Sea State Research Articles

Assessment of joint distributions of wave heights and periods

Short-term joint distributions of wave heights and periods provide information about the sea surface that is needed for engineering applications. In recent years much effort has been invested in predicting and validating the (univariate) distributions of wave heights; however, the same cannot be said about the joint probability of wave heights and periods. Comparisons of the joint distribution models with field observations are quite limited in terms of both the duration of the data and the number of locations considered. In addition, the often-contradicting demands for longer sea-state records and stationarity in the datasets have presented researchers with a bit of a conundrum. It is likely that some previous studies that aggregated data from several non-stationary sea states might have yielded improper inferences. The current study attempts a robust assessment of the available theoretical distribution models utilizing an extensive dataset of wave measurements around the UK coast. The results indicate that the Zhang and Guedes Soares (2106) model generally performs the best, and is perhaps a notable improvement over the somewhat bleak outlook laid out for these types of models in earlier years. The results also suggest that the discrepancy between the models and the data arises primarily from the poor ability of the marginal period distributions to capture reality.

Moving ships detection via the trajectory feature extraction from spatiotemporal slices of infrared maritime videos

In practical application scenarios, maritime infrared videosoften contain different types of sea state scenes, weather conditions, shooting time, shooting distance, etc. In these different types of maritime videos, ship targets have great differences in size, grayscaledistribution and contrast, which brings difficulties to ship target detection.At the same time, the diversity of fluctuation, grayscale distribution and reflected light of the sea surface will bring unpredictable interference noise to ship target detection.How to accurately detect ship targets in complex and changeable maritime infrared videos is a challenging task and research focus.The key to achieving accurate ship detection is to extract robust target features that can effectively distinguish targets from all thebackground noises.In this paper, a novel infrared video ship target detection algorithm based on spatiotemporal slice target trajectory features extraction is proposed. The algorithm is very sensitive to real targets and has excellentanti-noise ability.The main innovation of the algorithm is to extract the target trajectory feature from the spatiotemporal slice of the sequence image and generate the trajectory feature map.We use the trajectory texture formed by the ship target in the spatiotemporal slice to extract the target feature, which can greatly suppress the background noise.The adaptive dilation linear model algorithm can effectively detect the target trajectory line in the spatiotemporal slice. In addition, we also make full use of the gradient of the target trajectory line to distinguish different target trajectory pixels, and propose an adaptive iterative dilation target region localization algorithm combined with gradient consistency.For object segmentation, we calculate the segmentation double-threshold using the adjacent surrounding background pixels of the target, so as to achievetarget segmentationof multiple grayscaledistribution types. Finally, in the comparison experiment, our algorithm shows superior target detection performance, especially when detecting ships from a large number of highlighted sea clutter background, the robust anti-noise ability of the algorithm can be highlighted.

Trajectory reconstruction of buoys using Qingdao harbour data: Filling missing buoy trajectories using LSTM-Attention model

In maritime operations, instances occur where vessels flee after colliding with buoys. Automatic Identification System (AIS) data collected from these buoys play a vital role in identifying the responsible party and determining liability. However, data from buoys can be lost in rough sea conditions and equipment failure, which makes it difficult to identify accidents where ships collide with buoys. To address this issue, this study proposes a model that combines Long Short-Term Memory Network (LSTM) with Multiple Attention mechanisms to reconstruct buoy trajectories with high precision. In this paper, the buoy trajectory reconstruction test is carried out using Qingdao Harbour Buoy 304 a case study, and the validation results show that the mean squared error (MSE) of this model is 12.15. In addition, the LSTM-Attention model shows a significant improvement in all the metrics compared with other models: compared with the Random sampling model, the mean absolute error (MAE) is improved by 75.15%, and the root mean squared error (RMSE) by 71.02%; MSE by 77.31%, MAE by 36.70%, and RMSE by 52.36% compared to the Cubic spline model; and MSE by 49.92%, MAE by 27.35%, and RMSE by 29.52% compared to the Hermite model. These results show that the LSTM-Attention model significantly improves the accuracy and reliability of trajectory reconstruction.

