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 in | Ocean engineering Vol. 300; p. 117522 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
15.05.2024
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Subjects | |
Online Access | Get full text |
ISSN | 0029-8018 |
DOI | 10.1016/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. |
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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 |
Author_xml | – sequence: 1 givenname: Changqing orcidid: 0000-0003-1147-4263 surname: Jiang fullname: Jiang, Changqing email: changqing.jiang@uni-due.de organization: Institute of Ship Technology, Ocean Engineering and Transport Systems, University of Duisburg–Essen, Duisburg, 47057, Germany – sequence: 2 givenname: Qi orcidid: 0009-0004-3982-1217 surname: Zhang fullname: Zhang, Qi email: qi.zhang.007@stud.uni-due.de organization: Institute of Ship Technology, Ocean Engineering and Transport Systems, University of Duisburg–Essen, Duisburg, 47057, Germany – sequence: 3 givenname: Ould orcidid: 0000-0002-5096-4436 surname: el Moctar fullname: el Moctar, Ould organization: Institute of Ship Technology, Ocean Engineering and Transport Systems, University of Duisburg–Essen, Duisburg, 47057, Germany – sequence: 4 givenname: Peng orcidid: 0000-0003-1054-088X surname: Xu fullname: Xu, Peng organization: School of Naval Architecture and Maritime, Zhejiang Ocean University, Zhoushan, 316022, China – sequence: 5 givenname: Toshio surname: Iseki fullname: Iseki, Toshio organization: Tokyo University of Marine Science and Technology, Etchujima, Koto-ku, Tokyo, 135-8533, Japan – sequence: 6 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 |
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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 |
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