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In engineering, DIC is a widely used measurement technique. Its major advantage is that it provides real-time results (displacements, accelerations, stresses, strains, deformations) of the surface under examination relatively quickly and without contact. However, its application in medicine, biomechanics, and the field of criminalistics is novel. The present research focuses mainly on the frontier areas of forensics and medicine. The research aims to define the test boundary conditions and preparatory activities to measure the surface of the animal and then human skin. Injuries caused by low-energy ballistic bullets, blunt-force trauma, and cuts and punctures caused by knives and/or blades will be investigated. The present research focuses on puncture injuries in animal skin. The main challenge is to create a speckle pattern on the surface that can track deformation well. The research is about developing and validating this. The GOM ARAMIS measurement system was applied for the measurements. This paper demonstrates that a suitable preparation, painting procedure, and measurement setup has been established to measure the above effects, i.e., to identify displacements and deformations of up to tenths of a millimeter with sufficient accuracy. The evaluation of the results will also show that this method could be used in forensic applications, the automotive industry, medical orthopedics, and the textile industry.

Abstract The cross-level and twist irregularities are the most dangerous irregularity types that could cause wheel unloading with the risk of derailments and additional maintenance expenses. However, the mechanism of the irregularities initiation and development is unclear. The motivation of the present study was the previous experimental studies on the application of wide sleepers in the ballasted track. The long-term track geometry measurements with wide sleepers show an enormous reduction of the vertical longitudinal irregularities compared to the conventional track. However, wide sleepers had higher twist and cross-section level irregularities. The present paper aims to explain the phenomenon by discrete element method (DEM) modeling the development process of sleeper inhomogeneous support at cross-level depending on the sleeper form. The DEM simulations show that the maximal settlement intensity is up to 3.5 times lower for a wide sleeper in comparison with the conventional one. Nevertheless, the cross-level differential settlements are almost the same for both sleepers. The particle loading distribution after all loading cycles is concentrated on the smaller area, up to the half sleeper length, with fully unloaded zones under sleeper ends. Ballast flow limitation under the central part of the sleeper could improve the resilience of wide sleepers to the development of cross-level irregularities. The mechanism of initiation of the cross-level irregularity is proposed, which assumes the loss of sleeper support under sleeper ends. The further growth of inhomogeneous settlements along the sleeper is assumed as a result of the interaction of two processes: ballast flow due to dynamic impact during void closing and on the other side high pressure due to the concentration of the pressure under the middle part of the sleeper. The DEM simulation results support the assumption of the mechanism and agree with the experimental studies.

This paper introduces and describes a method for extracting, processing, and analyzing large amounts of track geometrical data. It allows for a more accurate description of the orbital deterioration correlations than currently applied procedures, and it seems to be more valuable and efficient in practice. The initial data were the track geometry measurement and classification data for the whole national network provided by the Hungarian State Railways, i.e., the MÁV PLC. The MÁV provided data for the whole Hungarian railway network for 27 half-years, measured and recorded by the FMK-004 type special diesel locomotive (i.e., track geometry measuring car). The paper discusses the development of a procedure to automatically compute important condition ratings from the available data set of millions of units according to the algorithms created for railway industry colleagues, thus helping the maintenance and renewal decision-making process. Functions have been developed to classify the track geometry condition of a given railway line, to predict how long the service level can be maintained without intervention (i.e., e.g., lining, leveling, and tamping with a mechanized maintenance train), to determine the time of the necessary maintenance intervention, the time of the upgrade (rehabilitation or modernization), and to develop a track geometry prediction procedure that makes full use of the mathematical and computational possibilities of the present day.

This research introduces a new approach for detecting mobile phone use by drivers, exploiting the capabilities of Kolmogorov-Arnold Networks (KAN) to improve road safety and comply with regulations prohibiting phone use while driving. To address the lack of available data for this specific task, a unique dataset was constructed consisting of images of bus drivers in two scenarios: driving without phone interaction and driving while on a phone call. This dataset provides the basis for the current research. Different KAN-based networks were developed for custom action recognition tailored to the nuanced task of identifying drivers holding phones. The system’s performance was evaluated against convolutional neural network-based solutions, and differences in accuracy and robustness were observed. The aim was to propose an appropriate solution for professional Driver Monitoring Systems (DMS) in research and development and to investigate the efficiency of KAN solutions for this specific sub-task. The implications of this work extend beyond enforcement, providing a foundational technology for automating monitoring and improving safety protocols in the commercial and public transport sectors. In conclusion, this study demonstrates the efficacy of KAN network layers in neural network designs for driver monitoring applications.

