Search Results (589)

In the realm of road–rail dual-use bridges, conducting accurate vehicle–bridge coupling analysis is crucial, as the combined effects of road traffic and rail transit induce complex dynamic challenges. This study investigates a road–rail dual-use network arch bridge, highlighting the dynamic effects induced by light rail loadings. By employing a noniterative vehicle–bridge coupling analysis method, the dynamic responses of hangers caused by vehicular and light rail loads are effectively captured. Additionally, this study explores the influence of various parameters, including vehicle types, driving lanes, and road surface roughness on the responses of hangers positioned at different locations along the bridge. The findings reveal that light rail induces significantly larger dynamic effects compared to motor vehicles. When the light rail operates closer to the hanger, the responses of hangers are more pronounced. Furthermore, different road surface roughness level notably affects the amplitude of axial stress and bending moment fluctuations. Poorer road conditions amplify these dynamic effects, leading to increased stress variations. These insights underscore the necessity of integrating considerations for both road and rail traffic in the structural analysis and design of network arch bridges to ensure their reliability and serviceability. Full article

The European Union (EU) is paving the way toward “Vision Zero”, a future goal of eliminating road fatalities and severe injuries. Railway level crossings are critical safety hotspots where road and rail traffic intersect and present a unique challenge in balancing the safety of both rail and road users while ensuring efficient traffic flow. Collisions at these crossings account for a significant proportion of railway-related fatalities in the EU, underscoring the need for targeted safety interventions. This article explores the impact of signal preemption strategies on the safety and operational performance of railway level crossings through a microsimulation analysis. Using VISSIM, a railway level crossing and its adjacent road intersection were modeled under existing and alternative scenarios. The preemption strategy was designed to clear vehicles from the crossing area before train arrivals, reducing conflict risks and optimizing traffic flow. Key findings reveal that the proposed preemption strategy significantly reduces queue lengths within critical safety zones, mitigating vehicle spillback and enhancing operational efficiency. The analysis highlights the importance of integrating railway operations with traffic signal systems, particularly in urban areas with limited queue storage capacity. Full article

Traditional track-based inspection schemes for caged poultry houses face issues with vulnerable tracks and cumbersome maintenance, while existing rail-less alternatives lack robust, reliable path planners. This study proposes TSO-HA*-Net, a hybrid global path planner that combines TSO-HA* with topological planning, which allows the inspection vehicle to continuously traverse a predetermined trackless route within each poultry house and conduct house-to-house inspections. Initially, the spatiotemporally optimized Hybrid A* (TSO-HA*) is employed as the lower-level planner to efficiently construct a semi-structured topological network by integrating predefined inspection rules into the global grid map of the poultry houses. Subsequently, the Dijkstra’s algorithm is adopted to plan a smooth inspection route that aligns with the starting and ending poses, conforming to the network. TSO-HA* retains the smoothness of HA* paths while reducing both time and computational overhead, thereby enhancing speed and efficiency in network generation. Experimental results show that compared to LDP-MAP and A*-dis, utilizing the distance reference tree (DRT) for h₂ calculation, the total planning time of the TSO-HA* algorithm is reduced by 66.6% and 96.4%, respectively, and the stored nodes are reduced by 99.7% and 97.4%, respectively. The application of the collision template in TSO-HA* results in a minimum reduction of 4.0% in front-end planning time, and the prior collision detection further decreases planning time by an average of 19.1%. The TSO-HA*-Net algorithm achieves global topological planning in a mere 546.6 ms, thereby addressing the critical deficiency of a viable global planner for inspection vehicles in poultry houses. This study provides valuable case studies and algorithmic insights for similar inspection task. Full article

The majority of electromagnetic force calculation models employed in maglev vehicle system dynamics focus exclusively on vertical and lateral movement while neglecting the nonlinear magnetization properties of ferromagnetic materials. This oversight leads to discrepancies between the dynamics simulations and actual conditions. To enhance the accuracy of dynamics simulations and evaluate the performance of maglev vehicle systems under various operational conditions, it is imperative to identify an electromagnetic force calculation model that combines accuracy and applicability. To address this objective, this paper examines a U-shaped electromagnet in medium–low-speed maglev vehicles as a case study. It constructs a spatial electromagnetic force calculation surrogate model using a Shallow Neural Network. The surrogate model is capable of accurately calculating electromagnetic forces considering relative position deviations in the lateral, vertical, rolling, pitching, and shaking directions. Moreover, it can be integrated into vehicle system dynamics simulations. The accuracy of the electromagnetic force calculation surrogate model is confirmed by extensive comparisons with finite element simulation results across various conditions, achieving an impressive concordance rate of up to 95%. An illustrative application of the electromagnetic force calculation surrogate model in maglev vehicle system dynamics simulation is provided to showcase its practical utility. Full article