Male Patient having a Spigelian Hernia, Prince Osman Digna Referral Hospital, Port Sudan City, Red Sea State, Sudan; 2024: A Case Report

Background: Spigelian hernia is a rare type of abdominal hernias; it occurs through a defect in Spigelian aponeurosis of transverse abdominis (Spiegel's fascia). Methods: A 65 years old male, presented to our refer clinic at Prince Osman Digna Referral Hospital; Port Sudan City; Red Sea State; Sudan, on July 2024, complaining of lower abdominal swelling for 2 months without features of obstruction or strangulation; following heavy lifting, obvious during standing and walking, disappear when lying down; and was not associated with gastrointestinal track disturbances. Patient had history of recurrent repaired right inguinal hernia, para-umbilical hernia, and transurethral resection prostatectomy for Benign Prostatic Hyperplasia. No family history of similar conditions. Result: Abdominal examination showed: positive visible cough impulse revealed reducible mass at the left lower abdomen, oval in shape about 15*15cm, without features of peritonism. CT abdomen showed: left lower lateral abdominal wall hernia defect lateral to the rectus abdominis muscle measuring (3*3.7 cm) with hernia sac lie between the external and internal oblique muscles containing bowel loops. Patient diagnosed as Spigelian hernia and planned for mesh hernioplasty. Intra-operative findings revealed: the hernia sac passed through the internal oblique and transverse abdominis muscles, it contained sigmoid colon which released smoothly, sac excised, external oblique aponeurosis sutured by nylon 2, prolene mesh fix onlay, no intraoperative complications. Post-operative course was smooth. Conclusion and recommendations: Spigelian hernia has to be suspected among patients having repeated abdominal hernias. Early diagnosis using CT Abdomen and urgent surgical intervention for such cases were highly recommended.

Marine Operations in the Norwegian Sea and the Ice-Free Part of the Barents Sea with Emphasis on Polar Low Pressures

The Arctic Seas are attractive for shipping, fisheries, and other marine activities due to the abundant resources of the Arctic. The shrinking ice cover allows for the opening of activities in increasingly larger areas of the Arctic. This paper evaluates the possibility of executing all-year complex marine activities, here termed “marine operations”, in the Norwegian Sea and the ice-free part of the Barents Sea. The approach used during the preparation of this review paper is to identify constraints to marine operations so users can be aware of the limitations of performing such operations. The weather conditions in the Norwegian Sea and the Barents Sea are well known, and these seas are considered representative of ice-free or partly ice-free Arctic Seas with considerable marine activities. Similar conditions could be expected for other Arctic Seas during periods without ice cover. Marine operations require safe and stable working conditions for several days. The characteristics of marine operations are discussed, and the particulars of the Norwegian Sea and the Barents Sea physical environments are highlighted. Emphasis is on the wind and wave conditions in unpredictable polar low-pressure situations. Furthermore, situations with fog are discussed. The large uncertainties in forecasting the initiation and the tracks of polar lows represent the main concern for executing marine operations all year. Improvements in forecasting the occurrence and the path of polar lows would extend the weather window when marine operations could be carried out. Discussions of the potential for similar conditions in the wider Arctic Seas during ice-free periods are presented.

