Gegenstand der vorliegenden Dissertationsschrift ist die Entwicklung und Umsetzung von neuartigen Hybridgarnen aus recycelten Carbonfasern (rCF) und Polyamid (PA) 6-Fasern für thermoplastische Verbundbauteile mit hohem Leistungsvermögen. Diese Hybridgarne können die hervorragenden mechanischen Eigenschaften der rCF im Gegensatz zu bisherigen Lösungen auf Basis von Spritzguss und Vliesstoffen in hohem Maße ausnutzen. Bedingt durch deren spezielle Fasereigenschaften (insbesondere hohe Querkraftempfindlichkeit, Sprödigkeit und fehlende Kräuselung) wurde dafür die Prozesskette der konventionellen Stapelfasergarnherstellung, bestehend aus Krempel, Strecke und Flyer, umfangreich analysiert und technologisch-konstruktiv weiterentwickelt, wodurch erstmalig eine schonende und gleichmäßige Herstellung der Hybridgarne ermöglicht werden konnte. Für eine reproduzierbare und effiziente Prüfung der Faserlänge der rCF wurde zudem ein anforderungsgerechtes Faserlängenmesssystem auf Basis der Fibrographmethode entwickelt. Die im Rahmen der Arbeit abschließend durchgeführten Verbund-prüfungen belegen das enorm hohe Potential der Hybridgarne, die über 80 % der Verbundzugfestigkeit von vergleichbaren Referenzprüfkörpern aus Carbon-Filamentgarn und PA 6-Matrix erreichen. Das entwickelte analytische Modell bietet zudem die Möglichkeit zur Berechnung der Verbundzugkennwerte in Abhängigkeit wesentlicher Faser- und Hybridgarnparameter.

The life of railway wheels and rails has been decreasing in recent years. This is mainly caused by more traffic and running at higher vehicle speed. A higher speed usually generates higher forces, unless compensated by improved track and vehicle designs, in the wheel-rail contact, resulting in more wear and rolling contact fatigue (RCF) damage to the wheels and rails. As recently as 15 years ago, RCF was not recognised as a serious problem. Nowadays it is a serious problem in many countries and ''artificial wear'' is being used to control the growth of cracks by preventive re-profiling and grinding of, respectively, the wheels and rails.  This can be used because a competition exists between wear and surface initiated RCF: At a high wear rate, RCF does not have the opportunity to develop further. Initiated cracks are in this case worn off and will not be able to propagate deep beneath the surface of the rail or wheel. When wheel-rail damage in terms of wear and RCF can be predicted, measures can be taken to decrease it. For example, the combination of wheel and rail profiles, or the combination of vehicle and track, can be optimised to control the damage. Not only can this lead to lower maintenance costs, but also to a safer system since high potential risks can be detected in advance. This thesis describes the development of a wheel-rail life prediction tool with regard to both wear and surface-initiated RCF. The main goal of this PhD work was to develop such a tool where vehicle-track dynamics simulations are implemented. This way, many different wheel-rail contact conditions which a wheel or a rail will encounter in reality can be taken into account. The wear prediction part of the tool had already been successfully developed by others to be used in combination with multibody simulations. The crack prediction part, however, was more difficult to be used in combination with multibody simulations since crack propagation models are time-consuming. Therefore, more concessions had to be made in the crack propagation part of the tool, since time-consuming detailed modelling of the crack, for example in Finite Elements models, was not an option. The use of simple and fast, but less accurate, crack propagation models is the first step in the development of a wheel-rail life prediction model. Another goal of this work was to verify the wheel-rail prediction tool against measurements of profile and crack development. For this purpose, the wheel profiles of trains running on the Stockholm commuter network have been measured together with the crack development on these wheels. Three train units were selected and their wheels have been measured over a period of more than a year. The maximum running distance for these wheels was 230,000 km. A chosen fatigue model was calibrated against crack and wear measurements of rails to determine two unknown parameters.  The verification of the prediction tool against the wheel measurements, however, showed that one of the calibrated parameters was not valid to predict RCF on wheels. It could be concluded that wheels experience relatively less RCF damage than rails. Once the two parameters were calibrated against the wheel measurements, the prediction tool showed promising results for predicting both wear and RCF and their trade-off. The predicted position of the damage on the tread of the wheel also agreed well with the position found in the measurements. / <p>QC 20150526</p>

