Structural Health Monitoring for Maintaining Aging Civil Infrastructure

EPSRC DTP CASE studentship in Engineering with MISTRAS Group Ltd

Lead supervisor Dr Matthew Pearson

Duration 4 years full time 7 years part time

Start date October 2023

Project Summary

Maintaining aging civil infrastructure poses a significant challenge across the world. As structures age, their degradation increases requiring more complex and frequent maintenance to ensure structure integrity. This combined with the requirement to extend operational life and prolong the operational capabilities of infrastructure all while ensuring uptime poses significant challenges in infrastructure management. Therefore, there is a demand for intelligent monitoring of the structures to direct, schedule and predict maintenance programs. MISTRAS Group Ltd. are a world-leader in asset management and monitors numerous large assets and structures throughout the world using Acoustic Emission (AE).

 AE is the spontaneous release of a stress wave that propagates through a structure when damage occurs. By mounting sensors on a structure, the source of the AE can be located and monitored for its activity. In practice however this presents a real challenge due to AE originating from other acoustic sources such as rubbing from movement within the structure, traffic noise and the undertaking of maintenance operations. Although methods exist that work to differentiate acoustic source mechanisms, these have short comings and often require the features of the different AE sources to be known. Furthermore, the methodology that is used has not changed for over thirty years. Therefore, there is a requirement to develop an improved signal acquisition and data analysis approach to better acquire AE data, analyse the data and correlate the AE signals with the extent of the developing damage.

 This project will require the student to:

·        Research and gain understanding of the AE acquisition, signal processing and state-of-the-art data processing approaches

·        Investigate artificial intelligence (AI) methods for signal decomposition

·        Explore statistical methods for determining the occurrence of AE transients, working both in the time and frequency domains

·        Review approaches for applying developed methodologies in state-of-the-art edge processing technologies

·        Plan and conduct laboratory investigations to gather data under realistic conditions

·        Apply methodologies developed in the laboratory to data gathered from real assets

·        Explore methods, such as acoustic tomography, for correlating and quantifying the extent of the monitored damage

Research Environment

The student will benefit from a supportive PhD supervisory team, each with their own areas of expertise that will allow the student to develop in a wide range of areas. The student will become part of an already existing team working in Structural Health Monitoring (SHM), that meets on a fortnightly basis, providing the student with experience of working in a research environment with multiple strands of work. In addition, to these meetings the student will attend the monthly research group PhD meetings.

 MISTRAS have two primary offices in the UK, Bridgend and Cambridge. The industrial supervisor has committed to providing opportunities to attend both sites (including cost for travel), access to field trial data and take part in site investigations. MISTRAS are expecting the student to spend a minimum of three months in the Bridgend office.

Learning and Development Opportunities

The student will be provided with training in a range of transferable skills including computational modelling, experimental techniques, science communication and report writing. These skills will help to ensure the student is provided with a suitable skill set to ensure excellent career prospects beyond the scope of the PhD. Furthermore, the student will become an expert user of the MATLAB/Python software suite, and an expert within the field of AE, giving them scope to specialise in exciting areas of research in the future.

 Throughout the project the student will be given opportunity to begin to develop as an independent researcher, for example the student will be encouraged to set the direction of their research, apply to attend international conferences, write journal publications and visit other research groups.

The student will also have opportunity to obtain industrial qualifications in Health and Safety and AE monitoring plus attend and support field investigations in conjunction with MISTRAS.

Academic Criteria

Candidates should hold or expect to gain a first-class degree or a good 2.1 (or their equivalent) or MSc degree in Engineering or a related subject with a keen interest in one or more of the following areas:

·        Structural health monitoring

·        Experimental testing and instrumentation

·        Computational modelling

·        Signal analysis and processing

Desirable skills include:

·        Good communication skills

·        Demonstration of ability to organise own work

·        Industrial experience

·        Programming ability in MATLAB and/or Python

Applicants whose first language is not English will be required to demonstrate proficiency in the English language (IELTS 6.5 or equivalent)

Contact for further information

Please contact Dr Matthew Pearson (pearsonmr@cardiff.ac.uk, Tel; 02920876120), Dr John McCrory (mccroryjp@cardiff.ac.uk, Tel: 029 2087 5924 or Prof Rhys Pullin (pullinr@cardiff.ac.uk Tel: 029 2087 9374) to informally discuss this opportunity

How to apply

Applicants should submit an application for postgraduate study via the Cardiff University webpages (http://www.cardiff.ac.uk/study/postgraduate/research/programmes/programme/engineering ) including;

·        an upload of your CV

·        a personal statement/covering letter

·        two references (applicants are recommended to have a third academic referee, if the two academic referees are within the same department/school)

·        Current academic transcripts

Applicants should select Doctor of Philosophy (Engineering), with a start date of July or October 2023.

In the research proposal section of your application, please specify the project title and supervisors of this project and copy the project description in the text box provided. In the funding section, please select "I will be applying for a scholarship / grant" and specify that you are applying for advertised funding, reference MP CASE 23

Deadline for applications

31^st May 2023. We may however close this opportunity earlier if a suitable candidate is identified.