Search Results (209)

High-speed trains have revolutionized modern transportation with their exceptional speeds, yet the essence of this technological breakthrough resides in the train’s wheels. These components are engineered to endure extreme mechanical stresses while ensuring high safety and reliability. In this paper, we selected the rim and web as representative components of the wheel and conducted a comprehensive and systematic study on their microstructure and mechanical properties. The wheels are typically produced through integral forging. To improve the mechanical performance of the wheel/rail contact surface (i.e., the tread), the rim is subjected to surface quenching or other heat treatments. This endows the rim with strength and hardness second only to the tread and lowers its ductility. This results in a more isotropic structure with improved fatigue resistance in low-cycle and high-cycle regimes under rotating bending. The web connects the wheel axle to the rim and retains the microstructure formed during the forging process. Its strength is lower than that of the rim, while its ductility is slightly better. The web satisfies current property standards, although the microstructure suggests further optimization may be achievable through heat treatment refinement. Full article

This study examines fatigue crack growth behavior in induction-hardened S38C axle steel with a gradient microstructure. High-frequency three-point bending fatigue tests were conducted to evaluate crack growth rates (da/dN) across three depth-defined regions: a hardened layer, a heterogeneous transition zone, and a normalized core. Depth-resolved da/dN–ΔK relationships were established, and Paris Law parameters were extracted. The surface-hardened layer exhibited the lowest crack growth rates and flattest Paris slope, while the transition zone showed notable scatter due to microstructural heterogeneity and residual stress effects. These findings provide experimental insight into the fatigue performance of gradient-structured axle steels and offer guidance for fatigue life prediction and inspection planning. Full article

Aiming at the problems of complex control processes, strong model dependence, and difficult engineering application when the existing active suspension control strategy is applied to multi-axle vehicles, an active suspension control strategy based on the inverse position solution of a parallel mechanism is proposed. First, the active suspension of the three-axle emergency rescue vehicle is grouped and interconnected within the group, and it is equivalently constructed into a 3-DOF parallel mechanism. Then, the displacement of each equivalent suspension actuating hydraulic cylinder is calculated by using the method of the inverse position solution of a parallel mechanism, and then the equivalent actuating hydraulic cylinder is reversely driven according to the displacement, thereby realizing the effective control of the attitude of the vehicle body. To verify the effectiveness of the proposed control strategy, a three-axis vehicle experimental platform integrating active suspension and hydro-pneumatic suspension was built, and a pulse road experiment and gravel pavement experiment were carried out and compared with hydro-pneumatic suspension. Both types of road experimental results show that compared to hydro-pneumatic suspension, the active suspension control strategy based on the inverse position solution of a parallel mechanism proposed in this paper exhibits different degrees of advantages in reducing the peak values of the vehicle vertical displacement, pitch angle, and roll angle changes, as well as suppressing various vibration accelerations, significantly improving the vehicle’s driving smoothness and handling stability. Full article

Since 1 January 2024, newly produced heavy-duty trailers are subject to the assessment of their performance regarding CO₂ and fuel consumption according to Implementing Regulation (EU) 2022/1362. The method is based on the already established approach for the CO₂ and energy consumption evaluation of trucks and buses, i.e., applying a combination of component testing and vehicle simulation using the software VECTO (Vehicle Energy Consumption calculation TOol). For the evaluation of trailers, generic conventional towing vehicles in combination with the specific CO₂ and fuel consumption-relevant properties of the trailer, such as mass, aerodynamics, rolling resistance etc., are simulated in the “VECTO Trailer” software. The corresponding results are used in the European HDV CO₂ standards with which manufacturers must comply to avoid penalty payments (2030: −10% for semitrailers and −7.5% for trailers compared with the baseline year 2025). Methodology and legislation are currently being extended to also cover the effects of electrified trailers (trailers with an electrified axle and/or electrically supplied auxiliaries) on CO₂, electrical energy consumption, and electric range extension (special use case in combination with a battery-electric towing vehicle). This publication gives an overview of the developed regulatory framework and methods to be implemented in a future extension of VECTO Trailer as well as a comparison of different e-trailer configurations and usage scenarios regarding their impact on CO₂, energy consumption, and electric range by applying the developed methods in a preliminary potential analysis. Results from this analysis indicate that e-trailers that use small batteries (5–50 kWh) to power electric refrigeration units achieve a CO₂ reduction of 5–10%, depending primarily on battery capacity. In contrast, e-trailers designed for propulsion support with larger batteries (50–500 kWh) and e-axle(s) (50–500 kW) demonstrate a reduction potential of up to 40%, largely determined by battery capacity and e-axle rating. Despite their reduction potential, market acceptance of e-trailers remains uncertain as the higher number of trailers compared with towing vehicles could lead to slow adoption, especially of the more expensive configurations. Full article

