Search Results (60)

Rail corrugation and roughness represent typical irregularities on railway and tramway tracks, which cause increased dynamic forces, high-frequency vibrations, reduced riding comfort, shorter track lifespan, higher maintenance costs, and increased noise levels. Roughness and corrugation can be measured by evaluating the unevenness of the rail longitudinal running surface, which can be conducted using handheld devices or trolleys (directly on the track). Alternatively, vehicle or track-based indirect methods offer practical solutions for determining the condition of the rail running surface. This paper presents a methodology for rail corrugation and roughness evaluation, using bogie frame vibration data from an instrumented in-service tramway vehicle operating on Zagreb’s tramway network. Furthermore, it investigates the effects of various factors on the evaluation method, including wheel roughness, lateral positioning, signal processing methods, horizontal geometry, wheel–rail contact force, and tramway vehicle vibroacoustic characteristics. It was concluded that a simplified methodology that did not include transfer functions or wheel roughness measurements yielded relatively good results for evaluating rail corrugation and roughness across several wavelength bands. To improve the presented methodology, future research should assess the vehicle’s vibroacoustic characteristics with experimental hammer impact tests, measure the influence of wheel roughness on wheel–rail contact and bogie vibrations, and refine the measurement campaign by increasing test runs, limiting speed variation, and conducting controlled tests. Full article

The Fit for 55 and Euro 7 regulations significantly reduce CO₂ emissions from combustion sources. This will be reflected in the regulations governing the approval of in-service vehicles, including those using alternative fuels. The present study focused on the rapid diagnostics of the technical condition of gas injectors. The test method was a modification of the Gaussian characteristic fields method using the Szpica–Warakomski rectilinear trend. The flow tests resulted in average volumetric intensities of 111 NL/min and 124 NL/min, depending on the operating conditions. The opening and closing times were in the range of (1.3…3.5) ms. The directional parameter of the rectilinear trend, which is important from the point of view of the analyses, was 0.97 for brand new (BN) injectors and 1.00 for in-service (IO) injectors. The intersection parameters were 0.64 and 0.24, respectively. The qualitative evaluation yielded coefficients of determination of 95.01 and 94.07. The values of the trend parameters were strongly dependent on the design solution and model/type of injector. Inferring the effect of operating condition on the trend parameter values, a one-factor analysis of variance was performed, which showed the significance of only the directional coefficient. A comparison of the same BN and IO injector model showed an apparent change in the value of the intercept only. No significant relationships between the injector opening and closing times and the trend parameters were shown. Thus, the usefulness of using the Szpica–Warakomski rectilinear trend in the functional evaluation of gas injectors of different designs and under different operating conditions was demonstrated. Full article

