Data-driven and physics-informed wind prediction and turbine control in offshore wind farms - ENG 1294 at University of Nottingham on FindAPhD.com

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities

Dr X Mao Applications accepted all year round Competition Funded PhD Project (Students Worldwide)

About the Project

We are seeking applications from highly motivated, enthusiastic candidates for a PhD position to start as early as possible. This 3-year PhD studentship will cover Home/EU tuition fees and an EPSRC standard tax-free stipend. Both Home/EU and Overseas applicants are welcome. The successful applicant would be situated in the Faculty of Engineering at the University of Nottingham (UK).

The project aims at reducing the cost of offshore wind power by applying the preview-based control techniques to offshore wind farms. A model of wind evolution in offshore wind farms will be established through a data-based and physics-informed approach. The model will be then tested in the model predictive control of wind turbines. The project requires strong background in mathematical modelling and numerical simulations of fluid flow.

The project involves collaborations with several academic partners both nationally and internationally. It will provide the student an attractive training environment via affiliates within the research institutes and doctor training centers hosted by the Engineering Faculty at the University of Nottingham. The collaborative and multidisciplinary nature of the project will improve the employability of the candidate and enhance career prospects in both Academia and in Industry.

Funding Notes

The ideal candidate will hold (or expect to hold) a master degree in mathematics, mechanics, mechanical engineering, aeronautical engineering or equivalent. Excellent written and oral communication skills are required, as well as the ability to work independently and in collaboration with other group members.

Further Information:

Prospective candidates should contact Dr. Xuerui Mao with a Cover Letter, CV and 2 letters of recommendations

Email: [Email Address Removed]

When applying for this studentship, please include the reference number (beginning ENG and supervisors name) within the personal statement section of the application. .

Where will I study?

University of Nottingham

Results from the 2021 Research Excellence Framework (REF2021) reaffirm it as among the best universities in the UK for the strength of our research.

Data-driven and physics-informed wind prediction and turbine control in offshore wind farms - ENG 1294

University of Nottingham Faculty of Engineering

This project is no longer listed on FindAPhD.com and may not be available.

About the Project

Funding Notes

Where will I study?

University of Nottingham

Select your nearest city

Do you want hassle-free information and advice?