Modernização da linha da Beira Baixa: troço Covilhã - Guarda

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Vias de Comunicação e Transportes

A numerical program for Railway vehicle-track-structure dynamic interaction using a modal substructuring approach

This work presents a program for simulations of vehicle-track and vehicle-trackstructure dynamic interaction . The method used is computationally efficient in the sense that a reduced number of coordinates is sufficient and doesn’t require high efficiency computers. The method proposes a modal substructuring approach of the system by modelling rails , sleepers and underlying structure with modal coordinates, the vehicle with physical lumped elements coordinates and by introducing interconnection elements between these structures (wheel-rail contact, railpads and ballast) by means of their interaction forces. The Frequency response function (FRF) is also calculated for both cases of track over a structure (a bridge, a viaduct ...) and for the simple vehicle-track program; for each case the vehicle effect on the FRF is then analyzed through the comparison of the FRFs obtained introducing or not a simplified vehicle on the system.

Optical fibre sensors and their applications in the industrial weighing and aerospace industries

This thesis presents the design, fabrication and testing of novel grating based Optical Fibre Sensor (OFS) systems being interrogated using “off the shelf” interrogation systems, with the eventual development of marketable commercial systems at the forefront of the research. Both in the industrial weighing and aerospace industries, there has been a drive to investigate the feasibility of using optical fibre sensors being deployed where traditionally their electrical or mechanical counterparts would traditionally have been. Already, in the industrial weighing industry, commercial operators are deploying OFS-based Weigh-In-Motion (WIM) systems. Likewise, in the aerospace industry, OFS have been deployed to monitor such parameters as load history, impact detection, structural damage, overload detection, centre of gravity and the determination of blade shape. Based on the intrinsic properties of fibre Bragg gratings (FBGs) and Long Period Fibre Gratings (LPFGs), a number of novel OFS-based systems have been realised. Experimental work has shown that in the case of static industrial weighing, FBGs can be integrated with current commercial products and used to detect applied loads. The work has also shown that embedding FBGs in e-glass, to form a sensing patch, can result in said patches being bonded to rail track, forming the basis of an FBG-based WIM system. The results obtained have been sufficiently encouraging to the industrial partner that this work will be progressed beyond the scope of the work presented in this thesis. Likewise, and to the best of the author’s knowledge, a novel Bragg grating based systems for aircraft fuel parameter sensing has been presented. FBG-based pressure sensors have been shown to demonstrate good sensitivity, linearity and repeatability, whilst LPFG-based systems have demonstrated a far greater sensitivity when compared to FBGs, as well the advantage of being potentially able to detect causes of fuel adulteration based on their sensitivity to refractive index (RI). In the case of the LPFG-based system, considerable work remains to be done on the mechanical strengthening to improve its survivability in a live aircraft fuel tank environment. The FBG system has already been developed to an aerospace compliant prototype and is due to be tested at the fuel testing facility based at Airbus, Filton, UK. It is envisaged by the author that in both application areas, continued research in this area will lead to the eventual development of marketable commercial products.

