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Modelling Techniques for Floating Offshore Wind Turbines

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: 1 May 2025 | Viewed by 8830

Special Issue Editors


E-Mail Website
Guest Editor
Ships and Ocean Structures, SINTEF Ocean AS, Trondheim, Norway
Interests: offshore hydrodynamics; station keeping; floating wind energy

E-Mail Website
Guest Editor
Energy and Transport, SINTEF Ocean, Trondheim, Norway
Interests: offshore wind energy; offshore hydrodynamics; station keeping; computational fluid dynamics

Special Issue Information

Dear Colleagues,

As the demand for sustainable energy sources grows, floating offshore wind turbines (FOWTs) have emerged as a promising solution to harness wind energy in deeper waters. While the projections for deployment capacity over the coming decades point towards exponential growth, the challenges to overcome are also very significant. Research and innovation are needed to allow for safe, cost-effective and sustainable projects.

This Special Issue focuses on the latest advancements in modelling techniques for FOWTs, both experimental and numerical, addressing critical challenges faced by the design, operation and decommissioning of floating wind turbines. We aim at collecting contributions focused on the following topics:

  • Wind resource assessment;
  • Wake modelling;
  • Experimental model testing;
  • Hydrodynamics;
  • Mooring analysis;
  • Power cables dynamics;
  • Wind turbine controllers;
  • Fully coupled modelling;
  • Structural analysis;
  • Digital twins;
  • Offshore operations.

Dr. Nuno Fonseca
Dr. Petter Andreas Berthelsen
Guest Editors

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Keywords

  • floating offshore wind turbine
  • numerical modelling
  • experimental modelling
  • fully coupled dynamics
  • wave–structure hydrodynamics
  • aero-elastic dynamics
  • control strategies

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Published Papers (7 papers)

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32 pages, 15864 KiB  
Article
Coupled Aerodynamic–Hydrodynamic Analysis of Spar-Type Floating Foundations with Normal and Lightweight Concrete for Offshore Wind Energy in Colombia
by Jose Calderón, Andrés Guzmán and William Gómez
J. Mar. Sci. Eng. 2025, 13(2), 273; https://doi.org/10.3390/jmse13020273 - 31 Jan 2025
Viewed by 1215
Abstract
Foundations for offshore wind turbines come in various types, with spar-type floating foundations being the most promising for different depths. This research analyzed the hydrodynamic–mechanical response of a 5 MW spar-type floating foundation under conditions typical of the Colombian Caribbean following the DNV [...] Read more.
Foundations for offshore wind turbines come in various types, with spar-type floating foundations being the most promising for different depths. This research analyzed the hydrodynamic–mechanical response of a 5 MW spar-type floating foundation under conditions typical of the Colombian Caribbean following the DNV standard. Two types of concrete were evaluated through numerical modeling: one with normal density (2400 kg/m3) and another with lightweight density (1900 kg/m3). Based on the hydrodynamic and structural dynamic response, it was concluded that the variation in concrete density only affected pitch rotation, with better performance observed in the lightweight concrete, achieving maximum rotations of 10°. The coupled model between QBlade and Aqwa was validated by code-to-code comparisons with QBlade’s fully coupled system with its ocean module. This study contributes to offshore engineering in Colombia by providing a detailed methodology for developing a coupled simulation, serving as a reference for both academia and industry amid the ongoing and projected wind energy development initiatives in the country. Full article
(This article belongs to the Special Issue Modelling Techniques for Floating Offshore Wind Turbines)
Show Figures

