This PhD position is supervised by Prof. Konstantinos Gryllias, and co-supervised by Prof. Johan Meyers (Department of Mechanical Engineering). The position is jointly hosted by the LMSD – Mechatronic System Dynamics and the Turbulent Flow Simulation and Optimization (TFSO) research group. The research is part of the project “Wind-farm co-design in the North-Sea basin given climate and market uncertainty” led by Prof. Johan Meyers, Prof. Dirk Van Hertem, Prof. Konstantinos Gryllias, Prof. Erik Delarue and Prof. Nicole van Lipzig.
Project
BACKGROUND
Europe aims at massive investments in wind energy, with 320GW offshore developments. Much of these installations will be in the North-Sea basin, where the combination of excellent wind conditions and an abundance of sand banks provides favorable conditions for bottom fixed wind farms. At this scale of development, windfarms start to mutually interact through farm wakes that can extend for 50km and more. In fact, recent climate simulations have found significant uncertainty on North-Sea wind conditions induced by unknown offshore development scenarios, much larger than, e.g., the uncertainty introduced by climate change. At a time when the business model of wind energy is becoming subsidy free, this leads to large uncertainties in planning and development.
In the past, wind-farm planning and design happened in separate stages: first wind resource assessment, next wind farm siting (topology optimization, turbine selection). Afterwards, wind-farm operation aimed at maximizing energy yield and minimizing operational expenses, given an assured income through a subsidy system. However, this approach is becoming untenable: windfarm planning and future development scenarios strongly influence wind conditions, and income is not guaranteed by subsidies, but needs to be earned in a market with variable pricing. As a result of the latter, wind-farm operational decisions (control) become important for income as well, leading to a co-design problem in which planning and operation of wind-farms need to be jointly addressed.
PHD PROJECT DESCRIPTION
Research aims at the development of an end-to-end methodology linking operation loads with the lifetime consumption of various components (including bearings, gears, shafts blades, etc.). Moreover high fidelity physical models will be built and subsequently a prognostics methodology will be developed to link the models with damage and remaining lifetime estimation algorithms. In order to avoid high-dimensional load look up tables, a surrogate model will be further developed. A wide range of synthetic inflow conditions (veer, sheer, wake effects, turbulence levels) will be used to train the model, connecting operating conditions with lifetime consumption and remaining useful life. Finally, transfer learning will be investigated in order to be able to avoid retraining the surrogate model from scratch for a different type of wind turbine.
Profile
Candidates have a master degree in one of the following or related fields: mechanical engineering, electrical engineering, fluid mechanics, aerospace or mathematical engineering, numerical mathematics, , or computational physics. They should have a good background or interest in wind energy, condition monitoring, fluid mechanics, optimization, simulation, and programming (Mtlab, Python, C/C++, …). Proficiency in English is a requirement. The position adheres to the European policy of balanced ethnicity, age and gender. Persons of all origins and gender are encouraged to apply.
Offer
Timeline and remuneration: Immediate start is possible. The PhD position lasts for the duration of four years, and is carried out at the University of Leuven. The candidate also takes up a limited amount (approx. 10% of the time) of teaching activities. The remuneration is generous and is in line with the standard KU Leuven rates. It consists of a net monthly salary of about 2400 Euro (in case of dependent children or spouse, the amount can be somewhat higher); social security is also included. Following Belgian law, the salary is automatically adjusted for inflation based on the smoothed health index.
Interested?
To apply, use the KU Leuven online application platform (applications by email are not considered). Applications should ideally include:
a) an academic CV and a PDF of your diplomas and transcript of course work and grades
b) a statement of research interests and career goals, indicating why you are interested in this position
c) a sample of technical writing in English, e.g. a paper with you as main author, or your bachelor or master thesis
d) preferably at least one recommendation letter
d) a list of at least two additional references (different from recommendation letters): names, phone numbers, and email addresses
e) some proof of proficiency in English (e.g. language test results from TOEFL, IELTS, CAE, or CPE)
Please send your application as soon as possible.
Decision: as soon as a suitable candidate applies.
Starting Date: immediate start possible, preferably before October 1st 2025.
For more information please contact Prof. dr. ir. Konstantinos Gryllias, tel.: +32 16 32 30 00, mail: [email protected] or Prof. dr. Johan Meyers, tel.: +32 16 32 25 02, mail: [email protected].
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