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  Advanced Leading Edge Protection System based on Machine Learning and AI (RDFC23/EE/MCE/XU)


   Faculty of Engineering and Environment

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  Prof Ben Xu  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

This full-time studentship is  available to Home and International students. To be classed as a Home student, candidates must meet the criteria set out in the funding notes below.

A key priority for the UK economy is the development of high-value and specialist manufacturing, especially in renewable energy, which is a strategic priority for the UK’s commitment to Net Zero, underpinned by research that is inherently multidisciplinary and disruptive. One of the critical structures in ORE system is the wind blade, where the erosion of wind blade, one of the key challenges facing the sector, often costs $2-3 million dollars per turbine or more. Recent studies have shown diverse approaches in mechanisms and strategies of preventing surface erosion. However, there is still more to be done in terms of enabling a practical strategy by integrating knowledge from materials science, aerodynamics, meteorology and mechanics. Effective computational models to predict the development of Leading-Edge Erosion (LEE) with machine learning and AI are highly desired by the ORE sector.

The proposed research will potentially create a novel wind blade strategy aligning with the UK and global needs. The successful delivery of the study of a reliable wind blade technology for high-performance enabled by machine learning and AI, will offer a promising value to develop a novel future wind turbine technology, to achieve higher operating efficiency and sustainability and further promote the impact of the UK as research leading, innovative nation.

This project aims to design and develop a blade technology with machine learning and AI, to achieve higher operating efficiency and sustainability. Particular objectives are:

1.    To scope and survey the machine learning and AI for wind blade design and development;

2.    To experimentally design and assess the wind blade design;

3.    To develop a model to understand the working principle of the novel wind blade design and maximise the life time of blade;

4.    To assess the overall system efficiency by considering the life cycle analysis.

Key skills used in research work packages are: 

1. Materials and structure fundamentals for blade design and Leading Edge Protection; 

2. Materials characterisation skills: SEM, AFM, Electrical testing Probe station, Profilometer, Ellipsometry, fluorescence microscopy, Laser confocal scanning microscopy  

3. Micro-engineering: Lithography, soft-lithography, RIE, CVDs, printing, packaging, integration, SAM, anodization/oxidation,  

4. Computational skills incl. Machine learning and AI related software engineering, numerical/FEA simulation (Matlab, ABAQUS and/or Ansys, etc). 

Academic Enquiries

This project is supervised by Prof. Ben Xu, Dr Yingke Chen and industrial supervisors. For informal queries, please contact [Email Address Removed] .. For all other enquiries relating to eligibility or application process please email [Email Address Removed]

Eligibility Requirements:

•       Academic excellence i.e. 2:1 (or equivalent GPA from non-UK universities with preference for 1st class honours); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.

•       Appropriate IELTS score, if required.

•       Applicants cannot apply if they are already a PhD holder or if currently engaged in Doctoral study at Northumbria or elsewhere.

 To be classed as a Home student, candidates must:

•       Be a UK National (meeting residency requirements), or

•       have settled status, or

•       have pre-settled status (meeting residency requirements), or

•       have indefinite leave to remain or enter.

If a candidate does not meet the criteria above, they would be classed as an International student.  

 Applicants will need to be in the UK and fully enrolled before stipend payments can commence and be aware of the following additional costs that may be incurred, as these are not covered by the studentship.

·        Immigration Health Surcharge https://www.gov.uk/healthcare-immigration-application

·        If you need to apply for a Student Visa to enter the UK, please refer to https://www.gov.uk/student-visa. It is important that you read this information carefully as it is your responsibility to ensure that you hold the correct funds required for your visa application, otherwise your visa may be refused.

·        Costs associated with English Language requirements which may be required for students not having completed a first degree in English, will not be paid by the University.

How to Apply

Visit https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/   

 In your application, please include a research proposal of approximately 1,000 words and the advert reference (e.g. RDFC23/…).

Deadline for applications: 13 March 2024

Start date of course: Preferred 1 May 2024, with potential for flexibility. Please contact Prof. Xu before applying to discuss when you would be available to start.

Northumbria University is committed to creating an inclusive culture where we take pride in, and value, the diversity of our postgraduate research students. We encourage and welcome applications from all members of the community. The University holds a bronze Athena Swan award in recognition of our commitment to advancing gender equality, we are a Disability Confident Leader, a member of the Race Equality Charter and are participating in the Stonewall Diversity Champion Programme. We also hold the HR Excellence in Research award for implementing the concordat supporting the career Development of Researchers and are members of the Euraxess initiative to deliver information and support to professional researchers.

Computer Science (8) Engineering (12)

Funding Notes

Home and International students (inc. EU) are welcome to apply. The studentship is available to Home and International (including EU) students and includes a full stipend at UKRI rates (for 2023/24 full-time study this is £18,622 per year) and full tuition fees.
Please also see further advice on additional costs that may apply to international applicants.

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