Figure 1

Figure 1
<p>Typologies of fixed and floating foundations for wind turbines. Reproduced with permission from Moisés Jiménez Martinez, International Journal of Fatigue; published by Elsevier, 2020 [<a href="#B21-jmse-13-00273" class="html-bibr">21</a>].</p>
Full article ">Figure 2
<p>Methodological process (stages) for the design of offshore floating wind turbines (FOWTs), modified from Rueda-Bayona [<a href="#B34-jmse-13-00273" class="html-bibr">34</a>].</p>
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<p>Bathymetry and elevations for the installation of the floating foundation.</p>
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<p>Study area: Barranquilla (Colombia).</p>
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<p>Validation of the WW3-NOAA database with in situ data from wave buoy 41194: (<b>a</b>) scatter plot; (<b>b</b>) Taylor diagram.</p>
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<p>Wave rose; significant wave height <span class="html-italic">Hs</span>.</p>
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<p>Wave rose; peak period <span class="html-italic">Tp</span>.</p>
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<p>Joint probability <span class="html-italic">Hs</span>-<span class="html-italic">Tp</span>.</p>
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<p>Joint probability <span class="html-italic">Hs</span>-<span class="html-italic">Dp</span>.</p>
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<p>Extreme regime of the significant wave height.</p>
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<p>Current profiles.</p>
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<p>Surface current intensity rose.</p>
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<p>Validation of the ERA5 database for the study area.</p>
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<p>Wind rose; average wind intensity over 1 h at 10 m above the free surface of the sea.</p>
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<p>Extreme regime of wind intensity at 10 m.</p>
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<p>(<b>a</b>) Multiyear monthly average of wind intensity and (<b>b</b>) available wind power density at 10 m elevation.</p>
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<p>Power curve. Source: NREL [<a href="#B44-jmse-13-00273" class="html-bibr">44</a>].</p>
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<p>Power coefficient. Source: NREL [<a href="#B44-jmse-13-00273" class="html-bibr">44</a>].</p>
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<p>Monthly wind cycle.</p>
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<p>Daily wind cycle.</p>
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<p>Joint probability of significant wave height <span class="html-italic">Hs</span>—wind intensity <span class="html-italic">V<sub>hub</sub></span>.</p>
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<p>Joint probability of wave direction—wind direction. The data were derived from the ERA5 reanalysis [<a href="#B40-jmse-13-00273" class="html-bibr">40</a>].</p>
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<p>Alternative geometries for the design.</p>
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<p>Dimensions of the selected spar foundation.</p>
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<p>Rotor thrust coefficient.</p>
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<p>Mooring line for the spar floating foundation.</p>
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<p>QBlade model. (<b>a</b>) Side view and (<b>b</b>) isometric view.</p>
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<p>Aqwa model. (<b>a</b>) Side view and (<b>b</b>) isometric view.</p>
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<p>Comparison of the time series of displacements and rotations between the QBlade and Aqwa models.</p>
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<p>Basic statistics for comparing the QBlade–Aqwa implementation.</p>
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<p>Comparison of floating foundations with normal and lightweight concrete.</p>
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19 pages, 3145 KiB  
Article
Investigating Morison Modeling of Viscous Forces by Steep Waves on Columns of a Fixed Floating Offshore Wind Turbine (FOWT) Using Computational Fluid Dynamics (CFD)
by Fatemeh Hoseini Dadmarzi, Babak Ommani, Andrea Califano, Nuno Fonseca and Petter Andreas Berthelsen
J. Mar. Sci. Eng. 2025, 13(2), 264; https://doi.org/10.3390/jmse13020264 - 30 Jan 2025
Viewed by 554
Abstract
Mean and slowly varying wave loads on floating offshore wind turbines (FOWTs) need to be estimated accurately for the design of mooring systems. The low-frequency drift forces are underestimated by potential flow theory, especially in steep waves. Viscous forces on columns is an [...] Read more.
Mean and slowly varying wave loads on floating offshore wind turbines (FOWTs) need to be estimated accurately for the design of mooring systems. The low-frequency drift forces are underestimated by potential flow theory, especially in steep waves. Viscous forces on columns is an important contributor which could be included by adding the quadratic drag of Morison formulation to the potential flow solution. The drag coefficients in Morison equation can be determined based on an empirical formula, CFD study, or model testing. In the WINDMOOR project, a FOWT support structure, composed of three columns joined at the bottom by pontoons and at the top by deck beams, is studied using CFD. In order to extract the KC-dependent drag coefficients, a series of simulations for the fixed structure in regular waves is performed with the CFD code STAR-CCM+. In this study, the forces along each column of the FOWT are analyzed using the results of CFD as well as potential flow simulations. The hydrodynamic interactions between the columns are addressed. A methodology is proposed to process the CFD results of forces on the columns and extract the contribution of viscous effects. Limitations of the Morison drag model to represent extracted viscous forces in steep waves are investigated. The obtained drag coefficients are compared with the available data in the literature. It is shown that accounting for potential flow interactions and nonlinear flow kinematics could, to a large degree, explain the previously reported differences between drag coefficients for a column in waves. Moreover, it is shown that the proposed model can capture the contribution of viscous effects to mean drift forces for fixed columns in waves. Full article
(This article belongs to the Special Issue Modelling Techniques for Floating Offshore Wind Turbines)
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Figure 1