Although the transition to electric vehicles (EVs) is well underway and expected to continue in global car markets, most vehicles on the world’s roads will be powered by internal combustion engine vehicles (ICEVs) and fossil fuels for the foreseeable future, possibly well past 2050. Thus, good environmental performance and effective emission control of ICE vehicles will continue to be of paramount importance if the world is to achieve the stated air and climate pollution reduction goals. In this study, we review 228 publications and identify four main issues confronting these objectives: (1) cheating by vehicle manufacturers, (2) tampering by vehicle owners, (3) malfunctioning emission control systems, and (4) inadequate in-service emission programs. With progressively more stringent vehicle emission and fuel quality standards being implemented in all major markets, engine designs and emission control systems have become increasingly complex and sophisticated, creating opportunities for cheating and tampering. This is not a new phenomenon, with the first cases reported in the 1970s and continuing to happen today. Cheating appears not to be restricted to specific manufacturers or vehicle types. Suspicious real-world emissions behavior suggests that the use of defeat devices may be widespread. Defeat devices are primarily a concern with diesel vehicles, where emission control deactivation in real-world driving can lower manufacturing costs, improve fuel economy, reduce engine noise, improve vehicle performance, and extend refill intervals for diesel exhaust fluid, if present. Despite the financial penalties, undesired global attention, damage to brand reputation, a temporary drop in sales and stock value, and forced recalls, cheating may continue. Private vehicle owners resort to tampering to (1) improve performance and fuel efficiency; (2) avoid operating costs, including repairs; (3) increase the resale value of the vehicle (i.e., odometer tampering); or (4) simply to rebel against established norms. Tampering and cheating in the commercial freight sector also mean undercutting law-abiding operators, gaining unfair economic advantage, and posing excess harm to the environment and public health. At the individual vehicle level, the impacts of cheating, tampering, or malfunctioning emission control systems can be substantial. The removal or deactivation of emission control systems increases emissions—for instance, typically 70% (NO_x and EGR), a factor of 3 or more (NO_x and SCR), and a factor of 25–100 (PM and DPF). Our analysis shows significant uncertainty and (geographic) variability regarding the occurrence of cheating and tampering by vehicle owners. The available evidence suggests that fleet-wide impacts of cheating and tampering on emissions are undeniable, substantial, and cannot be ignored. The presence of a relatively small fraction of high-emitters, due to either cheating, tampering, or malfunctioning, causes excess pollution that must be tackled by environmental authorities around the world, in particular in emerging economies, where millions of used ICE vehicles from the US and EU end up. Modernized in-service emission programs designed to efficiently identify and fix large faults are needed to ensure that the benefits of modern vehicle technologies are not lost. Effective programs should address malfunctions, engine problems, incorrect repairs, a lack of servicing and maintenance, poorly retrofitted fuel and emission control systems, the use of improper or low-quality fuels and tampering. Periodic Test and Repair (PTR) is a common in-service program. We estimate that PTR generally reduces emissions by 11% (8–14%), 11% (7–15%), and 4% (−1–10%) for carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NO_x), respectively. This is based on the grand mean effect and the associated 95% confidence interval. PTR effectiveness could be significantly higher, but we find that it critically depends on various design factors, including (1) comprehensive fleet coverage, (2) a suitable test procedure, (3) compliance and enforcement, (4) proper technician training, (5) quality control and quality assurance, (6) periodic program evaluation, and (7) minimization of waivers and exemptions. Now that both particulate matter (PM, i.e., DPF) and NO_x (i.e., SCR) emission controls are common in all modern new diesel vehicles, and commonly the focus of cheating and tampering, robust measurement approaches for assessing in-use emissions performance are urgently needed to modernize PTR programs. To increase (cost) effectiveness, a modern approach could include screening methods, such as remote sensing and plume chasing. We conclude this study with recommendations and suggestions for future improvements and research, listing a range of potential solutions for the issues identified in new and in-service vehicles. Full article

This study aims to present an integrated approach to customer experience, which was developed considering the identification and application of essential factors from the product life cycle. The study was conducted in the automotive industry and may be transferable to other products with high complexity and medium–long in-service use. The main goal is to identify the determining factors and perform a regression analysis of the effect of attribute-level performance on overall customer satisfaction through the customer’s entire journey during the product development phase. This study is based on a generic example that is meant to capture trends influencing customer satisfaction in the launch of a new product vehicle, focusing on factors that influence each stage of the process, from planning–exploration, design and development, and manufacturing and validation to performance measurement and after-sales assistance. Based on multiple surveys that were used as the main instruments for measuring the level of customer satisfaction at defined touchpoints, the product life cycle was followed through several stages: prospecting survey, upstream survey, launch preparation survey, post-launch investigation, life cycle survey, and after-sales support. Three meta-factors were identified—design, price, and durability—for which the ordinal regression demonstrated that they are significant predictors of customer experience in general. The approach may be transferable to other sectors by identifying relevant attributes and adapting tools for measuring customer satisfaction, customer experience, and consumer concerns, which act as key vectors influencing the product life cycle and, by extension, business sustainability. Full article

