Track quality measures differ from standard to standard. Widely used indices for track quality are the standard deviations of the rail longitudinal level data and the standard deviations of alignment data. Researchers have opted for various learning methods as to relate track quality to different parameters. Some research has gone to the point of using track quality interchangeably with the notion of defect density. What is common in all researches is that a track quality index is used as label for predictions. The differences are inherent to the variables/features that were chosen to conduct such predictions. With the plethora of data at the hands of asset managers nowadays, it has become easier to opt for these learning methods. Machine Learning classification is a method wherein a number of features are used to classify a datapoint into a label. With thorough learning, by inputting the features, the label would then be predicted. The features of interest in this project are structural elements describing the track sections. This can go from the sleeper type and subsoil type all the way to the distance from the nearest switch or bridge. This will allow for the relationships between the structural elements and the track’s quality to be bolstered all the while creating a predictor based on data that need not be measured. The research question is thus formulated as follows: How to relate track quality in a section to its surrounding structural elements and form a predictor out of it? 1.What structural elements are to be studied? 2.How to automate the generation of the features? 3.Which classifier algorithm yields the most accurate predictions? 4.Which structural features are the most important in predicting track quality? The research question is divided into 4 sub-research questions each pertaining to a part of the research. 1.Decide on which structural elements are the most relevant for the study. Some elements may be redundant with respect to other elements. For instance, subsoil type and ballast settlement could form a redundancy. This will be decided on from the literature. This part will contribute to a section in the thesis in which a strong relation will be drawn with respect to the courses taken and studied at the TU Delft. 2.Data Gathering is a huge part of this research. Input data will be from Fugro’s relative track geometry data and KRDZ data. In addition, ProRail’s informatieportaal, which is a website containing all the railway assets and their locations on the map will also be of huge aid to gather the structural elements data. The answer to this sub-research question lies in automating the structural feature generation, making them ready for learning. 3.Running the Machine Learning classification code on sections of a real-life track and comparing the accuracies of each classification algorithm as to come up with recommendations for future work. 4.Some machine learning algorithms, namely the random forest classifier have in their output an importance of features measure. This will give us insight on which structural elements affect track quality the most, which would allow for better resource allocation in the long run. In the goal of answering all the research questions and to realize the research objective, an outline of the research is included in this report along with a workflow diagram. The project has shown that predicting track quality using structural elements and relative track geometry can be done using classification methods, on the condition that the predicted track and the trained track have similar feature importance values, and that structural features that are displayed in the track to predict are also available in the trained model.

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

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.

Dit rapport behandelt een wissel die geen bewegende delen bezit en hierdoor geen controle circuit nodig heeft. Het rapport bezit een analyse van verschillende bestaande wissels en wisselconcepten, beide in hoofdspoor en tramspoor, om een evaluatie te geven van elk concept. Op deze manier is bepaald of een zodanig "statische wissel" wenselijk is in het Nederlandse spoor. Er is vastgesteld dat dit niet het geval is, daarentegen andere wissels wel. Er wordt daarom aangeraden om meer onderzoek te doen naar deze andere aanpassingen aan wissels. This report considers a switch that does not have moving parts and therefore has no control circuit. The report contains an analysis on current existing switches and switch designs, in heavyrail but also tramrail, to give an evaluation of the different concepts. This way it was determined if a so called "static switch" could be wished for in the Dutch Railroads. It was concluded that this kind of switch was not profitable, but other switches were. Recommended was, that certain (existing) changes in switch designs should be looked into more.

In this master thesis the behaviour of a high speed railway track constructed on top of a pile foundation with settlements under a dynamic load has been analysed. Therefore, a model was developed in the software program DARTS, dynamic analysis of rail track structures. In DARTS the railway track was modelled by stiff and elastic layers, which were loaded by a moving train load. The train was modelled as a mass spring system. The results of DARTS were analysed and validated with field measurements of the HSL. After the validation of the model multiple simulations were performed to analyse the structure for different uncertainties and possible solutions. These simulations showed that the model in DARTS is sensitive for changes of the pile stiffness. The results also show that it is difficult to model permanent displacements in DARTS.

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.