On the distribution of ocean wave crest heights in varying wave conditions

AbstractThis paper addresses the statistical distribution of wave crest heights in ocean environments. This is much needed in several engineering applications including risk and reliability assessment of marine and coastal structures and is an important input for design of ocean structures. However, even though crest height distributions have received a lot of attention within both academia and the industry, current state-of-the-art models have notable shortcomings and do not describe the distribution of crest heights well in all sea states. In particular, commonly used models do not accurately describe the upper tail in certain unstable wave conditions. This will be addressed in this paper, which investigates in what sea-state conditions, established crest height distributions describe the data well and under what conditions, these models fail to fit well to the data. A large dataset of crest heights observed in different sea states is analyzed, and various goodness-of-fit tests are applied to determine when the different statistical models are appropriate. Then rejection rates of the various statistical models will be linked to selected sea-state parameters to identify wave conditions where alternative statistical models are needed. Results from this study indicate that the well-known Forristall distribution, which is known to capture second-order effects well, fails to perform well in some sea states. Different variants of the Tayfun–Fedele distribution are also analyzed, and results suggest that this represent a slight improvement. Somewhat surprisingly, sea-state parameters such as significant wave height ($$H_S$$ H S ), significant wave steepness ($$S_1$$ S 1 ), and the Benjamin–Feir index (BFI) do not seem to be very influential on the probability of rejecting these distributions, even though empirical skewness and kurtosis play a significant role. The implications of this for describing the distribution of crest heights well in certain sea-state conditions are discussed.

The annual cycle and sources of relevant aerosol precursor vapors in the central Arctic during the MOSAiC expedition

Abstract. In this study, we present and analyze the first continuous time series of relevant aerosol precursor vapors from the central Arctic (north of 80° N) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. These precursor vapors include sulfuric acid (SA), methanesulfonic acid (MSA), and iodic acid (IA). We use FLEXPART simulations, inverse modeling, sulfur dioxide (SO2) mixing ratios, and chlorophyll a (chl a) observations to interpret the seasonal variability in the vapor concentrations and identify dominant sources. Our results show that both natural and anthropogenic sources are relevant for the concentrations of SA in the Arctic, but anthropogenic sources associated with Arctic haze are the most prevalent. MSA concentrations are an order of magnitude higher during polar day than during polar night due to seasonal changes in biological activity. Peak MSA concentrations were observed in May, which corresponds with the timing of the annual peak in chl a concentrations north of 75° N. IA concentrations exhibit two distinct peaks during the year, namely a dominant peak in spring and a secondary peak in autumn, suggesting that seasonal IA concentrations depend on both solar radiation and sea ice conditions. In general, the seasonal cycles of SA, MSA, and IA in the central Arctic Ocean are related to sea ice conditions, and we expect that changes in the Arctic environment will affect the concentrations of these vapors in the future. The magnitude of these changes and the subsequent influence on aerosol processes remains uncertain, highlighting the need for continued observations of these precursor vapors in the Arctic.

Experimental Investigation of Nonlinear Forces on a Monopile Offshore Wind Turbine Foundation Under Directionally Spread Waves

Abstract Accurate prediction of nonlinear wave loading is crucial for designing marine and offshore structures, yet it remains a challenging task. Prior research has primarily focused on uni-directional extreme sea states, revealing that linear loading cannot accurately represent the total wave forces acting on offshore wind turbine foundations, with significant contributions from high-order harmonics. This study broadens the scope to include multi-directional and bi-directional wave interactions with monopile offshore wind turbine foundations. We use a phase-based harmonic separation method to isolate harmonic components in the presence of complex wave scenarios. This approach allows for the clear delineation of individual harmonics from the total wave force by controlling the phase of incident focused waves. Remarkably, this method shown effective even with multi-directional and bi-directional spreading. The clean separation of individual harmonics enables the estimation of contributions from each harmonic. Our findings are in line with previous research, showing that nonlinear loading can constitute up to 40% of the total under certain wave conditions. We have also observed that wider wave spreading reduces nonlinear high-order harmonics, and uni-directional waves induce the most severe nonlinear forces. These insights emphasise the importance of accounting for high-order nonlinear wave loading in offshore structure design.

