Journal of Marine Science and Engineering

22 pages, 1990 KiB

Open AccessArticle

A Comparative Analysis of In Situ Testing Methods for Clay Strength Evaluation Using the Coupled Eulerian–Lagrangian Method

by Hebo Wang, Yifa Wang, Biao Li, Wengang Qi and Ning Wang

J. Mar. Sci. Eng. 2025, 13(5), 935; https://doi.org/10.3390/jmse13050935 - 9 May 2025

Abstract

The progression of marine resource exploration into deepwater and ultra-deepwater regions has intensified the requirement for precise quantification of the undrained shear strength of clay. Although diverse in situ testing methodologies—including the vane shear test (VST), cone penetration test (CPT), T-bar penetration test [...] Read more.

The progression of marine resource exploration into deepwater and ultra-deepwater regions has intensified the requirement for precise quantification of the undrained shear strength of clay. Although diverse in situ testing methodologies—including the vane shear test (VST), cone penetration test (CPT), T-bar penetration test (TPT), and ball penetration test (BPT)—are widely utilized for the assessment of clay strength, systematic discrepancies and correlations between their derived measurements remain inadequately resolved. The aim of this work is to provide a systematic comparison of strength interpretations across different in situ testing methods, with emphasis on identifying method-specific biases under varying soil behaviors. To achieve this, a unified numerical simulation framework was developed to simulate these four prevalent testing techniques, employing large-deformation finite element analysis via the Coupled Eulerian–Lagrangian (CEL) approach. The model integrates critical constitutive behaviors of marine clays, specifically strain softening and strain rate dependency, to replicate in situ shear strength evolution. Rigorous sensitivity analyses confirm the model’s robustness. The results indicate that, when the stain rate and softening effects are neglected, the resistance factors from the CPT and VST remain largely insensitive to shear strength variations. However, T-bar and ball penetrometers tend to underestimate strength by up to 15% in high-strength soils due to the incomplete development of a full-flow failure mechanism. As a result, their application in high-strength soils is not recommended. With both the strain rate and softening effects considered, the interpreted strength value S_ut from the CPT increases by 13.5% compared to cases excluding these effects, while other methods exhibit marginal decreases of 4–5%. The isolated analysis of strain softening reveals that, under identical softening parameters, the CPT demonstrates the least sensitivity to strain softening among the four methods examined, with the factor reduction ratio N_s/N₀ ranging from 0.76 to 1.00, while the other three methods range from 0.65 to 0.88. The results indicate that the CPT is well suited for strength testing in soils exhibiting pronounced softening behavior, as it reduces the influence of strain softening on the measured results. These findings provide critical insights into method-specific biases in undrained shear strength assessments, supporting a more reliable interpretation of in situ test data for deepwater geotechnical applications. Full article

(This article belongs to the Special Issue Wave–Structure–Seabed Interaction)

25 pages, 3631 KiB

Open AccessArticle

Hybrid Path Planning Method for USV Based on Improved A-Star and DWA

by Yan Liu, Zeqiang Sun, Junhe Wan, Hui Li, Delong Yang, Yanping Li, Wei Fu, Zhen Yu and Jichang Sun

J. Mar. Sci. Eng. 2025, 13(5), 934; https://doi.org/10.3390/jmse13050934 - 9 May 2025

Abstract

This paper presents a hybrid path planning method that integrates an enhanced A-Star algorithm with the Dynamic Window Approach (DWA). The proposed approach addresses the limitations of conventional A-Star algorithms in global path planning, particularly their inability to adaptively avoid obstacles in real-time. [...] Read more.

This paper presents a hybrid path planning method that integrates an enhanced A-Star algorithm with the Dynamic Window Approach (DWA). The proposed approach addresses the limitations of conventional A-Star algorithms in global path planning, particularly their inability to adaptively avoid obstacles in real-time. To improve navigation safety, the A-Star search strategy is enhanced by avoiding paths that intersect with obstacle vertices or pass through narrow channels. Additionally, a node optimization technique is introduced to remove redundant nodes by checking for collinearity in consecutive nodes. This optimization reduces the path length and ensures that the path maintains a safe distance from obstacles using parallel lines. An advanced Bézier curve smoothing method is also proposed, which adaptively selects control points to improve path smoothness and driving stability. By incorporating these improvements, the enhanced A-Star algorithm is combined with DWA to facilitate dynamic obstacle avoidance while generating global paths. The method accounts for the kinematic characteristics of the USV, as well as physical constraints such as linear and angular velocities, enabling effective handling of obstacles in dynamic environments and ensuring safe navigation. Simulation results demonstrate that the proposed algorithm generates secure global paths, significantly optimizing node count, path length, and smoothness, while effectively avoiding dynamic obstacles, thus ensuring safe navigation of the USV. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

