Sea State Research Articles

Changing Sea Conditions as a Threat to Our Underwater Cultural Heritage

Changing Sea Conditions as a Threat to Our Underwater Cultural Heritage

Approximate Dynamic Programming for Control of Wave Energy Converters With Implementation and Validation on a Point Absorber Prototype

It is recognized that the application of constrained optimal control for wave energy converters (WECs), represented by model predictive control (MPC), is hindered by its computation burden resulting from online optimization, especially when the model contains nonlinearities. In this article, a novel control solution based on approximate dynamic programming (ADP) is proposed, in which an explicit controller is solved by model sampling and neural network training. In this way, the major computation load is moved offline to enable fast online execution, and the need for wave prediction is eliminated. The effectiveness of ADP is verified by a simulation case study based on a nonlinear WEC system. Using nonlinear MPC as the performance benchmark, over 90% energy efficiency is achieved by ADP under various sea states with constraint satisfaction and dramatically faster computation. The ADP controller is further experimentally validated on a newly constructed WEC prototype through wave tank testing, where successful implementation and satisfactory performance are demonstrated.

Reconstruction of Wide Swath Significant Wave Height From Quasi‐Synchronous Observations of Multisource Satellite Sensors

AbstractGlobal sea wave monitoring is of utmost importance for tasks such as analysis of ocean climate change, offshore fisheries, and early warning of marine disasters. Significant wave height (SWH) is one of the most vital and widely used metrics for measuring sea waves in marine research. Hence, obtaining high precision and extensive coverage measurements of SWH is of great significance for comprehensive sea wave studies. A data set is constructed by combining wave spectrometer and scatterometer data from China‐French Ocean Satellite, synthetic aperture radar (SAR) wave mode data from Sentinel‐1, and altimeter data from Jason‐3 and HY‐2B through space‐time matching method. The multi‐sources integrated data set is used to complete the reconstruction of the wide swath SWH. A model based on stacked autoencoder and deep neural network (SAE‐DNN) is developed. The SWH reconstructed by the model is evaluated with the training‐independent test set. The results demonstrate that the accuracy of the SAE‐DNN model is significantly improved by incorporating SAR joint quasi‐synchronous observations and the root mean square error can reach 0.217 m, which is comparable to the SWH measured by altimeter and highlights the effectiveness and reliability of the model in accurately reconstructing SWH. We further examine and analysis the distance variations between SWH reconstruction sites and Surface Wave Investigation and Monitoring observations, the influence of different SAR features, and the influence of sea state, highlighting the benefits of incorporating SAR data into SAE‐DNN model.

Patent Technology of Shipborne Stabilized Platform

Background: When a ship is sailing or operating at sea, it is unavoidable to produce sixdegrees- of-freedom movements of rolling, pitching, and yawing under the action of sea wind and waves, which seriously impacts the operation of precision equipment on the ship and the safety of personnel. The ship-borne stabilized platform can isolate the ship's motion and eliminate the impact of sea waves on the personnel and equipment on it to a large extent. With the increasing demand for ship surfaces in marine fields, such as navigation equipment, military facilities, and sea condition simulation, there is an urgent need to study ship-borne platforms with high stability and efficiency to isolate swaying and ensure ship performance. Objective: This study aims to analyse the patents and summarize the characteristics and existing problems of the shipborne platform to provide a reference for the future development of the shipborne stabilized platform. Methods: Various representative patents related to shipborne stabilized platforms and multi-DOF platforms were researched in this study. Results: Through the analysis and comparison of patent technology, the main problems existing in the structure and design principle of the existing shipborne stabilized platform are summarized, and the development trend and direction of the shipborne stabilized platform are discussed. Conclusion: Shipborne stabilization is highly significant in isolating the ship's motion. At present, the ship-borne stabilized platform has produced six degrees of freedom of movement, but due to the improvement of control response requirements, the structure of the platform needs to be further improved. With the development of test technology toward intelligent and big data-driven technology, the shipborne stabilized platform is moving toward cloud computing and large-scale testing.

Integrating Computational Fluid Dynamics for Maneuverability Prediction in Dual Full Rotary Propulsion Ships: A 4-DOF Mathematical Model Approach

To predict the maneuverability of a dual full rotary propulsion ship quickly and accurately, the integrated computational fluid dynamics (CFD) and mathematical model approach is performed to simulate the ship turning and zigzag tests, which are then compared and validated against a full-scale trial carried out under actual sea conditions. Initially, the RANS equations are solved, employing the Volume of Fluid (VOF) method to capture the free water surface, while a numerical simulation of the captive model test is conducted using the rigid body motion module. Secondly, hydrodynamic derivatives for the MMG model are obtained from the CFD simulations and empirical formula. Lastly, a four-degree-of-freedom mathematical model group (MMG) maneuvering model is proposed for the dual full rotary propulsion ship, incorporating full-scale simulations of turning and zigzag tests followed by a full-scale trial for comparative validation. The results indicate that the proposed method has a high accuracy in predicting the maneuverability of dual full-rotary propulsion ships, with an average error of less than 10% from the full-scale trial data (and within 5% for the tactical diameters in particular) in spite of the influence of environmental factors such as wind and waves. It provides experience in predicting the maneuverability of a full-scale ship during the ship design stage.

