent the vast measured track irregularities from the probabilistic perspective. Finally, the third model, an imprecise track spectrum interval model based on a neighborhood uniform sampling Bootstrap method, is presented to identify the confidential interval of the track spectra when the track irregularity data are limited. Three examples are illustrated to demonstrate the feasibility of the three track irregularity models in characterizing the track irregularities in different conditions. This research can help capture the railway deformation status and optimize track maintenance strategies.

The dynamic characteristics of the track system can directly affect its service performance and failure process. To explore the load characteristics and dynamic response of the track system under the dynamic loads from the rack vehicle in traction conditions, a systematic test of the track subsystem was carried out on a large-slope test line. In the test, the bending stress of the rack teeth, the wheel–rail forces, and the acceleration of crucial components in the track system were measured. Subsequently, a detailed analysis was conducted on the tested signals of the rack railway track system in the time domain and the time–frequency domains. The test results indicate that the traction force significantly affects the rack tooth bending stress and the wheel–rail forces. The vibrations of the track system under the traction conditions are mainly caused by the impacts generated from the gear–rack engagement, which are then transferred to the sleepers, the rails, and the ballast beds. Furthermore, both the maximum stress on the racks and the wheel–rail forces measured on the rails remain below their allowable values. This experimental study evaluates the load characteristics and reveals the vibration characteristics of the rack railway track system under the vehicle’s ultimate load, which is very important for the load-strengthening design of the key components such as racks and the vibration and noise reduction of the track system.

Railway noise barriers are an essential piece of infrastructure for reducing noise propagation. However, these barriers experience aerodynamic loads generated by high-speed trains, leading to dynamic effects that may compromise their fatigue capacity. The most common structural design for railway noise barriers consists of vertical configurations of posts and panels. However, there have been few dynamic analyses of steel post/wood panel noise barriers under train-induced aerodynamic loads. This study used dynamic finite element analysis to assess the dynamic behavior of such noise barriers. Analysis of a 40-m-long noise barrier model and a triangular simplified load model, the latter of which effectively represented the detailed aerodynamic load, were first used to establish the model and input of the moving load during dynamic simulation. Then, the effects of different parameters on the dynamic response of the noise barrier were evaluated, including the damping ratio, the profile of the steel post, the span length of the panel, the barrier height, and the train speed. Gray relational analysis indicated that barrier height exhibited the highest correlations with the dynamic responses, followed by train speed, post profile, span length, and damping ratio. A reduction in the natural frequency and an increase in the train speed result in a higher peak response and more pronounced fluctuations between the nose and tail waves. The dynamic amplification factor (DAF) was found to be related to both the natural frequency and train speed. A model was proposed showing that the DAF significantly increases as the square of the natural frequency decreases and the cube of the train speed rises.

The current technical standards primarily relied on experience to judge the interfacial bonding properties between the self-compacting concrete filling layer and the steam-cured concrete precast slab in CRTS III slab ballastless track structure. This study sought to enhance technical standards for evaluating interfacial bonding properties by suggesting the use of the splitting tensile strength to evaluate the impact of bubble defects. Specimens were fabricated through on-site experiment. The percent of each area of 6 cm² or more bubble defect was 0 in most of specimens. When the cumulative area of all bubble defects reached 12%, the splitting tensile strength value was 0.67 MPa, which exceeded the minimum required value of 0.5 MPa for ensuring bonding interface adhesion. Furthermore, when the cumulative area of all bubble defects reached 8%, the splitting tensile strength value was 0.85 MPa, which exceeded the minimum required value of 0.8 MPa, thereby overcoming the negative impact of each area of 10 cm² or more bubble defect. Additionally, keeping the cumulative area of each area of 6 cm² or more bubble defect below 6% ensured adequate bonding strength and reduced the occurrence of specimens with lower splitting tensile strength values.

To ensure the compatibility between rolling stock and infrastructure when dynamically assessing railway bridges under high-speed traffic, the damping properties considered in the calculation model significantly influence the predicted acceleration amplitude at resonance. However, due to the normative specifications of EN 1991-2, which are considered to be overly conservative, damping factors that are far below the actual damping have to be used when predicting vibrations of railway bridges, which means that accelerations at resonance tend to be overestimated to an uneconomical extent. Comparisons between damping factors prescribed by the standard and those identified based on in situ structure measurements always reveal a large discrepancy between reality and regulation. Given this background, this contribution presents a novel approach for defining the damping factor of railway bridges with ballasted tracks, where the damping factor for bridges is mathematically determined based on three different two-dimensional mechanical models. The basic principle of the approach for mathematically determining the damping factor is to separately define and superimpose the dissipative contributions of the supporting structure (including the substructure) and the superstructure. Using the results of a measurement campaign on 15 existing steel railway bridges in the Austrian rail network, the presented mechanical models are calibrated, and by analysing the energy dissipation in the ballasted track, guiding principles for practical application are defined. This guideline is intended to establish an alternative to the currently valid specifications of EN 1991-2, enabling the damping factor of railway bridges to be assessed in a realistic range by mathematical calculation and thus without the need for extensive in situ measurements on the individual structure. In this way, the existing potential of the infrastructure with regard to the damping properties of bridges can be utilised. This contribution focuses on steel bridges, but the mathematical approach for determining the damping factor applies equally to other bridge types (concrete, composite, or filler beam).

