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Title: The development of modelling tools for railway switches and crossings
Author: Coleman, Ian
ISNI:       0000 0004 5348 8935
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2014
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Network Rail records indicate that approximately 24% of the total track maintenance and renewal budgets are spent on railway switches and crossings (S&C), which account for only 5% of the total main line track mileage. S&C complexities also introduce a degree of risk, which must be adequately managed to ensure a safe and reliable network. In recent years, risk mitigation fell short, resulting in some high profile incidents at S&C. A recent derailment investigation uncovered knowledge gaps within the UK rail industry, including the understanding of S&C degradation. This PhD research project was therefore initiated to investigating modelling tools for S&C wheel-rail interaction and degradation. A new wheel-rail contact detection routine has been developed and validated using existing software and a novel experimental technique using thermal imagery. Existing techniques were then integrated to enable the prediction of normal and tangential contact stresses whilst also simulating wear accumulation. To improve accuracy for long-term S&C damage, a combined tool for assessing non-Hertzian normal contact stresses and multiple modes of S&C degradation was sought. A novel 2.5D boundary element model capable of simulating wheel-rail contact detection, surface and sub-surface elastic and elastic-plastic stress analysis and dynamic material response is presented. Superior computational effort is also achieved, illustrating further the feasibility of such an approach. To conclude, a three-dimensional dynamic finite element model of a railway wheel passing through a cast manganese crossing has also been developed. For the first time, a tool capable of simulating both dynamic contact forces and corresponding plastic material response has been used to discover flaws within existing designs of UK cast manganese crossings. This approach has enabled immediate recommendations for asset improvement to be provided to Network Rail and gives the UK rail industry more scientific insight into the optimal design of railway crossings.
Supervisor: Smith, Roderick; Dini, Daniele Sponsor: Network Rail
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available