Hosting providers are essential for maintaining the security and reliability of digital services, but they continue to face challenges from malicious activities in their network, such as malware and phishing. The European Union’s Digital Services Act (DSA) was introduced to improve accountability and create a safer online environment, but its effectiveness in helping hosting providers mitigate abuse remains unclear. This study investigates whether compliance with the DSA has contributed to reducing malicious activity among Dutch hosting providers and examines the broader relationship between compliance levels and cybersecurity outcomes. This study evaluates the effectiveness of anti-abuse measures employed by Dutch hosting providers, with a focus on the role of the DSA in helping with compliance and reducing malicious activity. Specifically, it examines whether adherence to the DSA improves the ability of hosting providers to mitigate cyber threats, particularly in reducing the prevalence of malicious IP addresses. Using passive DNS data, the research examines changes in the prevalence of malicious IP addresses before and after the implementation of the DSA. Compliance levels were also analyzed to understand their correlation with malware percentages. The study employed statistical methods, including Interrupted Time Series (ITS) analysis and regression models, to evaluate trends and relationships between compliance and malicious activity. The findings indicate no statistically significant reduction in malicious IP activity following the implementation of the DSA, suggesting that compliance alone does not automatically translate into improved security outcomes. While the DSA strengthens transparency and procedural accountability, hosting providers continue to face operational challenges in implementing effective anti-abuse measures. Factors such as cybercriminal adaptation, enforcement inconsistencies, and resource constraints likely influence the weak correlation between compliance and actual abuse reduction. These results shows the need for a more holistic approach to cybersecurity regulation, combining technical advancements, industry collaboration, and proactive security enforcement alongside regulatory compliance. Evaluating the effectiveness of frameworks like the DSA is essential to ensuring that they not only establish compliance standards but also provide hosting providers with practical tools to enh The Dutch government aims to fully implement ERTMS (European Railway Traffic Management System) by 2050, with ETCS (European Train Control System) playing a crucial role. Currently, ETCS covers only 10% of the Dutch rail network, providing limited insight into train driver braking behavior. Differences between the current train control system (ATB) and ETCS systems cause deviations from the recommended speed curve, leading to inefficiencies in track utilization, increased wear and tear, and unrealistic capacity expectations. This research focuses on defining, visualizing and evaluating a balance between the ETCS requirements and the train driver behavior requirements, the comfort braking curve, within ETCS Level 2 parameters. As ETCS replaces ATB, it aims to enhance rail safety, capacity, and interoperability. However, train drivers currently operate under their own comfort preferences, which affects system performance. The goal is defining comfort and designing an optimal braking curve, compatible in the existing ETCS system based on the degree of comfort. And Investigate practical implications of the comfort braking curve, aligning train driver behavior, in relation to operational efficiency. The central research question is: What are the implications of implementing the comfort braking curve on capacity, wear and tear, safety, and driver experience? A literature review provided foundational knowledge on comfortable braking and driver behavior. The comfort braking curve is a smooth deceleration with minimal jerk ensuring smooth speed transitions, well-controlled braking and a balance between comfort, control, and safety. The comfort braking curve defines braking deceleration between 0.5 m/s2 - 0.6 m/s2 and a maximum jerk of 1.0 m/s3 to ensure a smooth ride. Practical observations show, for instance, that train drivers tend to coast 10% of their speed, avoid accelerating toward braking, and maintain margins to anticipate unforeseen situations. Expert interviews and analyses of train driver behavior in practice-, offered practical insights. This results in 6 factors and 6 scenarios that the train drivers described as discomfort. The comfort braking curve incorporates the anticipation strategies resulting from the 6 factors and 6 scenarios, so the comfort braking curve remains practical to be applied within operational constraints. Based on these insights and what the literature and practice say based on comfort, critical design parameters have been established. To do this, we examined how current braking curves are constructed and which parameters are important when designing the comfort braking curve, such as braking forces, velocities , and target distances. Simulations in FRISO validated the comfort braking curve under realistic conditions, analyzing its impact in terms of reliability, availability, maintenance, safety, health and environment. Results show the comfort braking curve fits within the timetable while maintaining robustness. Reduced energy consumption and power demands minimize equipment stress, leading to lower maintenance needs. Furthermore, the constant deceleration pattern improves driver experience by aligning with their natural behavior and enhancing predictability.ance online security and mitigate digital threats effectively.

