Modelling linearly excited resonant heave response of a semi-submersible floating wind turbine

Experimental investigation of the dynamic response of a semi-submersible floating wind turbine and its non-Gaussian behavior

Abstract. Fast response calculations in the frequency domain are valuable during the initial design of floating wind turbines, where many design variants must be evaluated. A direct frequency-domain treatment of aero-elastic rotor loads is typically infeasible due to the azimuthal time dependence of the system matrices. To overcome this limitation, we introduce a perturbation-based formulation inspired by Hill's method, which reformulates the response equations into separate orders involving constant system matrices derived via Fourier decomposition. This enables accurate and efficient response computation using the fast Fourier transform (FFT). For comparison, a Laplace-based perturbation method is also developed using the Laplace transform instead of the Fourier transform. To evaluate the novel fast response methods, we develop an azimuthally periodic and fully linearized model of a floating wind turbine. The response to various load cases is computed under different inflow and floater motion conditions. The proposed Fourier-based fast response method achieves high accuracy, with peak and standard deviation errors of 2 % and 3.5 %, respectively, while reducing computation time to 2.5 s for a 4096 s simulation – significantly faster than linear (45 s) and time-domain (90 s) models. Through detailed comparison, we find that one of our approaches, the so-called single perturbation method, offers an effective trade-off between accuracy and speed, making it suitable for design and optimization studies.

The rapid global expansion of offshore wind is matched by an emerging wave of decommissioning. By the 2030s, over 30 GW of Europe's capacity will reach end-of-life (EoL), rising to 40million tonnes of material waste globally by 2050, with blades alone contributing approximately 325,000 tonnes of waste per year in Europe if not effectively recovered. This shift presents a risk of waste accumulation and an opportunity to embed circular economy (CE) practices into infrastructure renewal. To address this challenge, this study develops a BIM-based framework for dismantling a semi-submersible floating wind turbine (FWT), combining 3D modelling, 4D time sequencing and component-level inventories. The analysis adopts three condition-based scenarios - intact, minor and major damage - reflecting the real uncertainty at EoL, where exposure to marine environments can produce highly variable outcomes. This structure allows engineers to assess recovery routes in a realistic manner, from high-value reuse to advanced recycling. Our new findings demonstrate that Scenario 1 enables reuse and delivers the lowest cost, time and CO₂e impacts, while enabling the highest-value CE applications. Scenario 2 introduces moderate repair burdens due to processing requirements and Scenario 3 is dominated by energy-intensive processes. By linking those results to cumulative inventory, the study provides a replicable digital catalog that captures component fate across scenarios. The creation of material passports / inventories provides traceability of resources, highlights landfill avoidance and supports market preparation for secondary materials. For engineers, the framework offers a reproducible, inspection-driven decision-support tool that links component conditions to dismantling schedules and CE pathways, informing planning and procurement in upcoming decommissioning projects of the offshore wind industry.

Failure response analysis of the mooring system of a deep-water spar floating wind turbine considering delta mooring configuration

Numerical modeling of porous curved barge-type floating wind turbine platforms with cage system under monotonically oscillating seabed

Control to structure pathways in the upstream TetraSpar floating wind turbine

Floating wind turbines (FWTs) present unique reliability challenges that require optimized design and risk management strategies. This study develops a structured expert-based Failure Mode and Effects Analysis (FMEA) framework under IEA Wind Task 49 to identify and prioritize critical failure modes across five subsystems: tower, transition piece, mooring system, dynamic power cable, and floater. By leveraging expert-driven risk evaluation, this approach provides a more comprehensive and practical prioritization of failure modes, addressing key gaps in field failure data. Multidisciplinary experts in offshore engineering, risk management, and structural health monitoring assessed severity, occurrence, and detection ratings, producing Risk Priority Numbers (RPNs) for 129 failure scenarios where the FMEA results are treated probabilistically. Results highlight that fatigue-induced cracks in primary steelwork and weldments are among the highest-priority failure modes, alongside mooring line and dynamic cable failures. This framework supports targeted design improvements, such as weld design and corrosion protection, while suggesting proactive maintenance strategies, such as focused inspections and SHM for high-risk areas, for a more effective resource allocation. Overall, this study provides a foundation for systematic risk management in floating wind, guiding safer and more cost-efficient deployment as the technology scales to commercial farms. • This study presents a risk assessment approach using FMEA for floating wind turbines. • Variability across expert judgment is captured with the probabilistic treatment. • Risk mitigation strategies are proposed based on the FMEA results.

