Sea State Research Articles

Geometry Optimisation of a Wave Energy Converter

The geometry optimisation of a point-absorber wave energy converter, focusing on the increase in energy absorption derived from heave forces, was performed. The proposed procedure starts by developing an initial geometry, which is later evaluated in terms of hydrodynamics and optimised through an optimisation algorithm to tune the shape parameters that influence energy absorption, intending to obtain the optimal geometry. A deployment site on the Portuguese coast was defined to obtain information on the predominant waves to assess several sea states. NEMOH and WEC-Sim (both open-source software packages) were used to evaluate the interaction between the structure and the imposed wave conditions. The results extracted and analysed from this software included forces in the six degrees of freedom. Under extreme wave conditions, the highest increase in the relative capture width between the initial and final shapes was around 0.2, corresponding to an increase from 0.36 to 0.54, while under average wave conditions, the increase only reached a value of around 0.02, corresponding to an increase from 0.22 to 0.24, as calculated through the relative capture width values.

On the Static Stability and Seakeeping Performance of a Submerged Floating Tunnel Module in Wet Tow

A case study is conducted for a submerged floating tunnel module (SFTM) in wet tow conditions. Inspired by the successful wet tow operations of spar platforms, a wet tow scenario is examined where a tunnel module, floating horizontally with a half-diameter draft, is towed by tugboats using towlines. To evaluate the static stability of the SFTM during wet tow, numerical static offset tests are performed at varying tow speeds to determine the equivalent system stiffness. These static offset tests consider surge, sway, roll, and yaw motions. Statistical analyses are subsequently performed based on the encounter-frequency approximation with varying equivalent stiffnesses. The most probable extreme motion analysis for 3 h under sea state 4 (HS=2.44 m and TP=8.1 s) shows that the beam sea condition causes the largest heave (0.6 m), and the stern sea (30 deg.) leads to the largest yaw response (0.85 deg.), which is likely to cause an instantaneous decrease in towing stability.

Microseism Amplitude and Wave Power in the Mediterranean Sea (1996–2023)

AbstractIn this work, we integrate seismic data recorded by nine coastal Mediterranean seismic stations and wave hindcast data for 1 January 1996 through 15 October 2023. We examine the relationships between the ocean wave‐generated microseism signal (the most continuous and ubiquitous seismic signal on Earth) in terms of temporally varying spectral content, root mean square amplitude, and microseism power spectral density, with the main features of principal ocean wave attributes, specifically significant wave heights, wave period and wave power. To explore relationships between microseism and sea state, we performed a correlation analysis between seismic root square mean amplitude and significant wave height time series for the entire Mediterranean Sea for 1996–2023, including retrieving long‐term trends for microseism energy and independently estimated wave power and calculating the Spearman correlation coefficient between the two trend time series. Despite the small number of stations available the analysis allows for a useful exploratory study on the microseism and its relationship with Mediterranean Sea state and wave power spanning 27 years. Given the recent increase in the number of regional seismic stations, the growth of data sharing, and the intensification of global warming and climate extreme events, the results and methods explored here can be further implemented and developed in coming years for coastal monitoring purposes in complement with other data sources.

Achievement of one health multi-sectoral collaboration in containment of Rift Valley Fever outbreak, Sudan, Red Sea State 2019.

Rift Valley Fever is endemic in Sudan, with a notable outbreak declared in 2019, affecting multiple states. In this study, we examine the Red Sea State, Sudan's experience in applying the One Health approach, to contain Red-Sea RVF outbreak. A retrospective analysis of national and sub-national data and a review of literature were conducted to assess the application of One Health response and to derive lessons learned. The analysis revealed a total of 576 human cases and two deaths, with a case fatality rate of 0.35%, from 25 September 2019 to 25 January 2020. Most cases (99%) were from the Red Sea and River Nile States, and only six sporadic cases were from other five states. The Red Sea State reported 322 human and 74 animal cases, including 74 abortions and 12 animal deaths. Triggers and risk factors include floods, uncontrolled movement of animal, close contact with animals, poor disposal, and unsafe burial practices for animals. One Health approach was utilized all through the defeat of outbreak. A multi-sectoral response plan was implemented, leading to the declaration of the end of the outbreak in 2020 which was reviewed and lessons were derived. One Health approach provided a coordinated action between health, veterinary, and environmental authorities at national and subnational levels. Synergistic efforts have minimized risk of RVF spreading among human and animal. The experience was leveraged to strengthen response approaches for zoonotic diseases. Structural and capacity gaps and financial constraints were identified as implementation challenges.