The motivation for this research is rooted in the expected increase in demand for international train trips within the EU railway network, driven by policies promoting sustainable transportation solutions. Notable initiatives include the EU’s Green Deal objectives and the commitment to achieve climate neutrality by 2050. Additionally, significant investments in rail infrastructure, such as the Trans-European Transport Network, the introduction of high-speed rail for international travel, and the reduction of barriers to promote international train travel, are contributing factors. This surge in demand requires a reliable railway network and improved management of temporary capacity reductions, particularly during maintenance operations at cross-border sections. Cross-border rail transport is essential for this strategy but faces significant challenges, including technical barriers, regulatory discrepancies, and coordination inefficiencies among infrastructure managers from different countries.

Despite its importance, academic literature on cross-border maintenance strategies is notably limited or non-existent. This thesis begins by describing the current situation of railway cross-border sections to identify the main challenges and existing coordination practices. It then proceeds to analyse these challenges through expert opinions gathered via a questionnaire. By highlighting the key issues and potential solutions, this research aims to fill the gap in the literature and provide a comprehensive framework for improving cross-border railway maintenance coordination.

This thesis also develops a digital and cooperative framework (DCF) to enhance cross-border maintenance decision support within the railway system of the European Union (EU), addressing the cross-border challenges holistically. It emphasizes the introduction of digital twin technology to meet the urgent need for infrastructure digitalization and coordination between the authorities and infrastructure managers in different countries, enabling the cooperative optimisation of the capacity of railway networks. The DCF consists of three components: the establishment of a European Railway Entity, the creation of a European Railway Forum, and the implementation of digital twin (DT) technology. The European Railway Entity aims to centralize coordination, streamline decision-making, and enforce standardized regulations across member states. The European Railway Forum focuses on fostering collaboration and knowledge sharing among stakeholders, facilitating continuous improvement in maintenance practices. The DT technology offers real-time data visualization, predictive maintenance, and advanced analytics to optimize maintenance operations and enhance infrastructure reliability, enabling an evidence-based decision-making process.

Each of the three components of the DCF is evaluated for its potential benefits and implementation challenges. The European Railway Entity can enhance the coordination and standardization of maintenance operations but may face resistance due to its hierarchical structure and potential conflicts with infrastructure managers whose national interests might be compromised for the sake of overall system performance. The European Railway Forum is cost-effective and practical, promoting voluntary data sharing and continuous improvement; however, suggestions and implementation involve complex procedures that require trust and the management of key confidential information. DT offers the greatest potential for innovation and future-readiness, but it demands a significant initial investment, robust data security measures, and the design of complex mechanisms to enable coordination between different DT platforms and protocols across countries.

The proposed DCF is discussed in two case studies. The first case study consists of a generic case of a bridge for railways between two countries focusing on the implementation and assessing potential benefits and limitations of DT as a tool of the DCF. The second case study addresses the cross-border situation in the Netherlands, proposing an implementation plan and evaluating potential advantages and disadvantages. Additionally, the Emmerich–Oberhausen maintenance project on the cross-border section between the Netherlands and Germany is analysed. This case study highlights the benefits, and challenges of implementing the proposed DCF.

In conclusion, the proposed digital and cooperative framework, integrating the European Railway Entity, the European Railway Forum, and DT technology, aims to support maintenance decisions and address the current challenges in cross-border railway maintenance. This integrated framework seeks to improve operational efficiency, increase network reliability, and support the sustainability goals of the EU, ultimately making the railway system more attractive to users.

Beams are the fundamental structural engineering element, supporting and stabilizing various structures ranging from suspension bridges to buildings and railways. Modeling and analyzing these structures necessitates a comprehensive understanding of the underlying beam dynamics constituting the structures. Simulating and predicting the beam dynamics is pivotal in ensuring structural integrity, optimizing structure design, and selecting appropriate materials. For instance, in railways, tracks and catenary contact wires are conceptualized as beams, allowing for the application of renowned beam theories like Euler-Bernoulli and Timoshenko. These theories provide a foundation for formulating partial differential equations (PDEs) that govern the dynamic behaviors of these beam systems.