The rapid measurement of three-dimensional bridge geometric shapes is crucial for assessing construction quality and in-service structural conditions. Existing geometric shape measurement methods predominantly rely on traditional surveying instruments, which suffer from low efficiency and are limited to sparse point sampling. This study proposes a novel framework that utilizes an airborne LiDAR–camera fusion system for data acquisition, reconstructs high-precision 3D bridge models through real-time mapping, and automatically extracts structural geometric shapes using deep learning. The main contributions include the following: (1) A synchronized LiDAR–camera fusion system integrated with an unmanned aerial vehicle (UAV) and a microprocessor was developed, enabling the flexible and large-scale acquisition of bridge images and point clouds; (2) A multi-sensor fusion mapping method coupling visual-inertial odometry (VIO) and Li-DAR-inertial odometry (LIO) was implemented to construct 3D bridge point clouds in real time robustly; and (3) An instance segmentation network-based approach was proposed to detect key structural components in images, with detected geometric shapes projected from image coordinates to 3D space using LiDAR–camera calibration parameters, addressing challenges in automated large-scale point cloud analysis. The proposed method was validated through geometric shape measurements on a concrete arch bridge. The results demonstrate that compared to the oblique photogrammetry method, the proposed approach reduces errors by 77.13%, while its detection time accounts for 4.18% of that required by a stationary laser scanner and 0.29% of that needed for oblique photogrammetry. Full article

This study focuses on the construction of a synthesis health index for metro vehicle wheelsets through theoretical foundation analysis, procedural steps, and practical examples. By analyzing the theoretical foundation, this study explains the advantages of the synthesis health index compared to traditional health indicators. The procedural steps describe the detailed process from data collection, preprocessing, and feature extraction to health index construction. Additionally, practical examples are used to validate the effectiveness and accuracy of this method in real-world applications. The results indicate that this synthesis health index construction method can accurately assess the real-time health status of in-service wheelsets and also reflect and predict the trends of their health status changes. Full article

Girth welds are weak points in pipelines, and failures occur frequently. In a gas transmission pipeline, a girth weld experienced cracking, prompting a failure analysis using experimental methods and finite element analysis (FEA). Experimental results showed that X-ray non-destructive testing (NDT) revealed cracks, porosity, and lack of fusion in the girth weld. However, the hardness and microstructure of the material showed no abnormalities. During operation, the pipeline experienced an increase in soil cover and was subjected to ground subsidence and vehicle loads. Finite element analysis was conducted on the defective girth weld under different conditions, including varying soil cover depths, different levels of subsidence, and varying vehicle loads, to examine the pipeline’s stress response. The results indicated that the combination of soil cover, subsidence, and vehicle loads led to pipeline failure, whereas none of these factors alone was sufficient to cause girth weld failure. To prevent such failures from occurring again, the following measures are recommended: strengthen on-site welding quality control of girth welds, conduct inspections for defects in girth welds of in-service pipelines, and promptly address any defects that exceed acceptable limits. Full article

Road restraint systems (RRSs) on European roads are provided by several manufacturers and, hence, lead to differences in geometry, material, and mode of operation. Focusing on the combination of soft steel RRSs with relatively stiffer concrete RRSs, it is vital to consider the potentially critical deformation kinematics during vehicle impacts, such as vehicle pocketing. Since a statutory test procedure was not introduced until mid-2024, much of the transition construction (TC) on Austrian roads has remained untested. Knowledge of the design features to be implemented during the refurbishment of such TCs is of great interest. The main focus of this study was to derive constructive measures (CMs) that increase traffic safety and are applicable to various TCs already installed on roads. The first step involved deriving design principles whose implementations in TCs reduce the risk of critical vehicle or RRS behavior. Based on finite element simulations, the functionality of a TC featuring all derived design principles was examined. The effect of each individual CM was analyzed in a parameter study. The results from a TB61 impact simulation on the derived TC showed the effectiveness of CMs, achieving smooth vehicle redirection. Vehicle pocketing was limited to a minimum, and neither penetration of the TC nor rollover of the vehicle was observed. The analysis of the influence of each CM indicated positive, and in some cases, negative effects. The working width was mainly positively influenced by the compaction of the posts, an additional steel bar, and the chamfering of the first concrete element. A rather diverse picture is drawn regarding the influence on the tensile forces in the guardrails. Some CMs had both positive and negative effects on the distribution of forces in the upper and lower guardrails. Nevertheless, all CMs had positive effects on the tensile forces in the coupling. The chamfering of the first concrete element was the most effective measure to prevent vehicle pocketing. However, through the combination of all CMs, the positive effects predominated, ensuring the functionality of the TC as a whole. This study provides basic insights into the effectiveness of constructive measures, which can serve as a reference for the renovation of in-service TCs or in the development phase of new TCs to be certified. Full article

