On the Effects of Motion Coupling on Linear and Quadratic Damping in Multi-DoF Modelling of Floating Offshore Wind Turbines

Accurate modelling of hydrodynamic damping remains a critical challenge in the dynamic analysis of floating offshore wind turbines (FOWTs), particularly when motion coupling between degrees of freedom is significant. This study addresses the limitations of conventional single-degree-of-freedom damping identification techniques by proposing a novel multi-degree-of-freedom identification procedure capable of including off-diagonal coupling terms in the estimation of both linear and quadratic damping matrices. The aim is to assess whether viscous cross-coupling effects can be explicitly identified within a multi-degree-of-freedom lumped-parameter framework and to evaluate their impact on motion prediction. The methodology employs a hybrid optimisation approach, combining a genetic algorithm with a gradient-based solver. The procedure is applied to a taut-leg moored semi-submersible floating platform, focusing on surge–pitch coupling and using both experimental wave-basin data and high-fidelity CFD free-decay simulations. The results show that diagonal damping coefficients can be robustly identified even under coupled free-decay conditions, whereas the inclusion of off-diagonal viscous terms does not significantly improve the reconstruction of free-decay responses. Moreover, the simultaneous calibration of the added mass matrix enabled by the proposed procedure further improves agreement with the reference data. Although the findings highlight limited identifiability of viscous cross-coupling effects from free-decay tests, this paper provides a flexible tool for more advanced damping identification in operational and extreme conditions.

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Publication Details

Journal
Applied Sciences
Published
2026-03-03
DOI
https://doi.org/10.3390/app16052448
Primary Topic
Wave and Wind Energy Systems
Type
article
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article

On the Effects of Motion Coupling on Linear and Quadratic Damping in Multi-DoF Modelling of Floating Offshore Wind Turbines

Oronzo Dell’Edera, Antonella Castellano, Francesco Niosi, Marco Cammalleri et al.
Applied Sciences
Wave and Wind Energy Systems
article

On the Effects of Motion Coupling on Linear and Quadratic Damping in Multi-DoF Modelling of Floating Offshore Wind Turbines

Oronzo Dell’Edera, Antonella Castellano, Francesco Niosi, Marco Cammalleri, Guglielmo Balistreri
article en

Abstract

Accurate modelling of hydrodynamic damping remains a critical challenge in the dynamic analysis of floating offshore wind turbines (FOWTs), particularly when motion coupling between degrees of freedom is significant. This study addresses the limitations of conventional single-degree-of-freedom damping identification techniques by proposing a novel multi-degree-of-freedom identification procedure capable of including off-diagonal coupling terms in the estimation of both linear and quadratic damping matrices. The aim is to assess whether viscous cross-coupling effects can be explicitly identified within a multi-degree-of-freedom lumped-parameter framework and to evaluate their impact on motion prediction. The methodology employs a hybrid optimisation approach, combining a genetic algorithm with a gradient-based solver. The procedure is applied to a taut-leg moored semi-submersible floating platform, focusing on surge–pitch coupling and using both experimental wave-basin data and high-fidelity CFD free-decay simulations. The results show that diagonal damping coefficients can be robustly identified even under coupled free-decay conditions, whereas the inclusion of off-diagonal viscous terms does not significantly improve the reconstruction of free-decay responses. Moreover, the simultaneous calibration of the added mass matrix enabled by the proposed procedure further improves agreement with the reference data. Although the findings highlight limited identifiability of viscous cross-coupling effects from free-decay tests, this paper provides a flexible tool for more advanced damping identification in operational and extreme conditions.

Applied SciencesVol. 16(5)
Politecnico di Torino (IT), University of Palermo (IT)
Openalex Percentile: Top 38%
Wave and Wind Energy Systems
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