As a new type of rail transit vehicle, maglev trains have extremely high requirements for safety and reliability. With the gradual commercial operation of maglev trains, how to scientifically and effectively assess the safety and analyze the risks of train equipment has become an urgent issue to be addressed. Against the backdrop of the practical application of maglev train projects, this paper integrates domestic and international risk analysis models, proposes the steps for conducting the risk analysis of maglev rail transit, and establishes a risk analysis system for the entire lifecycle of maglev rail transit. Based on the results of fault analysis, a risk analysis of the levitation system is carried out. The theory of multi-attribute decision-making is studied, new risk evaluation indicators are established using triangular fuzzy numbers, the risk levels of the levitation system are determined, and the weak links within the system and the relationships between the pieces of equipment are identified. These efforts provide guidance for enhancing the safety and reliability of train equipment and for carrying out train maintenance work. Full article

Based on the dynamic receptance method, a vehicle–track–bridge interaction model was developed to calculate the wheel–rail interaction forces and the forces transmitted to the bridge in an elevated urban rail transit system. A prediction model integrating the finite element method–boundary element method (FEM-BEM) and the statistical energy analysis (SEA) method was established to obtain the noise from the main girder, track slab, and wheel–rail system for elevated urban rail transit. The calculated results agree well with the measured data. Thereafter, the noise radiation characteristics of a single source and the total noise of elevated urban rail transit systems with resilient fasteners, trapezoidal sleepers, and steel spring floating slabs were investigated. The results demonstrate that the noise prediction model for elevated urban rail transit that was developed in this study is effective. The diversity of track forms altered the noise radiation field of elevated urban rail transit systems significantly. Compared to monolithic track beds, where the fastener stiffness is assumed to be 60 × 10⁶ N/m (MTB_60), steel spring floating slab tracks (FSTs), trapezoidal sleeper tracks (TSTs), and resilient fasteners with a stiffness of 40 × 10⁶ N/m (MTB_40) and 20 × 10⁶ N/m (MTB_20) can reduce bridge-borne noise by 24.6 dB, 8.8 dB, 2.1 dB, and 4.2 dB, respectively. These vibration-mitigating tracks can decrease the radiated noise from the track slab by −0.7 dB, −0.6 dB, 2.5 dB, and 2.6 dB, but increase wheel–rail noise by 0.4 dB, 0.8 dB, 1.3 dB, and 2.4 dB, respectively. The noise emanating from the main girder and the track slab was dominant in the linear weighting of the total noise of the elevated section with MTBs. For the TST and FST, the radiated noise from the track slab contributed most to the total noise. Full article

When a railway train runs along a curved track with braking, the dynamic behaviors of the vehicle are extremely complex and difficult to accurately reveal due to the coupling effects between the wheel–rail interactions and the disc–pad frictions. Therefore, a rigid–flexible coupled trailer car dynamics model of a railway train is established. In this model, the brake systems and vehicle system are dynamically coupled via the frictions within the braking interface, wheel–rail relationships and suspension systems. Furthermore, the effectiveness of the established model is validated by a comparison with the field test data. Based on this, the dynamic response characteristics of vehicle under curve and straight braking conditions are analyzed and compared, and the influence of the curve geometric parameters on vehicle vibration and operation safety is explored. The results show that braking on a curve track directly affects the vibration characteristics of the vehicle and reduces its operation safety. When the vehicle is braking on a curve track, the lateral vibration of the bogie frame significantly increases compared to the vehicle braking on a straight track, and the vibration intensifies as the curve radius decreases. When the curved track maintains equilibrium superelevation, the differences in primary suspension force, wheel–rail vertical force, and wheel axle lateral force between the inner and outer sides of the first and second wheelsets are relatively minor under both straight and curved braking conditions. Additionally, under these circumstances, the derailment coefficient is minimized. However, when the curve radius is 7000 m, with a superelevation of 40 mm, the maximum dynamic wheel load reduction rate of the inner wheel of the second wheelset is 0.54, which reaches 90% of the allowable limit value of 0.6 for the safety index, and impacts the vehicle running safety. Therefore, it is necessary to focus on the operation safety of railway trains when braking on curved tracks. Full article