Figure 1
<p>Platform geometrical model. The wave is propagating in the positive <span class="html-italic">x</span>-direction.</p>
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<p>A view of the computational domain with the rectangle showing the inner domain. <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>W</mi> </mrow> </semantics></math>: column to column distance. <math display="inline"><semantics> <mi>λ</mi> </semantics></math>: longest wave length considered. The magnitude of wave forcing function at the water level is shown with shading. The wave is propagating in the positive <span class="html-italic">x</span>-axis direction.</p>
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<p>Lateral view of the mesh discretization with body volume refinements.</p>
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<p>Horizontal segments along the column.</p>
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<p>Sectional force time series on the starboard column for three waves (W3, W5, W7) and two heights.</p>
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<p>Comparison of CFD and theoretical undisturbed free surface elevation at the middle of the platform. Theory: initialized domain using the fifth-order Stokes wave.</p>
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<p>Amplitude of the pressure over the structure from the potential flow solution of the diffraction problem for a 10 s wave.</p>
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<p>Comparison of CFD and potential forces on several segments along the starboard column for Wave 3. Pot.: Potential force from WAMIT. Pot. FS.: Potential forces stretched up to the instantaneous free surface.</p>
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<p>Drag coefficient for W1 and W7 extracted by decomposing the residual force after removing the potential flow sectional force contribution using both nonlinear and linear (-Lin) wave kinematics. See <a href="#jmse-13-00264-t003" class="html-table">Table 3</a> for wave condition details. The two dashed lines show the boundaries of the splash zone.</p>
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<p>Drag coefficient on Starboard column, extracted by fitting a quadratic model to the CFD force after removing the potential flow sectional force contribution using linear and nonlinear wave kinematics.</p>
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<p>Ratio of drag coefficients from linear and nonlinear kinematics.</p>
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<p>Drag coefficient extracted by decomposing the force.</p>
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<p>Comparison of CFD and force components on Z = <math display="inline"><semantics> <mrow> <mo>−</mo> <mn>10</mn> </mrow> </semantics></math> m segment on the starboard column for Wave 3, 5 and 7.Mor.: quadratic drag using linear wave kinematics. RP.: Same as Mor. but with recommended drag coefficients from [<a href="#B5-jmse-13-00264" class="html-bibr">5</a>]. Mor.NonLion.: same as Mor. but with nonlinear wave kinematics. Pot. FS.: Potential forces stretched up to the instantaneous free surface.</p>
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<p>Comparison of CFD and reconstructed forces on Z = <math display="inline"><semantics> <mrow> <mo>−</mo> <mn>10</mn> </mrow> </semantics></math> m segment on the starboard column for Waves 3, 5, and 7. Legends are the same as <a href="#jmse-13-00264-f013" class="html-fig">Figure 13</a>, and potential forces are added to all drag components.</p>
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<p>Comparison of CFD and force components on Z = 0 m segment on the starboard column for Wave 3, 5 and 7.Mor.: quadratic drag using linear wave kinematics. RP.: Same as Mor. but with the recommended drag coefficients from [<a href="#B5-jmse-13-00264" class="html-bibr">5</a>]. Mor.NonLion.: same as Mor. but with the nonlinear wave kinematics. Pot. FS.: potential forces stretched up to the instantaneous free surface.</p>
