Sea State Research Articles

An Underactuated Cable-Driven Parallel Robot for Marine Automated Launch and Recovery Operations

Abstract This paper presents the feasibility study and preliminary testing of an underactuated cable-driven parallel robot for automated launch and recovery operations on the sea surface. The robot frame is mounted onto a primary vessel (PV) subject to sea-induced motions. During launch, the end-effector (EE) is required to deploy a secondary vessel (SV) by lowering it from the PV onto the sea surface. During recovery, the ee has to track and grasp a SV and the EE-SV assembly needs to be stabilized during lifting from the sea surface to the PV. Sea conditions and the underactuated nature of the ee influence the operational feasibility and the overall robot performance. The paper presents the conceptual design and the robot model, as well as the methodologies for winch dimensioning and robot control. An extensive simulation campaign is conducted to optimize performances and assess the system behavior. Finally, the operations are tested on a scaled prototype in a laboratory environment.

A long sequence time-series forecasting model for ship motion attitude based on informer

Influenced by marine environmental factors, a ship sailing at sea will experience six degrees of freedom oscillating motions. These oscillating motions pose safety risks to ship navigation and maritime operations. Especially in severe weather conditions, these oscillating motions have a significant impact on the takeoff and landing of carrier aircraft, as well as the launch of carrier missiles. Therefore, studying and forecasting the ship motion attitude in wind and waves holds immense significance. This paper presents a sparrow search algorithm (SSA) optimized Informer model based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to forecast the long sequence time-series of ship motion attitude. Firstly, the ship motion attitude time series, as measured by the inertial navigation system, is decomposed using CEEMDAN to obtain several intrinsic mode functions (IMFs) and a residual. Then, the IMFs and residual are fed into SSA-Informer, where SSA is used to optimize the hyperparameter of Informer. Finally, the forecast values of IMFs and residual are superimposed and reconstructed to get the ship motion attitude forecasting result. The forecasting experiment under slight, moderate and rough sea conditions in the East China Sea shows that the proposed model achieves better performance and longer forecasting time compared with other popular methods.

On the spectral wave climate of the French Atlantic Ocean

The accurate description of wave climate at different spatio-temporal scales requires the application of advanced statistical models together with a good knowledge of geophysical processes. Furthermore, accurate modelling of multimodal sea states is of primary importance for most of offshore and coastal activities, such as wave energy device optimization, maritime design practice and for safety at sea. The present manuscript is conceived within this scientific framework proposing to assess wave climate of a complex area of French Atlantic Ocean bordering seas. The main “Spectral Climatology Types” of the area are identified as resulting of defined combinations of wave systems detected through directional spectra and partitioned wave systems analysis. The presence of swell systems is evaluated quantitatively on the whole area, characterized by different regimes of multimodal sea-states at strong regional variability and put into relation with main meteorological forcing active on the area at different spatial scales. Celtic Sea exhibits a marked regional characterization with a prevalence of multimodal conditions given by different combination of wave systems with increasing contribution of swell systems moving from North-West to South. A significant presence of crossing sea states is observed in South Celtic Sea especially in proximity of bathymetric slope. The South Bay of Biscay is influenced by fully developed swell systems enhanced by refraction effects caused by both the coastline and bathymetry gradients. English Channel and North Sea show complex sea-states conditions induced by local topography features together with wind channelling and tide effects able to trigger geophysical processes at a sub-scale responsible for the development of multimodal seas. Crossing and bimodal seas are also found to be influenced by bathymetry gradients acting directly on the directional spectrum shape as well as by tide due to tidal current-induced refraction effect on wave propagation. No generalized significant trends are detected within the investigated spatial domain for the wave spectrum integral quantities; locations sited at northern Celtic Sea show a downward Significant Wave Height, while only locations confined at eastern English Chanel only shows a Peak Period upward trend.

