Les voies ferrées sont de plus en plus sollicitées: le nombre de trains à grande vitesse, leur vitesse et leur charge ne cessent d'augmenter, ce qui contribue à la formation de défauts de géométrie sur la voie. En retour, ces défauts de géométrie influencent la réponse dynamique du train et dégradent les conditions de confort. Pour garantir de bonnes conditions de confort, les entreprises ferroviaires réalisent des opérations de maintenance de la voie, qui sont très coûteuses. Ces entreprises ont donc intérêt à prévoir l'évolution temporelle des défauts de géométrie de la voie pour anticiper les opérations de maintenance, et ainsi réduire les coûts de maintenance et améliorer les conditions de transport. Dans cette thèse, on analyse l'évolution temporelle d'une portion de voie par un indicateur vectoriel sur la dynamique du train. Pour la portion de voie choisie, on construit un modèle stochastique local des défauts de géométrie de la voie à partir d'un modèle global des défauts de géométrie et de big data de défauts mesurés par un train de mesure. Ce modèle stochastique local prend en compte la variabilité des défauts de géométrie de la voie et permet de générer des réalisations des défauts pour chaque temps de mesure. Après avoir validé le modèle numérique de la dynamique du train, les réponses dynamiques du train sur la portion de voie mesurée sont simulées numériquement en utilisant le modèle stochastique local des défauts de géométrie. Un indicateur dynamique, vectoriel et aléatoire, est introduit pour caractériser la réponse dynamique du train sur la portion de voie. Cet indicateur dynamique est construit de manière à prendre en compte les incertitudes de modèle dans le modèle numérique de la dynamique du train. Pour identifier le modèle stochastique des défauts de géométrie et pour caractériser les incertitudes de modèle, des méthodes stochastiques avancées, comme par exemple la décomposition en chaos polynomial ou le maximum de vraisemblance multidimensionnel, sont appliquées à des champs aléatoires non gaussiens et non stationnaires. Enfin, un modèle stochastique de prédiction est proposé pour prédire les quantités statistiques de l'indicateur dynamique, ce qui permet d'anticiper le besoin en maintenance. Ce modèle est construit en utilisant les résultats de la simulation de la dynamique du train et consiste à utiliser un modèle non stationnaire de type filtre de Kalman avec une condition initiale non gaussienne / Railways tracks are subjected to more and more constraints, because the number of high-speed trains using the high-speed lines, the trains speed, and the trains load keep increasing. These solicitations contribute to produce track irregularities. In return, track irregularities influence the train dynamic responses, inducing degradation of the comfort. To guarantee good conditions of comfort in the train, railways companies perform maintenance operations of the track, which are very costly. Consequently, there is a great interest for the railways companies to predict the long-time evolution of the track irregularities for a given track portion, in order to be able to anticipate the start off of the maintenance operations, and therefore to reduce the maintenance costs and to improve the running conditions. In this thesis, the long-time evolution of a given track portion is analyzed through a vector-valued indicator on the train dynamics. For this given track portion, a local stochastic model of the track irregularities is constructed using a global stochastic model of the track irregularities and using big data made up of experimental measurements of the track irregularities performed by a measuring train. This local stochastic model takes into account the variability of the track irregularities and allows for generating realizations of the track irregularities at each long time. After validating the computational model of the train dynamics, the train dynamic responses on the measured track portion are numerically simulated using the local stochastic model of the track irregularities. A vector-valued random dynamic indicator is defined to characterize the train dynamic responses on the given track portion. This dynamic indicator is constructed such that it takes into account the model uncertainties in the train dynamics computational model. For the identification of the track irregularities stochastic model and the characterization of the model uncertainties, advanced stochastic methods such as the polynomial chaos expansion and the multivariate maximum likelihood are applied to non-Gaussian and non-stationary random fields. Finally, a stochastic predictive model is proposed for predicting the statistical quantities of the random dynamic indicator, which allows for anticipating the need for track maintenance. This modeling is constructed using the results of the train dynamics simulation and consists in using a non-stationary Kalman-filter type model with a non-Gaussian initial condition. The proposed model is validated using experimental data for the French railways network for the high-speed trains