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<p>Comparison of CFD and reconstructed forces on Z = <math display="inline"><semantics> <mrow> <mo>−</mo> <mn>10</mn> </mrow> </semantics></math> m segment on the starboard column for Waves 3, 5 and 7. Legends are the same as <a href="#jmse-13-00264-f015" class="html-fig">Figure 15</a>, and potential forces are added to all drag components.</p>
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<p>Comparison of CFD and reconstructed total forces on the starboard column for Wave 3, 5 and 7. Mor.: quadratic drag and potential-flow forces using linear wave kinematics. RP.: same as Mor. but with recommended drag coefficients from [<a href="#B5-jmse-13-00264" class="html-bibr">5</a>]. Mor.NonLion.: same as Mor. but with nonlinear wave kinematics. Pot. FS.: linear diffraction forces from potential flow stretched up to the instantaneous free surface.</p>
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<p>Comparison of CFD forces on columns for three waves. Stb.: Starboard, Por.: Port, Tow.: Tower.</p>
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<p>Comparison of CFD and reconstructed forces on starboard (Stb.) and Tower (Tow.) columns. Mor. Nl.: Quadratic drag plus potential forces stretched up to the instantaneous free surface.</p>
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<p>Comparison of CFD forces on columns for three waves, perpendicular to wave propagation direction. Stb.: Starboard, Por.: Port, Tow.: Tower.</p>
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<p>Drift forces on the columns of FOWT support structure. Pot.: Potential flow mean drift. Mor.Lin.: Linear Morison, Mor.NL.: Nonlinear Morison, Mor.Lin.RP.: Linear wave kinematics with recommended drag coefficients from [<a href="#B5-jmse-13-00264" class="html-bibr">5</a>]. Mor.NL.RP.: Nonlinear wave kinematics with recommended drag coefficients from [<a href="#B5-jmse-13-00264" class="html-bibr">5</a>].</p>
Full article ">
22 pages, 1102 KiB  
Article
Improving O&M Simulations by Integrating Vessel Motions for Floating Wind Farms
by Vinit V. Dighe, Lu-Jan Huang, Jaume Hernandez Montfort and Jorrit-Jan Serraris
J. Mar. Sci. Eng. 2024, 12(11), 1948; https://doi.org/10.3390/jmse12111948 - 31 Oct 2024
Viewed by 1083
Abstract
This study presents an integrated methodology for evaluating operations and maintenance (O&M) costs for floating offshore wind turbines (FOWTs), incorporating vessel motion dynamics. By combining UWiSE, a discrete-event simulation tool, with SafeTrans, a voyage simulation software, vessel motion effects during offshore operations are [...] Read more.
This study presents an integrated methodology for evaluating operations and maintenance (O&M) costs for floating offshore wind turbines (FOWTs), incorporating vessel motion dynamics. By combining UWiSE, a discrete-event simulation tool, with SafeTrans, a voyage simulation software, vessel motion effects during offshore operations are modeled. The approach is demonstrated in a case study at two wind farm sites, Marram Wind and Celtic Sea C. Three major component replacement (MCR) strategies were assessed: Tow-to-Port (T2P), Floating-to-Floating (FTF), and Self-Hoisting Crane (SHC). The T2P strategy yielded the highest O&M costs—94 kEUR/MW/year at Marram Wind and 97 kEUR/MW/year at Celtic Sea C—due to the extended MCR durations (90–180 days), leading to lower availability (90–94%). In contrast, the FTF and SHC strategies offered significantly lower costs and downtime. The SHC strategy was most cost-effective, reducing costs by up to 64% while achieving 97–98% availability. The integrated approach was found to be either more restrictive or more permissive depending on the specific sea states influencing the motion responses. This variability highlights the critical role of motion-based dynamics in promoting safe and efficient O&M practices, particularly for advancing FOWT operations. Full article
(This article belongs to the Special Issue Modelling Techniques for Floating Offshore Wind Turbines)
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Figure 1