<p>Rolling contact fatigue (RCF) is the primary mode of failure in tribological contacts like rolling-element bearings (REBs), gears, and cam-follower systems. RCF processes have a crack initiation phase followed by a propagation and coalescence phase, resulting in spalls that lead to catastrophic failure. Crack initiation is a highly localized process that is strongly influenced by the inhomogeneity of the material microstructure. Therefore, a microstructure-sensitive model is required to simulate the damage evolution and failure due to RCF loading. This document presents the development of a microstructure-based finite element (FE) framework for RCF, which accounts for the inhomogeneity of bearing steel microstructure by using an explicit definition of polycrystal topology and material anisotropy. The granular topology of the bearing steel microstructure is described using randomly generated Voronoi tessellations. A cubic elastic material definition with a random spatial orientation is specified for each Voronoi grain to simulate the material anisotropy. The Voronoi grains generated using this approach were used to model the critically stressed microstructural volume in RCF loading. A domain size study was conducted to estimate the minimum number of grains that need to be contained by the critically stressed volume such that the macroscopic material response of the polycrystalline aggregate matches the linear elastic material properties of bearing steel. The estimated critically stressed volume was then embedded into a semi-infinite domain for the FE simulation of RCF line contact loading. The RCF domains developed were then subjected to a moving Hertzian pressure over the surface to simulate a bearing load cycle. A boundary averaging scheme was used to estimate the effective stresses along the grain boundaries of the Voronoi cells. Due to the anisotropy of the polycrystalline material, local stress concentrations occur at the grain boundaries as compared to isotropic models. The resolved grain boundary stresses were used to predict critical locations for RCF crack initiation, which closely match observations from RCF bench test data. Since RCF failures typically exhibit subsurface locations for the first crack initiation, the model uses the critical resolved shear stress (RSS) reversal along the grain boundaries and the corresponding subsurface location of the maxima as the driving parameters for RCF fatigue failures. The parameters from the model were fit into a Weibull distribution to estimate the stochasticity in initiation life. The Weibull predictions corroborate well with experimentally measured RCF life scatter. The framework was then extended using a coupled damage mechanics - cohesive element method (DM-CEM) to individually model the crack initiation and propagation phases in RCF. An explicit definition of the grain boundaries was incorporated using cohesive elements. Damage is initiated at the grain boundaries by degradation of the cohesive elements and the rate of damage/degradation is used to characterize the evolution of fatigue life. The rate of damage was calculated at each grain boundary using a fatigue damage law based on the RSS reversal parameter. The model is able to simulate the crack initiation and the propagation/ coalescence phases in RCF, with distinct life estimates for each phase. This model framework is further extended to investigate the effects of lubrication conditions in RCF by integrating an elastohydrodynamic lubrication (EHL) model to simulate the pressure load with the DM-CEM model. Further improvements to the fatigue life predictions using the DM-CEM model are made by coupling it with a crystal plasticity (CP) based submodel approach to predict the crack initiation life in RCF. CP-based metrics are used to correlate the microplasticity developed under RCF loading with the formation of fatigue micro-cracks and the corresponding initiation life estimations. The resulting final spall patterns and RCF life estimates were found to match well with experimental data available in the open literature.</p> <p><br></p>

Diploma thesis describes influence of directed modificated topography of frictional surfaces on fatigue wear non-conformal incurvate solids. It was created 3D parametric model of experimental test rig in modelling environment Autodesk Inventor. With the help of model was designed and carried reconstruction of experimental test rig so to possible obtain repeatable results under the sliding conditions of frictional surfaces. It enabled show influence of surface iregularities (dents) frictional surfaces on contact fatigue service life in conditions mixed lubrication regime and different values of slide to roll ratio.