The brain is a complex organ that is computationally strong. Recent research in the field of neurobiology help scientists to better understand the working of the brain, especially how the brain represents or codes external signals. The research shows that the neural code is sparse. A sparse code is a code in which few neurons participate in the representation of a signal. Neurons communicate with each other by sending pulses or spikes at certain times. The spikes send between several neurons over time is called a spike train. A spike train contains all the important information about the signal that it codes. This thesis shows how sparse coding can be used to do speech recognition. The recognition process consists of three parts. First the speech signal is transformed into a spectrogram. Thereafter a sparse code to represent the spectrogram is found. The spectrogram serves as the input to a linear generative model. The output of themodel is a sparse code that can be interpreted as a spike train. Lastly a spike train model recognises the words that are encoded in the spike train. The algorithms that search for sparse codes to represent signals require many computations. We therefore propose an algorithm that is more efficient than current algorithms. The algorithm makes it possible to find sparse codes in reasonable time if the spectrogram is fairly coarse. The system achieves a word error rate of 19% with a coarse spectrogram, while a system based on Hidden Markov Models achieves a word error rate of 15% on the same spectrograms. / Thesis (PhD)--University of Pretoria, 2008. / Electrical, Electronic and Computer Engineering / unrestricted

Tomáš ŠTÁBL Design of Gear Timing Mechanism for SI Engine MT, IAE, 2009, 62 pp., 27 fig. This master thesis is concerning the valve train proposal of the spark ignition engine for sports purposes. Antecedent to the actual proposal is the division and retrieval of the modern valve trains, the valve train acting forces description, division and description of the individual valve-lift curve parts , valve springs and the dynamic models of the valve train. In the thesis there are designed the valve lift curves with the continuous course of acceleration, valve springs and valve springs natural oscillations damper for engine Honda CBR 929RR. The dynamic analysis of valve train approach is performed.

This document is a report summering the master thesis work dealing with the Computational Fluid Dynamic (CFD) study of the flow around a high-speed train. The model is a scaled 1:50 generic train with two cars, one inter-car gap and simplified bogies. A platform is set on the side of the train since one of the aim of the study is to look at the consequences of the phenomena in the wake on people or objects standing on the platform. The slipstream is one of this phenomena, it is due to the fact that the viscous air is dragged when the train is passing. If too strong, it can move or destabilize people or objects on the platform. In addition of the slipstream study, a velocity profile study, a drag and lift coefficients analyze as well as a Q-factor study and a frequency study have been realized. Some results of these different studies are compared with the ones obtained on the same model with a Delayed Detached Eddy Simulation (DDES). Since the flow is turbulent, for those different studies, the flow has been simulated with a Reynolds Averaged Navier-Stokes equation model (RANS) which is the k-ω SST model for the turbulence. The study of the slipstream allowed to calculate the Technical Specification for Interoperability (TSI) which must not be higher that the European Union requirement set at 15.5 m/s, the result obtained is 8.1 m/s which is then lower than the limit. The velocity profile shows similarities with the DDES results even though it is less detailed. The same conclusion is done for the Q-plot where is clearly visible the two counter-rotating vortices in the wake. Finally, a Fast Fourier Transform algorithm has been applied to instantaneous velocity results in the wake of the train in order to get the frequency of the aerodynamic phenomena in that wake. The main frequency is 25 Hz and corresponds to a Strouhal number of 0.1, quite closed to the results obtained with DDES which is 0.085. The results of the RANS and DDES are reasonably similar and by regarding at the large difference between the cell numbers (respectively 8 500 000 and 20 000 000) it can be conclude that in some ways the RANS model can be preferred at the DDES to save time for the computation but it does not contain the small scales resolved by the DDES.

Train transportation is a vital part of the transportation system of today anddue to its safe and environmental friendly concept it will be even more impor-tant in the future. The speeds of trains have increased continuously and withhigher speeds the aerodynamic effects become even more important. One aero-dynamic effect that is of vital importance for passengers’ and track workers’safety is slipstream, i.e. the flow that is dragged by the train. Earlier ex-perimental studies have found that for high-speed passenger trains the largestslipstream velocities occur in the wake. Therefore the work in this thesis isdevoted to wake flows. First a test case, a surface-mounted cube, is simulatedto test the analysis methodology that is later applied to a train geometry, theAerodynamic Train Model (ATM). Results on both geometries are comparedwith other studies, which are either numerical or experimental. The comparisonfor the cube between simulated results and other studies is satisfactory, whiledue to a trip wire in the experiment the results for the ATM do not match.The computed flow fields are used to compute the POD and Koopman modes.For the cube this is done in two regions of the flow, one to compare with a priorpublished study Manhart & Wengle (1993) and another covering more of theflow and especially the wake of the cube. For the ATM, a region containing theimportant flow structures is identified in the wake, by looking at instantaneousand fluctuating velocities. To ensure converged POD modes two methods toinvestigate the convergence are proposed, tested and applied. Analysis of themodes enables the identification of the important flow structures. The flowtopologies of the two geometries are very different and the flow structures arealso different, but the same methodology can be applied in both cases. For thesurface-mounted cube, three groups of flow structures are found. First groupis the mean flow and then two kinds of perturbations around the mean flow.The first perturbation is at the edge of the wake, relating to the shear layerbetween the free stream and the disturbed flow. The second perturbation isinside the wake and is the convection of vortices. These groups would then betypical of the separation bubble that exists in the wake of the cube. For theATM the main flow topology consists of two counter rotating vortices. Thiscan be seen in the decomposed modes, which, except for the mean flow, almostonly contain flow structures relating to these vortices. / QC 20100518 / Gröna Tåget