22 pages, 732 KiB

Open AccessArticle

Optimal State Estimation in Underwater Vehicle Discrete-Continuous Measurements via Augmented Hybrid Kalman Filter

by Vadim Kramar, Kirill Dementiev and Aleksey Kabanov

J. Mar. Sci. Eng. 2025, 13(5), 933; https://doi.org/10.3390/jmse13050933 - 9 May 2025

Abstract

The paper focuses on the optimal state-estimation algorithm for discrete-continuous systems. The research aim is to create an effective strategy for combining data from continuous and discrete information sources to improve the state estimation accuracy and reliability of complex dynamic systems. The paper [...] Read more.

The paper focuses on the optimal state-estimation algorithm for discrete-continuous systems. The research aim is to create an effective strategy for combining data from continuous and discrete information sources to improve the state estimation accuracy and reliability of complex dynamic systems. The paper discusses, in detail, the theoretical foundations of the proposed method, including the mathematical description of continuous and discrete models, and its optimality criterion formulation. State-vector augmentation is proposed to improve the estimation convergence. The authors present numerical modeling results demonstrating the algorithm’s efficiency on the example of motion parameter estimation for the autonomous underwater vehicle. The conclusions are drawn about the promising application for the developed algorithm in various fields related to information processing in complex technical systems, such as navigation, motion control, and state and processes monitoring. It is noted that the proposed approach can be generalized to the case of more sources’ fusion. The paper is considered to be valuable for specialists in control theory and signal and information processing, as well as for navigation and motion-control system designers. The results obtained may find practical application in the development of high-precision state-estimation systems in various technical applications. Full article

(This article belongs to the Special Issue Marine Technology: Latest Advancements and Prospects)

29 pages, 12468 KiB

Open AccessArticle

Navigation Attitude Prediction for Unmanned Surface Vessels in Wave Environments Using Improved Unscented Kalman Filter and Digital Twin Model

by Shaochun Qu, Xuemeng Men, Minghao Liu, Jian Cui, Husheng Wu and Yanfang Fu

J. Mar. Sci. Eng. 2025, 13(5), 932; https://doi.org/10.3390/jmse13050932 - 9 May 2025

Abstract

Unmanned surface vehicles (USVs) face significant challenges in long-term operations in complex and dynamic marine environments. These include abnormal attitudes, low accuracy in navigation attitude prediction, and difficulties in maintaining operational stability and equipment safety. To address these issues, this paper proposed a [...] Read more.

Unmanned surface vehicles (USVs) face significant challenges in long-term operations in complex and dynamic marine environments. These include abnormal attitudes, low accuracy in navigation attitude prediction, and difficulties in maintaining operational stability and equipment safety. To address these issues, this paper proposed a USV navigation attitude prediction method that integrates Unscented Kalman Filtering (UKF) with a digital twin model. First, a three-degree-of-freedom mathematical model is constructed based on the motion characteristics of the USV to establish an initial digital twin model. Then, the UKF algorithm is improved with a dynamic sliding window approach and integrated with real vessel experimental data to achieve dynamic model parameter updates, further enhancing prediction accuracy. The updated twin model is subsequently used for USV navigation attitude prediction. Experimental results demonstrate that this method significantly improves prediction accuracy and robustness, even under complex sea conditions and sensor data loss, providing crucial support for the safety and reliability of USV autonomous navigation. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

18 pages, 8297 KiB

Open AccessArticle

Numerical Investigation of Jet Angle Effects on Thermal Dispersion Characteristics in Coastal Waters

by Longsheng Li, Hongyuan Shi, Huaiyuan Xue, Qing Wang and Chao Zhan

J. Mar. Sci. Eng. 2025, 13(5), 931; https://doi.org/10.3390/jmse13050931 - 9 May 2025

Abstract

Under the carbon neutrality framework, multiple coastal nuclear power plants in China have received construction approval. This development has drawn increased attention to the impact of thermal discharge on the marine environment. However, research on the diffusion effects caused by different thermal discharge [...] Read more.