Lithium-ion battery technology in the modern automotive industry utilizes highly temperature-sensitive batteries. Here, air cooling strategies will be the most applicable for the chosen example based on strategies for temperature control. Simulations have been utilized to evaluate the different thermal management strategies. A battery model was developed using the solutions offered by Computational Fluid Dynamics (CFD) simulation technology. It utilizes the heat produced by the discharge of the battery cells. Due to the simulation's limited computational capacity, the energy transfer model was implemented with a simplified but sufficiently complex physical mesh. Ten actual measurements were conducted in the laboratory to investigate the heating of the cell during the charging and discharging of 18650-type batteries. The results were applied to validate the simulation model. The simulation outcomes and thermal camera readings were compared. The cell-level numerical model was then extended to examine the temperature variation at the system level. The primary design objective is to achieve the highest energy density possible, which necessitates that the cells be constructed as closely as possible; however, increasing the distance between the cells can provide superior cooling from a thermal management perspective. The effect of varying the distance between individual cells on the system's heating was analyzed. Greater distance resulted in a more efficient heat transfer. It was also discovered that, in some instances, a small distance between cells produces inferior results compared to when constructed adjacently. A critical distance range has been established based on these simulations, which facilitates the placement of the cells.

While the effect of ballast degradation on lateral resistance is noteworthy, limited research has delved into the specific aspect of ballast breakage in this context. This study is dedicated to assessing the influence of breakage on sleeper lateral resistance. For simplicity, it is assumed that ballast breakage has already occurred. Accordingly, nine granularity variations finer than No. 24 were chosen for simulation, with No. 24 as the assumed initial particle size distribution. Initially, a DEM model was validated for this purpose using experimental outcomes. Subsequently, employing this model, the lateral resistance of different particle size distributions was examined for a 3.5 mm displacement. The track was replaced by a reinforced concrete sleeper in the models, and no rails or rail fasteners were considered. The sleeper had a simplified model with clumps, the type of which was the so-called B70 and was applied in Western Europe. The sleeper was taken into consideration as a rigid body. The crushed stone ballast was considered as spherical grains with the addition that they were divided into fractions (sieves) in weight proportions (based on the particle distribution curve) and randomly generated in the 3D model. The complete 3D model was a 4.84 × 0.6 × 0.57 m trapezoidal prism with the sleeper at the longitudinal axis centered and at the top of the model. Compaction was performed with gravity and slope walls, with the latter being deleted before running the simulation. During the simulation, the sleeper was moved horizontally parallel to its longitudinal axis and laterally up to 3.5 mm in static load in the compacted ballast. The study successfully established a relationship between lateral resistance and ballast breakage. The current study’s findings indicate that lateral resistance decreases as ballast breakage increases. Moreover, it was observed that the rate of lateral resistance decrease becomes zero when the ballast breakage index reaches 0.6.

On behalf of MÁV Hungarian State Railways Ltd., the authors carried out a research and development (R&D) project on behalf of the Budapest University of Technology and Economics, Department of Highway and Railway Engineering, on the subject of “Research and investigation of the causes of gauge narrowing by finite-element modeling in running track and turnout, and under operational and laboratory conditions”. The main objective of the research was to investigate the causes of localized defects of gauge narrowing in railway tracks based on machine and manual track measurements, laboratory measurements, and theoretical considerations. The measures proposed as a consequence of identifying the causes could significantly contribute to reducing the number and extent of local defects in the future. Furthermore, the research aims to develop new theories in less scientifically mature areas and provide procedures and instructions that professional engineers and practitioners can easily apply. The main areas of research, which are not exhaustive, are as follows: (i) the evaluation of the measurement results provided by track geometry measuring and recording cars; (ii) on-site investigations in the railway track in terms of gauge and rail profile measurements; and, based on these, (iii) the selection of concrete sleepers, which were removed from the track and subjected to more detailed geometrical investigations in the laboratory, together with the components of the rail reinforcement; (iv) the track–vehicle connection, tight running in straight and curved track sections under track confinement; (v) modeling of the stability and deflection of the rail when the rail fastenings lose part of their supporting function; and (vi) finite element modeling of the concrete sleepers under operating conditions such as slow deformation of the concrete, temperature variation effects, and lateral support on the ballast. In the already-narrowed track section, the tight vehicle running is not the cause of the track gauge narrowing but a consequence, so it is not investigated in this paper.

The article solves the problem of theoretically determining the deformable characteristics of railway ballast, considering its condition through mathematical modeling. Different tasks require mathematical models with different levels of detail of certain elements. After a certain limit, excessive detailing only worsens the quality of the model. Therefore, for many problems of the interaction between the track and the rolling stock, it is sufficient to describe the ballast as a homogeneous isotropic layer with a vertical elastic deformation. The elastic deformation of the ballast is formed by the deviation of individual elements; the ballast may have pollutants, the ballast may have places with different levels of compaction, etc. To be able to determine the general characteristics of the layer, a dynamic model of the stress–strain state of the system based on the dynamic problem of the theory of elasticity is applied. The reaction of the ballast to the dynamic load is modeled through the passage of elastic deformation waves. The given results can be applied in the models of the railway track in the other direction as initial data regarding the ballast layer.