Extreme rainfall events pose a growing threat to slab track subgrades by triggering mud pumping through fines migration and structural voids. This study introduces two innovations to enhance climate resilience in high-speed railway infrastructure: (i) the Rain Intensity Ponding (RIP) method, which links regional rainfall statistics with axle-pass thresholds to predict mud pumping potential; (ii) an optimized drainage retrofit using permeable shoulders and blind ditches. Physical model tests reveal that mud pumping occurs only when structural gaps, ponding, and cyclic loading coincide. The RIP method correctly identified a 71% exceedance in the critical ponding duration (52 min) on a representative high-speed line in Eastern China, explaining recurrent failures. Parametric analyses show that the proposed drainage retrofit—using shoulder fill with ka > 23 mm/s and blind ditches with kg > 23 mm/s—reduces ponding time by up to 90% under 1-year recurrence storms. This study establishes a physics-based, region-specific strategy for mud pumping mitigation, offering guidance for climate-adaptive slab track design and operation. Full article

The objective of our research was to ascertain the time intensity of timber skidding with a prototype ATV Salamander 600 4 × 4 micro-skidder and to characterize the operator’s field of view. The time intensity of skidding amounts to approximately 20 min/m³ at a distance of 20 m when skidding timber from the forest stand and approximately 10 min/m³ when skidding along the skid trail for a distance of 80 m, which is comparable to other machines of this type, despite reported problems with raw material causing jamming on rugged terrain in the first phase of the skidding process. The significant discrepancy (6%) in wheel slippage between the front and rear axles was particularly pronounced during the process of pulling timber up to the skid trail. This can be attributed to the transport hitch being positioned excessively high, thereby relieving the force on the hitch and causing the front axle to be affected. The observed difficulties in skidding resulted in the need to scan a wide visual scene when working in the stand. The initial phase of timber skidding in the forest stand exhibited a deficiency in its smooth flow, which led to an augmentation in mental workload, as indicated by the elongation of saccades. On average, these saccades were approximately 80% longer compared to those in work conducted on the skid trail. Full article

During locomotive operation, large amounts of operation data are recorded by the TCU (Traction Control Unit). The prediction and detection of slipping through the analysis of large amounts of data are of great significance for energy saving and locomotive operation safety. The TCU records time series data with a step length of 1 s. The transformer-based Informer algorithm performs well in time series prediction and analysis. Based on the improved Informer algorithm, this paper proposes a slip trend prediction method, which can predict the slipping state of n time steps according to the data of the previous seconds. By adding the improved prediction model of Informer to the classification model, this study, rather than adding a classification branch to the prediction model, directly improves the output structure, so as to realize long-sequence prediction with a multi-classification model. The model can effectively extract the important features in the data, and can realize multi-axle synchronous prediction and output the slipping state in parallel over the next few seconds. The comprehensive accuracy of this model in multi-axle synchronous prediction tasks can reach 94.75%. Finally, the model is analyzed according to the predicted results, and the effects of different models are compared. The attention mechanism and experimental data are analyzed by visualization. Full article

Railway track performance and durability face growing challenges from higher speeds, heavier axle loads, and changing environmental conditions. Crumb rubber-modified asphalt (CRMA) offers a sustainable solution by repurposing waste tires into a durable material for railway trackbeds, improving both performance and environmental impact. Following PRISMA-ScR guidelines, this scoping review synthesizes an extensive body of global research on the structural, mechanical, and environmental benefits of CRMA in railway trackbeds. A systematic literature search was conducted across major academic databases, covering studies published over several decades. Selection criteria focused on CRMA applications in railway trackbeds, using keywords such as “crumb rubber-modified asphalt”, “railway track vibration”, and “sustainable railway materials.” After rigorous screening and eligibility assessment, the most relevant peer-reviewed studies were included, emphasizing mechanical performance, durability, and environmental impact. Key findings indicate that CRMA effectively reduces ground vibrations, enhances load distribution, and lowers long-term maintenance costs while promoting sustainable waste management through tire recycling. However, challenges such as optimal mix design, potential emissions, and long-term bonding stability require further investigation. Additionally, the review was limited to English-language studies, potentially omitting relevant non-English research, and some reports were inaccessible during retrieval. This review maps critical research gaps, identifies key areas for future optimization, and highlights CRMA’s potential to advance resilient and eco-friendly railway infrastructure. Full article

