In this paper, various two-dimensional (2D) models of train-bridge dynamic interaction are established using multibody dynamics theory and beam theory. The models are solved using the Newmark-𝛽 method, a common implicit integration method for structural dynamics. The research gives a description of the effect of train parameters on the train-bridge dynamics using a full 2D train model. By clearly describing the train and bridge models used, an attempt will be made to accurately describe the physics behind the models. The result of the simulations describe the differences between different models, after which the effects of various train parameters on the midpoint displacements are illustrated.

The railway track is the most critical element that infrastructure managers have to ensure satisfactory health conditions to provide safe, sustainable, and adequate service quality. The condition of railway tracks is managed through maintenance strategies that benefit enormously from the availability of accurate and updated information from measurement devices. This thesis focuses on estimating the track support condition using Axle Box Acceleration (ABA) measurements. The ABA characteristics under different track support conditions are evaluated, effects of influential parameters in the measurements are analyzed, key performance indicators (KPIs) for condition monitoring of ballast and substructure layers are proposed, and results with traditional techniques such as impact tests are compared. Finally, an enhanced track quality index is proposed to improve the effectiveness of maintenance decision-making. Case studies in The Netherlands, Sweden, and Norway are considered.@en

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...@en

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?@en

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. @en

Crossings are important yet vulnerable parts of a railway network. This warrants that, in the Netherlands (a country with high traffic loads), crossing geometry is measured twice per year by dedicated measurement vehicles. This produces so much (point cloud) data that prioritizing and predicting is not possible by hand. It can be done by automating the assessments, by an automated process of four steps: cleaning the data, generating relevant performance indicators (features) per measurement, drawing conclusions from all features and visualizing/communicating the results. This project encompasses the first three steps for the most common type of crossing (the 1:9 fixed UIC54 common crossing). The results show that the features yield useful information and insights for both prioritizing and predicting.

Rail wear in curves at the tramway of Amsterdam is a considerable problem since it consumes a significant part of the maintenance budget. The wear mechanism is not fully understood because some curves could suffer much more than others, while the cause for the difference is unknown. GVB, the public transport operator of Amsterdam, wants to obtain better insight into this problem to optimise maintenance processes and reduce maintenance costs.

First, a literature review was conducted to assess knowledge on this issue and analyse methods to model train-track systems. Next, based on the literature review, parameters were identified which could influence the rail wear process, e.g. tram velocity, primary yaw stiffness or rail hardness. An evaluation of available data on those parameters at GVB was made. Data that was available and deemed essential was aligned and later used as input for a rail wear prediction model for the tramway of Amsterdam. The essential data analyses are the velocity analysis and wheel qR decay analysis. A tool was developed to obtain a detailed profile of driven velocities at the tram network, based on massive daily data from all the trams. Wheel measurement data from all the trams in the network were analysed to assess the wear of the tram wheels. Statistics were obtained over six years of wheel measurement data measured twice per year per tram. Besides, the usage data processed for inclusion in the model are tonnage, vehicle type distribution, amount of coupled vehicles and average vehicle loading.

Furthermore, more than six hundred simulations were performed at DEKRA rail with GVB tram models in VAMPIRE, to obtain more insight into tram curving behaviour. Based on the simulation outcomes, relationships between energy dissipation (\(T_{\gamma}\)) and radius, velocity, flange angle, vehicle loading and -type were derived. Those relationships were obtained per wheel and aggregated per tram passage. Finally, a rail wear model was made, which combines the relationships derived from the simulations, track characteristics and usage data about the curves. The energy dissipation (\(T_{\gamma}\)) was used as a wear indicator by the prediction model.

From the velocity analysis, trams generally keep to the speed limits, but trams drive too fast at specific curves. The wheel analysis showed qR at the tram's front wheels decays considerably faster than other wheels. Combino tram type's wheel decay was poorer than the older BN tram type. From the simulations, wheel wear has the most adverse effect on rail wear in curves. Increased vehicle velocity or amount of passengers also has a considerable negative influence on rail wear. The expected wear rises exponentially if the curve radius decreases. Also, the dependency on velocity increases exponentially when the curve radius decreases…

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.@en