Research outcomes for improved management of insulated rail joints

Insulated Rail Joints (IRJs) are safety critical component of the automatic block signalling and broken rail detection systems. IRJs exhibit several failure modes due to complex interaction between the railhead ends and the wheel tread near the gap. These localised zones could not be monitored using automatic sensing devices and hence are resorted to visual inspection only, which is error prone and expensive. In Australia alone currently there are 50,000 IRJs across 80,000 km of rail track. The significance of the problem around the world could thus be realised as there exists one IRJ for each 1.6 km track length. IRJs exhibit extremely low and variable service life; further the track substructure underneath IRJs degrade faster. Thus presence of the IRJs incur significant costs to track maintenance. IRJ failures have also contributed to some train derailments and various traffic disruptions in rail lines. This paper reports a systematic research carried out over seven years on the mechanical behaviour of IRJs for practically relevant outcomes. The research has scientifically established that stiffening the track bed for reduction in impact force is an ill-conceived concept and the most effective method is to reduce the gap size. Further it is established that hardening the railhead ends through laser coating (or other) cannot adequately address the metal flow problem in the long run; modification of the railhead profile is the only appropriate technique to completely eliminate the problem. Part of these outcomes has been adopted by the rail infrastructure owners in Australia.

Fatigue and sleepiness: Complex bedfellows

Do you know how to drive a train? If you don’t you probably believe that you have a fair idea of what it’s all about. Forget what you know, or think you know. Trains are heavy and fast but they feel and handle like driving on ice so they take a long time to stop. The braking distances for a typical piece of track are unlike anything you will have experienced before. With that in mind, imagine you were driving with a bit of dew, or grease, or millipede over the track. You would lose traction and slip everywhere. To avoid this, you would need a compensatory driving strategy. You could drive more slowly, or brake sooner, or change how you brake. Your experience and intuition would lead the way. Folks, this is why it’s called “driving by the seat of your pants”...

Direct observations of pedestrian unsafe crossing at urban Australian level crossings

The number of pedestrian victims at Australian and foreign level crossings has remained stable over the past decade and it continues to be a significant problem. To examine the factors contributing to pedestrians’ unsafe crossing behaviours, direct observations were conducted at three black spot urban level crossings in Brisbane for a total of 45 h during morning and afternoon peak. In total, 129 pedestrians transgressed the active controls. More transgressions were observed at the crossings located in more populated suburbs in close proximity to large shopping centres and school zones, whereas the smallest number of transgressions were observed at the least populated locations. In addition to characteristics associated with the larger socio-economic area, the patterns of transgression could be associated with the properties of the existing safety equipment and the design of each level crossing (i.e. location of the platforms, number of rail tracks). Indeed, the largest number of crossed unoccupied but “at risk” rail tracks (where a train could have passed), was observed at the crossing with the least transgressions. Contrary to previous findings, younger adults were the most frequent transgressors. School children and elderly were most likely to transgress in groups. Potential directions for future research and more effective measures are discussed.

How religiosity influences consumption: The impact of consumer religiosity on perceptions of psychological and social risk

For some people, religion is an important influence in decision-making. This thesis investigates the relationship between the religiosity of consumers and their perceived risk in adopting new products. Two studies gathered data from religious consumers living in Saudi Arabia, Australia, Canada, New Zealand, the UK and the USA. The results confirm the significant impact of religion on perceived risk, and suggest why this may lead to delays in adoption. Theoretically, these studies provide a better explanation of how religion influences consumption decisions, and offer brand managers options to improve the adoption of new products in religious markets.

Human factors evaluation of a novel Australian approach for activating railway level crossings

There are currently 23,500 level crossings in Australia, broadly divided active level crossings with flashing lights; and passive level crossings controlled by stop and give way signs. The current strategy is to annually upgrade passive level crossings with active controls within a given budget, but the 5,900 public passive crossings are too numerous to be upgraded all. The rail industry is considering alternative options to treat more crossings. One of them is to use lower cost equipment with reduced safety integrity level, but with a design that would fail to a safe state: in case of the impossibility for the system to know whether a train is approaching, the crossing changes to a passive crossing. This is implemented by having a STOP sign coming in front of the flashing lights. While such design is considered safe in terms of engineering design, questions remain on human factors. In order to evaluate whether such approach is safe, we conducted a driving simulator study where participants were familiarized with the new active crossing, before changing the signage to a passive crossing. Our results show that drivers treated the new crossing as an active crossing after the novelty effect had passed. While most participants did not experience difficulties with the crossing being turned back to a passive crossing, a number of participants experienced difficulties stopping in time at the first encounter of such passive crossing. Worse, a number of drivers never realized the signage had changed, highlighting the link between the decision to brake and stop at an active crossing to the lights flashing. Such results show the potential human factor issues of changing an active crossing to a passive crossing in case of failure of the detection of the train.

