4 PhD Studentships: Offshore Wind Energy Operations and Maintenance Research Cluster

University of Hull

To celebrate the University's research successes, the University of Hull is offering a full-time UK/EU PhD Scholarship or International Fees Bursary for candidates applying for each of the following projects.

Closing date: - Thursday 8th February 2018 

Studentships will start on 17th September 2018

Summary of Cluster

The UK is leading the world in the deployment of offshore wind energy and Hull is at the centre of the industry, with the largest companies in the sector based in the region (Siemens Gamesa Renewable Energy and Ørsted). The University of Hull is working with these companies and other leading organisations to support the development of the industry through Aura (aurawindenergy.com).

The rapid development of the offshore wind (OSW) industry in UK waters has opened up many challenges and opportunities for research and innovation.

The rapid development of the offshore wind (OSW) industry in UK waters has opened up many challenges and opportunities for research and innovation. This is particularly true of Operations and Maintenance (O&M) where novel approaches are required, and where many innovation opportunities exist. O&M accounts for 20-30% of the lifetime cost of electricity generated from OSW and is a priority within the Industrial Strategy Green Paper and for funding agencies. To exploit these opportunities for research funding, the University of Hull has recently agreed with the Offshore Renewable Energy Catapult (OREC) to establish a joint Offshore Wind Operations and Maintenance Centre of Excellence (O&M CE) with the purpose of supporting innovation to help reduce the lifetime cost of electricity and promote the UK supply chain. The Centre of Excellence will develop a portfolio of activities ranging from early stage research to nearer market development based around a series of roadmaps developed in collaboration with the OSW industry. Through discussion with OREC, six areas of focus have been identified: Human free O&M, Human factors in O&M, Data driven O&M decision making, Offshore logistics, planning and risk, Lifetime asset management and Whole life supply chain modelling. The recently awarded PhD cluster of 4 scholarships will conduct early stage research addressing these six priority areas, which will feed a pipeline of innovation that ensures the long term sustainability of the Centre of Excellence.

The successful candidate will be based in the appropriate academic school but will benefit from opportunities to collaborate with AURA (aurawindenergy.com), the O&M CE, and both of the Energy and Environment and the Logistics Institutes.

Summary of PhD Project 1

DREAM: Data-driven Reliability-centred Evolutionary Asset Manager

This PhD focuses on off-shore wind farms and develops techniques for prediction of failures and the evolution of optimal global plans of wind farm maintenance. The objectives of this PhD are: firstly, to develop techniques for predicting the Remaining Useful Life (RUL) of assets through condition monitoring and data analytics; secondly, to exploit prognoses of RUL in order to continually produce and update, through automated reliability/cost analysis and bio-inspired optimisation, an evolving optimal global plan of wind farm maintenance. The PhD builds on our strong track record on data analytics, reliability engineering and bio-inspired AI and will be carried out in collaboration with EDF Energy R&D UK.

Applicants should have a BSc, BEng or MSc in Computer Science and/or Electrical/Mechanical Engineering with a Software Engineering background

For further details, please contact Prof. Yiannis Papadopoulos (Y.I.Papadopoulos@hull.ac.uk, https://yipapadopoulos.wixsite.com/yiap).

Summary of PhD Project 2

Human Factors in Operations and Maintenance:

There are a number of studies that provide insight into the effects of work in Offshore Wind (OSW) on the human technician: transit, transfer, climbing, fatigue, shift-work, etc. There are also technological innovations to alleviate these, such as Service Operation Vessels, climbing assists, transfer vessels types, autonomous vehicles etc. This PhD will review the cumulative and combined effects of OSW work on humans, possible mitigations of these effects through innovations (and future innovations that are expected), the range of tasks and feasible maintenance/inspection policies, to develop an integrated system model of the effect on the human and thus the human-factors effect on maintenance/inspection, and the mitigation of technological solutions. The aim of this would be to build into a decision tool to help determine the most appropriate ways to manage maintenance and inspection, taking account of human-factors.

Applicants should have an appropriate first degree and an understanding of psychological ideas and humans within engineering systems, and of decision-support.

For further details, please contact Prof Terry Williams (terry.williams@hull.ac.uk)/Dr Fiona Earle (f.earle@hull.ac.uk).

Summary of PhD Project 3

Mission Planning for Autonomous Vehicles in O&M

Minimizing the need for human intervention in offshore maintenance is a key route to maximizing the potential, and minimizing the cost, for offshore low-carbon generation. This PhD will investigate best-suited optimization methodology to develop decision support system for mission planning of autonomous vehicles in operations and maintenance for offshore wind. The proposed system will utilize sensor data to facilitate integrated maintenance supply chain planning i.e. the number of parts in the warehouse, logistics, number of drones and its planning and scheduling in a timely and cost-effective way. 

Applicants should have a Master degree in Operations Research, Computer Science, Industrial Engineering or related area

For further details, please contact Prof Amar Ramudhin (A.Ramudhin@hull.ac.uk)/ Prof Nishikant Mishra (Nishikant.Mishra@hull.ac.uk).

Summary of PhD Project 4

Autonomous Prediction and Scheduling of Operations and Maintenance for Offshore Wind Farms

This PhD will focus on the use of data analytics and prediction for OSW O&M. Initially the PhD will apply domain-general data analytics - such as deep learning – and identify the family of algorithms best suited to failure prediction and maintenance scheduling in OSW O&M. Subsequently, it will investigate domain-tailored approaches combining disparate datasets, including real-time images and videos, met-ocean forecasts and turbine data. The PhD project will build upon and collaborate closely with the existing DSTL funded Hazardous Environment Autonomous Resupply (HEAR) project, which is developing a software framework for predicting, monitoring and route planning resupply using autonomous vehicles. The intended outcomes of the research will be utilised to help drive down the cost of offshore wind energy through operational and maintenance cost savings identified using a version of the HEAR framework suitable for OSW O&M. Our research will make use of the University’s new High-Performance Computing facility Viper, which is equipped with state of the art equipment for parallel processing, high-memory computation and GPUs, and is ranked amongst the top 7 in the North of England.

Applicants should have excellent programming skills and at least a 2:1 degree in Computer Science or a related discipline. Previous experience of one or more of the following areas is highly desirable: machine/deep learning, high performance computing or data analytics.

For further details, please contact Dr James Walker (J.A.Walker@hull.ac.uk).

Applicants should have at least a 2.1 undergraduate degree or Master’s degree in the disciplines noted above, together with relevant research experience.

To apply for these Scholarships please click on the Apply button below.


Full-time UK/EU PhD Scholarships will include fees at the ‘home/EU' student rate and maintenance (£14,553 in 2017/18) for three years, depending on satisfactory progress.

Full-time International Fee PhD Studentships will include full fees at the International student rate for three years, dependent on satisfactory progress.

Successful candidates will also be providing with up to £3,000 per year for equipment and for dissemination and industrial engagement activities.

PhD students at the University of Hull follow modules for research and transferable skills development and gain a Masters level Certificate, or Diploma, in Research Training, in addition to their research degree.

Successful applicants will be informed of the award as soon as possible and by 2nd April 2018 at the latest.

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