Maintenance cost is one of the important issues in railway heavy-haul operations. In most of the cases, these costs are majorly referring to reprofiling and changing the wheels of the locomotives and the wagons. The main reason of the wheel damages is usually severe wear and/or surface initiated rolling contact fatigue (RCF).This work tries to enhance and improve the knowledge of the wheel wear and RCF prediction models using dynamic simulations. While most of the contents of this study can be generalised to other operational networks, this study is focused on the locomotives and wagons of the Swedish iron-ore company LKAB. The trains are operating on the approximately 500 km long IORE line from Luleå to Narvik in the north of Sweden and Norway respectively.Firstly, a literature survey of dynamic modelling of the wagons with various three-piece bogie types is presented. Then, with concentrating on the standard three-piece bogies, parameter studies are carried out to find out what the most important reasons of wheel damages are. Moreover, the long-term stability of wheel profiles of the IORE wagons is analysed. This is done by visualising the wear and RCF evolution on the wheel profiles over 150,000km of simulated running distance.Most of the calculations for the wagons are repeated for the locomotives. However, traction and braking are also considered in the simulation model and their effects on wheel damages are briefly studied. To improve the accuracy of the wheel damage analysis, a newly developed algorithm called FaStrip is used to solve the tangential contact problem instead of FASTSIM. The damage prediction model developed in the thesis is used to study the effects of increasing axle load, correcting the track gauge, limiting the electro-dynamic braking and using a harder wheel material on the wheel life. Furthermore, a new method is developed to predict the running distance between two consecutive reprofilings due to severe surface initiated fatigue. The method is based on shakedown analysis and laboratory tests.Most of the research works in wear calculation are limited to two approaches known as wear number and Archard methods. The correlation between these two methods is studied. The possibility of using the relation between the two methods for the wear calculation process is investigated mainly to reduce the calculation time for wheel profile optimisation models. / <p>QC 20171219</p>

The master´s thesis deals with reconstruction of RCF test rig AXMAT. Main goal is design new hydraulic load system and his realization. The first part of thesis describes similar experimental machines and their pros and cons. This analysis is base for complete reconstruciton of AXMAT. New hydraulic load system allows dynamic programmable load cycles. Control system with close loop and feedback was created in software Matlab – Simulink. Main frame was reconstructed too. Control and action parts were asseble to station. Output of thesis is function sample.

Maintenance cost is one of the important issues in railway heavy haul operations. For the iron-ore company LKAB, these costs are mainly associated with the reprofiling and changing of the wheels of the locomotives and wagons. The main reason for the wheel damages is usually surface initiated rolling contact fatigue (RCF) on the wheels.The present work tries to enhance and improve the knowledge of the vehicle-track interaction of the Swedish iron-ore freight wagons and locomotives used at Malmbanan. The study is divided into two parts. Firstly, it is tried to get into the roots of RCF using the simulation model of the iron ore wagon (Paper A). Secondly, the study is focused on predicting wear and RCF on the locomotive wheels also via a dynamic simulation model (Paper B).In the first paper, some key issues of the dynamic modelling of the wagons with three piece bogies are first discussed and then parameter studies are carried out to find the most important reasons of wheel damages. These parameter studies include track design geometry, track irregularities, wheel-rail friction level, cant deficiency and track stiffness. The results show a significant effect of the friction level on the amount of RCF risk.As the locomotive wheel life is much shorter than that of the wagons, LKAB has decided to change the locomotive wheel profile. Two final wheel profiles are proposed; however, one had to be approved for the field tests. In the second paper, the long term evolution of the two profiles is compared via wear simulation analysis. Also, the RCF evolution on the wheel profiles as a function of running distance is discussed. The process is first carried out for the current locomotive wheel profiles and the results are compared with the measurements. Good agreement is achieved. Finally, one of the proposed profiles is suggested for the field test because of the mild wear and RCF propagation. / <p>QC 20150210</p>

