Mooring System Research Articles

Detection of damage in the mooring systems of Floating Offshore Wind Turbines (FOWTs) is essential to guarantee operational reliability and reduce corrective maintenance costs. However, the complex nature of environmental conditions, the high costs of data collection, and the rarity of damage events make it challenging to obtain extensive labelled datasets. As a result, addressing damage detection from limited labelled data is necessary, yet it remains a relatively under-explored area in the literature. To tackle these challenges, this paper introduces an image-transformed semi-supervised generative adversarial network (ITSGAN) technique based on deep generative models. The method transforms time series data into multichannel image representations, enabling deep learning models to more effectively capture both spatial and temporal features. By combining adversarial training with supervised learning, ITSGAN leverages both labelled and unlabelled data to improve damage detection ability, particularly in scenarios where labelled data is scarce. A comparative analysis with established models such as traditional semi-supervised GAN, Deep Convolutional Neural Networks (DCNN), Support Vector Machines (SVM), and Extreme Gradient Boosting (XGB) shows that ITSGAN consistently outperforms these models in accuracy, precision, recall, and F1 score. It is also demonstrated that the proposed ITSGAN model preserves richer feature representations by transforming time series data into images, resulting in enhanced performance in damage detection tasks.

The numerical analysis technique is one of the primary methods for the design and development of floating offshore wind turbines (FOWTs). This study presents a detailed investigation into the influences of fully coupled and decoupled numerical analysis methods on the dynamic responses of a floating offshore wind turbine. The fully coupled analysis is implemented via bidirectional FAST-OrcaFlex co-simulation, considering the dynamic interaction between rotor operation and platform motions. The decoupled analysis is conducted using OrcaFlex for wave-induced response analysis, incorporating unidirectional imported FAST-based thrust time series. First, the numerical tools used for simulating fully coupled numerical model of OC5 DeepCwind are verified against published model test data, including free-decay test, white noise wave test and working condition test. Then, the fully coupled and decoupled numerical models are compared under wind fields of different turbulence intensities and wind speeds to reveal the dynamic coupling effects. The results indicate that the predictions of the decoupled model are more aligned with the experimental data compared to those of the fully coupled model under conditions of combined wave and steady winds. The differences between the fully coupled and decoupled models are minor under wave-only condition. However, under turbulent condition, the decoupled model overestimates surge by up to 10% and mooring tension by less than 5%, while pitch deviations can reach 17%. These findings support the use of the decoupled method in preliminary design stages—especially for mooring system optimal design—to save computational cost and time. For detailed designs involving turbulent winds, low-frequency structure response analysis or pitch-sensitive performance, the fully coupled approach is recommended to ensure accuracy. This study could offer practical guidance for selecting suitable numerical methods in FOWT design and analysis.

Adaptive tension-leg mooring system with sliding counterweights: a novel shallow-water solution for floating offshore wind turbines

Effects of water level variation on the response of mooring systems for offshore floating photovoltaic platforms

A new prediction strategy on the taut mooring system for FPSO considering dynamic stiffness of polyester ropes by long short-term memory method

Prediction of the dynamic response on the spread catenary mooring system for FPSO by long short-term memory method

Optimization of floating wind turbine mooring system under mooring failure condition based on machine learning

A global shape function method for efficient dynamic analysis of mooring systems

This paper presents a 16 MW typhoon-resistant Tension Leg Platform floating offshore wind turbine (TLP FOWT) designed for the South China Sea. The survivability of the TLP FOWT under extreme environmental conditions is investigated through an integrated time-domain coupled analysis numerical model. The accuracy of the numerical model is calibrated by comparing its results with experimental data. In comparisons of mooring system static stiffness tests and white noise tests, the results from the calibrated numerical model show good agreement with the experimental data. Regarding the free decay tests and the statistical time-domain response results, the most significant discrepancies are only 1.17% and 6.91%, respectively. Subsequently, the time-domain response of the numerical model was investigated under extreme South China Sea conditions, configured according to the IEC 61400-3-2 design load conditions. The safety of the design was then evaluated against ABS specifications. The analysis yielded maximum platform motion amplitudes and inclinations of 34.99 m (less than 30% of water depth) and below 1°, respectively. Under both 50-year and 500-year return period conditions, the platform maintained stable TLP motion characteristics with no tendon slackness, evidenced by a minimum tendon tension of 107.23 kN. All motion responses and tendon tensions complied with the ABS safety factors, confirming the design’s capability to ensure safe operation throughout its service life. The present work provides valuable insights for the design and risk assessment of future large-scale TLP FOWTs.