Figure 1
<p>Motion characteristics and directional dynamics of vessels and platforms in FOWT operations. The figure illustrates the interaction between the platform and the support vessel, highlighting the six degrees of freedom (surge, sway, heave, roll, pitch, and yaw) that influence the operability and maintenance activities in offshore environments.</p>
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<p>Schematic of the methodology framework for evaluating O&amp;M costs and availability for FOWT, showing the input and output space of integrated models UWiSE O&amp;M Planner and SafeTrans.</p>
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<p>Time-series plots of mean wind speed (<math display="inline"><semantics> <msub> <mi>U</mi> <mn>10</mn> </msub> </semantics></math>) and significant wave height (<math display="inline"><semantics> <msub> <mi>H</mi> <mi>s</mi> </msub> </semantics></math>) for Marram Wind and Celtic Sea C, showing raw data (lighter shades) and moving averages (darker lines) calculated with a bin size of 1000.</p>
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<p>KPIs for the T2P strategy at Marram Wind and Celtic Sea C sites, showing MDC and <math display="inline"><semantics> <msub> <mi>A</mi> <mi>T</mi> </msub> </semantics></math>. The bars illustrate the breakdown of MDC into categories, including WTG major and minor repair, WTG major component replacement, scheduled maintenance, and floating substructure maintenance. Revenue losses are plotted separately. MDC is the sum of the stacked plot and the plot for revenue losses for the respective wind farm. <math display="inline"><semantics> <msub> <mi>A</mi> <mi>T</mi> </msub> </semantics></math> at Marram Wind is 94%, while at Celtic Sea C, it is 90%. Error bars indicate the variability in MDC estimates using 2 standard deviations.</p>
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<p>Normalized MDC for MCR strategies (T2P, FTF, SHC) at Marram Wind and Celtic Sea C. Each site shows variations in MDC with different MCR strategies while keeping other O&amp;M activities constant. Bars represent costs for vessels, technicians, spare parts, revenue losses, and <math display="inline"><semantics> <msub> <mi>A</mi> <mi>T</mi> </msub> </semantics></math> values indicate time-based availability.</p>
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<p>Box plots of MCR operation durations for three strategies (T2P, FTF, and SHC) at Marram Wind and Celtic Sea C sites. Blue and orange boxes represent UWiSE (weather limits only) and SafeTrans (weather and motion limits) simulations, respectively. Plots show the variability in MCR durations across different months, highlighting the impact of weather and motion constraints on each strategy’s performance.</p>
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<p>Scatter plot comparing allowable significant wave height (<math display="inline"><semantics> <msub> <mi>H</mi> <mi>s</mi> </msub> </semantics></math>) limits for the “Tow WT to Port” step in the T2P strategy, determined by UWiSE (weather limits) and SafeTrans (motion limits). SafeTrans allows higher <math display="inline"><semantics> <msub> <mi>H</mi> <mi>s</mi> </msub> </semantics></math> limits (above 3 m) due to accounting for dynamic vessel responses, while UWiSE maintains conservative <math display="inline"><semantics> <msub> <mi>H</mi> <mi>s</mi> </msub> </semantics></math> limits below 3 m.</p>
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<p>Map showing the locations of the Marram Wind site, accessible via the Port of Fraserburgh in the North Sea, and the Celtic Sea C site, serviced by the Port of Loughbeg in the Celtic Sea.</p>
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16 pages, 2230 KiB  
Article
Computational Analysis of Stiffness Reduction Effects on the Dynamic Behaviour of Floating Offshore Wind Turbine Blades
by Daniel O. Aikhuele and Ogheneruona E. Diemuodeke
J. Mar. Sci. Eng. 2024, 12(10), 1846; https://doi.org/10.3390/jmse12101846 - 16 Oct 2024
Viewed by 1069
Abstract
This paper describes the study of a floating offshore wind turbine (FOWT) blade in terms of its dynamic response due to structural damage and its repercussions on structural health monitoring (SHM) systems. Using a finite element model, natural frequencies and mode shapes were [...] Read more.
This paper describes the study of a floating offshore wind turbine (FOWT) blade in terms of its dynamic response due to structural damage and its repercussions on structural health monitoring (SHM) systems. Using a finite element model, natural frequencies and mode shapes were derived for both an undamaged and a damaged blade configuration. A 35% reduction in stiffness at node 1 was applied in order to simulate significant damage. Concretely, the results are that the intact blade has a fundamental frequency of 0.16 Hz, and this does not change when damaged, while higher modes exhibit frequency changes: mode 2 drops from 2.05 Hz to 2.00 Hz and mode 3 from 6.15 Hz to 6.01 Hz. The shifts show a critical loss in the capability of handling vibrational energy due to the damage; higher modes (4, 5, and 6) show larger frequency deviations going down to as low as 18.06 Hz in mode 6. The mode shape change is considerable for the edge-wise and flap-wise deflection of the 2D contour plots, indicating possible coupling effects between modes. These results indicate that lower modes are sensitive to stiffness reductions, and the continuous monitoring of the lower harmonic modes early is required to detect damages. These studies have helped to improve blade design, maintenance, and operational safety for FOWT systems. Full article
(This article belongs to the Special Issue Modelling Techniques for Floating Offshore Wind Turbines)
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Figure 1

