Abstract

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.

Abstract

Structural elasticity of floating wind turbines in integrated load analysis (ILA) is typically addressed by modelling the substructure with simplified beam models. The main reason can be found in the computational cost of the structural solver when solving the fully coupled hydroelastic problems. In this work, a reduce order method based on modal matrix reduction is applied to reduce the computational cost of the structural solver. The main idea is to largely reduce the number of degrees of freedom of the structural system by retaining only those modes with significant energy. The seakeeping hydrodynamics is solved using the finite element framework SeaFEM. The structural particulars are introduced into this framework to fully integrate the fluid-structure interaction. The hydroelastic model is also coupled with the wind turbine solver OpenFAST, resulting in a complete aero-hydro-servo-elastic tool for the ILA analysis of floating turbines. A methodology is proposed to identify critical conditions and hotspots based on the structural energy. An application case of the present strategy is presented for a detailed structural design of the well-known OC4-DeepCwind. The consistency of the modal approximation and methodology is verified against the FE structural solution. The capabilities of the proposed ILA framework are demonstrated in a fully coupled and detailed structural analysis, instead of at component level, with a significant reduction of its computational time.

Abstract

The numerical simulation of a ship’s hydroelastic structural response is typically carried out using simplified modelling approaches. The main reason can be found in the computational cost of the structural solver when solving the fully coupled hydro-elastic problems. In this work, a two-way coupled fluid-structure interaction model capable of efficiently and accurately computing the hydro-elastic response of a ship using a detailed full-length structural representation is proposed. To reduce the computational cost of the structural solver, a reduced-order method based on modal matrix reduction is applied. The main idea is to largely reduce the number of degrees of freedom of the structural system by retaining only those modes with significant energy. Furthermore, to improve the accuracy of the model, this work proposes a combined methodology in which a residual finite element (FE) solution is computed alongside the reduced model, while still achieving a reduction in the overall computational effort. The seakeeping hydrodynamics is solved using the computational framework SeaFEM. And the structural particulars are introduced into this framework to fully integrate the fluid-structure interaction. An application case of the proposed model strategy is presented for a detailed structural design of a ship. The consistency of the modal approximation and methodology is verified against the full FE structural solution. It shows the capabilities of the proposed framework to perform a fully coupled and detailed structural analysis, instead of at component level, with a significant reduction in computational time.

Abstract

Hydro-elastic effects such as springing, whipping and racking can significantly increase hull stresses and fatigue damage. However, fully coupled time-domain hydro-elastic simulations remain computationally prohibitive for practical ship design due to the high cost of the structural solver. Objective: Develop an efficient two-way coupled hydro-elastic framework capable of capturing resonance effects with full-length detailed structural models, while drastically reducing computational cost.

Abstract

Structural elasticity of floating wind turbines, in integrated load analysis, are typically addressed by modelling the substructure with simplified beam models. The main reason can be found in the computational cost of the structural solver when solving the fully coupled hydroelastic problems. In this work, a reduce order method based on modal matrix reduction (MMR) is applied to reduce the computational cost. The main idea is to largely reduce the number of degrees of freedom of the structural system by retaining only those modes with significant energy. The seakeeping hydrodynamics is solved using the computational framework SeaFEM, based on the finite element method (FEM). The structural particulars are introduced into this framework to fully integrate the fluid-structure interaction. The hydroelastic model is also coupled with the wind turbine solver OpenFAST, resulting in a complete aero-hydro-servo-elastic tool for the ILA analysis of floating turbines. Moreover a methodology is proposed to identify critical conditions and hotspots based on the structural energy. An application case of the present strategy is presented for a detailed structural design of the OC4-DeepCwind. The consistency of the modal approximation and methodology are