A Novel Robustness-Enhancing Adversarial Defense Approach to AI-Powered Sea State Estimation for Autonomous Marine Vessels

A Novel Robustness-Enhancing Adversarial Defense Approach to AI-Powered Sea State Estimation for Autonomous Marine Vessels

Numerical study on aerodynamic and hydrodynamic load characteristics of a floating pneumatic wave energy converter under real sea conditions

Numerical study on aerodynamic and hydrodynamic load characteristics of a floating pneumatic wave energy converter under real sea conditions

Effect of sea state parameters on oil spill trajectory and weathering process: a case study of the MV Wakashio oil spill in Mauritius

Effect of sea state parameters on oil spill trajectory and weathering process: a case study of the MV Wakashio oil spill in Mauritius

Modeling the motion of a ship with suspended cargo

The stability of a vessel determines its ability to safely navigate in any sea state. In the process of studying the dynamics of a vessel in rough seas, the method of mathematical modeling based on the linear theory of waves and rolling has been used. The models allow obtaining calculation formulas and methods used to analyze the rolling of vessels with shifting cargo on board (liquid, bulk, suspended). The effect of suspended cargo on the seaworthiness of a vessel is currently considered only when solving problems of static stability. When solving problems of dynamics, mathematical models of the roll of a vessel with suspended cargo in calm water and regular waves have been proposed, and linear differential equations of the roll of a vessel with suspended cargo have been obtained. The presence of suspended cargo on a vessel significantly changes the parameters of the roll due to the occurrence of heeling and variable moments of inertia of the vessel. The proposed mathematical methods allow simulating the roll in any regular waves, taking into account arbitrary values of the transverse metacentric height, cargo weight and suspension length.

Investigation into the Prediction of Ship Heave Motion in Complex Sea Conditions Utilizing Hybrid Neural Networks

While navigating at sea, ships are influenced by various factors, including wind, waves, and currents, which can result in heave motion that significantly impacts operations and potentially leads to accidents. Accurate forecasting of ship heaving is essential to guarantee the safety of maritime navigation. Consequently, this paper proposes a hybrid neural network method that combines Convolutional Neural Networks (CNNs), Bidirectional Long Short-Term Memory Networks (BiLSTMs), and an Attention Mechanism to predict the heaving motion of ships in moderate to complex sea conditions. The data feature extraction ability of CNNs, the temporal analysis capabilities of BiLSTMs, and the dynamic adjustment function of Attention on feature weights were comprehensively utilized to predict a ship’s heave motion. Simulations of a standard container ship’s motion time series under complex sea state conditions were carried out. The model training and validation results indicate that, under sea conditions 4, 5, and 6, the CNN-BiLSTM-Attention method demonstrated significant improvements in MAPE, APE, and RMSE when compared to the traditional LSTM, Attention, and LSTM-Attention methods. The CNN-BiLSTM-Attention method could enhance the accuracy of the prediction. Heave displacement, pitch displacement, pitch velocity, pitch acceleration, and incoming wave height were chosen as key input features. Sensitivity analysis was conducted to optimize the prediction performance of the CNN-BiLSTM-Attention hybrid neural network method, resulting in a significant improvement in MAPE and enhancing the accuracy of ship motion prediction. The research presented in this paper establishes a foundation for future studies on ship motion prediction.

Towards Real-Time Detection of Wakes for Various Sea States with Lightweight Deep Learning Model in Synthetic Aperture Radar Images

Synthetic aperture radar (SAR) is an essential tool for monitoring and managing maritime traffic and ensuring safety. It is particularly valuable because it can provide surveillance in all weather conditions. Ship wake detection has attracted considerable attention in offshore management as it has potential for widespread use in ship positioning and motion parameter inversion, surpassing conventional ship detection methods. Traditional wake detection methods depend on linear feature extraction through image transformation processing techniques, which are often ineffective and time-consuming when applied to large-scale SAR data. Conversely, deep learning (DL) algorithms have been infrequently utilized in wake detection and encounter significant challenges due to the complex ocean background and the effect of the sea state. In this study, we propose a lightweight rotating target detection network designed for detecting ship wakes under various sea states. For this purpose, we initially analyzed the features of wake samples across various frequency domains. In the framework, a YOLO structure-based deep learning is implemented to achieve wake detection. Our network design enhances the YOLOv8’s structure by incorporating advanced techniques such as deep separation convolution and combined frequency domain–spatial feature extraction modules. These modules are used to replace the usual convolutional layer. Furthermore, it integrates an attention technique to extract diverse features. By conducting experiments on the OpenSARWake dataset, our network exhibited outstanding performance, achieving a wake detection accuracy of 66.3% while maintaining a compact model size of 51.5 MB and time of 14 ms. This model size is notably less than the existing techniques employed for rotating target detection and wake detection. Additionally, the algorithm exhibits excellent generalization ability across different sea states, addressing to a certain extent the challenge of wake detection being easily influenced by varying sea states.

