Funding providers: Engineering and Physical Sciences Research Council (EPSRC) DTP and Swansea University's Faculty of Science and Engineering
Subject areas: Civil Engineering
Project start date:
- 1 January 2024 (Enrolment open from mid-December)
Project supervisors:
Aligned programme of study: PhD in Civil Engineering
Mode of study: Full-time
Project description:
For High-speed railway, one of the most widely used track forms is the ballastless railway tracks, where the concrete slabs are normally serving as the supports under the rails. During the regular service life of ballastless railway, there may exist severe distresses, like cracks, in the concrete slab due to the train loading and severe environmental conditions, which may further affect the public safety of rail passengers. Recently, the deep learning-based methods have emerged as a powerful tool to detect the cracks in the concrete slabs of the railway automatically and intelligently. However, it may face problems like low computation accuracy and high cost. To solve this problem, this project aims to propose a novel deep learning model for automatic crack identification in concrete slab of ballastless railway with high computation efficiency and low computation cost.
Eligibility
Candidates must hold an Upper Second Class (2.1) honours degree in Engineering or similar relevant science discipline. If you are eligible to apply for the scholarship (i.e. a student who is eligible to pay the UK rate of tuition fees) but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency.
Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by UKCISA regulations.
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