This paper examines the sustainability of railways. A comprehensive international literature review was conducted on railway vehicles, traction, and railway permanent way. The main goal was to find the factors and parameters that affect railway sustainability the most. CO2 emissions from transportation, mining, raw material production, manufacturing, use, operation and maintenance, and demolition and restoration must be significantly reduced. Naturally, the attention will be on the considerable energy and financial savings. This article's main topics are sustainability, affordable and clean energy, industry, innovation, infrastructure, sustainable cities and communities, responsible consumption and production, climate action, and life on land. Building materials come from quarries and gravel pits, but availability is decreasing. Future pavement construction and maintenance require recycling demolition and industrial waste. Engineers must choose materials and technology that extend track lifetimes to ensure reliability, availability, maintainability, safety, sustainability, and economy in permanent railroad ways. Life-cycle costs can be reduced, e.g., by Building Information Modeling. Electric machinery is preferred for construction equipment, materials, and management. Sustainability, like grassed tracks and recyclable plastics, has improved urban life. Sheet metal forming using recycled materials and sustainability shows how important environmental protection is in car and train design. Electric road and rail propulsion are driven by environmental concerns, while supercapacitors and batteries are studied. In conclusion, by preferring rail for freight and passenger transport, both for private and public transport, energy savings and CO2 emissions can be up to 2-10 times higher than for other modes of transport.

This research investigates the application of plastic fiber reinforcement in pre-tensioned reinforced concrete railway sleepers, conducting an in-depth examination in both experimental and computational aspects. Utilizing 3-point bending tests and the GOM ARAMIS system for Digital Image Correlation, this study meticulously evaluates the structural responses and crack development in conventional and plastic fiber-reinforced sleepers under varying bending moments. Complementing these tests, the investigation employs ABAQUS’ advanced finite element modeling to enhance the analysis, ensuring precise calibration and validation of the numerical models. This dual approach comprehensively explains the mechanical behavior differences and stresses within the examined structures. The incorporation of plastic fibers not only demonstrates a significant improvement in mechanical strength and crack resistance but paves the way for advancements in railway sleeper technology. By shedding light on the enhanced durability and performance of reinforced concrete structures, this study makes a significant contribution to civil engineering materials science, highlighting the potential for innovative material applications in the construction industry.

Monitoring bus driver behavior and posture in urban public transport’s dynamic and unpredictable environment requires robust real-time analytics systems. Traditional camera-based systems that use computer vision techniques for facial recognition are foundational. However, they often struggle with real-world challenges such as sudden driver movements, active driver–passenger interactions, variations in lighting, and physical obstructions. Our investigation covers four different neural network architectures, including two variations of convolutional neural networks (CNNs) that form the comparative baseline. The capsule network (CapsNet) developed by our team has been shown to be superior in terms of efficiency and speed in facial recognition tasks compared to traditional models. It offers a new approach for rapidly and accurately detecting a driver’s head position within the wide-angled view of the bus driver’s cabin. This research demonstrates the potential of CapsNets in driver head and face detection and lays the foundation for integrating CapsNet-based solutions into real-time monitoring systems to enhance public transportation safety protocols.

The growing number of electric vehicles and devices drives the demand for lithium-ion batteries. The purpose of the batteries used in electric vehicles and applications is primarily to preserve the cells and extend their lifetime, but they will wear out over time, even under ideal conditions. Most battery system failures are caused by a few cells, but the entire system may have to be scrapped in such cases. To address this issue, the goal is to create a concept that will extend the life of batteries while reducing the industrial and chemical waste generated by batteries. Secondary use can increase battery utilization and extend battery life. However, processing a large number of used battery cells at an industrial level is a significant challenge for both manufacturers and users. The different battery sizes and compositions used by various manufacturers of electric vehicles and electronic devices make it extremely difficult to solve the processing problem at the system level. The purpose of this study is to look into non-destructive battery diagnostic options. During the tests, the condition of the cells is assessed using a new diagnostic technique, 3D surface digitalization, and the fusion of electrical parameters. In the case of surface digitalization, the digital image correlation (DIC) technique was used to estimate the cell state. The tests were conducted on various cells with widely used geometries and encapsulations. These included a lithium polymer (soft casing), 18650 standard sizes (hard casing), and prismatic cells (semi-hard). The study also included testing each battery at various charge states during charging and discharging. The findings help to clarify the changes in battery cell geometry and their localization. The findings can be applied to cell diagnostic applications such as recycling, quality assurance, and vehicle diagnostics.