The steel–concrete composite beam, as a structural form that combines the advantages of steel and concrete, has been applied in railway engineering. However, with the increase in railway operation time, the degradation pattern of the service performance of steel–concrete composite bridges remains unclear. This paper proposes a method for calculating the long-term service performance of railway steel–concrete composite beams, considering the cumulative fatigue damage of steel beams and studs, based on the vehicle–bridge coupling theory and Miner’s linear cumulative damage criterion. The proposed method is validated using measured data from an in-service steel–concrete composite railway bridge with spans of 40 + 50 + 40 m. The calculated mid-span vertical displacement and the first two natural frequencies of the composite beam deviated from the measured results by only 2.1%, 7.7%, and 9.5%, respectively. The research results can provide a basis for extending the service life of composite beams and preventing the occurrence of safety accidents. Full article

Track and preventive maintenance are necessary for the safe and comfortable operation of railways. Track displacement measured by track inspection vehicles or trolleys has been primarily used for track management. Thus, vibration data measured in in-service vehicles have not been extensively used for track management. In this study, we propose a new technique for estimating track irregularities from measured car body vibration for track management. The correlation between track irregularity and car body vibration was analysed using a multibody dynamics simulation of travelling rail vehicles. Gaussian process regression (GPR) was applied to the track irregularity and car body vibration data obtained from the simulation, and a method was proposed to estimate the track irregularities from the constructed regression model. The longitudinal-level, alignment, and cross-level irregularities were estimated from the measured car body vibrations and travelling speeds on a regional railway, and the results were compared with the actual track irregularity data. The results showed that the proposed method is applicable for track irregularity management in regional railways. Full article

Detecting track geometry and rail surface defects using on-board vehicle monitoring systems is a key issue for rail infrastructure managers to increase availability and reliability while reducing the costs associated with monitoring and maintenance. Rail corrugation is one of the most common rail surface defects which grows in almost all metro, conventional and high-speed lines. This paper focuses on the development of a methodology to detect rail corrugation using axle box acceleration measurements acquired on an in-service high-speed vehicle. The main purpose of the proposed methodology is to distinguish the effect of rail corrugation on the accelerations from the other excitations that can be observed in the same wavelength range. For this purpose, the accelerations are analysed by calculating the fast Fourier transform and the spectrogram. Based on the characteristics of each excitation, the effects of modes of vibration, resonances, bridges, switches, and wheel defects are identified. From the remaining effects, which have congruent characteristics, a hypothesis of rail corrugation is formulated. The hypothesis is consolidated with multibody dynamics simulations and by comparing the corrugation indicators provided by the railway infrastructure company. Full article

Advanced finite element (FE) modeling and simulations were performed on vehicular crashes into a three-bar metal bridge rail (TMBR). The FE models of a sedan, a pickup truck, and a TMBR section were adopted in the crash simulations subject to Manual for Assessing Safety Hardware (MASH) Test Level 2 (TL-2) and Test Level 3 (TL-3) requirements. The test vehicle models were first validated using full-scale physical crash tests conducted on a two-bar metal bridge using a sedan and a pickup truck with similar overall physical properties and sizes to their respective vehicles used in the simulations. The validated vehicular models were then used to evaluate the crash performance of the TMBR using MASH evaluation criteria for structural adequacy, occupant risk, and post-impact trajectory. The TMBR met all MASH TL-2 requirements but failed to meet the MASH TL-3 Criteria H and N requirements when impacted by the sedan. The TMBR was also evaluated under in-service conditions (behind a 1.52 m wide sidewalk) and impacted by the sedan under MASH TL-3 conditions. The simulation results showed that the TMBR behind a sidewalk met all safety requirements except for the occupant impact velocity in the longitudinal direction, which exceeded the MASH limit by 3.93%. Full article

