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Details of Grant 

EPSRC Reference: EP/P012493/1
Title: Listening to Infrastructure
Principal Investigator: Smith, Dr A
Other Investigators:
Researcher Co-Investigators:
Project Partners:
CH2M HILL Costain Queen's University Canada
Severn Trent Water Ltd
Department: Civil and Building Engineering
Organisation: Loughborough University
Scheme: EPSRC Fellowship
Starts: 01 April 2017 Ends: 31 March 2020 Value (£): 284,824
EPSRC Research Topic Classifications:
Ground Engineering Structural Engineering
EPSRC Industrial Sector Classifications:
Construction
Related Grants:
Panel History:
Panel DatePanel NameOutcome
13 Feb 2017 Eng Fellowship Interviews Feb 2017 Announced
01 Dec 2016 Engineering Prioritisation Panel Meeting 1 and 2 December 2016 Announced
Summary on Grant Application Form
Infrastructure is vital for society - for economic growth and quality of life. Existing infrastructure is rapidly deteriorating, the rate of which will accelerate with increasing pressures from climate change and population growth, and the condition of the large majority of assets is unknown. Stewardship of infrastructure to ensure it continuously performs its function will be a colossal challenge for asset owners and operators. The performance of new infrastructure assets must be monitored throughout their life-cycle because they are being designed and constructed to withstand largely unknown future conditions. The UK must be better prepared to face these grand challenges by exploiting technology to increase understanding of asset deterioration and improve decision making and asset management.

This research is central to EPSRC's priority area of Engineering for Sustainability and Resilience. The goal is to transform geotechnical asset management by developing new, low-cost, autonomous sensing technologies for condition appraisal and real-time communication of deterioration. This new approach will sense Acoustic Emission (AE) generated by geotechnical assets. AE is generated in soil bodies and soil-structure systems (SB&SSS) by deformation, and has been proven to propagate many tens - even hundreds - of metres along structural elements. This presents an exciting opportunity that has never been exploited before: to develop autonomous sensing systems that can be distributed across structural elements (e.g. buried pipes, pile foundations, retaining walls, tunnel linings, rail track) to listen to AE - analogous to a stethoscope being used to listen to a patient's heartbeat - and provide information on the health of infrastructure in real-time. The idea to use AE sensing to monitor geotechnical assets in this way is novel - it is expected to lead to a disruptive advance in monitoring capability and revolutionise infrastructure stewardship.

AE has the potential to increase our understanding of how assets are deteriorating, which could lead to improved design approaches, and to extract more information about asset condition than existing techniques: not only deformation behaviour, but also, for example, changes in stress states, transitions from pre- to post-peak shear strength, and using correlation techniques it will be possible to locate the source of AE to target maintenance and remediation activities. AE sensing will also provide real-time warnings which will enable safety-critical decisions to be made to reduce damages and lives lost as a result of geotechnical asset failures.

The number of asset monitoring locations required per unit length to achieve sufficient spatial resolution will be less than other monitoring techniques, and significantly lower cost. Piezoelectric transducers, which sense the AE, are now being developed at costs as low as a few tens of pence per sensor - this recent technological advance makes this research timely. AE sensors could be installed during construction to monitor condition throughout the life-cycle of new-build assets (e.g. HS2), and retrofitted to existing, ageing assets.

This will be the most fundamental and ambitious investigation into the understanding of AE generated by SB&SSS yet attempted. The findings will mark a major leap forward in scientific understanding and our ability to exploit AE in novel asset health monitoring systems. The fellowship aims to develop robust diagnostic frameworks and analytics to interpret AE generated by geotechnical assets. This will be achieved using a powerful set of complementary element and large-scale experiments. The outcomes will be demonstrated to end-users and plans will be developed with collaborators for: full-scale field testing with in-service assets to demonstrate performance and benefits in intended applications and environments; and implementation in commercial products that could have significant societal and economic impact.
Key Findings
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Potential use in non-academic contexts
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Organisation Website: http://www.lboro.ac.uk