AbstractThe research presented within this thesis comprises eleven peer reviewed journal publications which address aspects of the challenge faced by rail transport using a steel-on-steel wheel-rail interface. It describes methods and analytical approaches for improving the safety and efficiency of the railway system through better understanding of this interface. Within this overall theme, the research may conveniently be sub-divided into three sub-topics; (1) wheel and rail damage and maintenance, (2) braking performance in low adhesion conditions, (3) developing understanding of the causes of signals passed at danger. Themes 1 and 2 focus principally on developments associated with the interface between the wheel and the rail while theme 3 connects this to the safety of train operations. They all aim to address the consequences and limitations of running steel wheels on steel rails which result in high contact pressures, large tangential forces and limitations on the adhesion available at the interface.
The methods and approaches developed in the research range from statistical methods through the development of engineering models to the application of ‘big data’ techniques. Notable outcomes of the research include the first demonstration of the role of active suspension in reducing rolling contact fatigue, changes to rail industry standards to allow wheel maintenance methods which extend wheelset life, insights into the development of railhead squat defects, a unique simulation model to investigate braking performance in low adhesion conditions and a tool to help quantify the risks posed by trains approaching red signals. Applying the tools and techniques described in the thesis presents opportunities for improved safety (fewer rail breaks and signals passed at danger), improved reliability and reduced carbon cost through extending the life of wheels and rails. Many of these have already been applied or have the potential for practical application by railway engineers in their day-to-day practice.
|Date of Award||13 May 2022|
|Supervisor||Simon Iwnicki (Main Supervisor) & Paul Allen (Co-Supervisor)|