About the Project
Closing Date for Applications: 20th April 2021
Interview date: 11th May 2021
Preferred start date PhD: 27th September 2021 (Studentship duration 3.5 years)
Will you help us to unlock the potential of new data from in-pipe robots to transform management of ageing pipe infrastructure? By combining the data from these new inspection systems with prediction of system performance, we believe it's possible to provide sufficient warning to water companies of localized failure.
Drinking water and wastewater pipe networks are not regularly inspected due to the technical challenges caused by inaccessible environments. Recent developments in autonomous robotics means that pervasive in-pipe inspection could become a reality. We need to match this step change in inspection capabilities through improved prediction of how defects in pipe networks develop with time. If this can be achieved, then the new pervasive inspection data sets can be linked with in-pipe deterioration models and network performance models. This enables water companies to predict localized failures and so adopt “just in time” repair approaches, eliminating the severe economic and environmental damage caused by failing underground pipes.
This PhD project is part of ‘Pipebots’, a collaborative project between 4 UK Universities and many industrial partners. In this PhD you will identify the characteristics of key pipe defects, how they deteriorate and cause pipe failure and then use this understanding to simulate the performance of large pipe networks as localized failures occur.
You will benefit from access to world leading experimental and computational facilities as well as regular close contact with industry and end user partners. Our department is committed to promoting diversity and inclusivity. We are committed to exploring flexible working opportunities which benefit the individual and University.
The project will be supervised by a combination of drainage and water supply infrastructure experts, with Dr Alma Schellart as 1st supervisor, and Prof Joby Boxall, Prof Simon Tait and Dr Will Shepherd as co-supervisors. The research will be based at the University of Sheffield, with data derived from activity at ICAIR (https://icair.ac.uk/) and potentially from collaborating water companies within Pipebots (https://pipebots.ac.uk/).
Have a good honours degree (2:1, or equivalent experience) in Engineering, Environmental Science, Computing Science, Mathematical and Physical Sciences, or a related subject.
How to apply
Interested candidates should email a covering letter and their Curriculum Vitae to Lindsay Hopcroft, [Email Address Removed].
For information and informal enquiries please contact: Dr. Alma Schellart, [Email Address Removed].
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