Wave excitation force prediction for arrays of wave energy converters in directional waves

The implementation of advanced control strategies is an effective means of maximizing the energy production of wave energy converters (WECs), and most of them require future wave excitation forces to determine the optimal control sequence. The WECs deployed in arrays can enable a significant reduction in the cost of wave energy and improve prediction performance by incorporating excitation forces from the array. In this paper, a critical comparison of the excitation prediction methods, including the time series, machine learning, and neural network, for a two-body heaving point absorber WEC is presented. Considering the symmetry of the WEC and arrays, the directional spectrum is utilized to determine the reference measurement of wave excitation. The prediction methods are applied to isolated WEC and different array layouts. Moreover, additional sensitivity analyses are performed to evaluate the performance. The results show that the autoregressive with extra input (ARX) model has the best performance in short-term wave excitation force prediction. In most cases, the ARX model is weakly influenced by the sampling period and can adapt well to changes in the directional distribution and sea states of irregular waves, and the ARX model requires the least amount of computational time in the simulations.

Dynamic response analysis of a semisubmersible floating offshore wind turbine subjected to mooring line failure under normal and extreme environmental conditions

Floating offshore wind turbines (FOWTs) offer a significant opportunity for harnessing wind energy and achieving clean energy goals. This paper investigates the effects of mooring line failure in semisubmersible FOWTs under normal and extreme environmental conditions. The OC4 DeepCwind type semisubmersible with an NREL 5 MW wind turbine is considered for investigating the behavior of FOWT under intact and failed mooring lines. This study covers a wide range of environmental conditions, operational conditions of wind turbines, and mooring line failure scenarios. This paper investigates the mooring line failure effects on platform responses, mooring line fairlead tensions, and tower responses. The results show that the platform surge, heave, pitch responses, tower fore-aft displacement, base shear force in X-direction, and base moment in Y-direction are increased for upwind side mooring line failure during the operational condition of FOWT. Subsequently, the platform sway, roll, yaw responses, tower side-to-side displacement, base shear force in Y-direction, and base moment in X-direction are more during downwind side mooring line failure in the same environment. On the other hand, the impact of upwind side mooring line failure affects all 6 Degrees of Freedom (DOF) platform responses significantly during the parked state of FOWT. The maximum fairlead tensions observed in the remaining mooring lines remain below the mooring line breaking strength even after a mooring line failure during both operational and parked states of FOWT. It is also observed that the platform responses (excluding heave), tower responses, and fairlead tensions exhibit greater values when an extreme turbulence wind model is employed. The platform surge, heave, pitch responses, maximum fairlead tension, tower fore-aft displacement, and tower base moment in Y-direction show higher values under severe sea state condition.

Oceanic and atmospheric oxygenation during the late Ediacaran based on multiple isotope records from South China

The Neoproterozoic–Cambrian transition was a key period in Earth's history, particularly because changes in the oceanic redox environment were crucial to the Cambrian explosion of life. However, the redox state of the ocean during this transition is unclear. In this study, the carbonate strata of the Dengying Formation in Yunnan Province, South China, were subjected to δ98/95Mo, δ13C, 87Sr/86Sr, and trace element analyses. The low δ98/95Mo results (0‰ ∼ +2‰) of most samples indicate that a shallow-marine sedimentary environment dominated by low-O2 conditions during the late Ediacaran period (Dengying Formation), but a brief period of marine oxidation existed at this time, reflected by elevated δ98/95Mo values (+2.07‰ ∼ +2.43‰). At this time, δ13C values were increasing, which possibly indicate an increase in primary productivity and photosynthesis in shallow waters, causing oxidation of the shallow seawater. However, two anomalously high δ98/95Mo values (>2.65‰) could have resulted from additional isotope fractionation due to the upwelling of euxinic bottom waters abruptly. In addition, an increase in 87Sr/86Sr ratios lagged the δ13C and δ98/95Mo changes, suggesting that atmospheric changes appear to have lagged oceanic oxidation, but more evidence are needed to prove the relationship. The dynamic changes in the redox conditions of the shallow sea during deposition of the Dengying Formation provided favorable conditions for changes in the atmosphere and the Ediacaran biota.

