34 citations as recorded by crossref.

1. Graph neural networks for virtual sensing in complex systems: Addressing heterogeneous temporal dynamics M. Zhao et al. https://doi.org/10.1016/j.ymssp.2025.112544
2. Enhancing Smart Grid Security and Efficiency: AI, Energy Routing, and T&D Innovations (A Review) H. Ishfaq et al. https://doi.org/10.3390/en18174747
3. Workflow for real-time simulation-based fatigue assessment in mobile machinery A. Nemov et al. https://doi.org/10.1177/16878132261424717
4. Computational fluid dynamics and digital twins for wind turbines: A review R. Cockcroft & B. Thornber https://doi.org/10.1016/j.apenergy.2026.127890
5. Design of Virtual Sensors for a Pyramidal Weathervaning Floating Wind Turbine H. del Pozo Gonzalez et al. https://doi.org/10.3390/jmse13081411
6. On the modeling errors of digital twins for load monitoring and fatigue assessment in wind turbine drivetrains F. Mehlan & A. Nejad https://doi.org/10.5194/wes-10-417-2025
7. Offshore wind turbine tower design and optimization: A review and AI-driven future directions J. Alves Ribeiro et al. https://doi.org/10.1016/j.apenergy.2025.126294
8. A Joint Method on Dynamic States Estimation for Digital Twin of Floating Offshore Wind Turbines H. Xie et al. https://doi.org/10.3390/jmse13101981
9. Sustainable Energy and Exergy Analysis in Offshore Wind Farms Using Machine Learning: A Systematic Review H. Soltani Motlagh et al. https://doi.org/10.3390/eng6060105
10. A review of digital twin methods and applications for bearings under marine operating constraints J. Shi et al. https://doi.org/10.1080/17445302.2026.2684687
11. A wind turbine digital shadow with tower and blade degrees of freedom - Preliminary results and comparison with a simple tower fore-aft model H. Hoghooghi et al. https://doi.org/10.1088/1742-6596/2767/3/032026
12. Real-Time Digital Twin for Structural Health Monitoring of Floating Offshore Wind Turbines A. Pastor-Sanchez et al. https://doi.org/10.3390/jmse13101953
13. Assessment of multi-fidelity hydrodynamic models of floating wind turbines in extreme wave events J. Fontaine et al. https://doi.org/10.1016/j.renene.2025.124639
14. Towards better fatigue predictions in large offshore wind turbines: A review of climate, aero-hydrodynamic, and computational approaches G. Mangia et al. https://doi.org/10.1016/j.joes.2026.02.009
15. Offshore Field Demonstration of a 1:4-Scale 20-MW VolturnUS+ Floating Wind Barge in the Gulf of Maine J. Dagher et al. https://doi.org/10.1088/1742-6596/3224/8/082035
16. 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
17. Data-driven surrogate model for wind turbine damage equivalent load R. Haghi & C. Crawford https://doi.org/10.5194/wes-9-2039-2024
18. Digital Twin-Based Approach for a Multi-Objective Optimal Design of Wind Turbine Gearboxes C. Llopis-Albert et al. https://doi.org/10.3390/math12091383
19. Strain virtual sensor for offshore wind turbine jacket supports: A time series transformer approach validated with Alpha Ventus wind farm data Á. Encalada-Dávila et al. https://doi.org/10.1016/j.ymssp.2025.112653
20. Offshore Wind in the Energy Transition: A Comparative Analysis of Floating and Bottom-Fixed Technologies L. Villani et al. https://doi.org/10.3390/en19020487
21. Artificial Intelligence in Floating Offshore Wind Turbines: A Critical Review of Applications in Design, Monitoring, Control, and Digital Twins E. Kostecka et al. https://doi.org/10.3390/en18225937
22. SCADA-Based Offshore Wind Turbine Monitoring: A Review of Methods of Addressing Marine Environmental Challenges K. Wrzask et al. https://doi.org/10.2478/pomr-2025-0061
23. Model Updating of an Offshore Wind Turbine Support Structure Based on Modal Identification and Bayesian Inference C. Yu et al. https://doi.org/10.3390/jmse13122354
24. Insights into corrosion-fatigue deterioration in offshore wind turbine structures through digital twin applications Y. Ali et al. https://doi.org/10.1016/j.oceaneng.2025.123514
25. A physics-informed autoencoder for digital twin development in offshore wind turbine installation D. Dunton et al. https://doi.org/10.1007/s00158-026-04368-w
26. Enhancing Reliability in Floating Offshore Wind Turbines through Digital Twin Technology: A Comprehensive Review B. Chen et al. https://doi.org/10.3390/en17081964
27. Wind Turbine SCADA Data Imbalance: A Review of Its Impact on Health Condition Analyses and Mitigation Strategies A. Oliveira-Filho et al. https://doi.org/10.3390/en18010059
28. Digital Twins for Clean Energy Systems: A State-of-the-Art Review of Applications, Integrated Technologies, and Key Challenges M. Kim et al. https://doi.org/10.3390/su18010043
29. Floating offshore wind sector development in the mediterranean: Economic, employment and social analysis D. Vespasiano et al. https://doi.org/10.1016/j.energy.2026.140389
30. POD-based sparse stochastic estimation of dynamic wind turbine blade deflections L. Schena et al. https://doi.org/10.1016/j.jsv.2026.119738
31. Blockchain-based intelligent equipment assessment in manufacturing industry T. Ahanger et al. https://doi.org/10.1007/s10845-025-02621-5
32. Considerations for the global commercialization of floating offshore wind energy A. Robertson et al. https://doi.org/10.1038/s44359-025-00093-7
33. A Review of Digital Twinning Applications for Floating Offshore Wind Turbines: Insights, Innovations, and Implementation I. Taze et al. https://doi.org/10.3390/en18133369
34. A wind turbine digital shadow for complex inflow conditions H. Hoghooghi & C. Bottasso https://doi.org/10.5194/wes-11-373-2026