The article examines the superstructures of the tramway tracks of tramway line No. 1 in Budapest (the capital of Hungary). Since the first appearance of tramways, several technological advancements have been made to serve passenger needs as efficiently as possible. Several types of tramway track superstructure systems can be differentiated, which are implemented differently in each project. Furthermore, these superstructure types have different degradation times (both geometrical and structural), which depend on several factors. Nowadays, visual inspections are no longer considered sufficient in monitoring the tracks’ condition and deterioration, thus it is necessary to consider examinations carried out using the sensors mounted on the vehicles. Adopting appropriate methods, the measured data can be modeled and the life cycle of superstructures and structural elements can be determined as a result of sufficiently long-term studies (i.e., life cycle costs, the whole lifetime, etc.). First, the authors present a review of the relevant international literature, after that they conduct analysis of track geometry parameters of the superstructures related to five sections on the investigated tramway line based on the results of the measurements performed for three consecutive years between 2019 and 2021. The analyses consist primarily in statistical examination of the measured and calculated parameters.

Methods of increasing the bearing capacity of corrugated metal structures of transport constructions using transversal stiffening ribs in the form of additional corrugation and stiffeners are given. Based on the theory of elasticity, a mathematical model for estimating the stress-strain state of transport constructions made of corrugated metal structures reinforced with stiffening ribs in the form of double corrugation was developed. The method of determining equivalent forces during rolling stock passage is offered. It has been established that double corrugation increases the bearing capacity of corrugated metal structures. Therefore, additional corrugation of corrugated metal structures reduces stresses by up to 20% and deflections by 50%. The obtained results show that the increase in rolling stock speed does not lead to a significant increase in stresses and strains in CMS when the railway track corresponds to the design state.

There is a class of tasks that requires considering the dynamics not only for rolling stock but also for the response of the railway track. One of the directions of railway transport development, which encourages the transition to fundamentally new dynamic models of the railway track, is undoubtedly an increase in traffic speed. To solve such problems, the authors applied a model of the stressed-strained state of a railway track based on the dynamic problem of elasticity theory. The feature of this model is the calculation of dynamic stresses and deformations induced by the spread of elastic waves through the objects of the railway track. Based on the mathematical modeling of stress propagation in the under-rail basis, authors have shown the influence of various objects of a railway track on the formation of the outline of the front of the elastic wave and determined the main time intervals. Furthermore, the authors propose the following analytical method, which, in addition to the soil's physical and mechanical properties, considers the properties of the ballast as a layer that transmits pressure to the roadbed and takes an active part in the formation of the interaction space.

Bus driver distraction and cognitive load lead to higher accident risk. Driver distraction sources and complex physical and psychological effects must be recognized and analyzed in real-world driving conditions to reduce risk and enhance overall road safety. The implementation of a camera-based system utilizing computer vision for face recognition emerges as a highly viable and effective driver monitoring approach applicable in public transport. Reliable, accurate, and unnoticeable software solutions need to be developed to reach the appropriate robustness of the system. The reliability of data recording depends mainly on external factors, such as vibration, camera lens contamination, lighting conditions, and other optical performance degradations. The current study introduces Capsule Networks (CapsNets) for image processing and face detection tasks. The authors’ goal is to create a fast and accurate system compared to state-of-the-art Neural Network (NN) algorithms. Based on the seven tests completed, the authors’ solution outperformed the other networks in terms of performance degradation in six out of seven cases. The results show that the applied capsule-based solution performs well, and the degradation in efficiency is noticeably smaller than for the presented convolutional neural networks when adversarial attack methods are used. From an application standpoint, ensuring the security and effectiveness of an image-based driver monitoring system relies heavily on the mitigation of disruptive occurrences, commonly referred to as “image distractions,” which represent attacks on the neural network.

In the 21st century, one of the key requirements is to develop and maintain our infrastructure facilities most efficiently using the available resources. Tramways are of significant national economic importance and represent an important national asset. There are currently seven different types of superstructure systems in Hungary, based on the national regulations and the related requirements currently in force. This paper compares the paved tramway superstructure systems in the context of track geometry, through-rolled axle tons of track, and the age of track sections. Paved tracks have many benefits, but the main ones are easier maintenance and road traffic use. Elastically supported continuous rail bedding (ESCRB; in Hungary, this is known as “RAFS”) and “large” slab superstructure systems are used to create paved superstructure systems. Road crossings use the latter systems, while heavily loaded lines use several ESCRB systems. This article examines the geometrical changes in several ESCRB superstructure systems. A TrackScan 4.01 instrument was used to take measurements in June and September 2021 and in April 2022, September 2022, and May 2023. Track gauge, alignment, and longitudinal level are examined. Regardless of the ESCRB superstructure system or age, a medium-loaded line’s track gauge trendline increases, which means that the track gauge is widening and, regardless of traffic load or age, the average longitudinal level is constantly increasing from year to year. When it is a medium-loaded line, the average value of alignment increases slightly, and the trendline is almost straight, but it decreases when it is an extremely heavily loaded line. The authors will analyze how the reference track section will change in the future. Based on the results, it is important to assess how subsequent measurements affect the trend lines. Because the data evaluations show similar results, comparing open tramway tracks to paved ones is crucial.