Fiber Bragg Gratings Strain Sensors for Railway Applications

Fiber optical sensors have played an important role in applications for monitoring the health of civil infrastructures, such as bridges, oil rigs, and railroads. Due to the reduction in cost of fiber-optic components and systems, fiber optical sensors have been studied extensively for their higher sensitivity, precision and immunity to electrical interference compared to their electrical counterparts. A fiber Bragg grating (FBG) strain sensor has been employed for this study to detect and distinguish normal and lateral loads on rail tracks. A theoretical analysis of the relationship between strain and displacement under vertical and horizontal strains on an aluminum beam has been performed, and the results are in excellent agreement with the measured strain data. Then a single FBG sensor system with erbium-doped fiber amplifier broadband source has been carried out. Force and temperature applied on the system have resulted in changes of 0.05 nm per 50 με and 0.094 nm per 10 oC at the center wavelength of the FBG. Furthermore, a low cost fiber-optic sensor system with a distributed feedback (DFB) laser as the light source has been implemented. We show that it has superior noise and sensitivity performances compared to strain gauge sensors. The design has been extended to accommodate multiple sensors with negligible cross talk. When two cascaded sensors on a rail track section are tested, strain readings of the sensor 20 inches away from the position of applied force decay to one seventh of the data of the sensor at the applied force location. The two FBG sensor systems can detect 1 ton of vertical load with a square wave pattern and 0.1 ton of lateral loads (3 tons and 0.5 ton, respectively, for strain gauges). Moreover, a single FBG sensor has been found capable of detecting and distinguishing lateral and normal strains applied at different frequencies. FBG sensors are promising alternatives to electrical sensors for their high sensitivity,ease of installation, and immunity to electromagnetic interferences.

Increasing learners’ satisfaction/intention to adopt more e-learning

Purpose: E-learning is an organisationally risky investment given the cost and poor levels of adoption by users. In order to gain a better understanding of this problem, a study was conducted into the use of e-learning in a rail organisation. Design/methodology/approach: Using an online survey, employees of a rail-sector organisation were questioned about their use and likelihood of adoption of e-learning. This study explores the factors that affect the way in which learners experience and perceive such systems. Using statistical analysis, twelve hypotheses are tested and explored. Relationships between learning satisfaction, intention to adopt and the characteristics of e-learning systems were established. Findings: The study found that e-learning characteristics can buffer the relationship between learner characteristics and intention to adopt further e-learning in the future. Further, we found that high levels of support can compensate individuals who are low in technological efficacy to adopt e-learning. Research limitations/implications: The cross-sectional design of the study and its focus on measuring intention to adopt as opposed to actual adoption are both limitations. Future research using longitudinal design and research employing a time lag design measuring actual adoption as well as intention are recommended. Practical implications: From a practical perspective, organizations can focus on the actual content and authenticity of the learning experience delivered by the e-learning system to significantly impact how employees will perceive and use e-learning in the future. Low technological efficacy individuals tend not to adopt new technology. Instead of changing individuals’ personalities, organizations can implement supportive policies and practices which would lead to higher e-learning adoption rate among low efficacy individuals. Originality/value: The study integrates technology adoption and learning literatures in developing enablers for e-learning in organizations. Further, this study collects data from rail employees, and therefore the findings are practical to an industry.

Editorial : is it the time for railway industry to reinvent itself?

Editorial: is it the time for railway industry to reinvent itself? Railway infrastructure plays a critical role in urban development, mobility, and economic growth of society. This focus issue of the Electronic Journal of Structural Engineering is devoted to a special theme, “Advances in Rail Track Infrastructure and Practice - ARTRP”. It contains articles, which were rigorously peer reviewed and accepted from a list of invited manuscripts that demonstrate significant innovation in the area of the structural engineering aspects of the rail track infrastructure...

Near-miss event detection at railway level crossings

Recent modelling of socio-economic costs by the Australian railway industry in 2010 has estimated the cost of level crossing accidents to exceed AU$116 million annually. To better understand the causal factors of these accidents, a video analytics application is being developed to automatically detect near-miss incidents using forward facing videos from trains. As near-miss events occur more frequently than collisions, by detecting these occurrences there will be more safety data available for analysis. The application that is being developed will improve the objectivity of near-miss reporting by providing quantitative data about the position of vehicles at level crossings through the automatic analysis of video footage. In this paper we present a novel method for detecting near-miss occurrences at railway level crossings from video data of trains. Our system detects and localizes vehicles at railway level crossings. It also detects the position of railways to calculate the distance of the detected vehicles to the railway centerline. The system logs the information about the position of the vehicles and railway centerline into a database for further analysis by the safety data recording and analysis system, to determine whether or not the event is a near-miss. We present preliminary results of our system on a dataset of videos taken from a train that passed through 14 railway level crossings. We demonstrate the robustness of our system by showing the results of our system on day and night videos.