These PDEs could be leveraged to simulate the underlying scenarios. The dissertation introduces physics-informed machine learning (PIML) based approaches tailored to simulate the dynamics of beam structures. The aim is to incorporate the physical laws in the neural networks training for more accurate and realistic simulations, handle noisy data effectively, and improve prediction accuracy while mitigating challenges such as multiscale problems and generalization. Chapter 1 outlines the primary challenges tackled in the dissertation. Chapters 2 through 5 detail the methodologies developed to address each challenge.

Chapter 2 presents a physics-informed neural network (PINN) based methodology to simulate complex beam systems with real-world mate- rial properties. In addition, inverse problems are solved in the presence of noisy data to predict unknown parameters, including force acting on the beam systems. It is essential to consider the real-world material parameters to simulate the dynamics of the modeled system and ensure the digital model represents the ground truth. However, incorporating material characteristics leads to multiscale PDE coefficients in the physical model, posing difficulty in training for PINNs. Subsequently, a frame- work is proposed to incorporate nondimensional PDEs into the PINN loss function. This approach facilitates efficient forward and inverse simulations while robust to noise and uncertainty in measurement data. The efficacy of this approach is demonstrated through simulations of Euler- Bernoulli and Timoshenko beam systems, contributing to the challenge of simulating large-scale systems with multiple interconnected components.

Chapter 3 investigates beam dynamic simulations on Winkler foundations for large spatiotemporal domains using PIML. Predictions on expansive spatiotemporal domains are vital for structural integrity, design optimization, and control mechanisms. A causality-respecting PINN frame- work is introduced, enhancing prediction accuracy. Furthermore, integrating transfer learning addresses the need to re-train the network for different initial conditions and computational domains. Numerical experiments based on Euler-Bernoulli and Timoshenko theories validate the methodology for respecting the causality and generalizing the beam dynamics across similar problems. The approach efficiently predicts beam dynamics under diverse engineering scenarios, reducing computational costs and improving convergence.

Chapter 4 explores the generalization abilities of PIML, essential for practical applications requiring accurate predictions in unexplored regions. The proposed framework exploits the inherent causality in the PDE solutions by merging PIML models with recurrent neural architectures, namely neural oscillators. The neural ordinary differential equations in the form of neural oscillators effectively handle long-time dependencies and address gradient-related issues, fostering improved generalization in PIML tasks. Benchmark equations like viscous Burgers, Allen-Cahn, Schrödinger, and biharmonic Euler-Bernoulli beam equations are used to demonstrate the effectiveness of the proposed approach. Through ex- tensive experimentation with time-dependent nonlinear PDEs, the study showcases superior performance compared to existing state-of-the-art methods. The proposed method provides accurate solutions for extrapolation and prediction beyond the training data by enhancing the generalization capabilities of PIML, promising advancements in complex system simulations.

Chapter 5 follows up on generalization of beam dynamics beyond PIML- based approaches. Computer-aided simulations are crucial for advancing engineering industries, but existing simulators often struggle to generalize beyond their training domain. The chapter proposes a two-stage methodology to tackle this challenge. Firstly, it utilizes specialized simulators tailored to the application, such as causal PINNs and black-box finite element simulations. Secondly, it integrates predictions from the first stage into a recurrent neural architecture, incorporating ordinary differential equations to capture intrinsic dynamics and enhance generalization. The approach efficiently captures causality and generalizes dynamics across various data sources. Numerical experiments cover fundamental structural engineering scenarios, including real-world catenary contact wire uplift predictions, and demonstrate superior performance compared to conventional methods, and promise for diverse industrial applications. This dissertation concludes with Chapter 6.

In particular, this dissertation introduces PIML methodologies for simulating complex beam structures, addressing key challenges such as incorporating real material properties, handling noisy data, and improving prediction accuracy. Chapter 2 introduces a PINN-based methodology that efficiently simulates beam systems and predicts unknown parameters, mitigating the difficulties posed by multiscale PDE coefficients. Chapter 3 tackles the challenge of large-domain beam dynamics predictions on the Winkler foundations by using causality-respecting PINNs and integrating transfer learning to reduce computational costs. Chapter 4 addresses the challenge of out-of-domain predictions in PIML by introducing neural oscillators. Chapter 5 proposes a two-stage methodology to generalize beam dynamics simulations, integrating beam dynamics solvers and recurrent neural-based architectures, showcasing its efficacy in real-world applications such as catenary contact wire uplift predictions.