High-quality data samples are essential for the early detection of bearing failures and the analysis of bearing behavior. The accurate simulation of bearing fault conditions can provide valuable insights into understanding failure mechanisms. This paper establishes a new numerical simulation method for double-row cylindrical roller bearing (DCRB) faults based on the augmented Lagrange dynamics method, overcoming the limitations of previous models by incorporating fault conditions related to cage fracture. This method accounts for the dynamic behavior of the rollers during the motion cycle and their interactions with other DCRB components. By comparing the characteristic frequencies of the fault components, the model not only replicates the dynamic behavior of faulty DCRBs more accurately but also offers a deeper understanding of fault-induced dynamics. This advancement provides a more comprehensive and realistic tool for bearing fault analysis. Full article

With the rapid development of urban rail transit, the intensity and impact range of train-induced vibrations are increasing. Investigating the transmission characteristics and attenuation patterns of these vibrations in track structures aids in understanding train-induced environmental vibrations. This study conducted rail impact experiments on a long sleeper integrated slab of a straight section of a subway tunnel. The hammer struck the rail at various positions, and acceleration sensors recorded the responses of the rail, slab, and tunnel. In order to determine the impact force, the vertical wheel–rail force and the vibration response of track structures were measured. Then, the Lance-LC1304B force hammer was selected for the experiment, and the hammer impact force reached 30 kN, the magnitude of which reached the measured wheel–rail force size for the line. Based on the results of the impact tests, the vibration attenuation characteristics of the track structure were analyzed. Accordingly, reference values for the truncation time and truncation distance in the vehicle–track coupled dynamics model’s moving window were provided. By comparing the results of the hammering experiment with the train-induced vibration results, the main excitation frequencies during train operation were determined. These findings provide valuable insights for the development of rail transit systems. Full article

This study investigates the viability of incorporating bicycles into the Dhaka Metro system, a groundbreaking urban transit project for Bangladesh. As Dhaka’s inaugural metro rail network, the system signifies a substantial advancement in addressing urban congestion and enhancing transportation alternatives in one of the world’s most densely populated cities. The current design of the metro fails to accommodate bicycles, hindering efficient first- and last-mile connectivity. The investigation utilized data from 382 fully completed questionnaires, obtained through purposive sampling, about metro–cycle integration in Dhaka. The research employed RIDIT and TOPSIS analyses to rank the characteristics deemed most essential for bicycle–metro integration according to user opinions. Research indicates that secure bicycle parking, multi-modal ticketing, route comfort, and safety measures are the foremost objectives for commuters. The high emphasis on secure parking indicates the need for safe and accessible storage options that would make cycling a viable mode for reaching metro stations. A multi-modal ticketing system further enhances convenience, providing seamless transitions between transit modes. Journey comfort and the need to mitigate risks posed by motorized vehicles underscore the importance of safe and user-friendly commuting environments. While features like road and station design were ranked lower in priority, the study emphasizes that a well-integrated bicycle infrastructure is essential to ensure the metro system’s success. With these improvements, Dhaka’s metro system can meet the growing demands for sustainable and inclusive urban mobility, setting a precedent for future infrastructure projects in Bangladesh. Full article

This paper presents a machine learning-based approach to grade engine health and generate a respective score ranging from 0 to 100 for tuned high-performance vehicles. It integrates the technical intricacies of automotive engineering with machine learning practices in a clear and sequential process. Data are collected from sensors monitoring revolutions per minute, boost, rail pressure, timing, and temperature. The data are processed for supervised learning and analyzed using visualizations such as a heatmap and t-SNE plots. Models are trained, innovatively tuned through hyperparameter optimization, and tested for their ability to grade new data logs. The results highlight K-Neighbors, Extra Trees, and Extreme Gradient Boosting as exceptional regressors for this task. The automated grading of engine health and performance enhances objectivity and efficiency in the tuning process and potentially serves as a basis for a digital twin. The developed methodology is discussed in the context of health evaluation for any sensor-based system, with practical applications extending across various domains and industries. Full article