Anomalous Diffusion by Ocean Waves and Eddies

Understanding the dispersion of floating objects and ocean properties at the ocean surface is crucial for various applications, including oil spill management, debris tracking and search and rescue operations. While mesoscale turbulence has been recognized as a primary driver of dispersion, the role of submesoscale processes is poorly understood. This study investigates the largely unexplored mechanism of dispersion by refracted wave fields. In situ observations demonstrate significantly faster and distinct dispersion patterns for objects influenced by wind, waves and currents compared to those solely driven by ocean currents. Numerical simulations of wave fields refracted by ocean eddies corroborate these findings, revealing diffusivities that exceed those of turbulent diffusion at scales up to 10 km during energetic sea states. Our results highlight the importance of ocean waves in dispersing surface material, suggesting that refracted wave fields may play a significant role in submesoscale spreading. As atmospheric forcing at the ocean surface will only strengthen due to anthropogenic contributions, additional research into wave refraction is necessary. This requires concurrent high-resolution measurements of wind, waves and currents to inform the revisions of large-scale coupled models to better include the submesoscale physics.

Predefined-Time Hybrid Tracking Control for Dynamic Positioning Vessels Based on Fully Actuated Approach

This study investigates the problem of tracking the trajectory of a dynamic positioning (DP) ship under sudden surges of elevated sea states. First, the tracking problem is reformulated as an error calibration problem through the introduction of fully actuated system (FAS) approaches, thereby simplifying controller design. Second, a predefined-time control term is designed to maintain the convergence time of the trajectory tracking error within a specified range; however, the upper bound of the perturbation must be estimated in advance. The high sea state during operation can result in an abrupt change in the upper bound of disturbance, thereby affecting the control accuracy and stability of the system. Therefore, a linear control matrix is developed to eliminate the system’s dependence on the estimation of the upper bound of disturbance following smooth switching, thereby achieving control decoupling and providing a conservative switching time. Additionally, a nonlinear reduced-order expansion observer (RESO) is constructed for feedforward compensation. The stability of the system is demonstrated using the Lyapunov function, indicating that the selection of appropriate poles can theoretically enhance the system’s convergence with greater control accuracy and robustness after switching. Finally, the effectiveness of the proposed method is validated through simulations and comparative experiments.

Analyzing AIS and wave hindcast data for global wave scatter diagrams with seasonality

Global scatter diagrams are used to estimate possible ship motions in a specified route and are required for comprehensive cargo-loading considerations of merchant ships. This study aims to update global wave scatter diagrams using the latest wave hindcast and Automatic Identification System (AIS) data. The AIS data for over 7500 merchant ships were collected between 2015 and 2022. The wave hindcast data ECMWF Reanalysis v.5 (ERA5), preferred for its recent coverage, were adjusted based on CCI satellite data. The duration of the AIS data is much shorter than the design lifetime of merchant ships, which is generally 25 years. This study found almost linear relationships between the maximum significant wave heights in storms and the generalized extreme value (GEV) parameters representing the distribution of encountered significant wave heights, with adjustments made for seasonality and tropical cyclones. By simulating the parameters based on these relationships and the wave hindcast data over 25 years, the encountered significant wave height distributions over 25 years were obtained. The results indicated a reduction in extremely significant wave heights compared with the BMT-GWS, in agreement with previous studies. This study also found that the difference in the wave period distribution between natural and encountered sea states was small in most sea areas for all significant wave height levels. Taking advantage of the abundant data volume of ERA5, this study adopted an empirical distribution of the wave period conditioned by the significant wave height. The novelty of this study is that we obtained wave scatter diagrams globally by month to consider the seasonal effect in detail and evaluated the confidence interval of the encountered wave height in its probability tail. In addition, this study quantifies the uncertainty of the wave height distribution by Monte Carlo simulation, which is not within the scope of previous studies on wave scatter diagrams based on the significant wave heights encountered by merchant ships around the world.