Manufacturing processes can be cited as significant research areas when examining infrastructure systems and infrastructure, as they are inextricably linked to both. Examples include automobile manufacturing, the production of traffic signs, etc. Connecting and utilizing Industry 4.0 technologies and processing simulation solutions to address industry challenges, such as process optimization and fault detection, are gaining in popularity. Cyber-physical systems and digital twins connect the physical and cyber worlds to enable intelligent manufacturing capabilities, increased system flexibility, decreased manufacturing-cycle times, and improved quality. This paper presents a solution that improves the synchronization between the real (physical) and simulation (digital) layers, using discrete-event-driven simulations to create more efficient and accurate digital-twin environments. Using a combination of inexpensive commercial microcontrollers and an inertial-measurement-unit sensor to enhance a standard programmable logic controller process, a discrete-event-simulation-based digital layer is updated in real time to produce a live digital twin. The system can accurately identify and track products throughout the production cycle while simultaneously updating the digital twin in real time. Even independently, the algorithm running on the microcontroller can be used to gather the input parameters required for the simulation of production processes. The implemented environment can serve as a suitable testing ground for investigating the practical applicability of digital-twin solutions.

In this paper, the authors examined the change in track gauges in curves for several railway lines with low and high traffic in Hungary (i.e., secondary lines and main lines). They covered the processing of raw data as well as statistical calculations. The considered curved sections were transition curves (TCs) and circular curves (CCs), as well as—in some cases—entire curves (ECs), including TCs and CCs, but not dividing them into parts. The change of track gauge parameter as a function of elapsed time was analyzed based on the distribution functions by calculating the Vaszary-type shape number. A statistical test with the Kolmogorov–Smirnov test was performed, in which the question as to whether the measurement data of the railway lines followed a normal or lognormal distribution was examined; additionally, the skewness and kurtosis parameters were calculated and analyzed. The authors also took into account the impact of the track system and the sleepers. For the selected curves, the authors observed how the average track gauge changes and categorized them according to tolerances. In presenting and summarizing the tests, the authors formulated a conclusion for each study fulfilled. Despite higher traffic loads, the value of track degradation over time is lower for mainline curves than for secondary line curves. It is because the main line has stricter tolerances due to the higher speeds allowed, and more maintenance work is carried out on these lines. The authors concluded that the type of the track system and the sleeper type also influence the change in track gauges in curves. The accurate deterioration ratios for all analyses are contained in the paper.

Unmanned Aerial Vehicles, also known as UAVs, play an increasingly important part in daily life. However, the ever-increasing number of UAVs pose an ever-increasing threat to the transportation infrastructure. Despite their precision and general efficiency, infrastructural-scale Unmanned Aerial Systems (UASs) have a disadvantage regarding their capability of being implanted in the ecosystem. There are several reasons for this, but the primary bottleneck is that their systems are not transparent to society and have very complicated processes. As a result, the authors decided to investigate the functional properties of UASs and make improvements to those properties. Throughout the study, the authors’ primary focus was on analysis, which boosts productivity and ensures a significant level of safety for routine flights. The amount of power that a UAV uses depends on several variables, including the amount of power that its individual components require, the temperature of its surroundings, and the condition of the battery that it is powered by. Therefore, critical parameters and interdependencies are taken into account in the risk assessment strategy for energy-efficient Unmanned Aerial Vehicles (UAVs). In the case of UAVs, the algorithm performs a risk calculation before take-off to estimate the amount of risk that can be associated with the given flight time when using the provided battery. On the one hand, several instances of the pre-take-off state and how its parameters interact are investigated. On the other hand, they demonstrate the calculation of the risk while in flight, which is based on actual flight data.

This paper investigates the usability of touch screens used in mass production road vehicles. Our goal is to provide a detailed comparison of conventional physical buttons and capacitive touch screens taking the human factor into account. The pilot test focuses on a specific Non-driving Related Task (NDRT): the control of the on-board climate system using a touch screen panel versus rotating knobs and push buttons. Psychological parameters, functionality, usability and, the ergonomics of In-Vehicle Information Systems (IVIS) were evaluated using a specific questionnaire, a system usability scale (SUS), workload assessment (NASA-TLX), and a physiological sensor system. The measurements are based on a wearable eye-tracker that provides fixation points of the driver’s gaze in order to detect distraction. The closed road used for the naturalistic driving study was provided by the ZalaZONE Test Track, Zalaegerszeg, Hungary. Objective and subjective results of the pilot study indicate that the control of touch screen panels causes higher visual, manual, and cognitive distraction than the use of physical buttons. The statistical analysis demonstrated that conventional techniques need to be complemented in order to better represent human behavior differences.

