Postgraduate research opportunities

Development of low cost, modular sensors to de-risk suction caisson foundations for offshore wind

This fully-funded PhD offers an exciting opportunity to undertake research on the development of a low cost, modular sensor platform for intelligent offshore wind foundation monitoring.

Number of places

1

Funding

Home fee, Stipend

Opens

18 January 2021

Deadline

30 June 2021

Eligibility

The successful candidate will be based primarily at the Department of Civil and Environmental Engineering, University of Strathclyde, and will be jointly supervised by Dr Stephen Suryasentana and Dr Marcus Perry. Furthermore, the candidate will collaborate closely with industry partners such as Ørsted. The unique combination of academic and industry contacts will be highly beneficial to the candidate’s learning and career development, and future employability. There will also be opportunities for local/international collaborations and to spend a period with collaborators at University of Oxford.

 This project will commence in 4 Oct 2021. The successful UK candidate will receive a fully-funded scholarship for 3.5 years, which covers all university tuition fees and an annual stipend that is in line with the UKRI guidelines i.e. £15,667 (tax-free) for the first year and at least that amount (inflation adjusted) for the subsequent years.

 We would expect the candidate to have good knowledge of sensor development, sensor fusion and sensor calibration, as well as coding skills in Python. Prior experience with the Robot Operating System would be an advantage.

 he successful candidate should also have (or expect to achieve) a distinction at Master’s level, or a First Class or Upper Second Class Honours degree (or the equivalent) in an Engineering or Physical Sciences subject, in particular Electronic Engineering, Mechanical Engineering or Physics.

UKRI Studentship Eligibility

The eligibility criteria for UKRI funding has changed for studentships commencing in the 2021/22 academic year. Now, all home and international students are eligible to apply for UKRI funding which will cover the full stipend and tuition fees at the home rate (not the international rate). Under the new criteria, UKRI have stipulated a maximum percentage of international students that can be recruited each year against individual training grants. This will be managed at the institutional level for all EPSRC DTP and ICASE grants. For EPSRC CDT grants, this will be managed by the individual CDT administrative/management team. For ESRC and AHRC studentships the final funding decision will be made by the respective grant holder.

 

To be classed as a home student, applicants must meet the following criteria:

  • 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.

 

The residency requirements are based on the Education (Fees and Awards) (England) Regulations 2007 and subsequent amendments. Normally to be eligible for a full award a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship (with some further constraint regarding residence for education).

If a student does not meet the criteria above, they will be classed as an international student. The international portion of the tuition fee cannot be funded by the UKRI grant and must be covered from other sources. International students are permitted to self-fund the difference between the home and international fee rates.

Project Details

This fully-funded PhD offers an exciting opportunity to undertake research on the development of a low cost, modular sensor platform for intelligent offshore wind foundation monitoring. This project is supported by a multi-disciplinary team of academics from University of Strathclyde and there will be opportunities for industry-linked collaboration with a leading offshore wind developer, Ørsted.


The goal of this project is to develop a flexible, low cost, modular platform for developing custom sensors for offshore wind foundations monitoring. The modular platform allows for rapid development for bespoke sensors to embed intelligence in offshore wind foundations.

 One of the planned applications of this platform is to develop a novel sensor to de-risk the installation process for suction caisson foundations. Suction caisson foundations are increasingly used for deep water offshore wind farms (e.g. as anchors for floating wind farms or jackets in transitional waters). However, there is still much uncertainty about the installation process of these caisson foundations. To reduce the risk and uncertainty associated with the installation process, new bespoke sensors are required to capture more comprehensive and accurate information of the process. These sensor information, coupled with machine learning powered ‘autopilot’ software, will provide the caisson foundation with the intelligence and autonomy to self-install safely.

 The PhD student will combine micro-electromechanical systems (MEMS) and various time-of-flight sensor techniques (e.g. ultrasonic or laser sensors) with the open-source Robot Operating System (ROS) and machine learning algorithms to produce intelligent sensing systems that provide caisson foundations with both the hardware and software to detect potential issues (e.g. soil plug lift) in real-time, and to constantly learn from data in order to make the installation process increasingly safer with more experience.

 This project is suitable for a candidate who is interested in robotics, sensor development and machine learning.

 

 

Funding Details

Fully-funded scholarship for UK students that covers all university tuition fees and an annual tax-free stipend (in line with UKRI guidelines e.g. £15,667 for year 2021/2022) for 3.5 years.

How to apply

Please apply at https://www.strath.ac.uk/courses/research/civilenvironmentalengineering/#apply

30 June 2021. Your application should include the following:

  •  An up to date curriculum vitae (CV)
  • Evidence of a distinction at Master’s level, or a first class or upper second class honours degree (or the equivalent) in subjects relevant to Electronic Engineering, Mechanical Engineering or Physics.
  • Two references from academic referees

 It is recommended to apply early as interviews will be carried out on a rolling basis until the position is filled.