This fully funded PhD Project is open to Home fee applicants only
Northumbria University, Faculty of Science and Environment
Application Deadline: Monday 2 February 2026, 11:59pm
PhD start date: Thursday 1 October 2026
Project Reference: ReNU+26/SE/EPM/FAROKHI
About ReNU+
The EPSRC Centre for Doctoral Training (CDT) in Renewable Energy Northeast Universities Plus (ReNU+) is a collaborative doctoral training programme run by the Universities of Northumbria, Newcastle and Durham. In addition to undertaking an individual scientific research project at one of the three partner Universities, doctoral candidates will have the opportunity to engage with added value training opportunities, for example in business, innovation and internationalisation through a 4-year full time (or longer on part-time) training programme that has been designed to enhance the benefits of a cohort approach to doctoral training. The anticipated start date is 1st October 2026.
About the Project
Offshore wind turbines are scaling rapidly towards higher power ratings with increasingly long blades, but testing infrastructure has not kept pace. Modern blades can exceed facility capacity, creating a critical bottleneck in certifying next-generation turbines essential for UK Net Zero targets. This project addresses two fundamental challenges facing blade testing facilities: firstly, ultra-long blades exhibit extremely low natural frequencies where conventional sensors suffer from drift and noise, making modal identification unreliable; secondly, when blades exceed facility length they must be sectioned and tested separately, yet no validated framework exists to reconstruct full-blade dynamics from these partial tests.
As blade lengths continue to increase, this challenge is inevitable for all testing facilities worldwide. Facility expansion costs tens of millions with no future-proofing guarantee, making robust segmented testing methodology a fundamental requirement for sustainable blade certification. This project will develop a comprehensive framework that solves both challenges, establishing vision-based full-field displacement measurement as the enabling technology combined with advanced computational modelling for accurate dynamic reconstruction.
Research Approach:
The project is structured around three core components:
1. Vision-Based Full-Field Measurement: Develop and validate computer vision algorithms to extract precise displacements across entire blade surfaces during static and dynamic testing. This approach captures ultra-low frequency motion and provides spatially continuous measurements impossible to obtain with discrete sensors, overcoming the fundamental limitations of conventional sensors.
2. Nonlinear Reduced-Order Modelling and Property Identification: Create computationally efficient models for each tested blade segment, using full-field displacement data to solve inverse problems that identify distributed structural properties. The spatial richness of full-field measurements provides hundreds of constraint points, making this identification problem well-conditioned and robust compared to sparse sensor approaches.
3. Dynamic Reconstruction Framework: Develop methods to reconstruct full-blade dynamic characteristics by enforcing mechanical continuity at segment interfaces, enabling prediction of complete blade natural frequencies, mode shapes, and nonlinear responses from segmented tests. This provides validated tools for certification of blades that cannot be tested intact.
Methodology and Validation:
The research combines experimental and computational approaches. You will develop computer vision techniques for displacement extraction, formulate geometrically nonlinear beam models and finite element-based nonlinear reduced-order models for structural analysis, and implement reconstruction algorithms based on continuity enforcement. The methodology will be validated through controlled laboratory experiments on scaled prototype blades, where intact blades are first tested to establish ground truth, then sectioned and retested to verify reconstruction accuracy. Additional validation will use high-fidelity finite element simulations and potential collaboration with industrial testing facilities.
Impact and Significance:
This research removes a critical technology readiness barrier for next-generation offshore wind deployment. The framework enables testing facilities to certify advanced turbines without costly infrastructure expansion, with strong potential for commercialisation through technology licensing and testing protocol development for blade manufacturers and certification bodies.
Training and Skills Development:
You will develop expertise in computer vision and image processing for engineering applications, nonlinear structural dynamics and reduced-order modelling techniques, experimental mechanics combining laboratory testing with computational validation, and inverse problems and model identification methods. You will publish in high-impact journals, present at leading international conferences, and receive training in responsible innovation and technology transfer, preparing you for careers in renewable energy, structural engineering, or research sectors.
Candidate Profile:
We welcome applicants with backgrounds in mechanical/civil/aerospace engineering, applied mathematics, or related disciplines. Strong analytical skills and interest in computational modelling are valuable. Familiarity with programming (Python or MATLAB) is beneficial. Prior experience with computer vision or advanced structural dynamics is not required; enthusiasm, rigorous thinking, and motivation to tackle real-world engineering challenges are what matter most.
Academic Enquiries
This project is supervised by Dr Hamed Farokhi. For informal queries, please contact hamed.farokhi@northumbria.ac.uk. For all other enquiries relating to eligibility or application process please email Admissions (pgr.admissions@northumbria.ac.uk).
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. However, a 3 or 2:2 may be considered with relevant work experience, skills and/or expertise that is equivalent, please get in touch with the Institution Director, vincent.barrioz@northumbria.ac.uk for further info.
- Appropriate IELTS score, if required.
- Applicants cannot apply if currently engaged in Doctoral study at Northumbria or elsewhere. Home applicants can apply for a second PhD under a different research area but international students are advised to check with our admission team at pgr.admissions@northumbria.ac.uk
- Must be able to commit to campus-based full-time or part-time study.
- Home fee student
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.
How To Apply
For further details on how to apply see https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/
Please complete the PhD application form in full, include the advert reference (e.g. ReNU+26/…) and also:
- Upload degree certificates, transcripts and English qualifications (if applicable).
- Upload your CV under the ‘Experience section’. This is MANDATORY.
- In the personal statement section, select ‘no’ and type ‘no personal statement required’ in the box.
- You don’t need to upload a research proposal. Instead, upload the completed competency assessment form. When asked, select “Yes” for ‘Are you applying for a UKRI studentship?’ and then choose ‘EPSRC ReNU Plus’.
- Choose ‘Scholarship’ under source of funding.
Please note that up to six offers will be made for the ReNU+ CDT projects advertised by Northumbria University. This is a competitive process.
Deadline for applications: 2 February 2026
Start date of course: 1 October 2026
Funding Information
The studentship is available to Home only students and includes a full stipend at UKRI rates (for 2025/26 full-time study this is £20,780 per year) and full tuition fees. Studentships are also available for applicants who wish to study on a part-time basis (0.6 FTE - Stipend £12,468 per year and full tuition fees) in combination with work or personal responsibilities).
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.