This paper presents a short literature review related to the fragmentation of the railway crushed ballast particles. With the help of the processed articles with the main topic of discrete element modelling (DEM) we aim to provide some insight into the international achievements and forward progress of the subject. Rock materials as granular elements can be investigated from several perspectives. The elements can be examined in laboratory conditions purely from the quarry, or even by obtaining already fragmented particles from the real railway tracks. In addition, DEM models can be created by using computer software. This article tackles only a small segment of the literature. Though each DEM topic was unique, they all involved examination of degradation of particles in some way. This review focuses on model building, including particle construction and calibration. The selected publications do not cover the current state of the entire DEM research related to ballast degradation.

The construction and maintenance of a railway track is an expensive process. Therefore, nowadays, except for advanced countries, considerable attention must be paid to apply the optimal maintenance of railway lines. In Hungary, until 2020 nearly 11% of railway tracks were renewed and rehabilitated from EU support, which means millions of Euros, i.e. billions of Hungarian Forints. It also follows from the support that planned preventive maintenance works must be performed on the renewed and rehabilitated lines. On the other hand, it takes away significant costs from the non-renewed (non-rehabilitated) lines maintenance works, but naturally, less money does not mean less failures, so cost-effective technologies are needed. A segment of maintenance is the local substructure problem(s). In this article, this segment will be mentioned from the development of the failures, through the applied technologies, to the possible new solutions like injection and the using of geosynthetic cementitious composite mats (so called GCCMs).

In this paper the authors detail the possibilities of modelling of finite element method (FEM) of glued insulated rail joints which are applied in railway tracks with continuously welded rails (CWR). A lot of laboratory tests (static and dynamic 3-point bending tests, axial pulling tests) were executed on glued insulated rail joints, the specimens were related to three different rail profiles applied in Hungary: MÁV 48.5; 54E1 (UIC54), 60E1 (UIC60), respectively. The static bending tests with many bay length values were conducted, before and after dynamic (fatigue) tests. 2-D beam models were made in FEM software using semi-rigid hinge as the simplified connection of fishplated glued insulated rail joint. The FEM models were calibrated and then validated with the static vertical displacement values in the middle-bay position measured in laboratory. The model validation was conducted with two methods.

The main objective of this research is to identify optimal printing strategies and PLA (polylactic acid) filament materials to produce rapid prototype deep drawing tools. Additive 3D printing technologies have been applied for a long time to produce tools, but the research is unique in that it uses conventional and various reinforced PLA materials with conventional FDM (Fused Deposition Modeling) printers. The advantage of this method is that PLA is easy to print and recycle and does not require expensive or special printers, this also gives the article its novelty. A further aim was to produce the tools using commercially available low-end printers. DX53D 0.8 mm thick body steel and AlMg3 2.5 mm thick sheet were the materials to be molded for the tests. The test tool was an Erichsen deep drawing punch. Tool wear was tested using the GOM ATOS measuring system, an optical coordinate measuring machine based on the DIC (Digital Image Correlation) principle, which is also popular in the automotive industry. The study aims to determine the 3D printing and material parameters that can safely produce a minimum batch of 100 parts.

The current paper deals with the numerical investigation of a unique designed pre-stressed reinforced concrete railway sleeper for the design speed of 300 km/h, as well as an axle load of 180 kN. The authors applied different methodologies in their research: traditional hand-made calculations and two types of finite element software. The latter were AxisVM and ABAQUS, respectively. During the calculations, the prestressing loss was not considered. The results from the three methods were compared with each other. The hand-made calculations and the finite element modeling executed by AxisVM software are adequate for determining the mechanical inner forces of the sleeper; however, ABAQUS is appropriate for consideration of enhanced and sophisticated material models, as well as the stress-state of the elements, i.e., concrete, pre-stressed tendons, etc. The authors certified the applicability of these methodologies for performing the dimensioning and design of reinforced concrete railway sleepers with pre-stressing technology. The research team would like to continue their research in an improved manner, taking into consideration real laboratory tests and validating the results from FE modeling, special material models that allow calculation of crackings and their effects in the concrete, and so that the real pattern of the crackings can be measured by GOM Digital Image Correlation (DIC) technology, etc.

This paper deals with the time-frequency characteristic analysis for track geometry irregularities using field data recorded by a comprehensive track inspection train. The parameters of the track gauge and the left and right rail alignment are considered to identify their characteristic wavelengths and the locations of their waveforms. In addition to the conventional time and frequency domain analysis, auto-adaptive signal decomposition techniques are used on four pre-selected track sections. During the time series analysis of the track gauge, the cumulative difference from the mean value is calculated, which makes it possible to distinguish the track section constructed with non-standard initial track gauges. The sensitive wavelengths of the track irregularities are obtained from the proper allocation of wavelength ranges in the Fourier Amplitude Spectrum of the original signal and the Fourier transform of the components detected by the Variational Mode Decomposition. This analysis can elucidate the wavelengths and positions of track irregularities that affect vehicle responses.