Based on a damaged continuous rigid-frame bridge in Shaanxi Province, this study deduced the crack damage simulation algorithm and the vehicle-bridge coupling numerical algorithm. Then, it established a finite element analysis model using ANSYS APDL. The Newmark-β iterative method was used to study the dynamic response of different speeds, vehicle weights, and damage degrees before and after the structural damage. In the analysis of the influence of different speeds, the results showed that the dynamic stress responses of key sections of the undamaged bridge reached the maximum when the speed was 80 km/h, indicating that the undamaged bridge was sensitive to a speed of 80 km/h. The peak response of the damaged bridge was 90 km/h. In addition, the displacement peaks and the stress peaks rose and fell together. The analysis of different vehicle weights and damage degrees showed that with the increase in them, the displacement and impact coefficients of each section increased significantly. It can be concluded that the dynamic performance of the in-service bridge decreases continuously with the aggravation of the damage. Therefore, the influence of vehicle-bridge coupling should be emphasized in maintenance, and the frequent cracking area at the midspan should be strengthened in time to prevent further damage. Full article

Rail transport plays a crucial role in promoting sustainability and reducing the environmental impact of transport. Ongoing efforts to improve the sustainability of rail transport through technological advancements and operational improvements are further enhancing its reputation as a sustainable mode of transport. Autonomous obstacle detection in railways is a critical aspect of railway safety and operation. While the widespread deployment of autonomous obstacle detection systems is still under consideration, the ongoing advancements in technology and infrastructure are paving the way for their full implementation. The SMART2 project developed a holistic obstacle detection (OD) system consisting of three sub-systems: long-range on-board, trackside (TS), and Unmanned Aerial Vehicle (UAV)-based OD sub-systems. All three sub-systems are integrated into a holistic OD system via interfaces to a central Decision Support System (DSS) that analyzes the inputs of all three sub-systems and makes decision about locations of possible hazardous obstacles with respect to trains. A holistic approach to autonomous obstacle detection for railways increases the detection area, including areas behind a curve, a slope, tunnels, and other elements blocking the train’s view on the rail tracks, in addition to providing long-range straight rail track OD. This paper presents a demonstration of the SMART2 holistic OD performed during the operational cargo haul with in-service trains. This paper defines the demonstration setup and scenario and shows the performance of the developed holistic OD system in a real environment. Full article

Coupling effects of various loading conditions can cause deflections, settlements and even failure of in-service bridges. Although it is one of the most critical loads, unfortunately, loading conditions of moving vehicles are difficult to capture in real time by bridge monitoring systems currently in place for sustainable operation. To fully understand the status of a bridge, it is essential to obtain instantaneous vehicle load distributions in a dynamic traffic environment. Although there are some methods that can identify overweight vehicles, the captured vehicle-related information is scattered and incomplete and thus cannot support effective bridge structural health monitoring (BSHM). This study proposes a noncontact, vision-based approach to identification of vehicle loads for real-time monitoring of bridge structural health. The proposed method consists of four major steps: (1) establish a dual-object detection model for vehicles using YOLOv7, (2) develop a hybrid coordinate transformation model on a bridge desk, (3) develop a multiobject tracking model for real-time trajectory monitoring of moving vehicles, and (4) establish a decision-level fusion model for fusing data on vehicle loads and positions. The proposed method effectively visualizes the 3D spatiotemporal vehicular-load distribution with low delay at a speed of over 30FPS. The results show that the hybrid coordinate transformation ensures that the vehicle position error is within 1 m, a 5-fold reduction compared with the traditional method. Wheelbase is calculated through dual-object detection and transformation and is as the primary reference for vehicle position correction. The trajectory and real-time speed of vehicles are preserved, and the smoothed speed error is under 5.7%, compared with the speed measured by sensors. The authors envision that the proposed method could constitute a new approach for conducting real-time SHM of in-service bridges. Full article