Derailment risk analysis, monitoring and management at railway turnouts

The general objective of the thesis is to develop a number of novel Bayesian- based mathematical models that are applicable for the railway sector. Hence, it is assumed that the thesis will be an element of, or facilitate future AI (Artificial Intelligence) Risk Management and Safety Standards, which will inevitably be developed for the sector. The thesis primarily concentrates on applications that support decision-making processes, related to derailments at railway turnout sys- tem. The first objective is to determine, evaluate and prioritise the risk factors that cause derailments; secondly, it will identify and demonstrate the relationship among these driving factors; and finally, it will show the prospective usage of Bayesian networks as an intuitive modelling instrument that makes the process of modelling risk more transparent and consistent. In order to achieve the aforementioned objectives, this thesis is established on various novel methodological approaches using either qualitative or quantitative methods, or a combination of the two. A comprehensive review is conducted in order to interpret and acquire an in-depth understanding of suitable methods of analysing risk in addition to five original studies on the subjects of component failures, human errors and the environmental impact to measure, rank, categorise, and identify the factors that cause derailment in the railway sector. The proposed novel methodologies in addition to their MATLAB and R codes are introduced for utilisation in a developed framework for analysing, monitoring and managing risk for railway turnout

Derailment-based fault tree analysis on risk management of railway turnout systems

Railway turnouts are fundamental mechanical infrastructures, which allow a rolling stock to divert one direction to another. As those are of a large number of engineering subsystems, e.g. track, signalling, earthworks, these particular sub-systems are expected to induce high potential through various kind of failure mechanisms. This could be a cause of any catastrophic event. A derailment, one of undesirable events in railway operation, often results, albeit rare occurs, in damaging to rolling stock, railway infrastructure and disrupt service, and has the potential to cause casualties and even loss of lives. As a result, it is quite significant that a well-designed risk analysis is performed to create awareness of hazards and to identify what parts of the systems may be at risk. This study will focus on all types of environment based failures as a result of numerous contributing factors noted officially as accident reports. This risk analysis is designed to help industry to minimise the occurrence of accidents at railway turnouts. The methodology of the study relies on accurate assessment of derailment likelihood, and is based on statistical multiple factors-integrated accident rate analysis. The study is prepared in the way of establishing product risks and faults, and showing the impact of potential process by Boolean algebra