Fatigue cracking is a major issue in asphalt pavements, reducing their lifespan and increasing maintenance costs. This study develops an artificial neural network (ANN) model to predict the onset and progression of fatigue cracking. The model is calibrated utilizing Falling Weight Deflectometer (FWD) testing data, alongside essential pavement characteristics such as layer thickness, air void percentage, asphalt binder proportion, traffic loads (Equivalent Single Axle Loads or ESALs), and mean annual temperature. By analyzing these factors, the ANN captures complex relationships influencing fatigue cracking more effectively than traditional methods. A comprehensive dataset from the Long-Term Pavement Performance (LTPP) program is used for model training and validation. The ANN’s ability to adapt and recognize patterns enhances its predictive accuracy, allowing for more reliable pavement condition assessments. Model performance is evaluated against real-world data, confirming its effectiveness in predicting fatigue cracking with an overall R² of 0.9. This study’s findings provide valuable insights for pavement maintenance and rehabilitation planning, helping transportation agencies optimize repair schedules and reduce costs. This research highlights the growing role of AI in pavement engineering, demonstrating how machine learning can improve infrastructure management. By integrating ANN-based predictive analytics, road agencies can enhance decision-making, leading to more durable and cost-effective pavement systems for the future. Full article

Railway tight and wide gauges are critical factors affecting the safety and reliability of railway systems. Undetected tight and wide gauges can lead to derailments, posing significant risks to operations and passenger safety. This study explores a novel approach to detecting railway tight and wide gauges by integrating accelerometer data, machine-learning techniques, and building information modeling (BIM). Accelerometers installed on axle boxes provide real-time dynamic data, capturing anomalies indicative of tight and wide gauges. These data are processed and analyzed using supervised machine-learning algorithms to classify and predict potential tight- and wide-gauge events. The integration with BIM offers a spatial and temporal framework, enhancing the visualization and contextualization of detected issues. BIM’s capabilities allow for the precise mapping of tight- and wide-gauge locations, streamlining maintenance workflows and resource allocation. Results demonstrate high accuracy in detecting and predicting tight and wide gauges, emphasizing the reliability of machine-learning models when coupled with accelerometer data. This research contributes to railway maintenance practices by providing an automated, data-driven methodology that enhances the proactive identification of tight and wide gauges, reducing the risk of derailments and maintenance costs. Additionally, the integration of machine learning and BIM highlights the potential for comprehensive digital solutions in railway asset management. Full article

Background: Head and neck cancer (HNC) evades immune responses by manipulating the tumor immune microenvironment (TIME). Tumor-bound Axl has been implicated in promoting an immunosuppressive TIME in HNC, though its precise role remains unclear. Understanding Axl’s contribution to immune evasion in HNC could lead to the identification of new therapeutic targets; therapies directed at these targets could be combined with and thereby enhance immunotherapies. Results: Using Axl knockout (Axl KO) cell lines derived from the immunologically “cold” MOC2 mouse model, we found that Axl loss delayed tumor growth in immunocompetent mice. This was accompanied by reduced immunosuppressive cells, including MDSCs, T_regs, B cells, and neutrophils, and increased infiltration of cytotoxic CD8 T cells and NK cells. To identify the immune population(s) responsible for these changes, Axl KO tumors were implanted in immune-deficient mice. Axl KO tumor growth in athymic nude mice (which lack T cells) was unchanged, whereas tumor growth in NCG mice (which lack NK cells) was rescued, suggesting that NK cells mediate the Axl KO tumor growth delay. Further, Axl loss enhanced NK cell cytotoxicity in vitro and in vivo, and NK cell depletion reversed delayed Axl KO tumor growth. Mechanistically, Axl KO tumors showed decreased expression of CD73 and CCL2, which inhibit NK cells, and increased expression of CCL5 and CXCL10, which promote NK cell recruitment and activation. Conclusions: These novel findings suggest that tumor-bound Axl fosters an immunosuppressive TIME by inhibiting NK cell recruitment and function, thereby promoting tumor growth. Targeting Axl may enhance NK cell-mediated tumor killing and improve immunotherapy efficacy in HNC. Full article

The object of the present research is a machine-tractor unit based on a tractor consisting of an energy (high-energy tractor—EM) and a technological (additional traction axle—TM) module. This tractor uses three-row crop cultivators, each with an operating width of 4.2 m. One of these cultivators is attached centrally to the technological module, and the other two are connected to the sides of the energy module in its front part. The research aimed to determine the influence degree of such a unit scheme and design parameters on the stability of its movement in the horizontal plane. The theoretical analysis was performed using amplitude (AFC) and phase (PFC) frequency characteristics obtained based on the developed mathematical model of the modular unit movement when it processes a disturbing effect. The difference in traction resistances of the unit’s side cultivators was adopted as the latter. Finally, it was established that blocking the vertical hinge of the TM contributes to a significant increase in the unit motion stability. The practical implementation of this method of joining EM and TM in the horizontal plane allows the unit to work out a disturbing influence in the frequency range 0.65–5.50 s⁻¹ to eliminate the resonant AFC peaks and reduce their value. When the TM hinge is locked at a torque oscillation frequency of 2.5 s⁻¹, the AFC is 2.82 times less than when it is free. Blocking the TM vertical hinge increases the delay in the unit’s response to a disturbance. At an oscillation frequency of the latter of 1.5 s⁻¹, this delay is 0.6 s, and at a frequency of 0.5 s⁻¹, it increases by more than three times, reaching a level of 1.9 s. Full article