Assessment of antenna characteristic effects on pedestrian and cyclists travel-time estimation based on Bluetooth and WiFi MAC addresses

Monitoring pedestrian and cyclists movement is an important area of research in transport, crowd safety, urban design and human behaviour assessment areas. Media Access Control (MAC) address data has been recently used as potential information for extracting features from people’s movement. MAC addresses are unique identifiers of WiFi and Bluetooth wireless technologies in smart electronics devices such as mobile phones, laptops and tablets. The unique number of each WiFi and Bluetooth MAC address can be captured and stored by MAC address scanners. MAC addresses data in fact allows for unannounced, non-participatory, and tracking of people. The use of MAC data for tracking people has been focused recently for applying in mass events, shopping centres, airports, train stations etc. In terms of travel time estimation, setting up a scanner with a big value of antenna’s gain is usually recommended for highways and main roads to track vehicle’s movements, whereas big gains can have some drawbacks in case of pedestrian and cyclists. Pedestrian and cyclists mainly move in built distinctions and city pathways where there is significant noises from other fixed WiFi and Bluetooth. Big antenna’s gains will cover wide areas that results in scanning more samples from pedestrians and cyclists’ MAC device. However, anomalies (such fixed devices) may be captured that increase the complexity and processing time of data analysis. On the other hand, small gain antennas will have lesser anomalies in the data but at the cost of lower overall sample size of pedestrian and cyclist’s data. This paper studies the effect of antenna characteristics on MAC address data in terms of travel-time estimation for pedestrians and cyclists. The results of the empirical case study compare the effects of small and big antenna gains in order to suggest optimal set up for increasing the accuracy of pedestrians and cyclists’ travel-time estimation.

Somewhere between haste and delay... Investigating the interactions of road users and pedestrians in a dynamic rail level crossing environment

There are currently 23,500 level crossings in Australia, broadly divided into one of two categories: active level crossings which are fully automatic and have boom barriers, alarm bells, flashing lights, and pedestrian gates; and passive level crossings, which are not automatic and aim to control road and pedestrianised walkways solely with stop and give way signs. Active level crossings are considered to be the gold standard for transport ergonomics when grade separation (i.e. constructing an over- or underpass) is not viable. In Australia, the current strategy is to annually upgrade passive level crossings with active controls but active crossings are also associated with traffic congestion, largely as a result of extended closure times. The percentage of time level crossings are closed to road vehicles during peak periods increases with the rise in the frequency of train services. The popular perception appears to be that once a level crossing is upgraded, one is free to wipe their hands and consider the job done. However, there may also be environments where active protection is not enough, but where the setting may not justify the capital costs of grade separation. Indeed, the associated congestion and traffic delay could compromise safety by contributing to the risk taking behaviour by motorists and pedestrians. In these environments it is important to understand what human factor issues are present and ask the question of whether a one size fits all solution is indeed the most ergonomically sound solution for today’s transport needs.

Lateralization of temporal lobe epilepsy based on resting-state functional magnetic resonance imaging and machine learning

Lateralization of temporal lobe epilepsy (TLE) is critical for successful outcome of surgery to relieve seizures. TLE affects brain regions beyond the temporal lobes and has been associated with aberrant brain networks, based on evidence from functional magnetic resonance imaging. We present here a machine learning-based method for determining the laterality of TLE, using features extracted from resting-state functional connectivity of the brain. A comprehensive feature space was constructed to include network properties within local brain regions, between brain regions, and across the whole network. Feature selection was performed based on random forest and a support vector machine was employed to train a linear model to predict the laterality of TLE on unseen patients. A leave-one-patient-out cross validation was carried out on 12 patients and a prediction accuracy of 83% was achieved. The importance of selected features was analyzed to demonstrate the contribution of resting-state connectivity attributes at voxel, region, and network levels to TLE lateralization.

Motorway crash duration and its determinants: Do durations vary across motorways?

Traffic congestion has been a growing issue in many metropolitan areas during recent years, which necessitates the identification of its key contributors and development of sustainable strategies to help decrease its adverse impacts on traffic networks. Road incidents generally and crashes specifically have been acknowledged as the cause of a large proportion of travel delays in urban areas and account for 25% to 60% of traffic congestion on motorways. Identifying the critical determinants of travel delays has been of significant importance to the incident management systems which constantly collect and store the incident duration data. This study investigates the individual and simultaneous differential effects of the relevant determinants on motorway crash duration probabilities. In particular, it applies parametric Accelerated Failure Time (AFT) hazard-based models to develop in-depth insights into how the crash-specific characteristic and the associated temporal and infrastructural determinants impact the duration. AFT models with both fixed and random parameters have been calibrated on one year of traffic crash records from two major Australian motorways in South East Queensland and the differential effects of determinants on crash survival functions have been studied on these two motorways individually. A comprehensive spectrum of commonly used parametric fixed parameter AFT models, including generalized gamma and generalized F families, have been compared to random parameter AFT structures in terms of goodness of fit to the duration data and as a result, the random parameter Weibull AFT model has been selected as the most appropriate model. Significant determinants of motorway crash duration included traffic diversion requirement, crash injury type, number and type of vehicles involved in a crash, day of week and time of day, towing support requirement and damage to the infrastructure. A major finding of this research is that the motorways under study are significantly different in terms of crash durations; such that motorway exhibits durations that are on average 19% shorter compared to the durations on motorway. The differential effects of explanatory variables on crash durations are also different on the two motorways. The detailed presented analysis confirms that, looking at the motorway network as a whole, neglecting the individual differences between roads, can lead to erroneous interpretations of duration and inefficient strategies for mitigating travel delays along a particular motorway.