A new approach for the assessment of coastal flooding risk. Application in Rhodes island, Greece

A directional, copula-based, Monte Carlo approach is proposed for the quantitative assessment of a new definition of coastal flooding risk, namely a probability-based index due to extreme combinations of wave conditions and sea levels, which could be a key element for coastal zone planning and management. This approach differs from the standard practice, which focuses on the extreme events and studies either their specific return values or their worst-case scenarios. The adopted approach incorporates mean wave direction as a covariate into the probabilistic representation of sea states, and via the use of a variety of probabilistic and statistical tools, represents a total of five stochastic variables, namely the significant wave height, the peak wave period, the mean wave direction, the storm surge, and tide. Two directional, alternative methods have been developed; a trivariate copula- and a bivariate copula-based method, that seemed to produce quite similar results. Four types of copulas have been examined for their goodness-of-fit, i.e., three Archimedean copulas, namely, the Clayton, the Gumbel, and the Frank copulas, as well as the elliptical Gaussian copula. A comparative analysis of the two methods is performed aiming to point out their pros, as well as their accuracy and complexity issues. The application of the proposed method to the natural beaches of the Rhodes Island in Greece, in combination with a recently developed formula for wave run-up, highlighted the most crucial parameters affecting the coastal flooding risk in the study area.

Future offshore wind energy evolution in the Bay of Biscay

A relevant point near the Biscay Marine Energy Platform (BiMEP) has been chosen and data from the ERA5 reanalysis and CMIP6 datasets in future SSP5-85 scenario (wind and wave data) have been used to analyse the energy potential and its trends from 2015 to 2100 for wind energy. A 15 MW wind turbine has been chosen in line with current technological state-of-the-art and needs, and its energy production has been computed considering the corresponding power curve, and the wind speed at its hub height based on the variation of sea roughness due to the sea state (wave height and period). The results, although most of them have not been relevant, have shown a slightly downward trend mostly on winter in all parameters analysed: mean wave period (Tm), significant wave height (Hs), corresponding sea roughness (z0), and wind speed at hub height (Ux). The 15MW wind turbine simulation has therefore shown a small decrease in energy production.

Research on path following control of unmanned ship based on fast wave inversion disturbance compensation and preset performance

In this paper, wave inversion is innovatively applied to the path following control of unmanned ship for the first time. At the same time, the performance constraint problem and input saturation of the control system are considered, and the model uncertainty problem of the system is solved by improving the RBF algorithm. Firstly, the system identification method is used to obtain the wave information in real time and quickly based on the ship motion response under the current sea condition, and the disturbance compensation is carried out in the unmanned ship control system. Secondly, in order to ensure the safety and stability of the unmanned ship during navigation, the performance constraints of the unmanned ship path following control system are carried out. In addition, considering the external disturbance and model uncertainty, the RBF neural network control algorithm based on the predictor estimation error is designed, which greatly improves the transient performance of the controller. Finally, the stability analysis and simulation comparison test verify the correctness and feasibility of the proposed control strategy.

Factors influencing water strategy objectives fulfillment: A survey findings from Sudan

AbstractChallenges faced by countries in their struggle for economic and social development are increasingly related to water. Developing and managing water resources requires an appropriate water strategy. However, many factors influence the achievement of desired goals of water strategies. This qualitative study analyzes factors influencing water strategies to promote appropriate water management. Data was collected during 2019 from 10 states of North Kurdufan, White Nile, Gezira, Sennar, Gedarif, Khartoum, Kassala, Red Sea, River Nile, and Northern state in Sudan. A total of 300 people including water officials, water supply engineers, and community leaders were interviewed. Water availability, community participation, coordination between water institutions, integrated water resources management (IWRM), and finance were identified as factors influencing water strategy objectives fulfillment. Out of 300 respondents in all states, a group of 149 (49.7%), mentioned that water strategy objectives were fulfilled and more than half of the respondents 151 (50.3%) evaluated that water strategy objectives were not fulfilled. A multiple regression statistically significantly predicted water strategy objective achievement, F (5, 295) = 57.6314 p < .005, R = .704. R2 = .485, from water availability, coordination between water‐related institutions, IRWM, and availability of finance. Results show that community participation, water availability, coordination between water‐related institutions, and availability of finance are insignificantly (p > .005) influenced water strategy objective fulfillment. The findings will contribute to the social dimension of water resources management and development.

