As offshore oil and gas exploration extends into deeper waters, fixed platforms are becoming less suitable, while semi-submersible platforms are gaining wider application owing to their strong wave resistance and deepwater adaptability. This paper presents a dynamic positioning control strategy for semi-submersible offshore platforms, combining an Extended Kalman Particle Filter (EKPF) and Fuzzy Model Predictive Control (FMPC), to cope with input saturation and non-Gaussian measurement noise under complex environmental disturbances. Firstly, the EKPF is utilized to observe the state of the semi-submersible platform, thereby mitigating the adverse effects of measurement noise on the control performance. Meanwhile, a fuzzy algorithm is integrated into the model predictive control (MPC) framework to adaptively adjust the weight matrices in the cost function based on the state error and its rate of change, thereby enhancing adaptability to varying operational environments. Simulation results demonstrate that the use of the EKPF significantly improves control accuracy in both set-point regulation and trajectory tracking of the semi-submersible platform. Furthermore, they indicate that the FMPC strategy provides superior trajectory tracking performance compared to conventional Model predictive control.

To investigate the effect of column form on the hydrodynamic performance of semi-submersible truss fishery aquaculture platforms, this study focused on an active semi-submersible aquaculture platform located in the South China Sea. Three platform models featuring distinct column structures were established. Employing three-dimensional potential flow theory and Morrison’s equations, numerical simulation methods were utilised to analyse the dynamic response of the three types of column platforms in both the frequency and time domains under wind, wave, and current action. Consequently, relevant conclusions regarding the influence of column form on the hydrodynamic performance of semi-submersible platforms were derived. The results show that: The quasi-elliptical column platform exhibits superior frequency-domain response characteristics, with the circular column platform following, while the square column platform demonstrates the poorest performance. When subjected to the combined effects of waves and currents, the circular column platform shows the most favourable time-domain dynamic response, with the quasi-elliptical column platform next, and the square column platform lagging behind. In contrast, under the combined influence of wind, waves, and currents, the quasi-elliptical column platform excels in time-domain dynamic response, followed by the square column platform, with the circular column platform being the least effective. These variations in time-frequency dynamic response characteristics among the three column platforms are attributed to their distinct structural forms.

Investigation of Hydrodynamic Characteristics of a Conceptual Semi-Submersible Platform Through Experiments

Assessment of air gap prediction techniques and influencing factors for semi-submersible platform

Semi-Submersible Hybrid Platforms for Wind–Wave Hydrodynamic Performance: High-Fidelity Numerical Simulations powered by SPH

Time-domain dynamic response analysis of progressive mooring failure for deep-sea semi-submersible platforms

Digital twins (DTs) offer significant promise for condition-based maintenance of floating offshore wind turbines (FOWTs); however, existing solutions typically compromise either on physical rigor or real-time computational performance. This paper presents a real-time DT framework that resolves this trade-off by embedding a hydro-elastic reduced-order model (ROM) that accurately captures structural dynamics and fluid–structure interaction. Integrated in a cloud-ready Internet of Things architecture, the ROM reconstructs full-field displacements, von Mises stresses, and fatigue metrics with near real-time responsiveness. Validation on the 5 MW OC4-DeepCWind semi-submersible platform shows that the ROM reproduces finite-element (FEM) displacements and stresses with relative errors below 1%. A three-hour load case is solved in 0.69 min for displacements and 3.81 min for stresses on a consumer-grade NVIDIA RTX 4070 Ti GPU—over two orders of magnitude faster than the full FEM model—while one million fatigue stress histories (1000 hotspots × 1000 operating scenarios) are processed in 37 min. This efficiency enables continuous structural monitoring, rapid *what-if* assessments and timely decision-making for targeted inspections and adaptive control. By effectively combining physics-based reduced-order modeling with high-throughput computation, the proposed framework overcomes key barriers to DT deployment: computational overhead, physical fidelity and scalability. Although demonstrated on a steel platform, the approach is readily extensible to composite structures and multi-turbine arrays, providing a robust foundation for cost-effective and reliable deep-water wind-energy operations.

ABSTRACT To improve hydrodynamic performance of semi-submersible platforms, influence of a bilge keel on moonpool responses and six degrees of freedom (6-DOFs) motion characteristics of a conceptual semi-submersible platform equipped with a hollow moonpool were investigated experimentally in this work. Results indicate that moonpool responses are predominantly dominated by piston-mode motion and green-water phenomena occur with incident wave period of 14 s. The intensity of piston-mode motion of the platform with bilge keel is significantly reduced compared to the platform without bilge keel under same incident waves. Furthermore, Response Amplitude Operators (RAO) indicate that hydrodynamic performance of the platform equipped with bilge keel is better with respect to reduced heave and pitch amplitudes due to increased viscous damping. Amplitudes of sway and roll motions of the platform with bilge keel are also decreased in irregular waves.

Novel conceptual design and performance analysis of a semi-submersible platform for 22 MW floating offshore wind turbine

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 Fine tuning of numerical models of Floating Offshore Wind Turbine (FOWT) dynamics is crucial to increase their response accuracy with respect to experimental data but still remains a significant challenge due to the large number of parameters involved. This paper builds on the results from a recent experimental campaign conducted on a 1:96 Froude-scaled model of the DeepCwind semi-submersible platform with a taut mooring system, presenting the development and calibration of a numerical model, focusing on the platform motion response. A two-stage optimization algorithm is employed to estimate linear and quadratic global damping coefficients exclusively using response data from free decay tests. Three operational sea-state conditions and one extreme condition are simulated leveraging the calibrated model, and results compared against experimental findings for validation. This study offers an efficient and widely applicable methodology for enhancing numerical modeling of FOWT systems.

