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 October 2023 (Enrolment open from mid-September)
Project supervisor: Dr Yue Hou
Aligned programme of study: PhD in Civil Engineering
Mode of study: Full-time
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.
Candidates must normally hold an undergraduate degree at 2.1 level (or Non-UK equivalent as defined by Swansea University) in Engineering or similar relevant science discipline.
English Language requirements: If applicable – IELTS 6.5 overall (with at least 5.5 in each individual component) or Swansea recognised equivalent.
This scholarship is open to candidates of any nationality.
Please contact Dr Yue Hou ([Email Address Removed]) for any enquiries.