| D'Antuono, Pietro |
ORCID
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Informatie laatst gewijzigd: 2023-04-26 |
| A1 publicaties (2) [show] |
 de Nolasco Santos, F.; D'Antuono, P.; Robbelein, K.; Noppe, N.; Weijtjens, W.; Devriendt, C. (2023). Long-term fatigue estimation on offshore wind turbines interface loads through loss function physics-guided learning of neural networks. Renew. Energy 205: 461-474. https://dx.doi.org/10.1016/j.renene.2023.01.093, meer- Sadeghi, N.; D'Antuono, P.; Noppe, N.; Robbelein, K.; Weijtjens, W.; Devriendt, C. (2023). Quantifying the effect of low-frequency fatigue dynamics on offshore wind turbine foundations: a comparative study. Wind Energy Science 8(12): 1839-1852. https://dx.doi.org/10.5194/wes-8-1839-2023, meer
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| Boekhoofdstukken (2) [show] |
- D'Antuono, P.; Weijtjens, W.; Devriendt, C. (2023). On the minimum required sampling frequency for reliable fatigue lifetime estimation in structural health monitoring. How much is enough?, in: Rizzo, P. et al. European Workshop on Structural Health Monitoring. EWSHM 2022 - Volume 1. pp. 133-142. https://dx.doi.org/10.1007/978-3-031-07254-3_14, meer
- de Nolasco Santos, F.; Robbelein, K.; D'Antuono, P.; Noppe, N.; Weijtjens, W.; Devriendt, C. (2023). Towards a fleetwide data-driven lifetime assessment methodology of offshore wind support structures based on SCADA and SHM data, in: Rizzo, P. et al. European Workshop on Structural Health Monitoring. EWSHM 2022 - Volume 1. pp. 123-132. https://dx.doi.org/10.1007/978-3-031-07254-3_13, meer
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