We investigated lubricants and thin teflon foils that can be applied in the formability testing of the thin aluminum sheets used in the electronics and automotive industries. For the tests, thirteen different industrial lubricants (oils and greases) (i.e., L1–L13) and two Teflon films (i.e., 0.08 and 0.22 mm thick) were applied. The authors conducted an Erichsen test, and the thickness reduction of the discs was measured first. In forming-limit curve (FLC) tests, it is crucial that the stresses are localized in the central area of the specimen during forming and that biaxial deformation is maintained throughout, if possible. We aimed to achieve and fulfill this task. To perform this measurement, the GOM ARAMIS measuring system was utilized. It is an optical measuring system based on the digital image correlation (DIC) principle, capable of measuring both stresses and displacements in real time. A specific validation method was also developed to qualify the DIC system. We concluded that there was a 5% difference in Erichsen indentation (IE) number diagrams between the best (L12) and worst (L4) cases for the lubricants and oils tested, which is a significant difference for thin plates. We found that this value could be increased and improved by using Teflon discs. Furthermore, the localization of stress maxima, i.e., the centering of cracks in the specimen, could be achieved by combining Teflon discs and L12 lubricant (with appropriate layer order), which significantly aids in the recording of standard FLC diagrams. Using foils is also advantageous because they are readily available, have no expiry date, and are of less environmental concern.

The preparatory operations of DIC (Digital Image Correlation) tests were investigated in this study, with special emphasis on specimen cleaning and painting operations. As it is well known, DIC tests are non-contact and applied in materials research, the analysis of complex structures, and, nowadays, the construction industry. The use of DIC technologies has seen a dynamic increase in all scientific fields. In our study, aluminum body panels for automotive and railway applications were tested using this technique. There are many articles on proper patterning in the literature but fewer on preparation and priming. These are critical for a successful DIC measurement. This paper looks at different surface cleaners and primers with different grading procedures and will also determine the time window within which the paint should be applied. Finally, the GOM ARAMIS system was applied to measure and characterize the painted surface and visible deformation defects resulting from inadequate painting.

The article deals with DIC (Digital Image Correlation) tests on steel plates used in the automotive and railway industries, as well as in the construction industry. The most critical part of DIC tests is the quality of proper surface preparation, painting, and random patterns. The paint mediates the deformation of the optical systems, and its quality is paramount. The authors’ goal in this research is to determine the optimal dye–cleaning–drying time parameters for DIC studies. Commercially available surface preparation and cleaning agents were tested alongside commercially available spray paints. Standard and specific qualification procedures were applied for the measurements. Once the appropriate parameters were determined, the results were validated and qualified by GOM ARAMIS tests. Based on the results, DIC measurements can be performed with higher accuracy and safety in laboratorial and industrial conditions, compared to the traditional deformation measurements executed by dial gauges or linear variable differential transformers.

The current paper concerns the investigation of CC (Concrete Canvas), a unique building material from the GCCM (geosynthetic cementitious composite mat) product group. The material is suitable for trench lining, trench paving, or even military construction activities, while the authors’ purpose is to investigate the application of the material to road and railway substructure improvement. This research was carried out to verify the material’s suitability for transport infrastructure and its beneficial effects. The authors’ previous study reported that the primary measurements were puncture, compression, and the parameters evaluated in four-point bending (laboratory) tests. However, based on the results, finite element modeling was not feasible because the testing of the composite material in a single layer did not provide an accurate indication. For this reason, the material characteristics required for modeling were investigated. A unique, novel testing procedure and assembly were performed, wherein the material was loaded under quasi-realistic conditions with a crushed stone ballast sample and other continuous particle size distribution samples in a closed polyethylene tube. In addition, the deformation of the material following deformed bonding was measured by computed tomography scanning, and the results were evaluated.

Automatic transmission is a key factor for autonomous driving. The transmission condition is highly affected by the quality and quantity of transmission oil in the system. However, the oil condition is not monitored in the system, and the oil change interval and method are still a subject of discussion. This paper analyzes the effects of oil changes in automatic transmissions. The measurements were carried out before and after the oil change with the same external conditions. With the vibration measurement method, data can be collected without disassembling the parts and during operational conditions. Furthermore, time- and frequency-based analyses were conducted to compare different transmissions’ operations. The results have shown that the effect of oil degradation is measurable on the amplitude of the signals and, therefore, predictable with vibration diagnostics. During the evaluation, the maximum values were compared on measurements with at least a 2-s length.