Modelling and Clustering Sea Conditions: Bivariate FiniteMixtures of Generalized Additive Models for Location, Shape, and Scale Applied to the Analysis of Meteorological Tides and Wave Heights

Modelling sea conditions is a complex task that requires a comprehensive analysis, considering various influencing factors. Observed and unobserved factors jointly play a role in the definition of sea conditions. Here, we consider finite mixtures of generalized linear additive models for location scale, and shape (GAMLSSs) to capture the effects of both environmental variables and omitted variables, whose effects are summarized using latent variables. The GAMLSS approach is flexible enough to allow for different data features such as non-normality, skewness, heavy tails, etc., and for the definition of a regression model not only for the expected values of the observed process but also for all the other distribution parameters, e.g., the variance. We collected data on multiple sea-related and environmental variables in Ancona (Italy) from two Italian networks: the Sea Level Measurement Network (Rete Mareografica Nazionale, RMN) and the Sea Waves Measurement Network (Rete Ondametrica Nazionale, RON). Our main outcomes were the meteorological tides (often also referred to as “residuals”) and the significant wave height. Atmospheric pressure and wind speed were considered as main drivers of the sea conditions, as well as the fetch associated with wind direction, linking these variables to the outcomes through the definition of multiple linear predictors in a regression framework. Our results confirm the importance of accounting for environmental variables and reveal that their effect is heterogeneous, where heterogeneity is modelled by three distinct mixture components, each capturing different sea conditions. These findings contribute to a deeper understanding of sea state dynamics and provide evidence of a clustering structure characterizing different sea conditions.

Wave energy resource classification system for the China East Adjacent Seas based on multivariate clustering

This study based on the 25-year wave hindcast database of the western Pacific and used three unsupervised learning clustering algorithms to classify the wave energy resources in the China East Adjacent Seas. Five wave energy characteristic parameters are comprehensively considered in the calculation process of the clustering algorithm. According to the analysis of the classification results, it can be seen that the Class Ⅳ is the most suitable for wave energy development in the China East Adjacent Seas, followed by the Class Ⅲ and Class Ⅴ. The Class Ⅵ is too far away from the coast to be used as the intended area for wave energy development. The Class Ⅰ is mostly located in inland seas and harbors, which are not suitable for wave energy development. By analyzing the annual average captured power, it can be seen that the optimal capture interval of the existing wave energy converters with mature technology is too large compared with the wave conditions in the China East Adjacent Seas. We should vigorously develop wave energy converters that are more suitable for the wave conditions of Class Ⅲ, Class Ⅳ and Class Ⅴ, and improve the capture efficiency of the wave energy converters.

Hydrodynamic Interactions and Enhanced Energy Harnessing amongst Many WEC Units in Large-Size Wave Parks

Interactions between wave energy converters (WECs) can significantly affect the overall energy-harnessing performance of a wave park. Although large-size wave parks with many WEC units are commonly considered in practical applications, it is challenging to simulate such parks due to huge computational costs. This paper presents a numerical model that uses the boundary element method (BEM) to simulate wave parks. Each wave energy converter (WEC) was modelled as a comprehensive system, including WEC buoys, power take-off, and mooring systems, with hydrodynamic interactions included. Two classical layouts for arranging 16 units were simulated using this numerical model. The energy-harnessing performance of these array layouts was analyzed for both regular waves and a selection of irregular sea state conditions with different wave directions, wave heights, wave periods and water depths. For each layout, three WEC separation distances were studied. An increase of up to 16% in the power performance of the WEC under regular waves was observed, which highlights the importance of interaction effects.

An investigation of sea state conditions at the time of ship accidents in Indonesia

ABSTRACT In this study, we investigate the sea state conditions during the two cases of ship accidents that have recently occurred in the Indonesian ocean. The first accident case occurred in the middle part of Indonesia at the end of May 2022 resulted in fatalities. Similarly, another incident was in the eastern part of Indonesia in the middle of July 2022, killing 12 people. For both cases, we observed the maximum wave height, significant wave height, and wind speed during the respective accident periods. The observations were carried out using the global ocean wave model, WAVEWATCH III, in conjunction with Altimeters and ASCAT scatterometers. Specifically, the study employed data from Cryosat-2, Jason-3, Saral, Sentinel-3B, Sentinel-6A, Metop-B and Metop-C. The resultant satellite observations are consistent with the model, meaning that the wave heights at the time of the accident were very high. The first case clearly shows that strong wind and high waves most likely triggered the accident. As a result, all stakeholders who run their ocean transport business must consider the warning from the related agency, which is, in this case meteorological, climatological, and geophysical agency. Such proactive measures have the potential to mitigate marine accidents stemming from adverse weather conditions.

Input saturated [formula omitted] optimal control to mitigate DTMB 5415 combatant roll motion using anti roll gyro stabilizer

Despite technological advances, rolling motion is the most critical motion for the stability and survivability of ships. This study examines the possibility of using Anti Roll Gyrostabilizer System (ARGS) as a control actuation system to mitigate the roll motion of the DTMB 5415. In the scope of conceptual study, state space model of the DTMB 5415 Combatant Warship has been obtained. Then, ARGS dynamics have been integrated into the roll motion dynamics. Parameters of the DTMB 5415 and actuator are identified from the literature. Comparing experimental and numerical studies in the literature have also expanded the damping term parameters in the equation of roll motion. However, a Monte Carlo analysis is carried out to define the preliminary parameters of ARGS. An actuator-saturated Linear Matrix Inequality (LMI) Full State-Feedback H∞ Optimal Controller is tested for this design iteration. The results are also contrasted with the requirements that military ships must meet. Ship roll amplitudes have significantly decreased (over 95% for various sea conditions) and have complied with STANAG 4154 standards. The 1 radian Precession Angle limit has not been overshot. Continuous and discrete-time control rules are implemented, thus demonstrating the applicability of this actuation and control method are shown.

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.

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.