Driving simulator evaluation of the failure of an audio in-vehicle warning for railway level crossings

It is impracticable to upgrade the 18,900 Australian passive crossings as such crossings are often located in remote areas, where power is lacking and with low road and rail traffic. The rail industry is interested in developing innovative in-vehicle technology interventions to warn motorists of approaching trains directly in their vehicles. The objective of this study was therefore to evaluate the benefits of the introduction of such technology. We evaluated the changes in driver performance once the technology is enabled and functioning correctly, as well as the effects of an unsafe failure of the technology? We conducted a driving simulator study where participants (N=15) were familiarised with an in-vehicle audio warning for an extended period. After being familiarised with the system, the technology started failing, and we tested the reaction of drivers with a train approaching. This study has shown that with the traditional passive crossings with RX2 signage, the majority of drivers complied (70%) and looked for trains on both sides of the rail track. With the introduction of the in-vehicle audio message, drivers did not approach crossings faster, did not reduce their safety margins and did not reduce their gaze towards the rail tracks. However participants’ compliance at the stop sign decreased by 16.5% with the technology installed in the vehicle. The effect of the failure of the in-vehicle audio warning technology showed that most participants did not experience difficulties in detecting the approaching train even though they did not receive any warning message. This showed that participants were still actively looking for trains with the system in their vehicle. However, two participants did not stop and one decided to beat the train when they did not receive the audio message, suggesting potential human factors issues to be considered with such technology.

Effects of particle size distribution in the response of model granular materials in multi-ring shear

Rail track undergoes complex loading patterns under moving traffic conditions compared to roads due to its continued and discontinued multi-layered structure, including rail, sleepers, ballast layer, sub-ballast layer, and subgrade. Particle size distributions (PSDs) of ballast, subballast, and subgrade layers can be critical in cyclic plastic deformation of rail track under moving traffic on frequent track degradation of rail tracks, especially at bridge transition zones. Conventional test approaches: static shear and cyclic single-point load tests are however unable to replicate actual loading patterns of moving train. Multi-ring shear apparatus; a new type of torsional simple shear apparatus, which can reproduce moving traffic conditions, was used in this study to investigate influence of particle size distribution of rail track layers on cyclic plastic deformation. Three particle size distributions, using glass beads were examined under different loading patterns: cyclic sin-gle-point load, and cyclic moving wheel load to evaluate cyclic plastic deformation of rail track under different loading methods. The results of these tests suggest that particle size distributions of rail track structural layers have significant impacts on cyclic plastic deformation under moving train load. Further, the limitations in con-ventional test methods used in laboratories to estimate the plastic deformation of rail track materials lead to underestimate the plastic deformation of rail tracks.

The Agent-Rule-Class Framework for Multi-Agent Systems

Multi-agent systems have become increasingly mature, but their appearance does not make the traditional OO approach obsolete. On the contrary, OO methodologies can benefit from the principles and tools designed for agent systems. The Agent-Rule-Class (ARC) framework is proposed as an approach that builds agents upon traditional OO system components and makes use of business rules to dictate agent behaviour with the aid of OO components. By modelling agent knowledge in business rules, the proposed paradigm provides a straightforward means to develop agent-oriented systems based on the existing object-oriented systems and offers features that are otherwise difficult to achieve in the original OO systems. The main outcome of using ARC is the achievement of adaptivity. The framework is supported by a tool that ensures agents implement up-to-date requirements from business people, reflecting desired current behaviour, without the need for frequent system rebuilds. ARC is illustrated with a rail track example.

Utilização de materiais anti-vibráteis e de isolamento acústico na via férrea

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes

Letter to S.D. Woodruff from Fred Holmes

Letter to S.D. Woodruff from Fred Holmes regarding the work done on the east side of the rail track. He gives the measurement of work done by W. Robinson, May 18, 1860.