Enhancing seagrass restoration success: Detecting and quantifying mechanisms of wave-induced dislodgement.

Seagrass meadows are one of the most productive ecosystems of the world. Seagrass enhances biodiversity, sequesters CO2 and functions as a coastal protection measure by mitigating waves and enhancing sedimentation. However, populations are declining in many regions and natural recolonization of bare sediment beds is protracted and unlikely. The widely used single shoot transplantation method for seagrass restoration is time-consuming and expensive, thus it is important that chances of survival are high. Dislodgement due to wave action poses a particular high risk during the first days after transplantation. This study replicates the transplantation method with a total of 224 harvested shoots (Zostera marina) planted in a wave flume under real sea state conditions. After varying rooting periods in cultivation tanks with low hydrodynamic exposure, the shoots together with their surrounding soil were installed inside the flume and exposed to increasing sea state in intermediate water depth (near-bottom maximum orbital velocity MOV=0.25-0.59m/s) for 250min (≈5000 waves). Half the plants were protected by a willow fence, serving as a restoration facilitator. Our results show that dislodgement is not driven by singular exceptional large waves, but by the wave-induced stress from long-term cyclic loads (fatigue). Furthermore, we found that shoots with a rooting period <12days are especially vulnerable. We also detected that dislodgement is critically impacted by belowground biomass and leaf surface. The deployed restoration facilitator enhances shoot survival by 22.4% and mitigates the effect of the rooting period. The findings indicate that wave exposure and shoot morphometrics are crucial to shoot survival in the first 12days after transplantation. Considering morphometrics in shoot selection for transplantation may thus reduce the need for restoration facilitation. In conclusion, our research facilitates planning of seagrass restoration including the identification of suitable weather windows, restoration facilitator necessity, and shoot traits.

A circumpolar review of the breeding distribution and habitat use of the snow petrel (Pagodroma nivea), the world’s most southerly breeding vertebrate

Knowledge of the spatial distribution of many polar seabird species is incomplete due to the remoteness of their breeding locations. Here, we compiled a new database of published and unpublished records of all known snow petrel Pagodroma nivea breeding sites. We quantified local environmental conditions at sites by appending indices of climate and substrate, and regional-scale conditions by appending 30 year mean (1992–2021) sea-ice conditions within accessible foraging areas. Breeding snow petrels are reported at 456 sites across Antarctica and subantarctic islands. Although many counts are old or have large margins of error, population estimates available for 222 known sites totalled a minimum of ~ 77400 breeding pairs. However with so many missing data, the true breeding population will be much higher. Most sites are close to the coast (median = 1.15 km) and research stations (median = 26 km). Median distance to the November sea-ice edge (breeding season sea-ice maximum) is 430 km. Locally, most nests occur in cavities in high-grade metamorphic rocks. Minimum air temperatures occur at inland sites, and maxima at their northern breeding limit. Breeding location and cavity selection is likely determined by availability of suitable breeding substrate within sustainable distance of suitable foraging habitat. Within this range, nest sites may then be selected based on local conditions such as cavity size and aspect. Our database will allow formal analyses of habitat selection and provides a baseline against which to monitor future snow petrel distribution changes in response to climate change.

An Improved Pied Kingfisher Optimizer for Maritime UAV Path Planning

Maritime activities have become increasingly frequent with the deepening of economic globalization, highlighting the burgeoning significance of maritime rescue. However, in practical applications, UAVs for maritime rescue face numerous challenges, such as limited endurance and inadequate autonomous planning capabilities. To optimize flight routes and circumvent adverse sea conditions, an improved Pied Kingfisher Optimizer (IPKO) that incorporates refraction reverse learning, variable spiral search, and Cauchy mutation strategies was proposed. Comparative experiments conducted on CEC2005 and CEC2022 datasets with seven traditional algorithms demonstrate that the proposed algorithm exhibits superior precision and convergence speed. Subsequently, a path planning objective function was constructed based on trajectory cost and threat cost to simulate a 3D space for UAV maritime rescue missions, and the IPKO algorithm was applied to address the UAV path planning problem. The results showed that the total cost incurred by the IPKO algorithm decreased by 5.77% compared to the PKO algorithm and by 51.19% compared to the SCA algorithm. Finally, through UAV flight tests validating its practical applicability, it is ascertained that IPKO can enhance rescue efficiency in complex maritime rescue environments.