Under the carbon neutrality framework, multiple coastal nuclear power plants in China have received construction approval. This development has drawn increased attention to the impact of thermal discharge on the marine environment. However, research on the diffusion effects caused by different thermal discharge configurations remains limited. This study focused on the Jinqimen Nuclear Power Plant. It employed the MIKE 3 (2014) three-dimensional numerical model, combined with field observations, to systematically investigate thermal plume dispersion. Specifically, it examined the effects of different jet angles at the discharge outlet (0°, 30°, 45°, 60°, 90°, and free diffusion conditions). The results indicate that the jet angle significantly influences the thermal rise envelope area and thermal stratification characteristics. Under free diffusion conditions (without jet velocity), the thermal rise area is the largest, with high-temperature zones concentrated near the surface. As the jet angle increases from 0° to 90°, the area of low-temperature rise gradually decreases, while the area of high-temperature rise expands. Among all tested configurations, the 30° jet angle exhibits the best overall performance. It demonstrates high thermal diffusion efficiency and strong heat dilution capacity. Moreover, it results in relatively smaller temperature rise areas at the surface, middle, and bottom layers. Additionally, tidal dynamics directly affect the thermal dispersion pattern. Smaller high-temperature rise areas are observed during peak flood and ebb tides. In contrast, heat accumulation is more likely to occur during slack tide periods. This study provides a scientific basis for optimizing the layout of nuclear power plant discharge outlets. It also serves as an important reference for mitigating thermal pollution and reducing ecological impacts of coastal nuclear power plants. Full article

(This article belongs to the Section Coastal Engineering)

► Show Figures

Figure 1

29 pages, 9843 KiB

Open AccessArticle

Coupled Response of Flexible Multi-Buoy Offshore Floating Photovoltaic Array Under Waves and Currents

by Xing-Hua Shi, Yiming Wang, Jing Zhang, C. Guedes Soares, Honglong Li and Jia Yu

J. Mar. Sci. Eng. 2025, 13(5), 930; https://doi.org/10.3390/jmse13050930 - 9 May 2025

Abstract

To study the response of a flexible offshore floating photovoltaic (FPV) array under waves and a current, a numerical model is established using OrcaFlex. The effects of different waves and currents, as well as their coupled effects on the motion response of the [...] Read more.

To study the response of a flexible offshore floating photovoltaic (FPV) array under waves and a current, a numerical model is established using OrcaFlex. The effects of different waves and currents, as well as their coupled effects on the motion response of the offshore PFV array and the tension in the connectors and moorings under different static tensions, are investigated. Differences are illustrated between the responses of the buoys at different positions and under different moorings under the wave. With the relaxed moorings, the surge response of the buoy facing the wave increased by 159.3% compared with the buoy facing away from the wave. The current causes the overall drift of the array, which greatly influences the buoys facing the current. The mooring tension facing the wave restricts the motion of the buoys under the same direction as the wave and current, which shows that the trend of the buoys’ responses with the wave decreases with the increase in the current velocity, as the pitch reduces to 76.9% under relaxed moorings. There is a significant difference between the results obtained by the superposition summation wave and current loads and the ones of the combined wave–current. With the increase in the wave–current angle, the response is increased by 348.2% as the constraint of the moorings and the connectors is weakened. Full article

(This article belongs to the Special Issue Development and Utilization of Offshore Renewable Energy)

► Show Figures

Figure 1

25 pages, 3951 KiB

Open AccessArticle

Port Green Transformation Factors Assessment

by Vytautas Paulauskas, Donatas Paulauskas and Antanas Markauskas

J. Mar. Sci. Eng. 2025, 13(5), 929; https://doi.org/10.3390/jmse13050929 - 9 May 2025

Abstract

The ambition of ports to become green and smart ports is one of the important ways to reduce environmental impacts and optimize energy consumption in passenger service and cargo handling operations in ports. One of the ways to transform a green port is [...] Read more.

