Search Results (1,729)

Oceanic whitecaps are caused by wave breaking and are very important in air–sea interactions. Usually, whitecap coverage is considered a key factor in representing the role of whitecaps. However, the accurate identification of whitecap coverage in videos under dynamic marine conditions is a tough task. An EMA-SE-ResUNet deep learning model was proposed in this study to address this challenge. Based on a foundation of residual network (ResNet)-50 as the encoder and U-Net as the decoder, the model incorporated efficient multi-scale attention (EMA) module and squeeze-and-excitation network (SENet) module to improve its performance. By employing a dynamic weight allocation strategy and a channel attention mechanism, the model effectively strengthens the feature representation capability for whitecap edges while suppressing interference from wave textures and illumination noise. The model’s adaptability to complex sea surface scenarios was enhanced through the integration of data augmentation techniques and an optimized joint loss function. By applying the proposed model to a dataset collected by a shipborne camera system deployed during a comprehensive fishery resource survey in the northwest Pacific, the model results outperformed main segmentation algorithms, including U-Net, DeepLabv3+, HRNet, and PSPNet, in key metrics: whitecap intersection over union (IoU_W) = 73.32%, pixel absolute error (PAE) = 0.081%, and whitecap F1-score (F1_W) = 84.60. Compared to the traditional U-Net model, it achieved an absolute improvement of 2.1% in IoU_W while reducing computational load (GFLOPs) by 57.3% and achieving synergistic optimization of accuracy and real-time performance. This study can provide highly reliable technical support for studies on air–sea flux quantification and marine aerosol generation. Full article

Three-wave resonant interaction equations can model nonlinear dynamics in many fields, e.g., fluids, optics, and plasma. Rogue waves, i.e., modes algebraically localized in both space and time, are obtained analytically. The aim of this paper is to study degenerate three-wave resonant interaction equations, where two out of the three interacting wave packets have identical group velocities. Physically, degenerate resonance typically occurs for dispersion relation, possessing many branches, e.g., internal waves in a continuously stratified fluid. Here, the Nth-order rogue wave solutions for this dynamical model are presented. Based on these solutions, we examine the effects of the group velocity on the width and structural profiles of the rogue waves. The width of the rogue waves exhibit a linear increase as the group velocity increases, a feature well-correlated with the prediction made using modulation instability. In terms of structural profiles, first-order rogue waves display ‘four-petal’ and ‘eye-shaped’ patterns. Second-order rogue waves can reveal intriguing configurations, e.g., ‘butterfly’ patterns and triplets. To ascertain the robustness of these modes, numerical simulations with random initial conditions were performed. Sequences of localized modes resembling these analytical rogue waves were observed. A spectral jump was observed, with the jump broadening in the case of rogue wave triplets. Furthermore, we predict new rogue waves based on information from two existing ones obtained using the deep learning technique in the context of rogue wave triplets. This predictive model holds potential applications in ocean engineering. Full article

This article presents a methodological framework for evaluating hydrodynamic loading on seabed structures in the eastern Mediterranean, originally motivated by the design requirements of special protective structures for a planned high-voltage subsea interconnection between Crete and the Greek mainland. The associated study highlighted the need for a comprehensive evaluation of hydrodynamic loading on seabed structures in the South-East Mediterranean. A methodology is presented for determining representative design kinematics near the seabed, accounting for large-scale oceanic circulation, local wind-induced currents, wind-generated surface waves, and tsunami effects. The method integrates long-term metocean datasets, spectral wave modelling, and reliability-based combinations of critical processes, with adjustments for anticipated climate change impacts. The approach is demonstrated through two case studies involving an electrode protective cage and a submarine electricity transmission cable, both representative of components in subsea power connections. The analysis provides design values of velocities, accelerations, and hydrodynamic forces, with typical checks against sliding, uplift, and vibration. Results highlight the depth-dependent magnitude interplay between ocean circulation and wave-induced particle motions, as well as the importance of biofouling and marine growth. The findings aim to support the safe and sustainable design of offshore energy infrastructure in the eastern Mediterranean and similar marine environments. Full article

