Advanced Design and Analysis of Floating Offshore Systems

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: 20 August 2026 | Viewed by 907

Editors


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School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, China
Interests: mooring systems; multibody hydrodynamic interactions; deep learning method for floating structures

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Guest Editor
College of Harbour Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China
Interests: offshore kelp farming technology; fiber mooring ropes; wave model testing
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Yantai Research Institute, Harbin Engineering University, Yantai 264006, China
Interests: mooring dynamic analysis; hydrodynamic model testing; floating offshore wind turbine
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Tsinghua Shenzhen International Graduate School, Tsinghua Univeristy, Shenzhen 518071, China
Interests: offshore floating systems; hydrodynamics; subsea engineering
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Guest Editor
State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China
Interests: offshore structures; mooring system; hydrodynamics
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Special Issue Information

Dear Colleagues,

The advanced design and analysis of floating offshore systems are pivotal for expanding ocean-based industries, including oil and gas, floating wind, photovoltaics, and aquaculture. This field addresses complex multibody hydrodynamic and structural dynamic challenges, focusing on flexible components like mooring systems, cables, and risers. Research in this area now integrates traditional theoretical analysis, high-fidelity numerical methods (CFD/FEM), and physical experiments with cutting-edge AI. Machine learning algorithms, particularly deep learning models like LSTM and GRU, are revolutionizing the field by enabling real-time motion prediction, structural health monitoring, and fatigue assessment. These data-driven surrogate models complement physics-based simulations, enhancing design optimization and predictive maintenance. A key challenge remains the soil–structure interactions at foundations, crucial for overall system stability. The goal is to create robust, intelligent, and cost-effective designs for sustainable ocean resource utilization.

Topics include, but are not limited to, the following:

  1. AI-Enhanced Coupled Dynamic Analysis of Multibody Floating Platforms;
  2. Real-Time Prediction and Integrity Management of Flexible Risers and Mooring Systems;
  3. Development of Hybrid Digital Twins for Floating Offshore Systems by Fusing High-Fidelity Simulations with Real-Time Sensor Data and Machine Learning;
  4. Data-Driven Modeling of Seabed–Structure Interaction and Anchor Performance Using Interpretable Machine Learning;
  5. Intelligent Control and Optimization of Hybrid Offshore Systems (Wind/PV/Aquaculture) through Reinforcement Learning and Predictive Analytics.

Dr. Wei Huang
Dr. Yushun Lian
Dr. Gang Ma
Dr. Binbin Li
Prof. Dr. Dongsheng Qiao
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • floating offshore systems
  • mooring systems
  • multibody interactions
  • hydrodynamics
  • structure–soil interactions
  • deep learning methods

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Published Papers (1 paper)

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Research

39 pages, 5443 KB  
Article
Broadband Vibration Suppression of Spar-Type Offshore Wind Turbines Using a Novel Folded-Beam Nonlinear Energy Sink
by Jinyu Li, Hui Liang, Yanliang Bi, Nana Sun, Yan Zhang and Hongyin Geng
J. Mar. Sci. Eng. 2026, 14(10), 871; https://doi.org/10.3390/jmse14100871 - 7 May 2026
Viewed by 435
Abstract
Spar-type floating offshore wind turbines (FOWTs) operating in deep-sea environments are subjected to coupled wind and wave excitations spanning a wide frequency range, rendering single-frequency passive damping solutions inadequate. A folded-beam nonlinear energy sink (FB-NES) is proposed for broadband vibration suppression of spar-type [...] Read more.
Spar-type floating offshore wind turbines (FOWTs) operating in deep-sea environments are subjected to coupled wind and wave excitations spanning a wide frequency range, rendering single-frequency passive damping solutions inadequate. A folded-beam nonlinear energy sink (FB-NES) is proposed for broadband vibration suppression of spar-type FOWTs. The device employs pre-buckled elastic beam arms integrated with constrained layer damping patches, and a closed-form analytical relationship between the beam geometric parameters and the nonlinear stiffness coefficients is derived, enabling direct parameter design without iterative calibration. The pre-buckled geometry introduces a negative-stiffness mechanism that substantially lowers the targeted energy transfer (TET) threshold, ensuring device engagement under all normal operational sea states. A 14-degree-of-freedom aero-hydro-elastic model of the NREL 5 MW OC3-Hywind FOWT with the FB-NES is established via the Euler–Lagrange formulation and validated against OpenFAST. Based on the numerical results under operational and extreme parked load cases, the FB-NES achieves substantial broadband vibration reductions that grow monotonically with wave severity, consistently and substantially surpassing both the optimally tuned mass damper (TMD) and a conventional cubic nonlinear energy sink of equal mass. Wavelet analysis confirms that targeted energy transfer, rather than direct viscous damping, is the dominant energy dissipation mechanism. The FB-NES also maintains effective control over a wide frequency detuning range, demonstrating superior robustness compared to the TMD. Full article
(This article belongs to the Special Issue Advanced Design and Analysis of Floating Offshore Systems)
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