The most important thing nowadays is to use available resources to develop infrastructure as efficiently as possible. In this regard, evaluating the deterioration of tramway tracks is critical from both a technical and an economic viewpoint. In Hungary, seven types of superstructure systems are currently differentiated in the case of tramway transport, but the geometrical deterioration, lifecycle, and lifecycle cost of the tramway tracks are not accurately known. The current study aimed to evaluate and compare the results of track geometry measurements of two different “open” tramway superstructure systems depending on their traffic load and age. The geometry measurements we re executed by TrackScan 4.01 instrument, developed and maintained by a Hungarian developer company called Metalelektro Méréstechnika Ltd. The evaluation of the measurements showed a clear relationship between the traffic load, age, and track deterioration. Based on the results, it can be generally stated, concerning “open” superstructure systems, that regardless of the “open” superstructure system or the level of traffic load, the average value of alignment is decreasing; however, the average value of the longitudinal level is increasing. Furthermore, the deterioration of an older ballasted track with lower traffic is similar to that of a younger ballasted track that has a higher traffic load. Another significant result was that the deterioration of the track gauge parameter in the case of concrete slab tracks is clearly described as the broadening of the track gauge.

Vehicle safety risk can be decreased by diagnosing the lithium-ion battery system of electric road vehicles. Real-time cell diagnostics can avoid unexpected occurrences. However, lithium-ion batteries in electric vehicles can significantly differ in design, capacity, and chemical composition. In addition, the battery monitoring systems of the various vehicles are also diverse, so communication across the board is not available or can only be achieved with significant difficulty. Hence, unique type-dependent data queries and filtering are necessary in most cases. In this paper, a Volkswagen e-Golf electric vehicle is investigated; communication with the vehicle was implemented via an onboard diagnostic port (so-called OBD), and the data stream was recorded. The goal of the research is principally to filter out, identify, and localize defective/weak battery cells. Numerous test cycles (constant and dynamic measurements) were carried out to identify cell abnormalities (so-called deviations). A query and data filtering process was designed to detect defective battery cells. The fault detection procedure is based on several cell voltage interruptions at various loading levels. The methodology demonstrated in this article uses a fault diagnosis technique based on voltage abnormalities. In addition, it employs a hybrid algorithm that executes calculations on measurement and recorded data. In the evaluation, a status line comprising three different categories was obtained by parametrizing and prioritizing (weighting) the individual measured values. It allows the cells to be divided into the categories green (adequate region), yellow (to be monitored), and red (possible error). In addition, several querying strategies were developed accordingly to clarify and validate the measurement results. The several strategies were examined individually and analyzed for their strengths and weaknesses. Based on the results, a data collection, processing, and evaluation strategy for an electric vehicle battery system have been developed. The advantage of the developed algorithm is that the method can be adapted to any electric or hybrid vehicle battery.

The maintenance of the ballast substructure is an important cost-driver for railway systems. The problem is that today’s condition monitoring methods are insufficient to collect detailed data on the compaction and stress allocation inside the ballast bed. That makes it challenging to improve the maintenance technology and organization. This study aimed to investigate the applicability of the ultrasound method for analyzing the state of stress of sand-soil and the relation between the residual stress and wave propagation velocity. The experiments on the sand in a box with different allocations of the ultrasonic receivers and pressure measurement cells were produced under different external loading. In addition, the vertical and horizontal stress distributions were measured. The results showed a correlation between the test load, the state of stress, and the ultrasound propagation velocity. Moreover, the residual stresses after the loading cycles were analyzed.

Railway damage detection is of great significance in ensuring railway safety. The cracks on the rail surface play a key role in studying the formation and development process of rail damage, predicting the occurrence of rail defects, and then improving the service life of the rail. However, due to the small shape of the cracks, the typical detection method is relatively complicated, and the speed is quite slow. Although traditional magnetic particle inspection technology is fairly accurate at detection, it is costly and inconvenient to carry and install, while also limiting the detection speed and affecting the system’s operation. In this paper, a semantic segmentation detection method is developed by using various collected rail surface crack data and deep learning through a neural network. By comparing the inspection of the same rail surface with magnetic particle inspection technology, only inexpensive cameras are used and the inspection speed is increased while maintaining relatively high accuracy. In addition, the method can achieve fast detection speeds if it is extended to be combined with high-frequency cameras. It is an economical, efficient, and environmentally friendly method for future rail surface detection.

This paper demonstrates the results in the research topic of the railway ballast particles’ breakage test with unique laboratory test. The most railway lines in the world have so called traditional superstructure (ballasted tracks). In the past few years there were a lot of railway rehabilitation projects in Hungary, as well as abroad. Nowadays cannot be expected that there is enough quantity of railway ballast in adequate quality, because of the modifications and restrictions in the related regulations in Hungary since 2010. In Hungary there are only a few quarries which are able to ensure adequate railway ballast material for construction and maintenance projects for speed values between 120 and 160 km/h. This may cause supply and quality risk in production of railway ballast. The authors’ research’s main goal is to be able to simulate the stress-strain effect of ballast particles in real and objective way in laboratory conditions as well as in discrete element modelling.