I juni år 2017 invigdes Citybanan och pendeltågsstationen Stockholm City. I samband med och efter stationens öppnande har flertalet synpunkter från resenärer samlats in gällande stationens utformning och trafikinformation efter att brister i stationens miljö upptäcktes. Konsultföretaget Sweco har därför på uppdrag av Trafikverket utrett bristerna på Stockholm City för att sedan komma med förbättringsförslag. Utredningen visade på en osäkerhet hos resenärerna för hur de skulle agera vid ankomster med korta pendeltåg. Det visade sig att resenärerna inte visste vart de skulle placera sig på stationen, att de ofta fick springa för att hinna med och ibland till och med missade ett kort pendeltåg på grund av bristfällig vägledning. Uppsatsen syftar därför till att undersöka hur människor agerar i stationsmiljö, mer specifikt på pendeltågsstationen Stockholm City genom observationer. Observationerna av totalt 800 resenärer skapar en förståelse för hur den fysiska miljön och trafikinformationen påverkar människans agerande när de ska placera sig på plattformen i väntan på sitt korta pendeltåg. Uppsatsens genomförda fältstudier och observationsstudier analyseras med metoden observiarie för att fånga upp enskilda resenärers ageranden och beteenden. De observerade resenärerna klustras sedan till fem olika resenärsidentiteter: den bestämda målsökaren, den självsäkra, gruppresenären, sökaren och den svårpåverkade för att förklara resenärernas agerande på en pendeltågsstation och varför somliga tycks missa sin avgång. / In June 2017, Citybanan and the commuter train station Stockholm City opened. In connection with the opening and after the opening, The Swedish Transport Administration gathered commuters' feedback regarding the station's overall design, environment and traffic information. The consulting company Sweco was also hired on behalf of the Swedish Transport Administration to identify the shortcomings of the station and to propose potential suggestions for further improvement. According to Sweco's investigation, there was uncertainty among travelers regarding how they should act upon arrivals with short commuter trains. The passengers did not know where to locate at the station, they often had to run to catch the train and sometimes some travelers even missed the short commuter train due to inadequate guidance and traffic information. This essay, therefore, aims to explore how individuals act in station environments, more specifically at Stockholm City commuter train station through observations. The observations of a total of 800 passengers help to create an understanding of how the physical environment and traffic information affect human actions when they have to navigate on the platform while waiting for a short commuter train. The essays completed field studies and observations are analyzed using observiarie as a method to capture the actions and behaviors of individual travelers. The passengers are then also clustered into five different passenger identities: the determined target seeker, the confident, the group traveler, the seeker, and finally the difficult to influence, to further explain passengers' actions at a commuter train station and explain why some travelers seem to miss their departure when short commuter trains arrives.

In a future vision for rail travel, trains will be designed as an activity-based whole space, with different areas for various activities, such as relaxing, socialising or family bonding. My degree project, in collaboration with SJ, proposes a concept carriage dedicated to work, analogous to spending a day at a mobile coworking space. By recognising the new ways of working, this carriage will cater for the needs of different individuals and various types of work and will include private digital meeting spaces, group compartments, collaborative open spaces and cocoon-like seating options in quiet areas. Unlike other modes of transportation, trains allow for passengers to navigate and experience different spaces. By enhancing the use of space and incorporating amenities that improve the user experience, I aim to transform the perception of long train journeys from tedious to exciting and allow a more seamless and efficient way of getting work done while travelling. Ultimately, this degree project encourages sustainable travel through user-centred design.