Control-induced modification in a tension-leg platform floating wind turbine

ABSTRACT To address the dynamic disturbance of wake flow induced by platform motions of offshore floating wind turbines (FOWTs), most existing engineering wake models focus primarily on the far-wake region and show limited capability in representing the velocity deficit in the near wake. In this study, a three-dimensional dynamic wake model for FOWTs is proposed with explicit consideration of platform motion characteristics. The proposed model is developed based on an improved Jensen model and the principle of mass conservation, and a double-Gaussian function is employed to describe the velocity deficit in the near-wake region. The effects of platform surge, pitch, and yaw motions on the incoming wind speed and wake development are explicitly taken into account. Validation results demonstrate that the proposed model can accurately predict the wake velocity distribution. Compared with wind tunnel experimental data, the maximum relative error is 7%, and the root mean square error is 2.66%. Compared with several existing wake models, the proposed model shows better performance in capturing near-wake characteristics, while the root mean square error in the far-wake region is only 2.33%. Furthermore, the impacts of single-degree-of-freedom and multi-degree-of-freedom platform motions on wake behavior are analyzed. The results indicate that both surge and pitch motions induce pulsating wake characteristics and significantly affect the wake velocity. Yaw motion causes wake deflection and accelerates wake recovery. Under coupled platform motions, the combination of surge and pitch has the most significant effect on the wake velocity, whereas the combination of pitch and yaw mainly induces wake deflection.

Abstract. Designing floating wind turbine systems requires integrated load assessments (ILA) using fully coupled hydro-servo-aero-elastic models. In most cases, floater hydrodynamics are represented using potential-flow models for mooring system design and motion estimation, while the floater itself is typically assumed to behave as a rigid body. However, this assumption can significantly affect tower eigenfrequency calculations, especially for large floaters. In this study, we investigate these effects using in situ sensor data from the Zefyros 2.3 MW spar wind turbine. We present a methodology to accurately determine the tower's eigenfrequencies. A rigid-floater model without added mass leads to an average error of 65 % for the first tower mode relative to measurements. Including hydrostatic added mass reduces the error to 40 %. Further incorporating floater flexibility decreases the error to 4.3 %, and accounting for blade flexibility lowers it to just 2.8 %. These discrepancies highlight the importance of refining the hydro-servo-aero-elastic model to align with eigenfrequencies derived from finite-element hydro-structural analyses. We present potential model adjustments, assess their impacts, and demonstrate the updated validation process.

Parameter optimization and performance evaluation of a nonlinear energy sink for vibration reduction in TLP floating wind turbine

Design and dynamic response analysis of a 15 MW semi-submersible floating wind turbine

Hardware-in-the-loop wind-tunnel testing of wake interactions between two floating wind turbines

Data-Driven Modelling of Aerodynamic Load Response to Platform Pitch Motion in Floating Wind Turbines

• Modal interpretation of cyber-physical test and numerical simulation results for shared mooring. • 5-9 modes capture the line-tension standard deviation of selected lines within 15% in the studied farms. • Quasi-static mooring models provides good approximation of floater horizontal motions in shared mooring but shared line tensions can be underestimated by up to 80% • Reconstructing line tensions using measured platform displacements and a dynamic mooring line model for better accuracy. • Modal approach explains comb-like frequency response in the power spectral density of line tensions and modal responses. Cyber-physical test and numerical simulation results for two shared mooring farms, consisting of 2 and 9 floating wind turbines, are analysed using a modal basis. Decay tests show a single dominant modal response. In irregular wave tests, comparisons with numerical simulations are limited to 5-9 modes that contribute significantly to line tension. These modes could reproduce the selected line tension standard deviation within 15%. The power spectral density of shared line tension and modal responses in the wave-frequency range exhibits a distinct comb-like frequency response associated with modal excitation from first-order wave loads. To meet the real-time computational requirement of cyber-physical tests, the mooring line model used during the test was a quasi-static model. Numerical comparisons are made between simulations with quasi-static and dynamic mooring line models for the tested shared-mooring farms to assess the impact of this simplification. In irregular wave tests, the quasi-static mooring line model overestimated the horizontal translational motion standard deviation by up to 20% (0.29 m full scale). Although direct application of the quasi-static mooring model underestimated the shared line tension standard deviation by up to approximately 80%, line tensions can be accurately reconstructed during post-processing.

Effect of floating wind turbine wakes on the thrust dynamics of a downstream turbine

Coupled aero-hydro-servo-elastic analysis of advanced wet-towing schemes for the IEA 15MW floating wind turbine

Investigation on the dynamics of shared-mooring floating wind turbines: assessing the impact of spacing and wake effect

Wind Generator design and testing: A lab scale 5×5 m2 WG for floating wind turbines