16 citations as recorded by crossref.

1. Neural Network-Enhanced Integrators for Simulating Ordinary Differential Equations A. Othmane & K. Flaßkamp https://doi.org/10.1007/s00332-026-10290-8
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4. A Time-Domain Irregular Wave Model with Different Random Numbers for FOWT Support Structures S. Ju & Y. Huang https://doi.org/10.32604/cmes.2025.067679
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7. Enhancing wind turbine load response tool through geometric non-linearities correction: Case study on DEFlex and design load comparison E. Barlas & O. Gözcü https://doi.org/10.1177/0309524X241280949
8. Symbolic multibody models for digital-twin applications N. Docquier et al. https://doi.org/10.1007/s11044-023-09957-x
9. Aeroelastic study of large offshore wind turbines under blade failure and detachment events H. Liu et al. https://doi.org/10.1016/j.oceaneng.2026.126304
10. Using intrusive approaches as a step towards accounting for stochasticity in wind turbine design E. Branlard et al. https://doi.org/10.1088/1742-6596/2767/8/082001
11. A digital twin solution for floating offshore wind turbines validated using a full-scale prototype E. Branlard et al. https://doi.org/10.5194/wes-9-1-2024
12. Study on large-scale floating wind turbine platforms under severe loads S. Ju & Y. Huang https://doi.org/10.1007/s40722-025-00424-7
13. Automatically generated state observers – toolchain and validation with real measurements J. Geisler https://doi.org/10.1088/1742-6596/2767/3/032003
14. A Modular C++/Eigen Aero-Elastic Simulation Code for Multi-Rotor Wind Turbines C. Qiu et al. https://doi.org/10.3390/en19102457
15. Vibration of blades and towers in large offshore and floating wind turbines: Mechanisms, modelling credibility and mitigation pathways Z. Zuo et al. https://doi.org/10.1016/j.rser.2026.117246
16. A generalized wind turbine cross section as a reduced-order model to gain insights in blade aeroelastic challenges E. Branlard et al. https://doi.org/10.1088/1742-6596/2767/2/022005