Linking historic, contemporary, and future inspection data for improved asset monitoring

This fully-funded project will see you solving issues related to how machines and infrastructure are inspected to find degradation and damage. This is a vital part of the operation of any engineered system and the field of non-destructive inspection is of importance across all industries. The project is sponsored by the Nuclear Decommissioning Authority (NDA), the organisation charged with decommissioning and cleaning up the UK’s nuclear sites at the end of their life.

The NDA is unique in possessing assets that will require monitoring for hundreds of years, presenting difficulties in comparing inspection data when inspection systems are replaced. In this project you will develop techniques for quantitatively comparing data from historic, contemporary and future sources to solve this problem.

Optical based inspection with a range of camera systems will be performed using a mock-up of a typical NDA asset. Data will be captured such that it is comparable to historic and current systems at NDA sites. A common concern for most long-term monitoring situations is to detect motion, either due to relative motion of equipment or due to defects such as cracks growing through welds or concrete. Digital image correlation will be used to quantify such movement between images from different systems – a current research challenge. Techniques for estimating measurement uncertainties will also be developed to help improve objective decision making.

The outcome will be a methodology for maximising the benefit of historic, contemporary and future inspection data, reducing the cost of monitoring assets on the NDA estate. During the project you will develop into a highly skilled expert in the inspection of decommissioning assets, helping you to drive change out into industry.

You will be part of a research group at the University of Liverpool containing PhD students working on projects in the nuclear, aerospace and bioengineering sectors. This will give you exposure to how different sectors approach inspection and data science. The studentship will be run as part of the SATURN Centre for Doctoral Training and thus you will get to interact with a large cohort of students who are studying nuclear science and engineering at six leading UK universities.

SATURN_Nuclear_CDT

 

Applicant Eligibility

Candidates will have, or be due to obtain, a Master’s Degree or equivalent from a reputable University in an appropriate field of Engineering. Exceptional candidates with a First Class Bachelor’s Degree in an appropriate field will also be considered.

 

Application Process

Candidates wishing to apply should complete the University of Liverpool application form [How to apply for a PhD – University of Liverpool] applying for a PhD in **Degree Title** and uploading: Degree Certificates & Transcripts, an up-to-date CV, a covering letter/personal statement and two academic references.

We want all of our staff and Students to feel that Liverpool is an inclusive and welcoming environment that actively celebrates and encourages diversity. We are committed to working with students to make all reasonable project adaptations including supporting those with caring responsibilities, disabilities or other personal circumstances. For example, If you have a disability you may be entitled to a Disabled Students Allowance on top of your studentship to help cover the costs of any additional support that a person studying for a doctorate might need as a result.

We believe everyone deserves an excellent education and encourage students from all backgrounds and personal circumstances to apply.

Candidates wishing to discuss the research project should contact the primary supervisor [email protected] those wishing to discuss the application process should discuss this with the School PGR Office [[email protected]] or specific question on the SATURN CDT framework for PhD to [email protected]