This thesis transforms the way we understand and monitor rail infrastructure with a digital twin that merges measurement data and physics-based models to deliver instant insights. This thesis will be of particular interest to professionals in the rail industry seeking to answer the following questions: What are the key features in the measurement data? How can an accurate physics-based vehicle-track interaction model be developed for a specific problem? And, how can mearsurement data and models be combined to deliver actionable insights in real-time?

Laser Doppler vibrometer (LDV) is a vibration-detecting instrument for noncontact and non-destructive measurement. It is superior to classic contact transducers in terms of the wide frequency range and high measurement resolution. LDV on moving platforms (LDVom) is one of the LDV measurement technology to one-way scan the vibrating surface, so that it is applicable in large-scale measurement like railway tracks. Speckle noise is a significant signal issue for LDV technologies, especially for LDVom. It distorts the local vibration signal dramatically and reduces the overall signal-to-noise ratio to a quite low level. The one-way scanning nature of LDVom makes it impossible to simply average the signals for noise removal. In view of the speckle noise issue of LDVom, the goal of this dissertation is to acquire new understanding of the problem and proposed there upon-based de-speckling solutions. Three aspects are investigated to achieve the research goal: 1) numerical simulation of speckle noise and characterization of noise behaviors. It can provide insight into behaviour changes of speckle noise in response to some variables and possible tools for minimizing noise strength; 2) the theoretical Fourier spectrum of speckle noise series. The resulted frequency domain characteristics can help design the de-noise signal filter accordingly; 3) development of classic approach-based and newly designed de-speckling algorithms...

Short pitch corrugation is a (quasi-) sinusoidal rail vertical defect on rail surface, and it was first found more than one century ago. The wavelength of short pitch corrugation is 20-80 mm, and its amplitude can be up to 100 µm. It mainly develops on straight tracks or at gentle curves with comparatively light axle loads. Due to short pitch corrugation, dynamic wheel-rail contact forces increase considerably, and hence the degradations of vehicle-track components are accelerated. In addition, the corrugation excited vibration is a source that radiates “roaring” noise. Because of those negative aspects, researchers have spent many efforts to understand and theoretically explain the problem. At present, the corrugation phenomenon is usually understood through a damage mechanism and a wavelength-fixing mechanism. Based on the explanation, almost all types of corrugations can be explained with their corresponding mechanisms, and countermeasures were confirmed to be capable of effectively mitigating them. Nevertheless, there has been yet no consensus on the mechanisms of short pitch corrugation due to: 1) it only appears at some tracks and some locations, 2) different from other types of corrugation, short pitch corrugation (after this shortened as “corrugation”) changes minorly with the change in train speed.In this dissertation, a three dimensional (3D) dynamic finite element (FE) vehicle-track frictional rolling contact model, which was initially used to research rail squats, is extended to understand the corrugation enigma. The goal is to investigate if the model can explain the root causes of the corrugation. A second goal is to characterize the rail material damages from rail corrugation metallurgically. After an introduction, the 3D dynamic FE vehicle-track frictional rolling contact model is applied to rail corrugation research. The damage mechanism evaluated is differential wear, and it is considered proportional to the frictional work. Nominal parameters and boundary conditions are used in the model. Corrugations with different phase angles are added to the rail model to investigate whether they can consistently grow. Similar to conclusions from previous research, the obtained differential wear is in phase with the corrugation, which means the corrugation will be worn off and not grow. Nevertheless, it is found that the longitudinal track vibration modes may be dominant for short pitch corrugation initiation, and the vertical modes become dominant at certain stages. The consistency of longitudinal and vertical contact forces, differential wear, and corrugation should determine the development of short pitch corrugation.Then in the second part of this thesis, through the variation of fastening modeling, an initial differential wear with large amplitudes is identified to form from the smooth rail. This differential wear is found to be correlated to the rail longitudinal dynamics. The corrugation explained by this differential wear can consistently initiate and grow up to 80 µm. Additionally, the corrugation from the numerical analysis agrees well with a rail corrugation recorded from the field. Consistency is shown during the corrugation growth between the vertical and longitudinal contact force, the differential wear, and the corrugation. Besides, a corrugation wavelength selection phenomenon can also be explained by this consistency. These results confirm the insights from the first part of the thesis, reveal the whole development process of corrugation, and explain its root cause.The third part of this thesis is a study of the rail material structural damage from a corrugation. A metallurgical study was performed to analyze the rolling contact fatigue damage of a rail sample with corrugation. Besides the well-known white etching layer (WEL), an extra layer called the brown etching layer (BEL) was identified with distinctly lower hardness and brown colour contrast. It bears some similar properties as the WEL, such as brittle though much softer. Compared to WEL, the cracks formed in the BEL were found to propagate downwards without branching and can lead to rail fracture in the end. It is unknown if the BEL is a transitional state from the pearlite structure to the WEL, if it forms after the WEL, or if it is a different layer formed under certain thermomechanical conditions. In conclusion, this thesis extends a 3D dynamic FE vehicle-track rolling contact model for the mechanism of corrugation study. Based on the research results, the root cause of the corrugation found on the Dutch railway network is identified. This finding opens the possibility to design methods to avoid or mitigate corrugation by optimising track structure parameters. Finally, the finding of BEL brings a new concept that will help to understand the rail material damage mechanisms from rail corrugation. The understanding of BEL will provide insight into crack development mechanisms, as BEL can lead to rail fracture. A complete understanding of rail material is crucial for the development of new rail technologies.