Live, Virtual, and Constructive (LVC) is a relatively newly developed system of systems concept designed to provide a new way of conducting training for, but not exclusively, fighter pilots. “Train like you fight” is a commonly used quote when talking about LVC. The ability to create an environment where fighter pilots are able to train in an environment that is as much alike their working environment as possible will give the pilots a huge advantage when having to work in such a challenging and dangerous environment like active war. Besides training, other areas to use LVC have been discussed, and one of those areas is system test and analysis for weapon systems. In this thesis the ability to use LVC as a system test and analysis tool is investigated. This is done by the development of a model of what the LVC system looks like, then a suggestion of an LVC-design with the purpose of using the system as a test and analysis tool is presented. The design is based on SWOT-analyses based on previous research and on LVC products existing on the market. To validate this design a workshop with experts was conducted to receive input on the design as well as discuss the possibilities of Sweden implementing LVC in the future. After the workshop the LVC-design was updated with the points from the workshop. / Live, Virtual och Constructive eller LVC är ett relativt nyutvecklat system av systemkoncept som är utformat för att tillhandahålla ett nytt sätt att genomföra träning för, men inte enbart, stridspiloter. "Träna som du slåss" är ett vanligt citat när man talar om LVC. Förmågan att skapa en miljö där stridspiloter kan träna så likt deras arbetsmiljö som möjligt, d.v.s. aktivt krig, kommer att ge piloterna en enorm fördel när de måste arbeta i en så utmanande och farlig omgivning. Förutom träning har andra användningsområden för LVC diskuterats, och ett av dessa områden är systemtest och systemanalys för vapensystem. I denna rapport undersöks just förmågan att använda LVC som ett systemtest- och analysverktyg. Detta görs genom att utveckla en modell för hur LVC systemet ser ut och vilka förändringar som skulle behöva göras för att det ska kunna fungera som ett systemtest- och analysverktyg, detta resulterar i en modell av en LVC-design. Den modellen är baserad på SWOT-analyser som i sin tur är baserade på tidigare forskning och på LVC-produkter som finns på marknaden. För att validera denna modell genomförs en workshop med experter för att få input om modellen samt diskutera möjligheterna för Sverige att eventuellt implementera LVC i framtiden. Efter workshopen uppdaterades LVC-designen med punkter från workshopen.

High-Speed Railway (HSR) technology requires the deployment of noise barriers to mitigate noise pollution affecting nearby residents. As train speeds increase, so does the magnitude of aerodynamic effects such as aerodynamic noise and the pressure on these barriers, meaning that these structures require robust sound insulation and structural load-bearing capacities. Train-induced aerodynamic loads must therefore be accounted for in the structural design of HSR noise barriers, and accurate characterization of these loads is vital for ensuring noise barrier performance and safety. Current European standards primarily evaluate aerodynamic loads on noise barriers based on train speed and the distance to the track centre. However, geometric differences between high-speed trains (HSTs) from different countries and regions necessitate the validation and potential revision of existing load calculation models. This thesis aims to enhance the characterization of train-induced aerodynamic pressure on HSR noise barriers and develop more accurate models for its calculation, focusing on the most common barrier type—vertical noise barriers. Initially, a thorough literature review was conducted to assimilate current knowledge on this topic and pinpoint existing gaps and challenges. Multiple factors including the geometric properties of trains and the heights of noise barriers were then analysed using computational fluid dynamics (CFD) simulations to evaluate their impact on the train-induced aerodynamic pressure on vertical noise barriers. Finally, the suitability of existing pressure calculation models was evaluated using literature data and a modified calculation model building on the EN 14067-4 model was developed.  A key finding is that the general applicability of existing pressure calculation models is limited because of the wide variation in HST geometries and noise barrier heights. The amplitude of train-induced aerodynamic pressure on vertical noise barriers increases with train height and width but decreases as nose length increases. While taller noise barriers experience greater aerodynamic pressures, the in-crease in pressure with barrier height is not significant. The proposed modified pressure calculation model that accounts for train geometry and the height distribution coefficient predicts the train-induced aerodynamic pressure on vertical noise barriers more accurately than existing models and could thus improve the structural design and safety of HSR noise barriers across a wide range of conditions.

This thesis concerns dynamic Soil-Structure Interaction (SSI) analysis of portal framerailway bridges. Dynamic problems are common for bridges used for high speedrailway traffic. The passing trains induce harmonic loads on the bridges causingvibration amplitudes that may cause damage to the bridge structures and userdiscomfort.Previous studies have shown that the effects of SSI are substantial for short spanportal frame bridges. The damping ratio of the system is greatly increased due to theenergy dissipation properties of the surrounding soil causing significant changes in thedynamic response of the structure. Therefore, it is of interest to investigate the effectsof SSI for portal frame bridges with longer spans.Two case study bridges with span lengths of approximately 16m have been investigatedin detail in this study. Dynamic analyses of the bridges and train passage simulationshave been performed. The results show that SSI significantly increases the dampingratio which leads to lower vibration amplitudes. It is also possible to draw theconclusion that more accurate results are achieved when modeling fixed foundationsrather than using static spring foundations to replicate the stiffness of the subsoil.Moreover, a simplified modeling approach accounting for the effects of SSI is proposed.The proposed method provides satisfactory results, but more future work may increasethe quality of the results further. To validate the conclusions from this study, a proposalfor experimental validation is presented. Performing full-scale dynamic tests on thestudied bridges would enable further comparison and validation of the results.