Hydrodynamic analysis and optimisation of a novel wind-wave hybrid system combined with the semi-submersible platform and various wave energy converters

ABSTRACT Floating offshore wind turbines (FOWTs) hold great potential in renewable energy. Heave plates are critical for enhancing platform stability. This study employs Computational Fluid Dynamics (CFD) to analyze free decay motions of semi-submersible platforms with different heave plate designs. Natural periods and damping coefficients are compared to identify the optimal configuration. Results reveal larger vortices around plates with greater edge ratios, improving damping performance. CFD findings are validated through wave basin decay tests, showing strong agreement. The best-performing design is further evaluated under operational and extreme conditions, including mooring line failure. Motion responses remain within acceptable limits, demonstrating robust stability. The study highlights the significant role of heave plate geometry in reducing platform motion and displacement, providing practical guidance for FOWT platform design and contributing to advancements in offshore wind technology.

With the increasing operational water depth, the non-stationary behavior of offshore floating structures has attracted significant attention. However, current detection methods for this behavior rely heavily on subjective judgment, limiting the understanding of motion mechanisms under non-stationary conditions due to the complexity of the operating environment. This paper proposes an algorithm for detecting the non-stationary behavior, emphasizing its impact on the behavior of offshore floating structures. The main contributions of this paper include (1) the development of an algorithm for detecting non-stationary behavior by constructing pseudo-distributions of motion responses using adaptive bootstrapping technology, thereby linking these pseudo-distributions to engineering intuition, and (2) the analysis of factors influencing non-stationary behavior using dimensionless analysis, as well as the exploration of the effects of marine environments and ancillary structures on structural non-stationary behavior. To demonstrate the correctness of the proposed algorithm, harmonic signals were first used to investigate the influencing factors, with the results compared to traditional methods. The numerical results demonstrate that the proposed algorithm effectively detects non-stationary behavior while being less impacted by timescale, sampling frequency, and environmental noise. Furthermore, the effects of marine environments, second-order wave forces, and ancillary structural failures on the non-stationary behavior were examined through both numerical and physical model experiments using a semi-submersible platform. The findings indicate that the proposed algorithm successfully detects non-stationary behavior and offers valuable insights for engineering applications, including assessing changes in marine environments and the integrity of mooring systems.

This study presents a detailed numerical investigation of a floating offshore wind turbine (FOWT) subjected to focused wave excitation, utilizing a high-fidelity, fully coupled aero-hydro-mooring computational fluid dynamics model implemented in OpenFOAM. The analysis focuses on the National Renewable Energy Laboratory 5-MW reference turbine mounted on a semi-submersible platform. The influence of wave focus positions, located upstream (FP-US), at the mid-position (FP-M), and downstream (FP-DS), is systematically evaluated in terms of platform motions, mooring line tensions, aerodynamic loading, and wake recovery behavior. Time–frequency spectrograms are employed to characterize the non-stationary and transient responses induced by the focused wave conditions. The results indicate that pitch motions are significantly amplified in the FP-US and FP-M cases compared to FP-DS, with strong pitch and surge coupling observed. Surge motions are also more pronounced in FP-US and FP-M, where low-frequency components corresponding to the natural surge frequency contribute to prolonged dynamic responses. Mooring line tensions follow a similar trend, with substantially higher loads in FP-US and FP-M due to intensified wave-induced excitation. Additionally, FP-US and FP-M demonstrate improved aerodynamic performance and wake recovery, although accompanied by increased aerodynamic fluctuations resulting from platform motions. These findings indicate the importance of accounting for wave focus positions to improve the FOWT design and performance, especially for long-term stability and efficiency.

Experimental and numerical investigations on hydrodynamic response of vessel-shaped semi-submersible aquacultural platform

Hydrodynamic model testing of a semi-submersible wind-tidal current combined power generation platform

Comparative analysis of three-column and three-column with central column semi-submersible platforms for floating wind turbines

Experimental study on the wave run-up of a semi-submersible platform under regular waves

To achieve efficient and sustainable marine aquaculture, STAR-CCM+ was used to simulate the internal and external field characteristics of a semi-submersible aquaculture platform based on a porous media model, focusing on the influence of incoming flow velocity and net solidity ratio. The results indicate that the flow field distribution around the platform exhibits no significant regularity and that low-velocity vortex regions are primarily concentrated near the pillars and nets. After velocity attenuation, the velocity reduction coefficients at the centers of the three cages are 90.26%, 63.65%, and 52.56%, respectively. Furthermore, the velocity attenuation inside the cages is minimally influenced by incoming flow velocity, with a maximum difference of 3.10%. In contrast, differences in net solidity ratio significantly affect velocity attenuation, particularly in downstream regions. The velocity reduction coefficient in the third cage varies by up to 43.25% depending on the net solidity ratio. These findings provide practical insights for the engineering design and application of aquaculture platforms.