Bachelor/Master Thesis: Faster MBS Simulations of Wind Turbines: Developing Surrogate Models for Journal Bearings

The Institute for Machine Elements and Systems Engineering (iMSE) together with the Chair for Wind Power Drives researches the behaviour of drive systems in modern multi-megawatt wind turbines. The research objectives are to increase the availability, robustness and energy efficiency of wind turbines and to reduce the energy costs. For this experiment’s with software simulation tools and modern test benches are combined.

In order to reduce the electricity generation costs of modern wind turbines, an increase in the power density of the planetary gears in wind turbines is desired. The use of compact planetary gears with journal bearings is of interest. Therefore, research is being carried out at CWD on the journal bearing of planetary gears in wind turbine gearboxes.

This thesis offers an exciting opportunity to contribute to the advancement of wind energy technology. The project involves developing and validating innovative bearing surrogate models using machine learning to improve the efficiency of multibody simulations (MBS) for wind turbines. The student will collaborate closely with industry partners and researchers to collect data, develop modelling algorithms, and validate the surrogate models under
real operational conditions.

Tasks:

• Research of the state of the art
• Familiarisation with FE, MBS and EHD modelling
• Develop Regressions and Machine Learning based bearing surrogate models
• Validate the surrogate models through comparison with detailed simulations and experimental data
• Demonstrate the applicability of the surrogate models in comprehensive MBS simulations for wind turbine systems

Your Profile:

• Analytical thinking and problem-solving skills
• Motivated and structured way of working
• Interest in wind energy, machine learning and simulations
• Previous knowledge in the field of simulation and programming (e.g. MATLAB/PYTHON) is desirable, but not mandatory

What We Offer:

• Working towards a climate-neutral future
• Intensive support during the final thesis
• Option to participate in a scientific publication
• Direct start and home-office possible
• Flexible working hours

Interested but still undecided?
We would be happy to discuss any questions in person

We look forward to your application by email:

Math Lucassen, M. Sc.
Institute for Machine Elements and Systems Engineering

Schinkelstraße 10, 52062 Aachen
math.lucassen@imse.rwth-aachen.de