Railway crossings are essential components of the railway track system that allow trains to switch from one track to another. Due to the complex wheel-rail interaction in the crossing panel, crossings are vulnerable elements of railway infrastructure and usually have short service lives. The crossing damage not only results in substantial maintenance efforts but also leads to traffic disruptions and can even affect traffic safety. In the Netherlands, the annual maintenance cost on railway crossings is more than 50 million euros. Due to the lack of monitoring systems, the real-time information on crossing condition is limited. As a result, the present maintenance actions on railway crossings are mainly reactive that take place only after the occurrence of visible damage. Usually, such actions (repairs) are carried out too late and result in unplanned disruptions that negatively affect track availability. In the Netherlands, around 100 crossings are urgently replaced every year, accompanied by traffic interruptions. Also, there is a considerable number of crossings with the service life of only 2-3 years. The maintenance methods used by the contractors on such crossings are somewhat limited and usually ended up with ballast tamping. In this case, the root causes of the fast crossing degradation are usually not resolved, and the crossings are still operated in degraded conditions after the maintenance. In order to improve the efficiency of the current maintenance of railway crossings aiming for better crossing performance, the goal of this study is to develop a monitoring system for railway crossings using which the crossing condition can be assessed, and the sources of the degradation can be detected. Using such a system timely and proper maintenance on railway crossings can be provided. The main steps in achieving this goal were as follows: Based on the measured dynamic responses of railway crossings due to passing trains, several condition indicators were proposed; To provide the fundamental basis for the proposed indicators a numerical model for the analysis of vehicle-crossing interaction was developed; The effectiveness of the proposed indicators was demonstrated using the data from long-term monitoring of 1:9 and 1:15 crossings. The railway crossing conditions can be reflected in the changes in the dynamic responses due to passing trains. In this study, the responses were obtained from the crossing instrumentation and wayside monitoring system. The responses reflect the wheel-rail interaction, which consists of the wheel impact accelerations, impact locations and the rail displacements due to the impacts, etc. Based on the correlation analysis of the responses, the indicators related to the wheel impact, fatigue area and ballast support were proposed. The indicators form a basis for the structural health monitoring (SHM) system for the railway crossings. To verify the effectiveness of the proposed indicators, and to explain the experimental findings, a numerical vehicle-crossing model is developed using the multi-body system (MBS) method. The model is validated using the measurement results and further verified using the finite element (FE) model. The proposed indicators and the MBS model were applied to the condition stage identification and damage source detection of the crossings. The main outcomes are presented below. In the condition monitoring of normally degraded crossings, the proposed indicators were capable to catch the main degradation stages of the railway crossing ranging from newly installed to damaged and repaired ones. With the assistance of these indicators, the maintenance actions can be timely applied before the occurrence of severe damage. The proposed indicators can also be used for assessing the effectiveness of the performed maintenance (repair welding and grinding, ballast tamping, etc.). It was demonstrated that ballast tamping has no positive effect on the performance of the monitored 1:9 crossing. The proposed indicators can also help to detect the root causes of the crossing damage. In some cases, the degradation is caused by adjacent structures, and therefore the maintenance should be performed not on the crossing itself but of the track nearby. In this study, the fast degradation of the monitored 1:9 crossing was found to be caused by the lateral track deformation in front of the crossing. The numerical results confirmed the phenomenon that the train hunting motion activated by the track deviation. It was the source of the extremely high impacts recorded by the monitoring system that ultimately resulted in the fast crossing degradation. By knowing the damage sources, proper maintenance can be performed rather than the currently used ineffective ballast tamping. Additionally, it was found that crossing degradation can also result from external disturbances. It was proven that highly increased rail temperature due to the long duration of sunshine would amplify the existed geometry deviation in turnout. Considering the high sensitivity of wheel-rail interaction in the crossing, higher standards for crossing maintenance and construction are required for better crossing performance. This study contributes to the development of the condition monitoring system for railway crossings. The application of the condition indicators is a big step forward for the current maintenance philosophies from damage repair to predictive maintenance, and from “failure reactive” to “failure proactive”. The outcomes in this study will contribute to the better performance of railway crossings. @en

Railway turnouts are important components of railway infrastructure as they provide flexibility and guidance to the rail traffic. Because of geometrical discontinuities in the crossing area of the turnouts, high impact forces due to passing wheels acting on the crossing nose can occur. In the field, severe rail damage problems are found in crossing areas. Statistical evidence shows that turnout failures cause major operational disturbances in a railway network, which lead to higher maintenance costs as compared with other track components. The research presented here was motivated by the short service life of the turnout crossing observed in the Dutch railway network and by the need to improve the performance of railway turnouts. Moreover, there is a lack of advanced numerical tools such as dynamic three-dimensional (3-D) models to analyse wheel–rail interactions in crossings on the stress and strain levels, particularly for models that are coupled with life estimation of the crossing. Therefore, the goal of this study is to develop numerical tools for the analysis of the dynamic interaction between the wheel and turnout crossing, and the prediction of fatigue life of crossings, aiming to improve the crossing performance and prolong its service life.@en

Nowadays, wheel-rail (W/R) interfaces are suffering from the practical problems (e.g. wear, rolling contact defects) with the increase of train speed and traffic density. For accurate prediction of wear and/or growth of rolling contact defects, rapid determination of detailed contact responses (i.e. contact stresses & strains) using numerical methods, is necessary. As one of the numerical methods, the explicit finite element (FE) method has been increasingly used due to its striking versatility (i.e., the consideration of dynamic effects, material and geometrical non-linearities). But there are still several FE modelling challenges to be addressed. First, the calculation accuracy & efficiency of the FE method can not be automatically guaranteed. Second, the default values of the interface parameters provided in the commercial FE packages are not always suitable for the modelling of W/R rolling contact. Third, the detailed verification & validation methods/procedures for the FE model of W/R interaction are still in demand. It is thus motivated to perform an in-depth study on the performance (i.e. accuracy and efficiency) of the explicit FE method applied to the analysis of the dynamic W/R frictional rolling contact behaviour. Through this study, it is aimed to enrich the detailed knowledge of W/R interaction, and help the researchers in the field of railway engineering to judge the benefits and drawbacks of explicit FE simulations. The dissertation is divided into four parts, in which four research problems are addressed...@en

Scientists say that trust in inter-organisational relationships leads to high performance, project success, and better quality in construction work. Later research shows that distrust also plays an important role in preventing excessive trust in relationships. It is better to say that a stable state of trust is the balance between trust and distrust and leads to optimal performance. As an employee at the Dutch rail infrastructure manager (the asset owner), my experience in the rail maintenance market is that trust has a limited role in inter-organisational relationships. Inter-organisational relationships are organised via contracts where the output (performance), minimum standards, and tasks and roles are described in detail. Corporate lawyers regularly discuss the requests of change (technically and financially) from the rail maintenance contractors. Trust may have a larger role in inter-organisational relationships between the key figures who manage the contract to improve the output (performance). @en