Meet over 65 universities on 27 & 28 April GET YOUR FREE TICKET >
University of Sheffield Featured PhD Programmes
Anglia Ruskin University ARU Featured PhD Programmes

New smart data approaches for ageing pipe networks


Department of Civil and Structural Engineering

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
Dr ANA Schellart , Prof J Boxall , Prof S Tait , Dr Will Shepherd No more applications being accepted Funded PhD Project (Students Worldwide)
Sheffield United Kingdom Civil Engineering Environmental Engineering

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.

Supervision

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/).

Selection Criteria

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].


Funding Notes

Due to funding restrictions: 3.5-years tax-free stipend of £15,609 per year, UK resident tuition fees are funded; there is no funding to cover international tuition fees, hence international students would need to pay the difference between home and international tuition fees.


FindAPhD. Copyright 2005-2021
All rights reserved.