Suction embedded plate anchors are widely used in deepwater mooring systems, which can withstand significant vertical loading. During the installation, the mooring chain is tensioned and causes the anchor to rotate, which is known as keying. With a large deformation finite element approach of the coupled Eulerian–Lagrangian method, the chain effects are incorporated into the keying of suction embedded plate anchors. The effectiveness of the proposed method is verified by numerical results and centrifuge tests. The numerical study reveals that the installation angle of the chain has a significant effect on the loss of embedment, especially combined with the effects of load eccentricity and soil strength. The losses of embedment are 0.024~0.273 and 0.217~1.755 anchor width for the installation angles of 15° and 90°, respectively. The ultimate bearing capacity factor decreases with the increasing of load eccentricity and soil strength, because a cavity is formed at the anchor back. Empirical formulae are finally developed for engineers to rapidly estimate the embedment loss and ultimate pullout capacity of suction embedded plate anchors.

Offshore wind turbines (OWTs) are being developed with larger capacities for deeper waters, facing complex environmental loads that challenge structural safety. In contrast to onshore turbines, OWT foundations must withstand combined hydrodynamic forces (waves and currents), leading to substantially higher construction costs. For floating offshore wind turbines (FOWTs), additional considerations include radiation hydrodynamic loads and additional hydrodynamic damping effects caused by platform motion. Dynamic analysis of these foundations remains a critical bottleneck, presenting new challenges for offshore wind power advancement. This article first introduces the main structural types of OWT foundations, with case studies predominantly from China. The remaining part of the article proceeds as follows: dynamics of fixed OWT foundations, dynamics of FOWT foundations, and conclusions. Next, it covers several important topics related to fixed offshore wind turbines, including pile–soil interaction, wave loads, and seismic analysis. It then discusses support platform motion analysis, hydroelastic analysis, and mooring system characteristics of floating offshore wind turbines. Finally, it presents some insights to improve design and optimization methods for enhancing the safety and reliability of offshore wind turbines. This research clarifies OWT foundation dynamics, helping researchers address challenges and optimize designs.

To address the issues of traditional mooring lines, such as high self-weight, low strength, and poor durability, Carbon-Fiber-Reinforced Polymer (CFRP) was investigated as a material for mooring lines of offshore floating wind turbines, aiming to achieve high performance, lightweight design, and long service life for mooring systems. Based on a “chain–cable–chain” configuration, a CFRP mooring line design is proposed in this study. Taking a 5 MW offshore floating wind turbine as the research object, the dynamic performance of offshore floating wind turbines with steel chains, steel cables, polyester ropes, and CFRP mooring lines under combined wind, wave, and current loads was compared and analyzed to demonstrate the feasibility of applying CFRP mooring lines by combining the potential flow theory and the rigid–flexible coupling multi-body model. The research results indicate that, compared to traditional mooring systems such as steel chains, steel cables, and polyester ropes, (1) under static water, the CFRP mooring system exhibits a larger static water free decay response and longer free decay duration; (2) under operating sea conditions, the motion response and mooring tension of the offshore floating wind turbine with CFRP mooring lines are smaller than those with steel cables and steel chains but greater than those with polyester ropes; and (3) under extreme sea conditions, the motion responses of the offshore floating wind turbine with CFRP mooring lines are smaller than those with steel wire ropes and steel chains but close to the displacement responses of the polyester rope system, while the increase in mooring tension is relatively moderate and the safety factor is the highest.

This study investigates the hydrodynamic loads of “Ningde No. 1” offshore aquaculture under current-only conditions using a fluid–structure interaction (FSI) approach with the computational fluid dynamics (CFD) solver OpenFOAM. A porous-media-based model is applied to simulate net-induced drag, while the rigid framework is resolved using a large eddy simulation (LES) turbulence model. A comprehensive set of 350 CFD simulations is performed, with varying flow velocities, flow directions, draft depths, and existence of nets. The results reveal that the load on this fishing facility in the streamwise direction (Fx) increases monotonically with flow velocity, direction, and draft. The lateral (Fy) and vertical (Fz) loads exhibit non-linear trends, peaking at a specific flow direction (approximately 60°) and draft levels (around 11.5 m). The fishing nets substantially increase the streamwise load by up to 80%, while their influence on the lateral forces is dependent on submergence depth. To efficiently predict hydrodynamic loads without performing additional and lengthy CFD simulations, a physics-informed neural network (PINN) is trained using the simulated data. The PINN model is found able to accurately reproduce the hydrodynamic force across a wide range of current conditions, offering a practical and interpretable surrogate approach for structural design optimization and mooring system development in offshore aquaculture industry.

Optimization and artificial intelligence integration for offshore mooring system design

With the rapid expansion of offshore wind power, efficient installation methods for 10 MW offshore wind turbines (OWTs) are increasingly being required. Conventional approaches using installation vessels, heavy-lift barges, and mooring systems incur high costs, long schedules, and weather-related constraints, particularly in harsh seas such as the West Sea and Jeju. This study investigates an anchor-free installation method for jack-up-type OWTs employing tugboats instead of specialized vessels. Environmental loads were estimated with MOSES and AQWA, and frequency-domain analyses were performed to evaluate wave responses and towline tensions. Results showed that maximum tensions remained below both the Safe Working Load of towlines and the Effective Bollard Pull of tugboats during all spudcan lowering stages. Even under conservative OPLIM conditions, feasibility was confirmed. The findings indicate that the proposed tug-assisted method ensures adequate station-keeping capability while reducing cost, construction time, and weather dependency, presenting a practical alternative for large-scale OWT installation.