Impact of altimeter-buoy data-pairing methods on the validation of Sentinel-3A coastal significant wave heights

Sea state information is critical for a broad range of human activities (e.g. shipping, marine energy, marine engineering) most of them being concentrated along the coastal zone. Satellite altimeter records of significant wave heights (SWH) represent the largest source of sea state observations available to date. However, the quality of altimeter observations is reduced in the coastal zone due to surface heterogeneity within the radar signal footprint. Major difficulties to assess the performance of coastal altimetry in the coastal zone are the reduced number of valid altimeter records and the increased sea state variability, which have recently fostered the development of new methods to pair and compare nearby altimeter and buoy data. In this study, we use a high-resolution numerical wave model implemented over the European coastal waters in order to characterize the spatial variability of sea states in the proximity of coastal in situ buoys, we explore different model-based data-pairing methods to account for coastal sea state variability and we assess their impact on the validation of Sentinel-3A 20Hz SWH measurements. Three Sentinel-3A processing modes are considered: the pseudo low rate mode processing, the SAR processing and the Low Resolution with Range Migration Correction (LR-RMC) processing. Our results indicate major impacts of data-pairing methods on the Sentinel-3A coastal validation and reveals the contribution of more frequent low SWH conditions, poorly resolved by radar altimeters, in the coastal zone as an additional source of errors in coastal altimetry.

A baroduric immobilized composite material promoting remediation of oil-polluted sediment at typical deep-sea condition: The performances and potential mechanisms

Contriving immobilized bioreagent is of great significance to enhance bioremediation of marine oil pollution. However, there remains a notable scarcity of correlational study conducted at deep sea condition. Herein, we first developed a baroduric microsphere encasing biotic and chemical materials to remediate oil-contaminated sediments at deep-sea microcosm. Total oil degradation efficiency of microsphere-treated group reached 71% within a month, representing an approximate 35% increase compared to natural remediation. Absorption and biodegradation by microsphere provided a comparable contribution to oil elimination. Together with scanning electron microscope observation, the physical mechanism was that the reticulate structure of microsphere surface facilitating oil adsorption and bacteria attachment. Via metabarcoding analysis for meta and metabolically-active microbes, we demonstrated the primary working center was located at the microsphere. Proteobacteria, Firmicutes, Bacteroidota and Desulfobacterota were the key activated bacteria. More importantly, we revealed the ecological mechanisms were associated with the following aspects: 1) the addition of microsphere significantly improved the metabolic activity of bacteria (particularly including several oil-degrading taxa); 2) the microspheres enhanced ecological stability and microbial functional diversification during bioremediation; 3) expressing activity of pathways involving oil component degradation, biosurfactant production, biofilm architecture, biogeochemical and energy cycling all were observed to be up-regulated in microsphere-treated samples. Altogether, our results provide important theoretical guidance and data support on application of immobilization technology in removing in-situ oil pollution of deep-sea sediment.

A two-stage deep learning architecture for detection global coastal and offshore submesoscale ocean eddy using SDGSAT-1 multispectral imagery

Submesoscale ocean eddies are essential oceanic phenomenon that control and influence the ocean energy cascade. Most existing eddy detection methods rely on low-resolution satellite altimeter data, which fail to capture submesoscale ocean features and oceanographic phenomena in shallow water. Introducing high-resolution multispectral data can alleviate these problems, yet it has been largely overlooked. A generalized and efficient deep learning architecture that combines developments in deep learning with Sustainable Development Goals Science Satellite 1 (SDGSAT-1) multispectral data from earth observations offers a potential pathway for more fine detection of ocean eddies. Considering that oceanic eddy exhibits spatially sparse characteristics on high-resolution remote sensing scenes, the oceanic eddy detection (OED) model suitable for global coastal and offshore regions is divided into two stages: eddy information judgment and eddy position determination. Correspondingly, SDGSAT-1 multispectral data from November 2021 to December 2022 were carried out to construct two submesoscale eddy datasets for training and testing each stage model. The union validation of multiple metrics demonstrates that the proposed OED model and its stage models achieve state-of-the-art (SOTA) performance, especially in optically complex coastal and offshore waters. We applied the model to real-world scenes captured by SDGSAT-1 in 2023, and found that the detected results were mainly located at the water depth below 200 m. The authenticity of the recognition results is validated using sea surface chlorophyll concentration, temperature, and topography data, indicating that the OED model has achieved remarkable effectiveness under various sea conditions. In addition, the temporal distributions and statistical characteristics of detected submesoscale eddies are analyzed over an extended period (November 2021 to November 2023). Finally, HISEA-2, Landsat-9, and Sentinel-2 served as testing grounds to validate the generalization of the proposed methodology, with experimental results demonstrating that the OED model possesses significant developmental potential for multi-source remote sensing data. This paper presents a comprehensive deep learning framework for the global-scale detection of submesoscale eddies and underscores the pivotal role of high-resolution multispectral imagery as an innovative data source for global coastal and offshore eddy identification.