Figure 1
<p>Schematic diagram of a NREL 5 MW OWT [<a href="#B27-jmse-12-01846" class="html-bibr">27</a>].</p>
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<p>Magnified view of the contour plot for 35% damage level.</p>
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<p>The graphical visualization of the mode shapes in undamaged and 35% damaged state.</p>
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<p>The graphical visualization of the mode shapes in an undamaged state and in states of 5%, 20%, and 35% damage.</p>
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<p>The graphical representation of the damage level in comparison to the mode number.</p>
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<p>Visualization Different Damage Levels through Contour Plots.</p>
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<p>Visualization Different Damage Levels through Contour Plots.</p>
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21 pages, 3418 KiB  
Article
Performance of a Cable-Driven Robot Used for Cyber–Physical Testing of Floating Wind Turbines
by Yngve Jenssen, Thomas Sauder and Maxime Thys
J. Mar. Sci. Eng. 2024, 12(9), 1669; https://doi.org/10.3390/jmse12091669 - 18 Sep 2024
Viewed by 1217
Abstract
Cyber–physical testing has been applied for a decade in hydrodynamic laboratories to assess the dynamic performance of floating wind turbines (FWTs) in realistic wind and wave conditions. Aerodynamic loads, computed by a numerical simulator fed with model test measurements, are applied in real [...] Read more.
Cyber–physical testing has been applied for a decade in hydrodynamic laboratories to assess the dynamic performance of floating wind turbines (FWTs) in realistic wind and wave conditions. Aerodynamic loads, computed by a numerical simulator fed with model test measurements, are applied in real time on the physical model using actuators. The present paper proposes a set of short and targeted benchmark tests that aim to quantify the performance of actuators used in cyber–physical FWT testing. They aim at ensuring good load tracking over all frequencies of interest and satisfactory disturbance rejection for large motions to provide a realistic test setup. These benchmark tests are exemplified on two radically different 15 MW FWT models tested at SINTEF Ocean using a cable-driven robot. Full article
(This article belongs to the Special Issue Modelling Techniques for Floating Offshore Wind Turbines)
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Figure 1
<p>Generic control loop of cyber–physical testing.</p>
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<p>Figure shows n <math display="inline"><semantics> <mrow> <mo>(</mo> <mi>O</mi> <mo>,</mo> <msub> <mi>n</mi> <mn>1</mn> </msub> <mo>,</mo> <msub> <mi>n</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>n</mi> <mn>3</mn> </msub> <mo>)</mo> </mrow> </semantics></math> and b <math display="inline"><semantics> <mrow> <mo>(</mo> <mi>B</mi> <mo>,</mo> <msub> <mi>b</mi> <mn>1</mn> </msub> <mo>,</mo> <msub> <mi>b</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>b</mi> <mn>3</mn> </msub> <mo>)</mo> </mrow> </semantics></math> coordinate systems relative to each other.</p>
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<p>The power spectrum of the load applied: (<b>a</b>) FWT1 and (<b>b</b>) FWT2—low-frequency range. From top to bottom: surge, sway, roll, pitch, and yaw.</p>
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<p>The power spectrum of the load—wave-frequency range: (<b>a</b>) FWT1; (<b>b</b>) FWT2. From top to bottom: surge, sway, roll, pitch, and yaw. Note that the scale on the <span class="html-italic">y</span>-axis is not the same across the plots.</p>
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<p>The power spectrum of the load—<math display="inline"><semantics> <mrow> <mn>3</mn> <mi>p</mi> </mrow> </semantics></math>-frequency range: (<b>a</b>) FWT1; (<b>b</b>) FWT2. From top to bottom: surge, sway, roll, pitch, and yaw.</p>
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<p>The power spectrum of the load—<math display="inline"><semantics> <mrow> <mn>6</mn> <mi>p</mi> </mrow> </semantics></math>-frequency range: (<b>a</b>) FWT1; (<b>b</b>) FWT2. From top to bottom: surge, sway, roll, pitch, and yaw.</p>
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<p>The Bode diagrams of the estimated transfer function between the commanded and measured force, (<b>a</b>) FWT1 and (<b>b</b>) FWT2, for each degree of freedom. The solid line is estimated from the benchmark chip test, and the dots represent the estimation during a wave and wind test under operating conditions. The latter is not displayed where the desired load was insignificant (as the ratio between measured and commanded would be singular).</p>
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<p>Overview of the requirements and benchmark tests.</p>
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<p>Chirp time series that consist of applying a constant amplitude load, centred on zero. First in surge, and then in sway at the tower top, at an increasing frequency.</p>
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<p>The FWT2, pitch decay test: (<b>a</b>) with the CDRP connected; (<b>b</b>) with the CDPR disconnected. The top plots show the pitch time series. The red crosses are the measured peaks, and the red stars are the fitted peaks at opposing peak locations.</p>
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<p>The motion power spectra (<b>a</b>) and time series (<b>b</b>) from tests with and without the CDPR connected—FWT1. Top: surge, mid: pitch, and bottom: yaw.</p>
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<p>The mooring line tension (<b>a</b>) spectra and (<b>b</b>) time series from the tests with and without the CDPR connected—FWT1.</p>
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<p>The tower base fore–aft bending moment: (<b>a</b>) the power spectrum; (<b>b</b>) the time series from the tests with and without the CDPR connected—FWT1.</p>