MACHINE VISION FOR AUTOMATICVISUAL INSPECTION OF WOODENRAILWAY SLEEPERS USING UNSUPERVISED NEURAL NETWORKS

The motivation for this thesis work is the need for improving reliability of equipment and quality of service to railway passengers as well as a requirement for cost-effective and efficient condition maintenance management for rail transportation. This thesis work develops a fusion of various machine vision analysis methods to achieve high performance in automation of wooden rail track inspection.The condition monitoring in rail transport is done manually by a human operator where people rely on inference systems and assumptions to develop conclusions. The use of conditional monitoring allows maintenance to be scheduled, or other actions to be taken to avoid the consequences of failure, before the failure occurs. Manual or automated condition monitoring of materials in fields of public transportation like railway, aerial navigation, traffic safety, etc, where safety is of prior importance needs non-destructive testing (NDT).In general, wooden railway sleeper inspection is done manually by a human operator, by moving along the rail sleeper and gathering information by visual and sound analysis for examining the presence of cracks. Human inspectors working on lines visually inspect wooden rails to judge the quality of rail sleeper. In this project work the machine vision system is developed based on the manual visual analysis system, which uses digital cameras and image processing software to perform similar manual inspections. As the manual inspection requires much effort and is expected to be error prone sometimes and also appears difficult to discriminate even for a human operator by the frequent changes in inspected material. The machine vision system developed classifies the condition of material by examining individual pixels of images, processing them and attempting to develop conclusions with the assistance of knowledge bases and features.A pattern recognition approach is developed based on the methodological knowledge from manual procedure. The pattern recognition approach for this thesis work was developed and achieved by a non destructive testing method to identify the flaws in manually done condition monitoring of sleepers.In this method, a test vehicle is designed to capture sleeper images similar to visual inspection by human operator and the raw data for pattern recognition approach is provided from the captured images of the wooden sleepers. The data from the NDT method were further processed and appropriate features were extracted.The collection of data by the NDT method is to achieve high accuracy in reliable classification results. A key idea is to use the non supervised classifier based on the features extracted from the method to discriminate the condition of wooden sleepers in to either good or bad. Self organising map is used as classifier for the wooden sleeper classification.In order to achieve greater integration, the data collected by the machine vision system was made to interface with one another by a strategy called fusion. Data fusion was looked in at two different levels namely sensor-level fusion, feature- level fusion. As the goal was to reduce the accuracy of the human error on the rail sleeper classification as good or bad the results obtained by the feature-level fusion compared to that of the results of actual classification were satisfactory.

Design of an optimised wheel profile for rail vehicles operating on two track gauges

This paper sets out an optimum synthesis methodology for wheel profiles of railway vehicles in order to secure good dynamic behaviour with different track configurations. Specifically, the optimisation process has been applied to the case of rail wheelsets mounted on double gauge bogies, that move over two different gauges, which also have different types of rail: the Iberian gauge (1668 mm) and the UIC gauge (1435 mm). Optimisation is performed using Genetic Algorithms and traditional optimisation methods in a complementary way. The objective function used is based on an ideal equivalent conicity curve which ensures good stability on straight sections and also proper negotiation of curves. To this end the curve is constructed in such a way that it is constant with a low value for small lateral wheelset displacements (with regard to stability), and increases as the displacements increase (to facilitate negotiation of curved sections). Using this kind of ideal conicity curve also enables a wheel profile to be secured where the contact points have a larger distribution over the active contact areas, making wear more homogeneous and reducing stresses. The result is a wheel profile with a conicity that is closer to the target conicity for both gauges studied, producing better curve negotiation while maintaining good stability on straight sections of track. The paper shows the resultant wheel profile, the contact curves it produces, and a number of dynamic analyses demonstrating better dynamic behaviour of the synthesised wheel on curved sections with respect to the original wheel.