Data-based modelling of arrays of wave energy systems: Experimental tests, models, and validation

One of the key steps towards economic feasibility of wave energy conversion technology concerns scaling up to farms of multiple devices, in the attempt to reduce installation costs by sharing infrastructure, and a consequent drop in levelised cost of energy. Moreover, whenever wave energy systems are deployed in proximity (in so-called arrays), the exploitation of the hydrodynamic interactions between single devices is fully enabled, potentially increasing the final energy outcome. To achieve this in real (operational) time, the employed energy-maximising control strategies require control-oriented array models, able to efficiently describe the dynamics of these interconnected systems in a representative fashion. This can be, nonetheless, a difficult task when considering first principles alone, under small motion assumptions, for modelling purposes. Recognising the uncertainty associated to array numerical models obtained from the linearisation of simplified system equations around their equilibria, this paper presents models of several array configurations identified following a frequency domain approach on the basis of experimental data. Tailored tests on laboratory-scale devices have been designed and conducted in the Aalborg University (Denmark) wave tank facility, with the purpose of performing representative system identification of the wave energy systems arrays. The obtained models are validated on different representative sea states configurations, in controlled and uncontrolled motion operational conditions. The validation results are fully discussed and analysed in terms of standard error measures and time lag, while the obtained models are made freely accessible via a linked repository (named OCEAN), in the attempt to openly provide validated models for different array configurations.

Contributions of atmospheric forcing and ocean preconditioning in the 2016 Antarctic sea ice extent drop

The 2016 Antarctic sea ice extent (SIE) drop was a rapid decrease that led to persistent low sea ice conditions. The event was triggered by atmospheric anomalies, but the potential preconditioning role of the ocean is unsettled. Here, we use sensitivity experiments with a fully-coupled regional climate model to elucidate the impact of the ocean conditions on the drop and on the persistence of the negative SIE anomalies during 2017. In particular, we re-initialize the model in January 2016 using different ocean and sea ice conditions, keeping lateral boundary forcings in the atmosphere and ocean unchanged. We find that the state of the Southern Ocean in early 2016 does not determine whether the drop occurs or not, but indeed has an impact on its amplitude and regional characteristics. Our results also indicate that the ocean initialization affects the sea ice recovery after the drop in the short term (one year), especially in the Weddell sector. The ocean’s influence appears not to be linked to the ocean surface and sea-ice initialization, but rather to the sub-surface conditions (between 50 m and 150 m) and heat exchange fluctuations at the regional scale, while the atmospheric forcing triggering the drop is driven by the large-scale circulation.

Modeling acoustic wavefields from moving sources in the presence of a time-varying free surface

Marine vibrators are increasingly being recognized as a viable alternative to seismic airguns for ocean-bottom acquisition due to their ability to generate more low-frequency content and their less adverse impact on marine wildlife. However, their use introduces processing challenges, such as the Doppler effect and time-dependent source-receiver offsets, which are negligible in conventional airgun acquisition. In addition, the time-varying nature of the sea surface during the multisecond acquisition time introduces further challenges for processing and inversion. To accurately account for source motion and time-varying sea-surface effects in seismic data processing, we develop a reliable and robust numerical modeling tool. We use a mimetic finite-difference method in a generalized coordinate system to model the full acoustic wavefield triggered by a moving source in the presence of a time-varying sea surface. Our approach uses a time- and space-dependent coordinate transformation, which tracks the source movement and conforms to the irregular time-varying sea surface, to map an irregular physical domain in Cartesian coordinates to a regular computational domain in generalized coordinates. We formulate this coordinate transformation such that the coordinate systems conformally match below the ocean-bottom level. Numerical examples demonstrate that this approach is accurate and stable, even for an unrealistically exaggerated sea state. This computational tool is not limited to modeling but also could be used to develop advanced processing techniques for marine vibrator data, such as imaging and inversion.