Nederland heeft ongeveer 7000 km spoor en bij het onderhoud daaraan komt er jaarlijks ongeveer 500 duizend ton aan ballast vrij. Het zou dus mooi zijn als dit allemaal hergebruikt kan worden. Maar doordat het ballast tijdens de levensduur vervuild en versleten raakt kan dit niet zomaar. De ballast wordt als chemisch afval beschouwd doordat er zware metalen in zitten door slijtage van metalen com- ponenten rondom het spoor.
Het doel van dit rapport is om antwoord te geven op de hoofdvraag: ’Hoe kan ballast een circulair materiaal worden?’
Ballast is wordt vaak gebruikt voor spoorwegen omdat het relatief goedkoop is om aan te leggen en omdat het makkelijk te onderhouden is. Ballast wordt altijd uit het buitenland geïmporteerd omdat het in Nederland niet voorkomt. Vaak uit Duitsland, Noorwegen of België.
Circulariteit staat voor het zo weinig mogelijk gebruiken van materiaal, het hoogwaardig hergebruiken van materiaal en het recyclen van materiaal. Om ballast circulair te laten worden moeten er dus ten eerste zo weinig mogelijk gebruikt worden, moet het zo vaak mogelijk voor de spoorwegen hergebruikt worden en moet het daarna op een andere manier hoogwaardig hergebruikt worden.
Dit wordt al voor een groot deel gedaan maar kan nog beter. Door middel van horren en zeven op locatie wordt al veel ballast hergebruikt voor de spoorwegen. Maar daarna wordt het vaak afgevoerd en niet op een hoogwaardige manier hergebruikt. Het gebeurt wel dat ballast wordt hergebruikt in beton maar het wordt ook vaak vermengd met puinkorrel.
Voor de circulariteit is het belangrijk dat er alles wordt hergebruikt, dus ook het kleinere grind en zand. Dit kan ook op veel manieren worden hergebruikt in bijvoorbeeld beton, asfalt of voor decoratief gebruik.
Tenslotte zijn er ook alternatieven voor ballast onderzocht, want ballast zou pas echt circulair zijn als het er helemaal niet meer is. Er kan bijvoorbeeld beton gebruikt worden, echter is dit veel duurder. Ook kunnen er metaalslakken gebruikt worden, alleen moet er nog meer onderzoek gedaan worden naar de vervuiling die het kan veroorzaken.
Kortom, ballast kan een circulair materiaal worden door alles op een hoogwaardige manier her te ge- bruiken. Waarbij er dus geen restproducten zijn, ook niet bij de tweede levenscyclus. Hierbij is het belangrijk dat het ballast niet zijn waarde verliest en dat het wordt hergebruikt voor iets wat aan gelijkwaardige waarde is of zelfs nog meer waard is, zoals beton of asfalt.