In a cellular maritime communication system, ocean buoys are essential to enable environmental monitoring, offshore platform management, and disaster response. Therefore, energy-efficient transmission from the buoys is a key requirement to prolong their operational time. A fixed uplink beamforming can be considered to save energy by leveraging its beam gain while managing the target link reliability. However, the dynamic condition of ocean waves causes buoys’ random orientation, leading to frequent misalignment of their predefined beam direction aimed at the base station, which degrades both the link reliability and energy efficiency. To address this challenge, we propose a wave-adaptive beamforming framework to satisfy data-rate demands within limited power budgets. This strategy targets scenarios where sea state information is unavailable, such as in network-assisted systems. We propose a Two-Dimensional Thompson Sampling (2DTS) scheme that jointly selects beamwidth and transmit power to satisfy the target-rate constraint with minimal power consumption and thus achieve maximal energy efficiency. This adaptive learning approach effectively balances exploration and exploitation, enabling efficient operation in uncertain and changing sea conditions. In simulation, under a moderate sea state, 2DTS achieves an energy efficiency of $1.26 \times {10}^4$ bps/Hz/J at round 600, which is $73.7\%$ of the ideal ($1.71 \times {10}^4$), and yield gains of $96.9\%$ and $447.8\%$ over exploration-based TS and conventional TS, respectively. Under a harsh sea state, 2DTS attains $3.09 \times {10}^4$ bps/Hz/J ($85.6\%$ of the ideal $3.61 \times {10}^4$), outperforming the exploration-based and conventional TS by $83.9\%$ and $113.1\%$, respectively. The simulation results demonstrate that the strategy enhances energy efficiency, confirming its practicality for maritime communication systems constrained by limited power budgets. Full article

This paper presents an innovative approach to efficiently harvesting energy from ocean waves through a buoy-type Wave Energy Converter (WEC). The proposed methodology integrates a buoy, a Mechanical Motion Rectifier (MMR), a Motion Rectifier (MR), an Energy Storage Element (ESE), and an electric generator. A MATLAB-2023 model has been employed to assess the electrical power generated under varying wave heights and frequencies. Experimental data and numerical simulations reveal that the prototype Wave Energy Harvester (WEH) achieved a peak voltage of 6.7 V, peak power of 3.6 W, and an average power output of 8.5 mW, with an overall efficiency of 47.2% for the device’s actual size. Additionally, a theoretical analysis has been conducted to investigate the impact of incorporating additional buoys on the electrical power output. Full article

For large-scale measurement of microbubble parameters on the ocean surface beneath breaking waves, a buoy-type bubble sensor (BBS) is proposed. This sensor integrates a panoramic bubble imaging sub-sensor with a circular array fiber-optic sub-sensor. The sensitive unit of the latter sub-sensor is designed via theoretical modeling and experimental validation. Theoretical calculations indicate that the optimal cone angle for a quartz fiber-optic-based sensitive unit ranges from 45.2° to 92°. A prototype array element with a cone angle of 90° was fabricated and used as the core component for feasibility experiments in static and dynamic two-phase (gas and liquid) identification. During static identification, the reflected optical power differs by an order of magnitude between the two phases. For dynamic sensing of multiple microbubble positions, the reflected optical power varies from 13.4 nW to 29.3 nW, which is within the operating range of the array element’s photodetector. In theory, assembling conical quartz fiber-based sensitive units into fiber-optic probes and configuring them as arrays could overcome the resolution limitations of the panoramic bubble imaging sub-sensor. Further discussion of this approach will be presented in a subsequent paper. Full article

This study presents a significant wave height correction model using deep learning techniques to enhance long-term wave forecast capabilities. The model utilises buoy measurements to assess the forecasting accuracy of the ECMWF 15-day forecast of significant wave height in the western Atlantic Ocean under various input conditions. The performance of different deep learning methods in modelling the wave forecast error is compared. The model predictions are validated against buoy data, revealing that the forecasting accuracy of the various deep learning methods is comparable. In addition, the model’s adaptability is examined for varying locations and water depths within the study area. The results demonstrate that the proposed method significantly improves the accuracy of the 15-day wave height forecasting and exhibits good adaptability to a vast sea area. Full article