The spatial offset of bridge has a significant impact on the safety, comfort, and durability of high-speed railway (HSR) operations, so it is crucial to rapidly and effectively detect the spatial offset of operational HSR bridges. Drive-by monitoring of bridge uneven settlement demonstrates significant potential due to its practicality, cost-effectiveness, and efficiency. However, existing drive-by methods for detecting bridge offset have limitations such as reliance on a single data source, low detection accuracy, and the inability to identify lateral deformations of bridges. This paper proposes a novel drive-by inspection method for spatial offset of HSR bridge based on multi-source data fusion of comprehensive inspection train. Firstly, dung beetle optimizer-variational mode decomposition was employed to achieve adaptive decomposition of non-stationary dynamic signals, and explore the hidden temporal relationships in the data. Subsequently, a long short-term memory neural network was developed to achieve feature fusion of multi-source signal and accurate prediction of spatial settlement of HSR bridge. A dataset of track irregularities and CRH380A high-speed train responses was generated using a 3D train–track–bridge interaction model, and the accuracy and effectiveness of the proposed hybrid deep learning model were numerically validated. Finally, the reliability of the proposed drive-by inspection method was further validated by analyzing the actual measurement data obtained from comprehensive inspection train. The research findings indicate that the proposed approach enables rapid and accurate detection of spatial offset in HSR bridge, ensuring the long-term operational safety of HSR bridges.

This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways, aiming to support the development of concrete capable of withstanding higher operational speeds. Fatigue tests were conducted at loading frequencies ranging from 5 to 40 Hz, with a focus on fatigue life, damage evolution, energy dissipation, and residual fatigue strain in the concrete. The results indicate that between 5 and 15 Hz, the fatigue life and energy dissipation remain relatively stable, with minimal damage evolution and small residual strains. As the frequency increases to 15–20 Hz, the fatigue life and energy dissipation gradually decrease, while damage accumulation and residual strain increase. Beyond 20 Hz, both fatigue life and energy dissipation decrease rapidly, damage accumulation becomes more pronounced, and residual strain continues to rise. These phenomena are primarily attributed to the increased strain rate and load change rate at higher frequencies, which affect the microstructure evolution and lead to reduced fatigue performance.

Since the view that the localized rail third-order bending mode can cause high-order polygonization (mainly 18–23) of high-speed train wheels was put forward in 2017, many scholars have attempted to link a connection between the localized rail bending modes and wheel polygonization phenomenon and polygonal wheel passing frequency. This paper first establishes a flexible track model considering the structural and parametric characteristics of fasteners, verifies the model by using vehicle tracking test data, then investigates the influence of fastener parameter matching on the localized rail bending modes, and obtains the following conclusions: (1) There is nearly a 1:1 mapping relationship between the localized rail bending modal frequency and polygonal wheel passing (PWP) frequency, which supports that the localized rail bending mode is one of the causes of wheel polygonization. (2) The iron plate of the fastener system plays a role of dynamic vibration absorber in the vehicle-rail coupled system, and the fastener parameters significantly influence the localized rail bending modal vibration. Finally, this paper proposes a design principle of a high-frequency vibration-absorbing fastener, which provides a feasible solution to mitigate the localized rail bending modal vibration and high-order wheel polygonization. Meanwhile, it points out that this measure may induce other high-frequency vibration problems, e.g., aggravating modal vibration above 800 Hz. Further, this paper proposes a concept of differentiated arrangement of fasteners, suggesting that different high-frequency vibration-absorbing fasteners be installed in different sections of the whole line to make the localized rail bending modal frequency of the whole line disordered, thus disrupting and further mitigating the development of the wheel polygonization.

The diversion effect caused by the linked structure in a metro tunnel with cross-passage complicates the impact of longitudinal fire source location on the smoke backflow layering behavior that has not been clarified, despite the fact that the scenario exists in practice. A series of laboratory-scale experiments were conducted in this study to investigate the smoke back-layering length in a model tunnel with cross-passage. The heat release rate, the velocity of longitudinal air flow, and the location of the fire source were all varied. It was found that the behavior of smoke backflow for the fire source located at the upstream of bifurcation point resembles a single-hole tunnel fire. As the fire source’s position shifts downstream from the bifurcation point, the length of smoke back-layering progressively increases. A competitive interaction exists between airflow diversion and smoke diversion during smoke backflow, significantly affecting the smoke back-layering length in the main tunnel. The dimensionless smoke back-layering length model was formulated in a tunnel featuring a cross-passage, taking into account the positions of longitudinal fire sources. The dimensionless smoke back-layering length exhibits a positive correlation with the 17/18 power of total heat release rate Q and a negative correlation with the 5/2 power of longitudinal ventilation velocity V.