Railway sleepers form an important part of a classic track structure. Sleepers exists in their current form for a long time. The transition from wood to concrete sleeper has been made, but wood is still used and present in many track sections. As creosoted wooden sleepers are not allowed to be installed on the tracks anymore the search for durable and sustainable alternatives has started. One promising type is a hybrid sleeper constructed from recycled plastic (polyethylene) with steel reinforcement. The main part of this thesis is to create a finite element model that is capable of describing hybrid plastic sleepers. The ultimate goal is to be able to use this model to assist in sleeper acceptation. Current rules, regulations and high availability requirements make it difficult to test sleepers in the track under live loading conditions. Not many infrastructure managers are eager to install not already proven technology in their tracks. The general parameters of the model were investigated and combined with some specific finite element modelling methods. Those formed the starting point of the design. Important design methods were the parametrisation of the model as much as possible to allow assessment of slightly different models. Secondly a mapped mesh was preferred above a free mesh to improve on accuracy. Also the amount of detail is kept high to be able to fully investigate the sleepers, e.g. to investigate the reinforcement bond. The ANSYS APDL-language is used to program the FEM parametrically. This resulted in a comprehensive finite element model of one a whole sleeper. Fully modelled with base plate (without detailed fastening), rail pad and rail section. Every part is constructed out of solids and meshed with a mapped mesh including the reinforcement. Two model methods, a general circular and a more element wise optimal octagonal model, were used to generate the reinforcement. All single sleeper models can be connected to form a piece of track with several possibilities in altering the foundation parameters per sleeper or allowing for different types of sleepers inside the track. Concluding all generated finite element analysis (FEA) results could not impress enough to recommend the usage of FEA for sleeper acceptation. Especially with new, very non-linear behaving materials and a very dynamic loads, the effort involved in creating a validated finite element model (FEM) would be too great and the results not usable enough. For some parts a FEM can be beneficial, during design for example. Other simpler models than the one constructed here could be helpful if directly based on test results. But at least at this point in time, with relatively unknown materials, the direct testing of sleepers under loading conditions laboratory and in the track itself with close monitoring are regarded much more informative.

In recent decades, rail transport has become a popular mean of transportation due to its efficiency and environmental friendliness technology which lead to increasing the axle loads, speed and recurrence of the trains. These enhanced service provisions resulted in new challenges to the sustainability of the railway systems. Insulated rail joint (IRJ) is one of the crucial structural components of the railway track with the function of serving the signaling control by securing the occupancy of the track with one and only train in each divided block. An IRJ includes the application of two joint bars being bolted with the purpose of connecting two adjoining rails. In addition to the insulation layers between the joint bars and the rail, the end post which is positioned between the end-to-end rails, assure the disruptions of current flow between two blocks. The emerge of discontinuity in the stiffness and geometry at IRJs influence the service life of this component due to the introduced high dynamic forces. Subsequently, the IRJ is considered as one of the weak spots of the railway tracks which requires the allocation of great concern in their maintenance. In order to attain understanding of the wheel-rail dynamic interaction at IRJs, various analytical, experimental and numerical studies have been conducted in the past few years. The application of the finite element method (FEM), as a flexible numerical tool, reveals distinct advantages for understanding the behavior of the track structure under the pass-by wheel. This M.Sc. thesis utilizes an explicit finite element analysis to investigate the influence of the sleeper spacing and traffic speed on the impact force and vibration of the track. The FE model includes the detailed demonstration of the rail, joint bars and sleepers while simulated spring and damper elements are preferred to the rail pads and ballast to reduce the complexity of the model. Besides, the detailed illustration of the wheel and axle as well as the effects of the carbody and bogie are considered in the FE model. Based on the parametric studies conducted in this thesis, the impact force as well as the low (0–3kHz) and high (3-10kHz) -frequency vibrations are prominently influenced by the application of non-uniform sleeper spacing and various traffic speed. With considering the two factors; sleeper spacing and traffic speed, a typical statistical approach -Design of Experiment- is implemented to attain an optimized track model with the aim of reducing the impact force and the impact vibration of the track, and thus to reduce the maintenance necessity and noise generation as well as to increase the passenger comfort. The performance of the nominated optimized model has been observed under the application of two typical trains operated on the Dutch railway network. Finally, the conclusions are presented and recommendations for future research are proposed.

