Doctoral Candidate – no. 3
Accurate hydrodynamic load models for wind turbine jackets based on numerical modelling and machine learning
Scope and Objectives
With ever increasing wind turbine sizes and a move towards locations further offshore and with deeper waters, a significant number of future wind turbines are going to be established on jacket type support structures. These multi-member structures are robust but can be costly. Accurate knowledge of the wave forces acting on these structures is necessary to reduce risks and develop more economic designs.
A major challenge is the complex geometry of joints and multiple members, leading to hydrodynamic shadowing and wake effects. The main objective of this project is to develop a better understanding of fatigue loads on jacket structures, based on extensive computational fluid dynamics simulations.
The secondary objective is to develop an efficient data-driven model that, after training, allows the prediction of wave forces for different jacket geometries without large computational expenses.
Expected Results
The fellow will develop novel load models for jacket structures.
A first result will be a computational fluid dynamics model for accurately predicting wave forces on such a complex, multi-membered structure, with particular focus on different possible joint geometries and important geometric features (e.g. boat landings and J-tubes). A second result will be a database of various structural details and their loadings, evaluated with the simulation model. Finally, ML techniques will be used to develop an efficient meta-model able to interpolate and predict loads for different geometries from non-linear wave kinematics, with an eye towards use with structural optimisation algorithms.
Planned secondments
Two secondment periods (3 months). Academic at TU DELFT (Pim van der Male, M13-15) for joint work on jacket design and screening relevant geometries. Industrial at MARIN (Tim Bunnik, M22-24) for joint work on efficient non-linear wave kinematics calculation.
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Doctoral Candidate
Name Candidate
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Supervisor
Prf. H. Bihs
- hans.bihs@ntnu.no
NTNU