Probabilistic Modeling of Fatigue Damage of Floating Wind Turbines

Titel: Probabilistic Modeling of Fatigue Damage of Floating Wind Turbines
  • Masterarbeit
Status: offen


The accurate fatigue design of floating wind turbines (FOWT) requires a large amount of simulations due to the complex interaction of the system (turbine, substructure and mooring lines) with its environment (wind, waves and current). In order to reduce the simulation effort, the state-of-the-art is to use conservative assumptions, which may lead to expensive designs.
A methodology to take into consideration all relevant environmental conditions is the so-called Monte Carlo method. With this method, design conditions are selected as they are expected to occur in the real environment. This is based on measurement data and allows a realistic, cost efficient design. The Monte Carlo method typically requires a large number of simulations. Current work at the SWE focusses on developing approaches which allow the use of a limited number of simulations to gather the required information as efficient as possible.


The work of this study will focus on one of two available options of this field: the investigation of sampling procedures which determine the samples used in the preprocessing of the Monte-Carlo method. Alternatively, focus may be put on machine learning algorithms used in the post-processing of the simulation results to obtain models which can accurately predict the load behavior of the turbine. The chosen approach will be investigated by in-depth simulation studies (based on the tools WITLIS and FAST and the requirements, advantages and shortcomings of the selected approach will be highlighted.


  • Literature study on fatigue assessment of floating wind turbines and the Monte-Carlo method
  • Theoretical investigation of available approaches in pre- and/or post-processing
  • Work into multibody wind turbine simulation tool FAST
  • Conception of work
  • Simulation studies to investigate chosen methodology
  • Conclusions and recommendations, presentation


The ideal candidate works independently, has a large interest in numerical modeling of multiphysical systems, simulation studies and data analysis. Advanced capabilities in Matlab and statistical approaches are an asset.
Duration: ca. 6 Months
Start: Fall 2017
Language: German or English