The high speed rail line in the Netherlands, constructed since 2002, is built to create a fast travel connection from Amsterdam to Rotterdam and the Belgium border. The track is designed for trains with a maximum operating train speed of 300 km/h. A great part of the structure is founded on typical Dutch soft soils consisting of Holocene clay and peat layers. To ensure high speeds, mostly settlement free plates with a ballastless track structure are constructed to produce optimum track qualities. At the village Rijpwetering a part of the track, parallel to the highway, has shown lateral deformations since construction. This has resulted in the research question “What are the main factors driving the horizontal deformation mechanism in the high-speed rail settlement free plate structure and what measures can be taken to solve these horizontal deformations?” The research consists of an analysis of the measurement results since 2005. From the measurement results a clear division can be made between the supported and the unsupported sections of the structure. The supported sections have almost stopped displacing in time with an average deformation rate of 0 to 0.5 mm per year. Unsupported sections show an ongoing deformation with a rate of 2.7 to 3.3 mm per year. This deformation will continue and lead to problems concerning structural safety due to bending moments in the top of the foundation pile. To identify the mechanism, a finite element modelling of the track structure embankment is performed from which the deformation behaviour is assessed. Multiple geometrical variants are considered which lead to asymmetrical horizontal deformations. From the simulations an asymmetrical soil layer with a varying stiffness in the subsoil on either side has led to the highest deformation behaviour. In other words, an embankment partly founded on soft soils (peat) and partly on stiff soils (sand). This can be identified as the main factor driving the horizontal deformation mechanism. The combination of different variants leads to results corresponding to the field measurements. To stop horizontal deformations the model is updated with 2 variants to observe the effectivity of the measures. One option is to apply a prestressed sheetpile wall, the other option is to reduce the structures weight with a low weight material (EPS). By applying a prestressed sheetpile in the slope of the embankment the resulting deformations can be stopped when applying a prestressing force of 100 to 150 kN. For the weight reduction, the EPS has to be placed in the slope on the soft soil. Reducing the weight with 144 kN/m or when applying EPS an area of 8.5mm2 stops further deformations. Applying weight reduction on the side of the stiff soil will only increase the problem and deformations will grow. Since weight reduction is usually a cheaper and a lower risk measure in comparison to prestressed sheetpile structures, it’s a very interesting alternative to investigate more accurately. Depending on the surrounding structures and construction possibilities the best option can be chosen to reduce deformations in this structure and prevent deformations in future structures.

Railway catenary is the main infrastructure that delivers electric power for train operation. It is a structure commonly constructed along the railway line with contact wires suspended above the track. One or multiple pantographs mounted on the roof of a moving train collects electric current from the catenary through the sliding contact with a contact wire. With the increase of train speed and traffic density in recent years, the catenary is subject to higher impacts from pantographs, leading to critical failures such as the breakage of contact wire. This results in not only an increasing cost for reactive maintenance, but also disruptions of train service that affect many passengers.

To reduce the life cycle cost and failure rate of catenary in practice, planned and predictive maintenance is desired based on the condition monitoring of catenary. However, the monitoring data are underutilized to effectively assess the catenary condition and facilitate maintenance decision-making. This dissertation contributes in improving the dynamic condition assessment of catenary using the data from condition monitoring. New performance indicators (PIs) of catenary are defined in a way that is adaptive to the variations of monitoring data measured under different circumstances, such as the changes of catenary structure, pantograph type and train speed. The relationship between the monitoring data and the contact wire irregularities is studied using historical data and simulations. Data-based approaches are developed for the quantitative assessment of dynamic catenary condition.

First, an intrinsic wavelength contained in the pantograph-catenary contact force is identified and defined as the catenary structure wavelength (CSW). It is caused by the periodic variations of contact wire stiffness attributed to the cyclic structure of catenary that must regulate the height of contact wire in every spans and interdropper distances. An approach that adaptively extracts the CSWs of pantograph-catenary contact force is proposed based on the empirical mode decomposition algorithm. It extracts the CSW signals corresponding to the span lengths and interdropper distances, respectively, summing to form a characteristic signal of CSWs. The residual signal of the contact force excluding the CSWs is regarded as the non-CSW signal. The mean and standard deviation of the CSWs signal are used as PIs to indicate the condition of the main catenary geometric parameters. A PI based on the quadratic time-frequency representation of the non-CSW signal is proposed for detecting and localizing the local irregularities of contact wire. The proposed PIs are tested by simulation and measurement data and proven effective and adaptive owning to the use of CSWs and non-CSW signal.

