Supervised by Rasa Remenyte-Prescott (Faculty of Engineering)
Bridges are vital to the UK’s economic and societal infrastructure, and railway bridges are critical infrastructure for Network Rail, forming a vital part of the 30,000 bridges, tunnels and viaducts which they manage across Britain. Increased traffic demand, limited maintenance, and ageing structural systems have pushed many bridges beyond their original design capacities. In addition, climate change is altering environmental exposure conditions, particularly temperature and relative humidity, which further accelerate the deterioration of bridges. Physics-based formulations with probabilistic models are necessary to capture uncertainty and environmental variability in bridge component degradation modelling. The processes of atmospheric and pitting corrosion, chloride‑induced corrosion, thermal cycling and fatigue, protective painting and coating degradation, to name a few, are most affected by increased rainfall and humidity, extreme heat conditions and air pollution, especially due to increasing effects of climate change.
It is envisaged that the approach will incorporate climate‑dependent parameters and their influence on the deterioration of a bridge, and it will allow a clear integration of regional/national climate projections. Climate projections will be taken from the UK Climate Projections (UKCP18) based on multiple Representative Concentration Pathways (RCPs) and used along the probabilistic models of deterioration to capture uncertainty and environmental variability. The proposed approach will consider interdependencies, providing a realistic system‑level variability in condition‑state evolution, ranging from baseline ageing to pessimistic climate change effects, which would indicate acceleration of deterioration.
Aim: To include climate change effects into railway asset degradation and asset management modelling
Summary
Open to UK/EU/overseas students. Look for funding sources at www.nottingham.ac.uk/pgstudy/funding/postgraduate-funding.aspx
Entry Requirements:
Starting October 2027, we require an enthusiastic graduate with a 1st class degree in engineering, maths or a relevant discipline, preferably at Masters level (in exceptional circumstances a 2:1 degree can be considered).
For any enquiries about the project please email Rasa Remenyte-Prescott (r.remenyte-prescott@nottingham.ac.uk)
This position is open until filled. Early application is strongly encouraged.
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PhD project: Railway Asset Degradation and Management Modelling for Climate Change in Nottingham employer: University Of Nottingham
The University of Nottingham Ningbo China (UNNC) is an exceptional employer for those passionate about academia, offering a vibrant work culture that fosters innovation and collaboration. With a strong emphasis on professional development, faculty members are encouraged to engage in cutting-edge research while enjoying the benefits of a supportive environment in a culturally rich location. This role not only provides opportunities for personal growth but also allows you to make a significant impact in the field of Applied Mathematics and Statistics.