A comprehensive numerical model for aero-hydro-mooring analysis of a floating offshore wind turbine

This paper presents a comprehensive study of a Floating Offshore Wind Turbine (FOWT), requiring multidisciplinary expertise in floating platform hydrodynamics, mooring system dynamics, and wind turbine aerodynamics. We introduce a fully coupled numerical model, focusing specifically on the NREL's (National Renewable Energy Laboratory's) 5 MW OC4 FOWT. The model is validated through both numerical simulations using the Computational Fluid Dynamics (CFD) based software OpenFOAM and experimental results. Key findings demonstrate the model's accuracy in forecasting the aerodynamic behaviors of the turbine, the platform's response to motions, and the behavior of the mooring system across diverse wind and sea state scenarios. Furthermore, the study enhances the understanding of FOWT's stability and efficiency by examining the influence of different Center of gravity (COG) heights. Results show that reduction in COG height has a minor effect on heave and surge motion but significantly decreases pitch motion and mooring line tension, thereby improving static stability and reducing the impact of wave loads on dynamic responses. Additionally, the results show that this reduction in COG height enhances the aerodynamic power output, suggesting that optimized FOWT designs could achieve improved energy capture efficiency. These insights optimize FOWT design and efficiency, enhancing renewable energy performance.

A Novel Sea State Classification Scheme of the Global CFOSAT Wind and Wave Observations

AbstractOcean waves are essential elements across the air‐sea interface, regulating momentum and energy transfer. The mixture of wind sea and ocean swell coupled with surface winds results in diverse sea state conditions that modify the local air‐sea interaction. Previous classifications of wind waves and swells are mostly binary that are insufficient to represent the complexity of sea states. In this study, we utilize wind and wave measurements from the China‐France Oceanography Satellite (CFOSAT) to construct an observational wind‐wave ensemble. Four key parameters: wind speed, significant wave height, inverse wave age, and spectral width are selected out of six variables based on their correlations. Employing the unsupervised learning of k‐means clustering, global sea states are categorized into six distinct classes. These classes, characterized by unique centroids and separated in the feature space, represent specific wind regimes and degrees of wave development. Global occurrence highlights that each sea state is region‐specific, bridging the spatial gap of swell and wind sea dominated areas, respectively. This new grouping scheme complements the traditional wind sea and/or swell classification by resolving the diversity of wave regimes. The six‐class classification enables us to identify transitional states and hybrid conditions that may have been overlooked in the binary classification scheme, which shall help investigate the impact of ocean waves on the air‐sea interaction under varying sea states.

Wind stress modification by offshore wind turbines: A numerical study of wave blocking impacts

Offshore wind energy, as a clean and renewable resource, offers numerous advantages over onshore wind energy due to higher wind speeds and greater turbine capacity. However, the inadequate representation of wave-atmosphere interaction within the marine-atmospheric boundary layer may constrain wind resource assessments and, consequently, the design and layout of offshore wind turbines. By using the third-generation spectral wave model WAVEWATCH III, high-resolution numerical experiments which are capable of resolving the wind turbine foundation have been conducted to explore the blocking impact of wind turbine foundation on downstream wind stress. The findings provided significant insights into the factors influencing this effect, including foundation diameter, sea state, water depth, and wave directional spreading. Specifically, higher model resolution enables a more detailed characterization of wind stress distribution behind wind turbines. Increasing the foundation diameter resulted in a reduction of downstream wind stress. Notably, changes in wind stress exhibit a strong dependence on the sea state. The use of double periodic boundary conditions for the simulation domain enables an approximate representation of the entire wind farm by using a single turbine. Model results indicate that after waves pass through 20 turbines, domain-averaged wind stress decreases by approximately 3%, a figure that increases to 6% after passing through 50 turbines. The findings suggest the need to explore to what extent the changes in wind stress can alter wind profiles and how to parameterize the blocking impact of turbine foundations in wave models. This could have significant implications for wind farm site selection and layout design.