Observations of Rogue Seas in the Southern Ocean.

We report direct observations of surface waves from a stereo camera system along with concurrent measurements of wind speed during an expedition across the Southern Ocean in the austral winter aboard the South African icebreaker S.A. Agulhas II. Records include water surface elevation across a range of wave conditions spanning from early stages of wave growth to full development. We give experimental evidence of rogue seas, i.e., sea states characterized by heavy tails of the probability density function well beyond the expectation based on bound mode theory. These conditions emerge during wave growth, where strong wind forcing and high nonlinearity drive wave dynamics. Quasiresonance wave-wave interactions, which are known to sustain the generation of large amplitude rogue waves, capture this behavior. Wave statistics return to normality as the wind forcing ceases and waves switch to a full developed condition.

Predicting propeller emergence severity in adverse sea conditions: An integrated approach using stacked machine learning models

In adverse sea conditions, variations in the propeller submergence depth can induce ventilation and out-of-water effects. These effects result in propeller-torque and thrust losses, impacting the shipboard power network's reliability and accelerate wear on propulsion shaft system. Ensuring the stability and safety of sailing ships necessitates predicting the occurrence and severity of ventilation and out-of-water effects. This, in turn, enables the implementation of a switching strategy with a fast response for propulsion control. Nonetheless, existing methods can only identify current propeller ventilation states, mainly categorised as ventilation and non-ventilation, or more elaborately, as full ventilation, partial ventilation and non-ventilation. These methods, however, face a critical limitation—they cannot predict the severity of ventilation or the out-of-water effect, leading to ineffective propulsion-control-strategy switching. This study proposes a method for predicting propeller emergence severity (that is, non-emergence, light emergence and severe emergence) under wave conditions. This method introduces a novel approach for establishing propeller emergence states and a sophisticated stacked model. The new method categorises different propeller emergence states for diverse classifications based on the maximum emergence severity that the propeller can develop. This to overcome the challenges in predicting the development of the ventilation severity and the out-of-water effect. The innovative stacked model helps improve the overall prediction performance of a single intelligent algorithm. Finally, using simulation experimental data, it is verified that the propeller emergence severity method has satisfactory effectiveness and accuracy. The proposed method provides crucial technical support for the efficient switching of propulsion control strategies in electric propulsion systems when ships are navigating under adverse sea conditions.

The Propagation Velocity and Influences of Environmental Factors of Deterministic Sea Wave Prediction in the Long Crest Wave

Ocean waves are one of the leading environmental factors that cause motion of the ocean’s structure. Wave prediction is of great significance for the safety of marine structures. The deterministic sea wave prediction (DSWP) has been focused on because it provided an accurate temporal wave surface. The propagation velocity of wave components is one of the critical problems in DSWP. In this paper, the research of propagation velocity is focused on. The Taylor expansion to wave number is used to prove that the group velocity is the propagation velocity of wave components. The simulated irregular long crest wave data is generated. Utilizing the simulated data, the calculated wave surfaces based on group velocity are consistent with the simulated results. Meanwhile, the comparisons of calculated results based on the group velocity and phase velocity are given. Then, a tank experiment is set to verify the prediction results. To further investigate the prediction performance under different conditions, the influences of environmental factors, including the wind speed, water depth and sea state are analyzed in this paper.

