Population based Structural health monitoring for bridges
Applications are now CLOSED
Overview
Managing existing civil infrastructure is a major challenge. For example, a backlog of bridge maintenance works in the UK - identified in 2019 – will cost $6.7bn [1]. The representative cost of replacing a ‘standard’ bridge is of the order of £4-7m and 10,675 tCO2e (equivalent to 4,873 return flights from Brussels to New York). The UK has around 118,000 bridges, maintaining even 0.5% of these as opposed to replacing would represent a major financial and carbon saving. Currently, the bridges on a given network are managed via a system of periodic visual inspections undertaken by a bridge inspector. Unfortunately, not all bridge damage is readily identifiable via visual inspection, for example a railway bridge in Dublin collapsed in 2009 within days of an inspection [3], while a pedestrian bridge in Florida [4] collapsed only hours after an inspection. Therefore, the last two decades has seen a significant body of research into how much value sensor data recorded on the bridge could add to the existing management procedure. Unfortunately, an approach that is logistically implementable has yet to be found. This is largely due to the fact that each bridge is different and therefore sensor data or information you might have about one bridge is currently not easily used to help you manage/make decisions about another bridge. However, recent pioneering work at the University of Sheffield on population based structural health monitoring (PBSHM) has opened the possibility of exploiting data and information you have on one structure, to manage a different structure.
This PhD studentship is part of an exciting multidisciplinary research project with Mechanical Engineers, Civil Engineers, Electrical Engineers and Computer Scientists, from University of Sheffield (UoS), University of Exeter (UoE), Queen’s University Belfast (QUB) and University of Cambridge (UoC). The aim of the wider project is to exploit the new PBSHM technology to manage civil infrastructure. The work in QUB and the focus of this PhD studentship will be on applying PBSHM to bridges and in particular to look at the sensing technology needed to make this implementable, hence a background in civil, mechanical or electrical engineering would be useful. The The successful candidate will be working as part of an institutional project team in QUB with two full time post doctoral researchers, three PhD students and the academic supervisors. Consequently a high level of support will available to assist the successful candidate with their PhD studies within QUB. Moreover, as this PhD project is an important piece of the wider project, the successful applicant will have the opportunity to visit, work with and lean from the internationally renowned research teams in Cambridge, Sheffield and Exeter who will have similar sized teams working on the project. Using truly innovative research the ultimate aim of the project is to create technology that infrastructure stakeholders can leverage in significant applications. To make this a reality requires significant industrial input. Therefore the industrial partners in the project include leading engineering companies (e.g. Amey, Cowi, dywidag, Arquiva, Siemans gamesa) and large infrastructure owners (e.g. Translink, NI Department for infrastructure, Devon County Council, Arquiva). Consequently the successful candidate will have the opportunity to engage with these organisations at a high level. Due to the novelty of the work to be carried out the successful candidate will have the opportunity to publish in the top journals which will support future career progression. Further details on the project and publications to date are given on the project website. ROSEHIPS - Revolutionising Operational Safety and Economy for High-value Infrastructure using Population-based SHM (https://pbshm.ac.uk/).
References
[1] D. Browne. Cost of bridge maintenance backlog is $6.7bn. https://www.transport network.co.uk/Costof-bridge-maintenance-backlog-is-67bn/15557, 2019.
[2] R. Lobley. European bridge maintenance and safety https://www.governmenteuropa.eu/european-bridge-maintenance/92201/, 2019.
[3] Railway Accident Investigation Unit. Malahide Viaduct Collapse on the Dublin to Belfast Line, on the 21st August 2009, page 115. Railway Safety Commission, 2010.
[4] A. Mohammad. Investigation of March 15, 2018 Pedestrian Bridge Collapse at Florida International University, Miami, FL, page 115. U.S Department of Labor, Occupational Safety and Health Administration, Directorate of Construction, 2019.
RESEARCH PROPOSAL
Please note that applicants are not required to upload a research proposal as part of the application. Instead, interested candidates should upload a copy of their CV and a covering letter outlining their motivation to undertake a PhD on this theme, and describing any relevant experience in: bridges, sensing systems, data processing, or more broadly in Civil engineering, mechanical engineering or electrical/electronic engineering.
APPLICATION PROCEDURE
• Apply for Degree of Doctor of Philosophy in Civil Engineering at Queen's University Belfast, School of Natural and Built Environment.
• State name of lead supervisor on application form ‘Dr David Hester’.
• Include your Research Proposal (see above for research proposal guidance).
• State the intended SOURCE OF FUNDING on your application as ‘EPSRC’
• To apply, visit https://dap.qub.ac.uk/portal/user/u_login.php (link to the QUB Direct Application Portal)
Funding Information
This funded studentship is open to UK candidates. The value of an award includes the cost of approved fees as well as maintenance support (stipend). As an indicator, the level for 2023/2024 is currently £18,622.
Candidates should hold the minimum of a strong upper second class (2.1) honours degree (completed or in the final stages of completion) in Civil engineering, mechanical engineering or electrical/electronic engineering.
Please note that this research project is one of five advertised projects at Queen’s which are in competition for funding. Only four of these will go ahead. The selection will be based on the 4 projects which receive the best application.