Abstract In the pursuit of mitigating the wake effect, floating wind turbines have additional degrees of freedom compared to their fixed-bottom counterparts. The mooring system with which floating wind turbines are anchored to the seabed allows a range of motion in which turbines can be repositioned. Turbine repositioning uses yaw control to reposition floating wind turbines, and to thereby actively optimize the wind farm layout. Previous research has focused on obtaining optimal steady-state yaw angles for turbine repositioning by using steady-state wake models. Here, the primary conclusion is that mooring line tension needs to be relaxed to facilitate a range of movement large enough for steady-state turbine repositioning to be effective. The presented work studies the effect of using dynamic yaw signals for turbine repositioning by using a dynamic wake model. To study the effect of including wake dynamics, an optimization problem to find the optimal yaw control signals for a two turbine floating wind farm is solved for various mooring configurations. This work shows that for stiffer mooring configurations, turbine repositioning can still be leveraged to increase wind farm efficiency, but that the optimal yaw control action is dynamic for these cases.

Abstract Floating offshore wind turbines are subjected to hydrodynamic and aerodynamic loads, influencing the design of the anchor and mooring systems. A well-designed shared anchor system can reduce the needed number of anchors in a wind farm, potentially lowering costs. To facilitate a better understanding of the anchor loads, this study presents the dynamic simulation results of a prototype wind farm that consists of three 15 MW VolturnUS-S semi-submersible floating wind turbines in the North Sea. In the simulations, the wind turbines are parked, and collinear and misaligned wind and wave directions are considered. Compared with the anchors of a single turbine, the shared anchors in the wind farm experience a reduction in the peak anchor loads, and wind-wave misalignment may significantly increase the anchor loads. This study highlights the importance of considering multiple wind and wave directions and the misalignment in anchor load analysis, contributing to a better understanding of load distributions in floating wind farms aiding shared anchor system design.

Abstract The dynamic interaction between mooring system, floating platform, and wind turbines is complex, leading to greater uncertainties in design and higher operational and maintenance costs (OPEX). A potential solution to mitigate these uncertainties and reduce OPEX is the application of remote Structural Health Monitoring (SHM) systems. Among SHM techniques, Operational Modal Analysis (OMA) is particularly valuable for assessing the dynamic properties of structures under actual operating conditions. This research explores the reliability of detecting low-frequency modes of Floating Offshore Wind Turbines (FOWTs) using OMA. The analysis employs the Least Squares Complex Frequency (LSCF) algorithm and numerical sensor data. The NREL 5MW reference wind turbine mounted on the OC4 semi-submersible platform was used. Acceleration time-series signals were generated using the time-domain software OpenFAST at various points on the FOWT, simulating accelerometer placements. The pre-processed signals were then analyzed using the LSCF algorithm to estimate the natural frequencies and damping ratios of the low-frequency modes, including the first tower mode, via stabilization diagrams. Results showed that the LSCF algorithm successfully detected all low-frequency modes of the FOWT, up to the first tower bending modes. The study on window length sensitivity indicated that a window length above 600s is required for consistent modal parameter estimation. Additionally, the analysis of sensor placement revealed that placing translational and rotational accelerometers close to the platform provides good estimates of the platform low-frequency motions, particularly yaw.

Abstract This paper focuses on the impact of various wind and wave conditions on the motion, tower base forces/moments and mooring line tension of a reference Floating Offshore Wind Turbine (FOWT) platform. The simulations are performed using OpenFAST to assess a total of 576 operational and 576 damaged scenarios. Selected results are presented to assess the impact of three different hydrodynamic modelling: i) Linear Potential Flow (LPF) ii) LPF combined with Morison drag (hybrid) and iii) hybrid approach with the inclusion of Quadratic Transfer Function (QTF). The importance of including the Morison drag term is demonstrated by assessing the platform’s transient motion and the contribution of the heave disk to the heave motion. The impact of mean-drift from the difference-frequency second-order wave forces is evaluated by analysing the surge motion of the platform, comparing it with the LPF-only model. Power Spectral Density (PSD) of the tower base moment reveals several peaks in the frequency range corresponding to the contribution of the sum-frequency QTF. The impact of including QTF is more apparent for shorter wave periods. The loss of one mooring line has been found to increase the fairlead tension amplitude and induces higher load in the low-frequency region, visible on the PSD of the fairlead tension. Lastly, different wind directions are analysed to assess the impact of aerodynamic load to the mooring system, keeping the same wave direction. The wind-wave misalignment induces higher peak tensions in the lower frequency region, close to its surge natural frequency. The datasets containing a total of 1152 simulation cases results are made publicly available.

Analysis of mooring system for floating wind turbine based on macro-model of chain-seabed interaction