Review and future options for computer modelling in the sugar industry

Computer modelling has been used extensively in some processes in the sugar industry to achieve significant gains. This paper reviews the investigations carried out over approximately the last twenty five years, including the successes but also areas where problems and delays have been encountered. In that time the capability of both hardware and software have increased dramatically. For some processes such as cane cleaning, cane billet preparation, and sugar drying, the application of computer modelling towards improved equipment design and operation has been quite limited. A particular problem has been the large number of particles and particle interactions in these…

Experimental studies on the performance of rail joints with modified wheel/railhead contact

Rail joints are provided with a gap to account for thermal movement and to maintain electrical insulation for the control of signals and/or broken rail detection circuits. The gap in the rail joint is regarded as a source of significant problems for the rail industry since it leads to a very short rail service life compared with other track components due to the various, and difficult to predict, failure modes – thus increasing the risk for train operations. Many attempts to improve the life of rail joints have led to a large number of patents around the world; notable attempts include strengthening through larger-sized joint bars, an increased number of bolts and the use of high yield materials. Unfortunately, no design to date has shown the ability to prolong the life of the rail joints to values close to those for continuously welded rail (CWR). This paper reports the results of a fundamental study that has revealed that the wheel contact at the free edge of the railhead is a major problem since it generates a singularity in the contact pressure and railhead stresses. A design was therefore developed using an optimisation framework that prevents wheel contact at the railhead edge. Finite element modelling of the design has shown that the contact pressure and railhead stress singularities are eliminated, thus increasing the potential to work as effectively as a CWR that does not have a geometric gap. An experimental validation of the finite element results is presented through an innovative non-contact measurement of strains. Some practical issues related to grinding rails to the optimal design are also discussed.

Implementation of a chest pain management service improves patient care and reduces length of stay

Objective Chest pain is one of the most common complaints in patients presenting to an emergency department. Delays in management due to a lack of readily available objective tests to risk stratify patients with possible acute coronary syndromes can lead to an unnecessarily lengthy admission placing pressure on hospital beds or inappropriate discharge. The need for a co-ordinated system of clinical management based on enhanced communication between departments, timely and appropriate triage, clinical investigation, diagnosis, and treatment was identified. Methods An evidence-based Chest Pain Management Service and clinical pathway were developed and implemented, including the introduction of after-hours exercise stress testing. Results Between November 2005 and March 2013, 5662 patients were managed according to a Chest Pain Management pathway resulting in a reduction of 5181 admission nights by more timely identification of patients at low risk who could then be discharged. In addition, 1360 days were avoided in high-risk patients who received earlier diagnosis and treatment. Conclusions The creation of a Chest Pain Management pathway and the extended exercise stress testing service resulted in earlier discharge for low-risk patients; and timely treatment for patients with positive and equivocal exercise stress test results. This service demonstrated a significant saving in overnight admissions.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

Milling innovations at Rocky Point

This paper reviews the innovations that have been introduced in the milling train at Rocky Point mill since 2001 and provides some operational, performance and maintenance comparisons of the technologies in use. The decision to install BHEM mills in the #2 and #3 mill positions to complement the six-roll mills in the #1 and #4 mill positions has proven a good one. Satisfactory performance is being obtained by these mills while maintenance costs are significantly less. Very good #1 mill extraction and final bagasse moisture content are being achieved. The innovation of using Hägglunds hydraulic drives at higher speed…

TrainYarn: Probing perceptions of social space in urban commuter trains

We studied the ways that urban commuter train passengers experience their journeys. We present the design process and in-situ evaluation of TrainYarn, a mobile app prototype designed to facilitate social interaction between co-located urban train passengers. Through the deployment of the prototype, we sought to probe perceptions of social space with a view to positively impact the assessment of public transport. Our results support that our target users saw value in the use of TrainYarn, perceiving it as emancipatory, in alignment with their communicative needs, and having the ability to transform their perceptions of social space. To further inform future research and practice, we put forward a series of design recommendations.