The Use of Air Pressure Measurements Within a Sealed Moonpool for Sea-State Estimation

To assess the viability of locations for wave energy farms and design effective coastal protection measures, knowledge of local wave regimes is required. The work described herein aims to develop a low-cost, self-powering wave-measuring device that comprises a floating buoy with a central moonpool. The relative motion of the water level in the moonpool to the buoy will pressurise and depressurise the air above the water column. The variation in air pressure may then be used to estimate the sea-state incident upon the buoy. Small-scale proof of concept tank testing was conducted at a 1:20 scale and at a larger 1:2.4 scale before a full-scale prototype was deployed at the Smartbay test site facility in Galway Bay, Ireland. A number of techniques by which full-scale sea states may be estimated from the pressure spectrum are explored. A successful technique, based on the average of multiple linear squared magnitude of the transfer functions obtained under different wave regimes is developed. The applicability of this technique is then confirmed using validation data obtained during the full-scale sea trials. While the technique has proven useful, investigation into potential seasonal bias has been conducted, and suggestions for further improvements to the technique, based on further calibration testing in real sea states, are proposed.

Atmospheric Variability Drives Anomalies in the Bering Sea Air–Sea Heat Exchange

Abstract High latitudes, including the Bering Sea, are experiencing unprecedented rates of change. Long-term Bering Sea warming trends have been identified, and marine heatwaves (MHWs), event-scale elevated sea surface temperature (SST) extremes, have also increased in frequency and longevity in recent years. Recent work has shown that variability in air–sea coupling plays a dominant role in driving Bering Sea upper-ocean thermal variability and that surface forcing has driven an increase in the occurrence of positive ocean temperature anomalies since 2010. In this work, we characterize the drivers of the anomalous surface air–sea heat fluxes in the Bering Sea over the period 2010–22 using ERA5 fields. We show that the surface turbulent heat flux dominates the net surface heat flux variability from September to April and is primarily a result of near-surface air temperature and specific humidity anomalies. The airmass anomalies that account for the majority of the turbulent heat flux variability are a function of wind direction, with southerly (northerly) wind advecting anomalously warm (cool), moist (dry) air over the Bering Sea, resulting in positive (negative) surface turbulent flux anomalies. During the remaining months of the year, anomalies in the surface radiative fluxes account for the majority of the net surface heat flux variability and are a result of anomalous cloud coverage, anomalous lower-tropospheric virtual temperature, and sea ice coverage variability. Our results indicate that atmospheric variability drives much of the Bering Sea upper-ocean temperature variability through the mediation of the surface heat fluxes during the analysis period. Significance Statement A long-term ocean warming trend and a recent increase in marine heatwaves in the Bering Sea have been identified. Previous work showed that anomalies in the exchange of heat between the ocean and the atmosphere were the primary driver of Bering Sea temperature variability, but the processes responsible for the heat exchange anomalies were unknown. In this work, we show that the atmosphere is the primary driver of anomalies in the Bering Sea air–sea heat exchange and therefore plays an important role in altering the thermal state of the Bering Sea. Our results highlight the importance of understanding more about how the ocean and the atmosphere interact at high latitudes and how this relationship will be affected by future climate change.

A Novel 10 MW Floating Wind Turbine Platform—SparFloat: Conceptual Design and Dynamic Response Analysis

New conceptual designs for floating offshore wind platforms (FOWPs) are crucial for deep-sea wind power generation, increasing power output, lowering construction costs, and minimizing the risk of damage. While there have been various conceptual designs, tailored solutions for the South China Sea are limited due to the relatively harsh environment. This study proposes a novel 10 MW FOWP—“SparFloat”, which combines the advantages of a semi-submersible platform and Spar platform to cater for the sea conditions of the South China Sea. By systematically adjusting the distance between columns and the diameters of the side column and heave plate, the impact of geometrical changes in the platform on its dynamic response is investigated for the purpose of design optimization. The results highlight that roll/pitch natural periods are predominantly governed by restoring stiffness, whereas heave motion exhibits a higher sensitivity to added mass and radiation damping. Increasing the inter-column distance and side column diameter enhances stability and reduces roll/pitch natural periods, while enlarging the heave plate diameter extends the heave natural period. Time-domain simulations using a coupled FAST-AQWA framework confirm that the optimized design meets rule requirements, verifying the robustness and suitability of the SparFloat concept for the challenging environment of the South China Sea.