Abstract

Structural elasticity of floating wind turbines, in integrated load analysis, are typically addressed by modelling the substructure with simplified beam models. The main reason can be found in the computational cost of the structural solver when solving the fully coupled hydroelastic problems. In this work, a reduce order method based on modal matrix reduction (MMR) is applied to reduce the computational cost. The main idea is to largely reduce the number of degrees of freedom of the structural system by retaining only those modes with significant energy. The seakeeping hydrodynamics is solved using the computational framework SeaFEM, based on the finite element method (FEM). The structural particulars are introduced into this framework to fully integrate the fluid-structure interaction. The hydroelastic model is also coupled with the wind turbine solver OpenFAST, resulting in a complete aero-hydro-servo-elastic tool for the ILA analysis of floating turbines. Moreover a methodology is proposed to identify critical conditions and hotspots based on the structural energy. An application case of the present strategy is presented for a detailed structural design of the OC4-DeepCwind. The consistency of the modal approximation and methodology are verified against the FE structural solution. It is shown the capabilities of the proposed ILA framework to perform a fully coupled and detailed structural analysis.

Abstract

En las jornadas Nacionales Españolas de Costas y Puertos se presenta las actividades de monitorización. En ella se expone que la operación de un buque está condicionada por su interacción continua con el medio físico, especialmente durante fases de alta exigencia como la aproximación al puerto, el acceso, el atraque, el amarre y la estancia atracado. En estas situaciones, la respuesta dinámica del buque constituye una fuente de información relevante para evaluar la seguridad, el confort, la eficiencia operativa y la exposición a condiciones meteo-oceánicas desfavorables. En el marco del proyecto ML-AMAR (Machine Learning Applications in Marine Engineering), se ha desarrollado una estrategia de monitorización continua orientada a integrar datos de navegación, respuesta dinámica y condiciones ambientales. Esta comunicación presenta su aplicación al buque Ro-Pax Ciudad de Barcelona, utilizado como demostrador en condiciones operativas reales. La metodología se basa en la instrumentación del buque mediante el sistema DeepMOTION-RTK, que permite registrar posición, velocidad, rumbo, aceleraciones y movimientos angulares mediante sensores GNSS/IMU. La campaña de monitorización cubre un periodo prolongado de operación, incluyendo navegación en ruta, aproximación, maniobras portuarias y estancia en puerto. Las señales registradas se integran con información meteo-oceánica procedente de fuentes externas, como Puertos del Estado y Copernicus, para relacionar la respuesta dinámica del buque con el oleaje, el viento y otras condiciones ambientales. Los resultados permiten estructurar la operación del buque por fases, identificar episodios de mayor solicitación dinámica y derivar indicadores trazables asociados a seguridad, confort y eficiencia. Asimismo, la información obtenida alimenta la plataforma DEEPVIEW, concebida para la visualización y análisis de los datos monitorizados, así como para la generación de métricas operativas de apoyo a la decisión. El trabajo confirma el interés de la monitorización dinámica como herramienta para mejorar la gestión operativa portuaria, validar modelos predictivos y avanzar hacia sistemas de apoyo basados en datos para la explotación de buques en condiciones reales. Palabras clave

Abstract

The project ML-AMAR (Machine Learning Applications in Marine Engineering) aims to develop machine learning tools to optimize the lifecycle management of ships, from design and operation to maintenance and structural monitoring.   The repository includes two public anonymized datasets generated from the ML-AMAR monitoring campaign. Both datasets have been prepared for scientific and technical distribution by removing sensitive information such as exact coordinates, precise timestamps, vessel/sensor identifiers and individual trajectories. The first dataset, ML_AMAR_anonimizacion_version_B_public, contains aggregated information on maritime routes, trip frequencies, departure time slots, trip duration classes, recurrent movement patterns and a non-georeferenced schematic network. It is intended for the analysis of maritime mobility and general route patterns. The second dataset, ML_AMAR_positions_1min_metocean_public_B, is derived from the original one-minute monitoring records. It provides aggregated information on operational state, route phase, distance-to-port classes, metocean conditions and vessel dynamic response. It is intended for scientific and technical analyses of the relationship between navigation, waves, wind and vessel behaviour. In both cases, the data are published only in aggregated and anonymized form. The repository does not include raw files, real GNSS positions, exact timestamps, operational identifiers or confidential correspondence tables between anonymized codes and real locations. Aggregation, discretization and suppression rules have been applied to prevent the reconstruction of individual trips or specific operational patterns. The dataset ML_AMAR_anonimizacion_version_B_public includes aggregated route summaries, trip frequencies, time slot distributions, duration classes, recurrent cycles and a schematic non-georeferenced network. Its main purpose is the analysis of maritime mobility and route patterns. The dataset ML_AMAR_positions_1min_metocean_public_B includes aggregated operational states, route phases, distance-to-port classes, vessel motion statistics and metocean conditions. Its main purpose is the scientific and technical analysis of vessel dynamics and metocean forcing.  

