Data-driven modelling of wave–structure interaction for a moored floating structure

We present a data-driven nonlinear model for predicting the motions and loads of a moored floating structure in waves, which is a challenging problem in offshore hydrodynamics that requires coupled computation of nonlinear wave–structure interactions and mooring dynamics. A high-fidelity viscous-flo...

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Published inOcean engineering Vol. 300; p. 117522
Main Authors Jiang, Changqing, Zhang, Qi, el Moctar, Ould, Xu, Peng, Iseki, Toshio, Zhang, Guiyong
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 15.05.2024
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ISSN0029-8018
DOI10.1016/j.oceaneng.2024.117522

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Abstract We present a data-driven nonlinear model for predicting the motions and loads of a moored floating structure in waves, which is a challenging problem in offshore hydrodynamics that requires coupled computation of nonlinear wave–structure interactions and mooring dynamics. A high-fidelity viscous-flow solver, based on solving the Navier–Stokes equations for the free surface flow and implicitly coupled resolution of rigid body nonlinear motions and mooring dynamics, is employed to generate the ground truth. The data-driven model is trained using wave elevations as inputs and computed hydrodynamic motions and loads as outputs. We assess the effectiveness of the data-driven framework for modelling wave–structure interactions in both regular and irregular waves, demonstrating accurate predictions of hydrodynamic motions and loads in nonlinear waves with varying wavelengths and steepness. Leveraging the long short-term memory network, our surrogate model offers substantial computational savings for complex physical models and has the potential to create a digital twin of real offshore structures, ensuring operability and safety in various nonlinear sea states. •A data-driven technique models the fully nonlinear wave–structure interactions of a moored floating structure.•A high-fidelity approach solves the Navier–Stokes equations for the free-surface flow and formulates nonlinear rigid body motions and mooring dynamics.•Effectiveness of the proposed model is systematically verified through a parametric sensitivity analysis.•The model consistently demonstrates accurate predictions in both regular and irregular waves.•The computational efficiency makes it an attractive alternative to numerical hydrodynamic tools.
AbstractList We present a data-driven nonlinear model for predicting the motions and loads of a moored floating structure in waves, which is a challenging problem in offshore hydrodynamics that requires coupled computation of nonlinear wave–structure interactions and mooring dynamics. A high-fidelity viscous-flow solver, based on solving the Navier–Stokes equations for the free surface flow and implicitly coupled resolution of rigid body nonlinear motions and mooring dynamics, is employed to generate the ground truth. The data-driven model is trained using wave elevations as inputs and computed hydrodynamic motions and loads as outputs. We assess the effectiveness of the data-driven framework for modelling wave–structure interactions in both regular and irregular waves, demonstrating accurate predictions of hydrodynamic motions and loads in nonlinear waves with varying wavelengths and steepness. Leveraging the long short-term memory network, our surrogate model offers substantial computational savings for complex physical models and has the potential to create a digital twin of real offshore structures, ensuring operability and safety in various nonlinear sea states. •A data-driven technique models the fully nonlinear wave–structure interactions of a moored floating structure.•A high-fidelity approach solves the Navier–Stokes equations for the free-surface flow and formulates nonlinear rigid body motions and mooring dynamics.•Effectiveness of the proposed model is systematically verified through a parametric sensitivity analysis.•The model consistently demonstrates accurate predictions in both regular and irregular waves.•The computational efficiency makes it an attractive alternative to numerical hydrodynamic tools.
ArticleNumber 117522
Author Xu, Peng
Zhang, Qi
Zhang, Guiyong
el Moctar, Ould
Jiang, Changqing
Iseki, Toshio
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  givenname: Qi
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  surname: el Moctar
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  givenname: Peng
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  organization: Tokyo University of Marine Science and Technology, Etchujima, Koto-ku, Tokyo, 135-8533, Japan
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  givenname: Guiyong
  surname: Zhang
  fullname: Zhang, Guiyong
  organization: State Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Naval Architecture Engineering, Dalian University of Technology, Dalian, 116024, China
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Keywords Long short-term memory
Coupled mechanics
Wave–structure interaction
Computational fluid dynamics
Data-driven modelling
Mooring dynamics
Language English
License This is an open access article under the CC BY license.
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Snippet We present a data-driven nonlinear model for predicting the motions and loads of a moored floating structure in waves, which is a challenging problem in...
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SubjectTerms Computational fluid dynamics
Coupled mechanics
Data-driven modelling
Long short-term memory
Mooring dynamics
Wave–structure interaction
Title Data-driven modelling of wave–structure interaction for a moored floating structure
URI https://dx.doi.org/10.1016/j.oceaneng.2024.117522
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