Coral Reef Restoration for Coastal Protection: Water Quality Monitoring in Indonesia Coral Reef Garden Nusa Dua, Bali

The Indonesia Coral Reef Garden (ICRG) is a coral reef restoration program with Nusa Dua as one of five sites in Bali. A plantation program has been done by 2020, but it is necessary to monitor the condition. A field survey in Nusa Dua was carried out on October 3-4, 2022 to measure and check ocean parameters that are suitable for coral life and diving in artificial coral reefs installed. In the survey, several points had been measured through CTD Valeport Midas+ prior to measuring ocean parameters in the same location as a preliminary survey done two years in advance. The sea condition of temperature, salinity, pH, turbidity, and DO is 24.89 - 28.69 °C, 33.75 - 34.22 psu, 8.0 - 8.1, 1.19 - 4.27 FTU, and 4.47 - 5.24 mg/L, respectively. Based on the conformity of water quality, the water condition is good for coral growth. A total of 15 locations are used to put artificial coral reefs in many forms or structures. The coral plantation program in Nusa Dua shows promising progress in qualitatively consisting of species of Montipora sp., Acropora sp., and Alcyonacea sp. A continuous measurement is demanded to monitor the condition of coral growth quantitatively.

Performance improvement of a full-scale oscillating water column device by employing a novel double oscillating water column

The energy present in the ocean surface waves can be extracted using an oscillating water column (OWC) device. In the present work, the performance characteristics of a normal OWC, an opposite OWC and a novel double OWC employing Savonius rotors are investigated at different sea states in a numerical wave tank (NWT) using the computational fluid dynamics (CFD) code ANSYS-CFX. The Savonius rotor is known to be an inexpensive energy harvesting device. The waves in the NWT were generated using a piston type wave-maker. The results from the computational work were compared with experimental work. For the normal OWC, a maximum power output of 18.85 kW, which corresponds to an efficiency of 22.44% was recorded at 60 rpm for the mean wave condition. On the other hand, for the opposite OWC, the peak power and efficiency were 10.4 kW and 12.38% respectively for the mean sea state. For the novel double OWC, the flow in the front OWC has more energy compared to the flow in the rear OWC for both advancing flow and retreating flow, resulting in a combined peak power of 19.5 kW at the mean sea state. This represented an increase of 3.45% in the power production.

A multi-fidelity approach for the evaluation of extreme wave loads using nonlinear response-conditioned waves

In the present study, a multi-fidelity methodology based on response-conditioned waves (RCW) is demonstrated for the probabilistic assessment of wave-induced loads and responses of offshore structures. The methodology consists of two steps: (i) the RCW are determined using a surrogate response model and (ii) they are reproduced in an experimental or CFD-based numerical wave tank (NWT) to obtain the fully nonlinear response, as a high-fidelity evaluation. The main novelty of the proposed response-conditioning technique is that it uses a fully nonlinear wave solver that calculates the wave propagation inside an NWT. In this work, the extreme Vertical Bending Moment (VBM) of a zero-speed containership is investigated. It is found that the proposed approach provides nonlinear wave sequences that can be explicitly and exactly reproduced experimentally, up to very extreme sea states (Hs=17 m, Tp=15.5 s). Moreover, through comparison of the obtained results with an experimental Monte Carlo approach, it is shown that the overall framework can predict the short-term distribution of the VBM accurately and efficiently. Finally, given that model tests are costly and not widely accessible, the implementation of the high-fidelity response evaluation within a CFD-based NWT is also demonstrated and validated against the available experimental results.

Directional Spectrum Estimation for Sea States Generated by the Single Summation Method

The influence of directional spreading of waves is significant for wave-induced loads, wave breaking and nonlinearity of the waves. For physical model testing performed at test facilities such as the Ocean and Coastal Engineering Laboratory at Aalborg University, it is crucial to validate if the test conditions match the target sea states by measurement and analysis of the generated directional wave field. Most of the existing methods assumes a double summation sea state to be present which is valid in the prototype. However, waves in the laboratory are usually generated by single summation. The current paper presents a method to analyse short-crested waves generated by the single summation method. Compared to similar methods oblique reflections are considered instead of only in-line reflections. The results show that the method successfully decomposes the incident and reflected wave fields in the time domain. Thus, for example the incident wave height distribution may be obtained. The sensitivity of the new method to additional reflective directions, noise, calibration errors and positional errors of the wave gauges was found small.