The range-dependence on polarization distortion of spaceborne polarimetric synthetic aperture radar (SAR) affects the accuracy of wide-swath polarization applications, such as environmental monitoring, sea ice classification and ocean wave inversion. Traditional calibration methods, assessing the distortion mainly based on ground experiments, suffer from tedious active calibrator deployment work, which are time-consuming and cost-intensive. This paper proposes a novel polarimetric assessment and calibration method for the quad-polarized wide-swath ScanSAR imaging mode. Firstly, by using distributed target data that satisfy the system reciprocity requirement, we assess the polarization distortion matrices for a single beam in the mode. Secondly, we transfer the matrix results from one beam to another by analyzing data from the overlapping region between beams. Thirdly, we calibrate the quad-polarized data and achieve an overall assessment and calibration results. Compared to traditional calibration methods, the presented method focuses on using cross-beam (overlapping area) data to reduce the dependence on active calibrators and avoid conducting calibration work beam-by-beam. The assessment and calibration experiment is conducted on Gaofen-3 quad-polarized ScanSAR experiment mode data. The calibrated images and polarization decomposition results are compared with those from well-calibrated quad-polarized Stripmap mode data located in the same region. The results of the comparison revealed the effectiveness and accuracy of the proposed method. Full article

The detection of internal solitary waves (ISWs) in the ocean using Synthetic Aperture Radar (SAR) images is important for the safety of marine engineering structures. Based on 4120 Sentinel SAR images obtained from 2014 to 2024, an ISW dataset covering the Andaman Sea (AS), the South China Sea (SCS), the Sulu Sea (SS), and the Celebes Sea (CS) is constructed, and a deep learning dataset containing 3495 detection samples and 2476 segmentation samples is also established. Based on the YOLOv8 lightweight model, combined with an anti-interference strategy, a multi-size block detection strategy, and a post-processing repair module, an ISW detection method is proposed. This method reduces the false detection rate by 44.20 percentage points in terms of anti-interference performance. In terms of repair performance, the repair rate reaches 85.2%, and the error connection rate is less than 3.1%. The detection results of applying this method to Sentinel images in multiple sea areas show that there are significant regional differences in ISW activities in different sea areas: in the AS, ISW activities peak in the dry season of March and are mainly concentrated in the eastern and southern regions; the western part of the SS and the southern part of the CS are also the core areas of ISW activities. From the perspective of temporal characteristics, the SS maintains a relatively high ISW activity level throughout the dry season, while the CS exhibits more complex seasonal dynamic features. The lightweight detection method proposed in this study has good applicability and can provide support for marine disaster prevention work. Full article

Wave-powered desalination systems integrate reverse osmosis (RO) with renewable ocean energy, providing a sustainable and environmentally responsible approach to freshwater production. This study aims to investigate wave-powered RO desalination using supervised and deep machine learning (ML) models to predict the effects of variable feed flow on permeate recovery and salt rejection under dynamic hydrodynamic conditions. Multiple ML models, including Gaussian process regression (GPR), support vector machines (SVMs), multi-layer perceptron (MLP), linear regression (LR), and decision trees (DTs) were systematically assessed for the prediction of permeate recovery and salt rejection (%) using three distinct input configurations: limited physicochemical features (M1), flow- and salinity-related parameters (M2), and a comprehensive variable set incorporating temperature (M3). GPR achieved near-perfect predictive accuracy R² values (~1.00) with minimal errors for permeate recovery and salt rejection, attributed to its flexible kernel and probabilistic design. MLP and SVM also performed well, though they showed greater sensitivity to feature complexity. In contrast, DT models exhibited limited generalization and higher error rates, particularly when key features were excluded. Sensitivity analyses revealed that feed pressure (FP) and brine salinity (BS) were dominant positive influencers of permeate recovery and salt rejection. In contrast, brine flow (BF) and permeate salinity (PS) had negative impacts. Full article

The motion of ships in the ocean follows six degrees of freedom, and accurately measuring this motion is crucial for improving marine engineering operations. Among the six degree-of-freedom movement of ships, the change in ship heave freedom has the worst impact on offshore lifting operations. At present, the most common method for measuring heave displacement is by integrating heave acceleration twice. The heave motion of ships belongs to low-frequency motion, but the low-frequency band range is often easily overlooked. This paper first analyzes the wave spectrum to determine the dominant frequency range of ship heave motion under typical wind speeds, which is found to be between 0.22 Hz and 0.45 Hz. The accuracy of low-frequency ship heave displacement signals largely depends on the heave acceleration signal, and filtering acceleration signals in the low-frequency range is particularly difficult. To address this challenge, this paper proposes a low-frequency component filtering method for heave acceleration signal of marine ships, which effectively avoids the phase and peak-to-peak errors introduced by traditional filters. This method further improves the filtering performance of acceleration signals in the 0.2 Hz to 0.5 Hz low-frequency range and can provide the crane driver with a motion reference for the heave of the ship when the ship is performing lifting operations. Full article

