Real-time wetted-surface modeling method for floating offshore wind turbines: Validation and application to compartment flooding conditions

Floating offshore wind turbines (FOWTs) face significant hydrodynamic challenges during large-amplitude motions caused by extreme waves or ballast failures. Most FOWTs integrated simulation tools cannot capture these critical nonlinearities because they rely on constant hydrostatic matrices and linearized potential flow theory. To address this gap, this study proposes FAST2WASIM (F2W), a coupled time-domain framework integrating FAST and WASIM to simulate real-time wetted-surface variations and nonlinear wave–structure interactions of FOWTs. First, the F2W framework is validated against FAST, demonstrating its accuracy. Then, comparative analysis demonstrates that F2W's nonlinear hydrodynamic model effectively captures the wetted-surface variations induced by the spar-type platform's tapered geometry. Compared to the linear hydrodynamic model, the nonlinear model predicts a 21.8% increase in heave motion natural frequencies and enhanced nonlinear hydrodynamic responses, particularly in low-frequency resonances. Moreover, the F2W tool further enables high-fidelity simulation of compartment flooding scenarios, where dynamic waterplane changes significantly and impacts the stability performances of the FOWT. Results confirm that the spar-type FOWT is more susceptible to excessive sinking during flooding because of its small waterplane area. This work revolutionizes FOWT design, considering real-time wetted-surface modeling and paves the way for next-generation digital twins in offshore renewables.

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Publication Details

Journal
Physics of Fluids
Published
2025-10-01
DOI
https://doi.org/10.1063/5.0293404
Citations
1
Primary Topic
Surface Modification and Superhydrophobicity
Type
article
Field-Weighted Citation Impact
0.66
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article

Real-time wetted-surface modeling method for floating offshore wind turbines: Validation and application to compartment flooding conditions

Chao Sun, Fan Zhang, Jiahao Chen, Yanfei Deng
1 citations
Physics of Fluids
Surface Modification and Superhydrophobicity
0.66
article

Real-time wetted-surface modeling method for floating offshore wind turbines: Validation and application to compartment flooding conditions

Chao Sun, Fan Zhang, Jiahao Chen, Yanfei Deng
article en
1 citations

Abstract

Floating offshore wind turbines (FOWTs) face significant hydrodynamic challenges during large-amplitude motions caused by extreme waves or ballast failures. Most FOWTs integrated simulation tools cannot capture these critical nonlinearities because they rely on constant hydrostatic matrices and linearized potential flow theory. To address this gap, this study proposes FAST2WASIM (F2W), a coupled time-domain framework integrating FAST and WASIM to simulate real-time wetted-surface variations and nonlinear wave–structure interactions of FOWTs. First, the F2W framework is validated against FAST, demonstrating its accuracy. Then, comparative analysis demonstrates that F2W's nonlinear hydrodynamic model effectively captures the wetted-surface variations induced by the spar-type platform's tapered geometry. Compared to the linear hydrodynamic model, the nonlinear model predicts a 21.8% increase in heave motion natural frequencies and enhanced nonlinear hydrodynamic responses, particularly in low-frequency resonances. Moreover, the F2W tool further enables high-fidelity simulation of compartment flooding scenarios, where dynamic waterplane changes significantly and impacts the stability performances of the FOWT. Results confirm that the spar-type FOWT is more susceptible to excessive sinking during flooding because of its small waterplane area. This work revolutionizes FOWT design, considering real-time wetted-surface modeling and paves the way for next-generation digital twins in offshore renewables.

Physics of FluidsVol. 37(10)
Shenzhen Institute of Information Technology (CN), Harbin Institute of Technology (CN), Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN), Digital Wave (United States) (US)
Openalex Percentile: Top 27%
Surface Modification and Superhydrophobicity
0.66
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