Abstract

During the design of a vessel or marine artefact, one of the main objectives is to ensure a long service life. The structure of these artefacts is essential to achieve this goal, as it is responsible for withstanding the extremely unfavourable stresses of the high seas. The aim of this paper is to present a method of detailed structural assessment by applying a dynamic hydroelastic model [1] that allows structural verification by greatly reducing the calculation time without losing accuracy. The current procedures used for this purpose require a detailed study of each loading condition, which implies many simulation hours and high computational cost. In this model, the high-fidelity structural solution is projected onto the modal basis to get the system modal matrix and extend the response amplitude operators (RAO) to the modal response amplitude operators (MRAO) of the structure. By retaining only those eigenmodes that preserve most of the structural elastic energy, the number of structural degrees of freedom can be significantly reduced. This reduced model has been implemented and coupled in the time domain with the seakeeping software SeaFEM, enabling quick analysis of a large number of load cases of the structure [2]. In this work, the first case study of a ship is presented.

Abstract

Structural assessment is a main concern when designing and operating any sort of offshore structure. This assessment is meant to ensure that the structural integrity is preserved along the lifespan of the asset, withstanding the worst sea-states that will be encountered and making sure that the accumulated fatigue damage will not jeopardize its structural integrity neither. The purpose of this paper is to present a fast and reliable hydroelastic model. This model is based on time-domain tight-coupling of a three-dimensional FEM (finite element method) linear structural model and a three-dimensional FEM seakeeping hydrodynamics model. In order to reduce the computational cost of structural dynamic simulations, the high-fidelity structural solution is projected onto the modal basis to obtain the modal matrix system and to extend the response amplitude operators (RAO) to the modal responses (MRAO). From there, the number of structural degrees of freedom can be greatly reduced by retaining only those eigenmodes preserving most of the structural elastic energy. The use MRAOs and/or the large reduction in structural degrees of freedom allows us to: first, quickly analyse the large number of loadcases required on the design stage; and second, to implement a digital twin for structural health monitoring in operational conditions. The paper also presents an application case of the developed methodology.

Abstract

Floating Offshore Multi-Wind Turbines (FOMWTs) are an interesting alternative to the up-scaling of wind turbines. Since being new incoming concepts, there are few numerical tools for its coupled dynamic assessment at the present time. In this work, a numerical framework is implemented for the simulation of multi-rotor systems under environmental excitations. It is capable to analyse a platform with leaning towers handling wind turbines with their own features and control systems. This tool is obtained by coupling the seakeeping hydrodynamics solver SeaFEM with the single wind turbine simulation tool OpenFAST. The coupling of SeaFEM provides a higher fidelity hydrodynamic solution allowing the simulation of any structural design since using the Finite Element Method (FEM). Besides, a methodology is proposed for the extension of the single wind solver, allowing the analysis of multi-rotor configurations. To do so, the solutions of the wind turbines are computed independently by several OpenFAST instances, performing its dynamic interaction through the floater. The method is applied to the single turbine Hywind concept and the twin-turbine W2Power floating platform, supporting NREL 5-MW wind turbines. The rigid-body Response Amplitude Operators (RAOs) are computed and compared with other numerical tools. The results showed consistency in the developed framework. Agreement is also obtained in simulations with aerodynamic loads. This resulting tool is a complete time-domain aero-hydro-servo-elastic solver, able to compute the combined response and power generation performance of multi-rotor systems.