Multi-scale Dynamic Wake Modeling and Prediction of Floating Offshore Wind Turbines via Physics-Informed Neural Networks and Fourier Neural Operators
Multi-scale dynamic wake modeling and prediction are essential for the real-time control and optimization of floating offshore wind turbines (FOWTs). In this study, wakes of FOWTs under coupled surge and pitch motions across a range of Strouhal numbers (St), which can induce wake meandering, are modeled via two novel deep-learning frameworks: physics-informed neural networks (PINNs) and Fourier neural operators (FNOs). The high-fidelity dataset is obtained from large-eddy simulations with the actuator line model (LES-AL). The results demonstrate that the dominant large-scale dynamic structures, such as meandering, can be well modeled by both frameworks; however, FNOs exhibit significant a...
| Authors | Guodan Dong, Jianhua Qin, Chang Xu |
|---|---|
| Primary category | physics.flu-dyn |
| Published | 27 April 2026 |
| Last updated at source | 20 May 2026 |
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