Experimental decomposition of nonlinear hydrodynamic loads and hydroelastic responses in wave–structure interactions of monopile wind turbines

This study explores the nonlinear effects of hydrodynamic loads and hydroelastic responses in monopile-supported offshore wind turbines, with a focus on their harmonic structures. High-quality experimental data were collected in a shallow water basin across various irregular waves. Their harmonic components up to the fourth order were successfully isolated using a novel four-phase decomposition technique, which effectively extracts harmonics from random time series. The results highlight significant contributions of higher-order harmonics across various sea states. Specifically, two physical models were employed: a flexible monopile to capture structural hydroelastic deformations during large wave events and a rigid monopile to accurately estimate hydrodynamic loads without hydroelastic effects. Additionally, numerical results from fully nonlinear potential-flow calculations were compared, revealing that while the potential-flow solver underestimates total wave loading, especially for higher harmonics. In terms of the free-surface elevations and hydrodynamic forces, this study confirms that their higher-order harmonics align well with the scaling of their corresponding linear components in both amplitude and phase. This enables the prediction of higher-order profiles based solely on their linear components. However, this efficient model is inadequate for accurately estimating the higher-order harmonics of monopile's hydroelastic responses during these extreme wave events, highlighting the need for further refinement.

Multi-body dynamic assessment of vessel-floater accessibility for floating wind

Abstract The floating wind industry faces several challenges in the road map to full maturity of commercial-scale floating projects. Accessing the floating offshore wind turbines poses larger risks due to the added degrees of freedom of the platform, with respect to bottom-fixed technology. When a vessel approaches, the platform’s motion leads to the introduction of multi-body dynamic effects. This work deals with the modeling of the vessel-platform dynamics for the VolturnUS-S 15MW platform and IEA15MW Reference Wind Turbine and a generic Crew Transfer Vessel (CTV) by means of performing a fully coupled assessment. The hydrodynamic properties are computed by solving the multi-body radiation-difraction problem. The inertial and hydrodynamic properties are included in an OrcaFlex model to perform a time-domain analysis under several sea states. A P-controller represents the helmsman pushing the vessel against the access point. The contact forces are modeled using a linear fender system to represent slip-and-stick events during the CTV’s push-on maneuver. The resulting relative motions are analyzed, and industry-typical limits are considered to quantify accessibility levels. The results show that peak wave period and wave heading play a major role in the accessibility scores.

Reconstruction of Nearshore Surface Gravity Wave Heights From Distributed Acoustic Sensing Data

AbstractDistributed Acoustic Sensing (DAS) is a photonics technology converting seafloor telecommunications and optical fiber cables into dense arrays of strain sensors, allowing to monitor various oceanic physical processes. Yet, several applications are hindered by the limited knowledge of the transfer function between geophysical variables and DAS measurements. This study investigates the quantitative relationship between surface gravity DAS‐recorded wave‐generated strain signals along the seafloor and the pressure at a colocated sensor. A remarkable linear correlation is found over various sea conditions allowing us to reliably determine significant wave heights from DAS data. Utilizing linear wave potential theory, we derive an analytical transfer function linking cable deformation and wave kinematic parameters. This transfer function provides a first quantification of the effects related to surface gravity waves and fiber responses. Our results validate DAS's potential for real‐time reconstruction of the surface gravity wave spectrum over extended coastal areas. It also enables the estimation of waves hydraulic parameters at depth without the need from offshore deployments.