Tradipitant Effective in the Reduction of Vomiting Associated with Motion Sickness Across Varied Sea Conditions (S3.003)

Tradipitant Effective in the Reduction of Vomiting Associated with Motion Sickness Across Varied Sea Conditions (S3.003)

The theory of the regional security complex — Case study, the riparian states of the Black Sea

Known in Antiquity as the Pontus Euxinus, the Black Sea has been the bridge between European and Eastern civilizations since ancient times. Possessing a multi-varied mosaic of cultures, the Black Sea area has facilitated over the centuries, both the development of commercial and political relations and the maintenance and production of conflicts, being like the Sword of Damocles. Located at the intersection of three security zones (Euro-Atlantic, Russian, and Eastern), the Black Sea is currently a vulnerable space in terms of security. Heir to Byzantine culture, most of the riparian states have a complicated internal and external policy, being caught between the idealism of the Western world and the realism of the Eastern European space. At the same time, the revisionism of the Russian Federation and Turkey in terms of foreign policy will also mean a change in the dynamics of the relations between the states bordering the Black Sea, which could result either in its return to the status of a Russian lake or in a division of the spheres of influence between the Russian Federation and Turkey. In this sense, in order to analyze the future security dynamics of the riparian states, we used the theory of the regional security complex, which we consider very appropriate in our study of the Black Sea region.

Indirect load measurement method and experimental verification of floating offshore wind turbine

Accurate load data of wind turbines operating in real sea conditions is crucial for real-time control and offline structural optimization. However, the sheer size of these structures and the complexities of their working environments challenge the direct load measurement through strain gauges and fiber Bragg grating sensors. To address these problems, this paper introduces an indirect measurement method to acquire the thrust and pitch moment loads of the turbine. First, load identification techniques based on the frequency domain separation and aerodynamic damping were applied to decouple the wind and wave loads and establish the inverse load calculation model. Then, numerical simulations were carried out to calibrate and verify this model under a range of steady and unsteady conditions. Preliminary conclusions indicated the strong viability of this method, revealing a mean relative error of 2.32% for thrust and a corresponding equivalent high-frequency error of 24.66% for pitch moment under the designed operating conditions. Finally, a hybrid scaled model was constructed, combining a virtual wind turbine with a physical platform. Experimental results in the wave basin demonstrated the effectiveness of this indirect method in measuring thrust loads of wind turbines, achieving a mean relative error of less than 10%.

Introducing the Azimuth Cutoff as an Independent Measure for Characterizing Sea-State Dynamics in SAR Altimetry

This study presents the first azimuth cutoff analysis in Synthetic Aperture Radar (SAR) altimetry, aiming to assess its applicability in characterizing sea-state dynamics. In SAR imaging, the azimuth cutoff serves as a proxy for the shortest waves, in terms of wavelength, that can be detected by the satellite under certain wind and wave conditions. The magnitude of this parameter is closely related to the wave orbital velocity variance, a key parameter for characterizing wind-wave systems. We exploit wave modulations exhibited in the tail of fully-focused SAR waveforms and extract the azimuth cutoff from the radar signal through the analysis of its along-track autocorrelation function. We showcase the capability of Sentinel-6A in deriving these two parameters based on analyses in the spatial and wavenumber domains, accompanied by a discussion of the limitations. We use Level-1A high-resolution Sentinel-6A data from one repeat cycle (10 days) globally to verify our findings against wave modeled data. In the spatial domain analysis, the estimation of azimuth cutoff involves fitting a Gaussian function to the along-track autocorrelation function. Results reveal pronounced dependencies on wind speed and significant wave height, factors primarily determining the magnitude of the velocity variance. In extreme sea states, the parameters are underestimated by the altimeter, while in relatively calm sea states and in the presence of swells, a substantial overestimation trend is observed. We introduce an alternative approach to extract the azimuth cutoff by identifying the fall-off wavenumber in the wavenumber domain. Results indicate effective mitigation of swell-induced errors, with some additional sensitivity to extreme sea states compared to the spatial domain approach.