<p dir="ltr">Rolling contact fatigue (RCF) is one of the leading causes of failure in critical tribological components such as rolling element bearings (REBs), gears, cam and followers, etc. This is especially paramount for advanced aerospace applications where REB components need to operate for billions of RCF cycles before routine maintenance or inspection is performed. The rolling motion between the rolling elements and raceway produces RCF, wherein a complex, non-proportional, alternating contract stress is applied over a small material volume. Moreover, the highly localized stress occurs on the same length scale as microstructural features such as carbides, inclusions, grain size, hardness gradients from carburization, surface roughness, thereby amplifying their effect on fatigue performance. Therefore, the objective of this dissertation is to investigate critical microstructural modifications and their effects on RCF performance via experiments and computational modeling.</p><p dir="ltr">Initially, an investigation was undertaken to investigate surface roughness effects on RCF. The surface roughness of various REBs was measured through optical surface profilometry and used to construct rough surface pressure distributions, which were then used in a continuum damage mechanics (CDM) finite element (FE) framework. The results demonstrated that life is reduced as lambda ratio decreases. It was also observed that a 2-parameter Weibull cumulative distribution function can describe the relationship between the near surface orthogonal shear stress concentration and ratio of surface failures.</p><p dir="ltr">Next, the enhancement to RCF life from grain size refinement of through hardened bearing steels was studied. To capture the effects of grain refinement, torsion stress-life data of various grain size were used in the RCF model. A predictive life equation for different grain sizes was constructed based on the exponential trend observed between grain size and life from the simulation data. The life equation was then used to calculate the quotient of RCF at two different grain sizes. This quotient was defined as the life improvement ratio and it was observed that this investigation’s ratios compared well with existing life improvement ratios from RCF experiments.</p><p dir="ltr">Hardness gradient is a common microstructural modification to improve RCF life of tribo-components. Variation of hardness gradients is prevalent in case hardened (i.e. case carburized) bearing materials. Therefore, the CDM-FE RCF model was modified to investigate the effects of various hardness gradient types and depths on fatigue life improvement. The simulation results enabled the identification of potentially optimal gradients aimed to mitigate manufacturing challenges and provided the foundation for the construction of a general fatigue life equation.</p><p dir="ltr">A fundamental study to understand the impact various common RCF failure criteria have on RCF life estimation was then conducted using computational modeling. To capture the variation of a material’s resistance to fatigue, the critical CDM damage parameters were assumed to follow a probabilistic distribution instead of a singular value. The CDM-FE model was modified to consider the shear reversal, the octahedral shear stress, the maximum shear stress, the Fatemi-Socie criteria, and the Dang Van multi-axial fatigue parameter as failure criteria. Simulation life results revealed that the CDM-FE model with shear reversal and Fatemi-Socie criteria best match empirical predictions from well-established RCF life theory. Notably, the Fatemi-Socie exhibited the best agreement over all operating conditions.</p><p dir="ltr">The next investigation focused on the cleanliness of aerospace-quality bearing steels. Torsion fatigue experiments established the stress-life (S-N) relation for three common aerospace quality bearing steels. The S-N data was later used to calibrate the RCF model’s damage equation, which considered the Fatemi-Socie criteria following conclusions from a previous investigation. Simulation results were observed to corroborate well with RCF experiments that were conducted for all three materials, while noting the simulations offered a significant time saving. As a result, a subsequent investigation focused on establishing the stress-life relationship for one of the aerospace quality bearing steels through a combined experimental and analytical approach. Good corroboration was observed between simulations and experiments at three contact pressures. This finding is particularly significant as it strengthens the reliability of computational RCF model as an efficient means to assess the RCF performance of bearing materials.</p><p dir="ltr">Furthermore, the detailed investigation on RCF performance of each critical microstructural modifications and their respective effect greatly improves the state-of-the-art. The findings emanating from the various investigations offer informed fatigue design recommendations that aid in the selection of rolling element bearings for critical tribological and aerospace applications.</p>

Semantic segmentation of a scene aims to give meaning to the scene by dividing it into meaningful — semantic — parts. Understanding the scene is of great interest for all kinds of autonomous systems, but manual annotation is simply too time consuming, which is why there is a need for an alternative approach. This thesis investigates the possibility of automatically segmenting 3D-models of urban scenes, such as buildings, into a predetermined set of labels. The approach was to first acquire ground truth data by manually annotating five 3D-models of different urban scenes. The next step was to extract features from the 3D-models and evaluate which ones constitutes a suitable feature space. Finally, three supervised learners were implemented and evaluated: k-Nearest Neighbour (KNN), Support Vector Machine (SVM) and Random Classification Forest (RCF). The classifications were done point-wise, classifying each 3D-point in the dense point cloud belonging to the model being classified. The result showed that the best suitable feature space is not necessarily the one containing all features. The KNN classifier got the highest average accuracy overall models — classifying 42.5% of the 3D points correct. The RCF classifier managed to classify 66.7% points correct in one of the models, but had worse performance for the rest of the models and thus resulting in a lower average accuracy compared to KNN. In general, KNN, SVM, and RCF seemed to have different benefits and drawbacks. KNN is simple and intuitive but by far the slowest classifier when dealing with a large set of training data. SVM and RCF are both fast but difficult to tune as there are more parameters to adjust. Whether the reason for obtaining the relatively low highest accuracy was due to the lack of ground truth training data, unbalanced validation models, or the capacity of the learners, was never investigated due to a limited time span. However, this ought to be investigated in future studies.

This master thesis deals with influence of topography of friction surfaces on rolling contact fatigue. This influence is examined by newly reconstructed R-MAT station, whose reconstruction and fully report about it, is part of this master thesis. Influence is examined on area with higher surface's roughness which it wasn't examined before. Further research is made on area of surfaces with topographical modification with higher surface's roughness.