Establishing an accurate vehicle fatigue load spectrum is a critical prerequisite for fatigue life analysis and design of highway bridges. However, the time-varying and regional characteristics of vehicle loads pose significant challenges to achieving this goal. This study focuses on vehicle data collected by a weigh-in-motion system installed on a highway bridge in Chongqing, China. The statistical characteristics of vehicle-load-related parameters are analyzed, and the actual vehicle fatigue load spectrum for this section of the road is established. Specifically, vehicles are first categorized based on axle count characteristics. Then, statistical analyses are conducted on key parameters such as vehicle weight, headway time, and axle load for each vehicle type. Finally, the actual vehicle fatigue load spectrum is developed based on Miner’s linear damage rule and the equivalent fatigue damage principle, and the contributions of different vehicle types to fatigue damage are investigated. The results show that the weight distributions of different vehicle types follow a Gaussian mixture distribution, while the headway time distribution for each lane follows a log-normal distribution. A linear approximate relationship was observed between the axle loads of different vehicle types and their respective total weights. Although two-axle trucks exhibited higher frequencies, six-axle trucks contributed the most to structural fatigue damage, accounting for 53.81%. Therefore, six-axle trucks can be regarded as the standard fatigue vehicle model for this section of the road. These findings provide valuable insights for fatigue design and fatigue life assessment of highway bridges under similar vehicle loading conditions. Full article

A friction loss model for a loading brake tester with adjusted shaft distance was constructed to correct the test results of the braking rate of the loading shaft, which could largely improve the accuracy of automobile braking performance tests. Specifically, the influence of tire pressure, vehicle axle load, placement angle, and vehicle speed on the friction loss was tested and analyzed on the tester. The friction loss model for the tester was constructed based on the first defined relative slip and placement angle, which was validated through actual tests on four types of vehicles. The results showed that the maximum relative error between the simulation and the measured values is 2.2%, indicating the friction loss model is valid and can provide a basis for correcting the braking force of automobile brakes. Meanwhile, the maximum braking force increased from 3982 N to 4772 N, increased by 19.8%, when the placement angle was raised from 36.9° to 47.0°, demonstrating the effectiveness of constructing a friction loss model and enhancing the accuracy of the loading brake tester with adjusted shaft distance test results. Accordingly, in order to improve the detection accuracy of the self-developed tester, the friction loss model is essential for correcting the friction loss caused by the change in the placement angle, and then the braking rate of the vehicle should be determined according to the relevant regulations stipulated in China, EU, USA, Japan, and other countries or regions, which can accurately reflect the performance of the vehicle’s braking system. Full article

Bovine coronavirus (BCoV) exhibits dual tissue tropism, infecting both the respiratory and enteric tracts of cattle. Viral entry into host cells requires a coordinated interaction between viral and host proteins. However, the specific cellular receptors and co-receptors facilitating BCoV entry remain poorly understood. Similarly, the roles of host proteases such as Furin, TMPRSS2, and Cathepsin-L (CTS-L), known to assist in the replication of other coronaviruses, have not been extensively explored for BCoV. This study aims to identify novel BCoV receptors and host proteases that modulate viral replication and tissue tropism. Bovine cell lines were infected with BCoV isolates from enteric and respiratory origins, and the host cell gene expression profiles post-infection were analyzed using next-generation sequencing (NGS). Differentially expressed genes encoding potential receptors and proteases were further assessed using in-silico prediction and molecular docking analysis. These analyses focused on known coronavirus receptors, including ACE2, NRP1, DPP4, APN, AXL, and CEACAM1, to identify their potential roles in BCoV infection. Validation of these findings was performed using the qRT-PCR assays targeting individual genes. We confirmed the gene expression profiles of these receptors and enzymes in some BCoV (+/−) lung tissues. Results revealed high binding affinities of 9-O-acetylated sialic acid and NRP1 to BCoV spike (S) and hemagglutinin-esterase (HE) proteins compared to ACE2, DPP4, and CEACAM1. Additionally, Furin and TMPRSS2 were predicted to interact with the BCoV-S polybasic cleavage site (RRSRR|A), suggesting their roles in S glycoprotein activation. This is the first study to explore the interactions of BCoV with multiple host receptors and proteases. Functional studies are recommended to confirm their roles in BCoV infection and replication. Full article