The ocean heat content (“OHC”)—the heat energy within the ocean integrated to a reference depth—has physical drivers spanning spatial and temporal scales, including seasonality, the El Niño/Southern Oscillation (ENSO), and others. The present article investigates changes in the OHC100 during the period 1994–2020 using GLORYS12 monthly averaged ocean reanalysis. OHC100–ENSO correlation patterns are explored to glean insights about the oceanic mechanisms that facilitate the ENSO’s global teleconnections. After extracting known seasonality and ENSO signals using the Oceanic Niño Index (ONI), the OHC100 residual is analyzed to investigate multidecadal drivers of the OHC100. Lagged ENSO–OHC100 correlations (±12 months) reveal basin-scale oscillations in the sign of ENSO influence likely attributable to Rossby waves. The OHC100 is increasing globally (in total, 2.4 × 10²² J decade⁻¹), with the greatest increases near western boundary currents (WBCs). Some regions are decreasing, notably the Atlantic main development region (MDR) for tropical cyclones (TCs). Correlations and multidecadal variability in the OHC100 tendency (OHCT) and zonal and meridional advections of the OHC100 (ZAO and MAO) support the hypothesis that upper-ocean dynamics mediate ENSO teleconnections as well as exert independent control on OHC100 variability. Local increases in the OHC100 would support the observed TC rapid intensification irrespective of the ENSO phase as the TC-supporting region expands. Full article

Several experimental and numerical studies have been conducted on the towing behavior of floating offshore wind turbines (FOWTs); however, these studies mainly focus on tension-leg platform (TLP) and semi-submersible designs with cylindrical features. The University of Maine’s VolturnUS+ concept is a cruciform-shaped barge-type FOWT with distinctive hydrodynamic properties that have not been characterized in previous research. This study presents basin-scale experiments that characterize the hydrodynamic drag properties of the VolturnUS+ platform, as well as observing the motion behavior of the platform and added resistance during towing in calm water and waves. The towing experiments are conducted in two towing configurations, with differing platform orientations and towline designs. The basin experiments are supplemented with a numerical study using computational fluid dynamic (CFD) simulations to explore flow-induced motion (FIM) on the platform during towing. In both the experiments and the CFD simulations, it was determined that the towing configuration significantly impacted the drag and motion characteristics of the platform, with the cruciform shape producing FIM phenomena. Observations from the towing tests confirmed the feasibility of towing the VolturnUS+ platform in the two orientations. The results and observations developed from the experimental and numerical towing studies will be used to inform numerical models for planning towing operations, as well as develop informed recommendations for towing similar cruciform-shaped structures in the future. Full article

Wireless optical communication technology offers advantages, such as high-data transmission rates, confidentiality, and robust anti-interception capabilities, making it highly promising for cross-sea–air interface communication applications. However, to our knowledge, no studies have been conducted on the spatial transmission efficiency of light after it passes through ocean waves. To address this issue, a seawater-wave–atmosphere model based on Gerstner waves was constructed. Using the Monte Carlo method, the optical power distributions of the laser light passing through the sea–air interface at the first- and second-level sea scales were simulated. The optimal positions for deploying one to three receiving optical systems were analyzed, and a laser communication receiving system was designed. Furthermore, simulations were conducted to determine the optical transmission efficiency of the designed optical receiver system. At the first-level sea scale, the optimal position for a single-point detector was (0°, ±5.61°), whereas those for the two detectors were (0°, ±5.61°) and (0°, ±5.68°). At the second-level sea scale, the optimal position for a single-point detector was (0°, ±3.17°), and the optimal positions for the two detectors were (0°, ±3.1°) and (0°, ±2.98°). Under the designed conditions, the optical transmission efficiency for a single detector at the first- and second-level sea scales was 0.74–0.88%, respectively, while it was 0.79–1.09% in the two-detector case. At the second-level sea scale, the optical transmission efficiency for a single detector was 0.37–2.09% and 0.50–1.97% in the two-detector case. Full article