Real-Time Digital Twin for Structural Health Monitoring of Floating Offshore Wind Turbines
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| Publicado en: | Journal of Marine Science and Engineering vol. 13, no. 10 (2025), p. 1953-1979 |
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| Autor principal: | |
| Otros Autores: | , , , |
| Publicado: |
MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 001 | 3265915339 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2077-1312 | ||
| 024 | 7 | |a 10.3390/jmse13101953 |2 doi | |
| 035 | |a 3265915339 | ||
| 045 | 2 | |b d20251001 |b d20251031 | |
| 084 | |a 231479 |2 nlm | ||
| 100 | 1 | |a Pastor-Sanchez, Andres |u Departamento de Arquitectura, Construcción y Sistemas Oceánicos y Navales, Escuela Técnica Superior de Ingenieros Navales, Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain | |
| 245 | 1 | |a Real-Time Digital Twin for Structural Health Monitoring of Floating Offshore Wind Turbines | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Digital twins (DTs) offer significant promise for condition-based maintenance of floating offshore wind turbines (FOWTs); however, existing solutions typically compromise either on physical rigor or real-time computational performance. This paper presents a real-time DT framework that resolves this trade-off by embedding a hydro-elastic reduced-order model (ROM) that accurately captures structural dynamics and fluid–structure interaction. Integrated in a cloud-ready Internet of Things architecture, the ROM reconstructs full-field displacements, von Mises stresses, and fatigue metrics with near real-time responsiveness. Validation on the 5 MW OC4-DeepCWind semi-submersible platform shows that the ROM reproduces finite-element (FEM) displacements and stresses with relative errors below 1%. A three-hour load case is solved in 0.69 min for displacements and 3.81 min for stresses on a consumer-grade NVIDIA RTX 4070 Ti GPU—over two orders of magnitude faster than the full FEM model—while one million fatigue stress histories (1000 hotspots × 1000 operating scenarios) are processed in 37 min. This efficiency enables continuous structural monitoring, rapid *what-if* assessments and timely decision-making for targeted inspections and adaptive control. By effectively combining physics-based reduced-order modeling with high-throughput computation, the proposed framework overcomes key barriers to DT deployment: computational overhead, physical fidelity and scalability. Although demonstrated on a steel platform, the approach is readily extensible to composite structures and multi-turbine arrays, providing a robust foundation for cost-effective and reliable deep-water wind-energy operations. | |
| 651 | 4 | |a Scotland | |
| 651 | 4 | |a United Kingdom--UK | |
| 653 | |a Deep water | ||
| 653 | |a Finite element method | ||
| 653 | |a Offshore | ||
| 653 | |a Wind power | ||
| 653 | |a Reduced order models | ||
| 653 | |a Deep learning | ||
| 653 | |a Internet of Things | ||
| 653 | |a Inspection | ||
| 653 | |a Estimates | ||
| 653 | |a Steel structures | ||
| 653 | |a Adaptive control | ||
| 653 | |a Physics | ||
| 653 | |a Computer applications | ||
| 653 | |a Submersibles | ||
| 653 | |a Semisubmersible platforms | ||
| 653 | |a Submersible platforms | ||
| 653 | |a Stresses | ||
| 653 | |a Structural health monitoring | ||
| 653 | |a Turbines | ||
| 653 | |a Simulation | ||
| 653 | |a Materials fatigue | ||
| 653 | |a Digital twins | ||
| 653 | |a Sensors | ||
| 653 | |a Fluid-structure interaction | ||
| 653 | |a Mathematical models | ||
| 653 | |a Wind turbines | ||
| 653 | |a Composite structures | ||
| 653 | |a Real time | ||
| 653 | |a Floating | ||
| 653 | |a Embedding | ||
| 653 | |a Decision making | ||
| 653 | |a Structural dynamics | ||
| 653 | |a Turbine engines | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Garcia-Espinosa, Julio |u Departamento de Arquitectura, Construcción y Sistemas Oceánicos y Navales, Escuela Técnica Superior de Ingenieros Navales, Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain | |
| 700 | 1 | |a Di Capua Daniel |u Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE), Gran Capitan s/n, 08034 Barcelona, Spain; dicapua@cimne.upc.edu (D.D.C.); bservan@cimne.upc.edu (B.S.-C.); irene.berdugo@upc.edu (I.B.-P.) | |
| 700 | 1 | |a Servan-Camas Borja |u Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE), Gran Capitan s/n, 08034 Barcelona, Spain; dicapua@cimne.upc.edu (D.D.C.); bservan@cimne.upc.edu (B.S.-C.); irene.berdugo@upc.edu (I.B.-P.) | |
| 700 | 1 | |a Berdugo-Parada Irene |u Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE), Gran Capitan s/n, 08034 Barcelona, Spain; dicapua@cimne.upc.edu (D.D.C.); bservan@cimne.upc.edu (B.S.-C.); irene.berdugo@upc.edu (I.B.-P.) | |
| 773 | 0 | |t Journal of Marine Science and Engineering |g vol. 13, no. 10 (2025), p. 1953-1979 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3265915339/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3265915339/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3265915339/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |