Fatigue assessment of riveted railway bridges
Start date3 January 2020
The studentship is partially funded by Network Rail.
The funding covers academic fees for UK/EU students. You will also receive a stipend of £15,500 per annum to cover your living expenses.
Additional funding is available to present your work in a conference and for project related costs.
Opportunities for tutorial support in the department are available and will enhance your teaching experience as well as provide further income (approximately £1200 - £1500 per annum).
Funding sourceMatch-funded studentship
The majority of metallic railway bridges in UK, approximately 10,000 in total, are already exceeding 100 years of age and are approaching the end of their theoretical service life. Replacement of these structures will be extremely expensive and practically impossible unless phased-in over several decades. Therefore, in many cases, rehabilitation and repair options need to be further developed, since they will be more economic and compatible with available resources. However, even this course of action is likely to create severe logistical problems on the railway network, if deemed necessary on a large scale.
The principal objective of this project, i.e. better understanding, modelling and prediction of a bridge's fatigue performance, will lead to a more effective use of limited and stretched resources and can reduce the rate of rehabilitation/repair or unwarranted early replacement, thus keeping the railway network operating for longer periods without unnecessary disturbances.
The project will review critically existing fatigue assessment methods used by Network Rail to identify their limitations and inherent uncertainties arising due to the non-standardised designs that were used during construction in the late 19th and early 20th centuries. As a result, an important strand of research needs to be undertaken, specifically focusing on a better understanding of fatigue in the context of specific materials and assembly methods used in railway bridges, followed by development of modelling techniques that can lead to more accurate prediction of a bridge's fatigue performance.
The outcomes of this applied research will feed into the standardisation and dissemination of these issues and their integration within existing rules.
This project aims in contributing to the aforementioned through the following tasks:
- Assessing the most common cases where current fatigue verification rules pose challenges to bridge engineers towards the prediction of remaining life of old railway bridges, leading to open questions and assumptions to be made (or forcing an unduly conservative solution).
- Developing, after a critical appraisal of advanced fatigue verification frameworks in other sectors, a fatigue assessment method that can provide more accurate predictions of the fatigue performance of old metallic railway bridges. This is expected to build on a framework that has been explored by the supervisors through earlier research on the TCD (theory of critical distances) method, which requires the generation of material specific test results but which can then be applied to different designs without the requirement of detail-specific fatigue testing. Specific areas of development in this project include: the variability of railway materials (wrought iron, early steel), , the complexity arising from characterising material that has already been in use for many years (and is no longer produced), the characteristics of riveted construction in railway bridges, and the reliability of inferring expended life based on limited information regarding past railway loading.
- Execution of an experimental programme, consisting of small-scale fatigue testing of typical bridge material extracted from a disassembled old metallic railway bridge provided by Network Rail, which will be used to benchmark and verify the analytical/numerical methods mentioned above and assess their predictive capability and accuracy.
- Integration of the findings and recommendations towards updating of existing fatigue verification rules currently used by Network Rail to overcome the applicability challenges and shortage of options mentioned previously.
The PhD project will be supervised by Dr Boulent Imam, who has extensive experience on fatigue analysis of railway bridges and Professor Marios Chryssanthopoulos, who will provide expertise on uncertainty modelling and experimental planning and implementation. There will be interaction with Network Rail engineers to enhance the industrial relevance of the project.
Related linksCentre for Infrastructure Systems Engineering (CISE)
Only available for UK/EU students.
- MEng in Civil / Structural / Mechanical / Aeronautical / Automotive Engineering with a UK equivalent 2:1 classification or above or
- BEng in Civil / Structural / Mechanical / Aeronautical / Automotive Engineering with a UK equivalent 2:1 classification or above and MSc degree in Structural Mechanics / Structural Engineering.
IELTS of 6.5 or above (or equivalent) with 6.0 in each individual category.
In addition to the academic qualifications listed above, skills in numerical modelling of structures using Finite Element Analysis and/or Matlab are highly desirable, as is a rigorous understanding of fatigue/fracture phenomena in metallic structures.
Relevant work experience is also useful (please provide sufficient detail so that its relevance can be established). Evidence of good technical writing either in an academic or professional context will be considered.
How to apply
Apply via the Civil and Environmental Engineering PhD course page.
Applicants are required to send a cover letter explaining their interest in the project, a CV with relevant qualifications and prior expertise in areas relevant to the project, relevant transcripts and the names and contact details of two referees. At least one reference should be from an individual with good knowledge of the applicant’s academic record, especially in projects/dissertations.
Suitable interview dates will be directly arranged with shortlisted applicants.
Civil and Environmental Engineering PhD