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<p>A close-up view of the fore–aft bending moment time series during a slamming event triggering tower vibrations—FWT1.</p>
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<p>Top: nacelle acceleration power spectrum (<b>a</b>) and time series (<b>b</b>); close-up of the acceleration spectrum for various frequency ranges: (<b>c</b>) LF, (<b>d</b>) WF, and (<b>e</b>) 3<span class="html-italic">p</span> and (<b>f</b>) 6<span class="html-italic">p</span>.</p>
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<p>The Bode diagrams of the average RAO between the commanded and measured <span class="html-italic">tensions</span> in the cables: (<b>a</b>) FWT1 and (<b>b</b>) FWT2. The grey background illustrates ±2 standard deviations to the average. Amplitude is denoted <span class="html-italic">T</span> and phase denoted <math display="inline"><semantics> <mi>ϕ</mi> </semantics></math>.</p>
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20 pages, 5239 KiB  
Article
A Wave Drift Force Model for Semi-Submersible Types of Floating Wind Turbines in Large Waves and Current
by Nuno Fonseca and Fatemeh H. Dadmarzi
J. Mar. Sci. Eng. 2024, 12(8), 1389; https://doi.org/10.3390/jmse12081389 - 14 Aug 2024
Cited by 1 | Viewed by 1151
Abstract
The correct prediction of slowly varying wave drift loads is important for the mooring analysis of floating wind turbines (FWTs). However, present design analysis tools fail to correctly predict these loads in conditions with current and moderate and large waves. This paper presents [...] Read more.
The correct prediction of slowly varying wave drift loads is important for the mooring analysis of floating wind turbines (FWTs). However, present design analysis tools fail to correctly predict these loads in conditions with current and moderate and large waves. This paper presents a semi-empirical method to correct zero-current potential-flow quadratic transfer functions (QTFs) of horizontal wave drift loads in conditions with current and moderate and large waves. The method is applicable to column-stabilized types of substructures or semi-submersibles. In the first step, the potential-flow QTF is corrected for potential-flow wave–current effects by applying a heuristic method. Second, the generalized Exwave formula corrects for viscous drift effects. Viscous drift effects become important for moderate and large waves. Conditions with current in the same direction as the waves increase the viscous drift contribution further. The method is validated by comparing QTF predictions with empirical QTFs identified from model test data for the INO Windmoor semi. While potential-flow QTFs agree well with the empirical data for small seastates without current, they underestimate the wave drift loads for moderate and large seastates. Conditions with current increase the underestimation. The semi-empirical correction method significantly improves predictions. Full article
(This article belongs to the Special Issue Modelling Techniques for Floating Offshore Wind Turbines)
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Figure 1
<p>INO Windmoor 1:40 scaled model.</p>
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<p>Surge wave drift force QTF real and imaginary parts (kN/m<sup>2</sup>). Comparison between empirical values (black lines) and potential-flow predictions (gray lines). Tests 4050 to 4525 with Hs = 2.0 m, Tp = 7 s, heading = 0 deg.</p>
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<p>INO Windmoor semi body mesh and free surface mesh (<b>left</b>) and control surface mesh (<b>right</b>).</p>
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<p>Convention for the coordinate systems, heading angles and LF velocities.</p>
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<p>Real and imaginary parts of the surge QTF for the INO Windmoor semi and wave heading of 0 degrees. Continuous lines represent zero-current potential-flow results and the dashed lines represent the potential-flow QTF corrected for wave–current effects by the heuristic method.</p>
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<p>Real part of the surge QTF (kN/m<sup>2</sup>); gray lines represent uncorrected potential-flow predictions and black lines represent empirical results. Hs = 6.2 m, Tp = 9.0 s. Heading = 0 deg. and Uc = 0 for the upper plots and Uc = 1.2 m/s for the lower plots.</p>
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<p>Imaginary part of the surge QTF (kN/m<sup>2</sup>); gray lines represent uncorrected potential-flow predictions and black lines represent empirical results. Hs = 6.2 m, Tp = 9.0 s. Heading = 0 deg. and Uc = 0 for the upper plots and Uc = 1.2 m/s for the lower plots.</p>
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<p>Flowchart representing the procedure to correct potential-flow QTFs for moderate and severe seastates with current.</p>
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<p>Modulus of the surge QTF (kN/m<sup>2</sup>) for four moderate and severe seastates without current (Hs = 6.2 m, Tp = 9 s; Hs = 6.2 m, Tp = 12 s; Hs = 11.0 m, Tp = 12 s; Hs = 15.0 m, Tp = 14 s). Comparison between empirical coefficients and predictions by two force models.</p>
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<p>Modulus of the surge QTF (kN/m<sup>2</sup>) for four moderate and severe seastates without current (Hs = 6.2 m, Tp = 9 s; Hs = 6.2 m, Tp = 12 s; Hs = 11.0 m, Tp = 12 s; Hs = 15.0 m, Tp = 14 s). Comparison between empirical coefficients and predictions by two force models.</p>
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<p>Real part, imaginary part and modulus of the surge QTF (kN/m<sup>2</sup>). Comparison between empirical coefficients and predictions by three force models. Hs = 6.2 m, Tp = 9.0 s, Uc = 1.2 m/s.</p>
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<p>Real part, imaginary part and modulus of the surge QTF (kN/m<sup>2</sup>). Comparison between empirical coefficients and predictions by three force models. Hs = 11.0 m, Tp = 12.0 s, Uc = 1.2 m/s.</p>
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Review