Second, the concept of CSW is expanded to the pantograph head acceleration from which the CSWs and non-CSW signal can also be extracted using the same approach developed for the contact force. Considering the characteristics of pantograph head acceleration, the wavelet packet entropy of the CSWs and non-CSW signal is proposed as PIs for detecting contact wire irregularities with different lengths. The entropy of CSWs is used for detecting irregularities with a length longer than 5 m, while the entropy of non-CSW signal is for the short-length local irregularities. An approach to detect and verify contact wire irregularities using the measurement data of pantograph head vertical acceleration from frequent inspections is proposed. The approach is tested using historical inspection data from which irregularities at all lengths are detected and verified. Maintenance resources can thus be specifically allocated to verified detection results to save cost and time.

Third, through analyzing historical inspection data and data-based simulation results, it is found that while the contact wire irregularity deteriorates the pantograph-catenary interaction, the formation of irregularity is also associated with the effects of the interaction like variations of contact and friction forces. Concretely, the contact wire height irregularity with an amplitude of 8 mm can cause considerable increase in the standard deviation of pantograph-catenary contact force. In addition, the irregularity with a certain wavelength can induce the dynamic response with the same wavelength in the contact force. This in turn makes the irregularity part deteriorating faster than the other parts of catenary. At a smaller scale, when the wear irregularity of contact wire has an average wire thickness loss of about 1.5 mm, it can also increase the standard deviation of contact force by more than 5%. Due to the fixing effect at the registration arms and droppers, the wear irregularity commonly contains structural wavelengths of catenary including span lengths and interdropper distances. It is also found that the wear irregularity tends to grow and spread toward in the common or dominant running direction of trains in the specific line. Nevertheless, an existing defect may not affect every pantograph passage and every type of data measured. It is thus advised to measure multiple types of data and perform more frequent inspections to avoid undetected defects.

Last, a data-driven approach using the Bayesian network (BN) to fuse the available inspection data of catenary into an integrated PI is proposed. The BN topology is first structured based on the physical relations between five data types including the train speed, dynamic stagger and height of contact wire, pantograph head acceleration, and pantograph-catenary contact force. Then, tailored PIs are individually defined and extracted from the five types of data as the BN input. As the output of BN, an integrated PI is defined as the overall condition level of catenary considering all defects that can be reflected by the five types of data. Finally, using historical inspections data and maintenance records from a section of high-speed line, the BN parameters are estimated to establish a probabilistic relationship between the input and the output PI. By testing the BN-based approach using new inspection data from the same railway line, it is shown that the integrated PI can adequately represent the catenary condition, leading to considerable reduction in the false alarm rate of catenary defect detection compared with the current practice. The approach can also work acceptably with noisy or partly missing data.

In summary, this dissertation answers how to adequately transform the condition monitoring data of catenary into quantitative assessments of the dynamic catenary condition. The proposed approaches are intended for generic implementations in railway catenaries worldwide.

This dissertation aims to gain a better understanding of the dynamic wheel-rail interaction at crossings, including characterizing the wheel-rail contact behavior, evaluating the performance of crossings under traffic loads and monitoring the health condition of the structure. The first part of this dissertation focuses on an in-depth analysis of wheel-rail contact behavior and related rail degradation. An explicit 3D finite element (FE) model is developed to simulate the passage of a wheelset across a nominal crossing. The second part proposes a method to evaluate the performance of long-term serviced crossings. In the method, in-situ 3D profile and hardness measurements are conducted on a long-term serviced crossing and are used as the input for the FE modeling of dynamic wheel-rail interaction. The simulated wheel-rail contact parameters are then used to predict the distributions of plastic deformation and wear. The third part analyses the characteristic dynamic response of wheel-rail interaction at crossings. In-situ axle box acceleration (ABA) measurements were conducted on a nominal crossing with various test parameters. Thereafter, a roving-accelerometer hammer test was carried out to extract the relationship between the signature tune of the ABA and the natural frequencies of the crossing. The fourth part investigates the feasibility of the ABA system for monitoring the health condition of crossings. Information from multiple sensors was collected from both nominal and degraded crossings. By proper correlation of the gathered data, an algorithm was proposed to identify the characteristic ABA related to crossing degradation and then to evaluate the health condition of the structure.