Cement–asphalt (CA) mortar voids in earth’s structure are prone to inducing abnormal vibrations in vehicle and track systems and are more difficult to recognize. In this paper, a vehicle–ballastless track coupling model considering cement–asphalt mortar voids is established and the accuracy of the model is verified. There are two main novel results: (1) The displacement of the track slab in the ballastless track structure is more sensitive to the void length. Voids can lead to blocked vibration transmission between the ballastless track slab and concrete base. (2) The wheel–rail vibration acceleration is particularly sensitive to voids in cement–asphalt mortar, making the bogie pendant acceleration a key indicator for detecting such voids through amplitude changes. Additionally, the train body pendant acceleration provides valuable feedback on the cyclic characteristics associated with single-point damage in the cement–asphalt mortar, thereby enhancing the accuracy of dynamic inspections for vehicles. In the sensitivity ordering of the identification indexes of voids, the bogie’s vertical acceleration in high-speed trains > the nodding acceleration of the bogie > the vehicle’s vertical acceleration. Adaptive suspension parameters can be designed to accommodate changes in track stiffness. Full article

Intelligent Guided Vehicles (IGVs) in U-shaped automated container terminals (ACTs) have longer travel paths than those in conventional vertical layout ACTs, and their interactions with double trolley quay cranes (DTQCs) and double cantilever rail cranes (DCRCs) are more frequent and complex, so the scheduling strategy of a traditional ACT cannot easily be applied to a U-shaped ACT. With the aim of minimizing the maximum task completion times within a U-shaped ACT, this study investigates the integrated scheduling problem of DTQCs, IGVs and DCRCs under the hybrid “loading and unloading” mode, expresses the problem as a Markovian decision-making process, and establishes a disjunctive graph model. A deep reinforcement learning algorithm based on a graph neural network combined with a proximal policy optimization algorithm is proposed. To verify the superiority of the proposed models and algorithms, instances of different scales were stochastically generated to compare the proposed method with several heuristic algorithms. This study also analyses the idle time of the equipment under two loading and unloading modes, and the results show that the hybrid mode can enhance the operational effectiveness. of the U-shaped ACT. Full article

Previous studies on highway_rail grade crossing collisions have primarily focused on identifying factors contributing to the frequency and severity of driver injuries. In recent years, increasing attention has been given to modeling driver injury severity at these crossings. Recognizing the variations in injury severity under different road surface conditions, this study investigates the impact of road surface conditions on driver injury severity at highway_rail grade crossings. Using nearly a decade of accident data (2012–2021), thi study employs a LightGBM model to predict factors influencing injury severity and utilizes SHAP values for result interpretation. The symmetry principle of SHAP esures that factors with identical influence receive equal values, enhancing the reliability of predictive outcomes. The findings reveal that driver injury severity at highway_rail grade crossings varies significantly under different road surface conditions. Key factors identified include train speed, driver age, vehicle speed, annual average daily traffic (AADT), driver presence inside the vehicle, weather conditions, and location. The results indicate that collisions are more frequent when either the vehicle or train travels at high speed. Implementing speed limits for both vehicles and trains under varying road conditions could effectively reduce accident severity. Additionally, older drivers are more prone to severe accidents, highlighting the importance of installing control devices, such as warning signs or signals, to enhance driver alertness and mitigate injury risks. Furthermore, adverse weather conditions, such as rain, snow, and fog, exacerbate accident severity on road surfaces like sand, mud, dirt, oil, or gravel. Timely removal of surface obstacles may help reduce the severity of such accidents. Full article

The normalized operation of 30,000-ton heavy-haul trains is of significant importance for enhancing the transportation capacity of heavy-haul railways. However, with the increase in train formation size, traditional braking strategies result in excessive longitudinal impulse when combined pneumatic and electric braking is applied on long, steep gradients. This presents a serious challenge to the braking safety of the train. To this end, this paper establishes a longitudinal dynamic model of a 30,000-ton heavy-haul train based on vehicle system dynamics theory, and validates the model’s effectiveness through line test data. On this basis, the influence of two braking parameters, namely, the distribution of the magnitude of the electric braking force and the matching time of pneumatic braking and electric braking, on the longitudinal dynamic behavior of heavy-haul trains is studied. Thereby, an optimized combined pneumatic and electric braking strategy is formulated to reduce the longitudinal impulse of the trains. The results show that setting reasonable braking parameters can effectively reduce the longitudinal impulse, with the braking matching time having a significant impact on the longitudinal impulse. Specifically, when using a strategy where the electric braking forces of three locomotives are set to 90 kN, 300 kN, and 300 kN, with a 30 s delay in applying the electric braking force, a better optimization effect is achieved. The two proposed braking strategies reduce the maximum longitudinal forces by 20.27% and 47.83%, respectively, compared to conventional approaches. The research results provide effective methods and theoretical guidance for optimizing the braking strategy and ensuring the operational safety of 30,000-ton heavy-haul trains. Full article