Jump to: Research

37 pages, 4699 KiB  
Review
Coupled Aero–Hydrodynamic Analysis in Floating Offshore Wind Turbines: A Review of Numerical and Experimental Methodologies
by Jinlong He, Xuran Men, Bo Jiao, Haihua Lin, Hongyuan Sun and Xue-Mei Lin
J. Mar. Sci. Eng. 2024, 12(12), 2205; https://doi.org/10.3390/jmse12122205 - 2 Dec 2024
Viewed by 1329
Abstract
Floating offshore wind turbines (FOWTs) have received increasing attention as a crucial component in renewable energy systems in recent years. However, due to the intricate interactions between aerodynamics and hydrodynamics, accurately predicting the performance and response remains a challenging task. This study examines [...] Read more.
Floating offshore wind turbines (FOWTs) have received increasing attention as a crucial component in renewable energy systems in recent years. However, due to the intricate interactions between aerodynamics and hydrodynamics, accurately predicting the performance and response remains a challenging task. This study examines recent advancements in the coupled aero–hydrodynamic numerical simulations for horizontal-axis FOWTs, categorizing existing research by coupling methods: uncoupled, partially coupled, and fully coupled. The review summarizes models, methodologies, and key parameters investigated. Most partially coupled analyses rely on forced oscillation, while the interplay between aerodynamics and elasticity, as well as interactions among multiple FOWTs, remain under-explored. Additionally, this review describes relevant physical model tests, including wave basin tests, wind tunnel tests, and real-time hybrid tests (RTHT). Although RTHT faces issues related to system time delays, they have garnered significant attention for addressing scale effects. The paper compares the three coupling methods, emphasizing the importance of selecting the appropriate approach based on specific design stage requirements to balance accuracy and computational efficiency. Finally, it suggests future research directions, offering a meaningful reference for researchers engaged in studying the aero–hydrodynamic behavior of FOWTs. Full article
(This article belongs to the Special Issue Modelling Techniques for Floating Offshore Wind Turbines)
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<p>Different types of FOWTs: (<b>a</b>) HAWT and VAWT; (<b>b</b>) floating support platforms.</p>
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<p>Changes in the flow field due to the pitching motion of the platform [<a href="#B4-jmse-12-02205" class="html-bibr">4</a>].</p>
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<p>Vorticity fields and streamlines at the wind speed of 4.5 m/s [<a href="#B88-jmse-12-02205" class="html-bibr">88</a>]. (<b>a</b>) fixed wind turbine, (<b>b</b>) floating wind turbine.</p>
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<p>Results of vorticity iso-volumes between 11.5 s and 13.0 s, in which blade vortex interaction at the tip, as well as flow recirculation at the root, is seen to occur in the 12.5 s and 13.0 s snapshots, reflecting VRS conditions: (<b>a</b>) 11.5 s; (<b>b</b>) 12.0 s; (<b>c</b>) 12.5 s; (<b>d</b>) 13 s [<a href="#B87-jmse-12-02205" class="html-bibr">87</a>].</p>
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<p>The model of a floating wind turbine supported by the X30 platform [<a href="#B101-jmse-12-02205" class="html-bibr">101</a>].</p>
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<p>Schematic diagram of working condition combinations [<a href="#B98-jmse-12-02205" class="html-bibr">98</a>].</p>
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<p>The Contour of Vortex (Q = 0.25) depicted by the velocity component (Ux), with the free surface colored according to surface elevation across one wave period [<a href="#B103-jmse-12-02205" class="html-bibr">103</a>].</p>
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<p>The platform model of Biomimetic Leaf–Vein Branch Fractal under random fractal and regular fractal [<a href="#B122-jmse-12-02205" class="html-bibr">122</a>].</p>
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