The ambition of ports to become green and smart ports is one of the important ways to reduce environmental impacts and optimize energy consumption in passenger service and cargo handling operations in ports. One of the ways to transform a green port is to use renewable energy sources, more environmentally friendly fuels and reduce emissions in passenger service and cargo handling operations. The article analyses the main factors of green port transformation and factors assessment, including port strategy, port management, passenger service and cargo handling operations (port activity level), additional port services, and the activities of companies providing services to the port. Optimization of the indicated factors is important from the point of view of environmental sustainability. The article presents a methodology for direct and relative assessment of the current state of the green transformation and emissions generated in the port and options for reducing the environmental impact. This approach enables each port to evaluate its stage in the green transformation process and identify the primary emissions it produces. By understanding the actual state of green transformation, ports can identify the factors and measures necessary to improve their environmental performance and reduce their ecological footprint. The article presents a methodology for assessing green transformation and calculating both absolute and relative emissions, which can be adapted and applied to any port. Full article

(This article belongs to the Special Issue Maritime Logistics and Green Shipping)

► Show Figures

Figure 1

20 pages, 5879 KiB

Open AccessArticle

A High-Precision Method for Evaluating the Similarity of Maritime Vessel Trajectories

by Ran Ji, Mengkai Ma, Jian Dong and Sen Wang

J. Mar. Sci. Eng. 2025, 13(5), 928; https://doi.org/10.3390/jmse13050928 - 8 May 2025

Abstract

This study investigates the demand for high-precision trajectory similarity assessment in intelligent maritime navigation. This is done by analyzing discrepancies between GPS-derived trajectories and actual vessel paths, while identifying critical limitations in existing evaluation methods. To address these challenges, we propose a robust [...] Read more.

This study investigates the demand for high-precision trajectory similarity assessment in intelligent maritime navigation. This is done by analyzing discrepancies between GPS-derived trajectories and actual vessel paths, while identifying critical limitations in existing evaluation methods. To address these challenges, we propose a robust framework that integrates three core innovations: firstly, a linear feature accuracy-constrained resampling method to ensure computational precision under diverse complexity conditions, validated through experimental verification; secondly, a shape feature extraction and transformation protocol designed to maintain consistency across multi-scale and heterogeneous operational scenarios; thirdly, a quantitative similarity evaluation criterion based on extracted shape characteristics, enabling systematic alignment between localized trajectory segments and historical navigation patterns. The experimental results confirm the method’s enhanced robustness and its capability to bridge local and global trajectory comparisons, demonstrating that shape-driven quantification significantly refines similarity analysis. This approach advances intelligent maritime systems by providing a technically rigorous solution for real-time decision support and actionable insights into next-generation navigation applications. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

16 pages, 3560 KiB

Open AccessArticle

Year-Round Acoustic Presence of Beaked Whales (Ziphiidae) Far Offshore off Australia’s Northwest Shelf

by Evgenii Sidenko, Iain Parnum, Alexander Gavrilov, Robert McCauley and Christine Erbe

J. Mar. Sci. Eng. 2025, 13(5), 927; https://doi.org/10.3390/jmse13050927 - 8 May 2025

Abstract

Beaked whales are a cryptic pelagic species, rarely sighted at sea. In a ~2.5-year passive acoustic monitoring program on Australia’s Northwest Shelf, a variety of marine mammal sounds were detected, including beaked whale (Ziphiidae) clicks. An automatic detection routine for beaked whale clicks [...] Read more.

Beaked whales are a cryptic pelagic species, rarely sighted at sea. In a ~2.5-year passive acoustic monitoring program on Australia’s Northwest Shelf, a variety of marine mammal sounds were detected, including beaked whale (Ziphiidae) clicks. An automatic detection routine for beaked whale clicks was developed, tested, and run on these recordings. The detection workflow included: (1) the extraction of impulsive signals from passive acoustic recordings based on an auto-regression model, (2) the calculation of a set of features of extracted signals, and (3) binary signal classification based on these features. Detector performance (Precision, Recall, and F1-score) was assessed using a manually annotated dataset of extracted clicks. This automated routine allows for quick analysis of animal (acoustic) presence and distribution spatially and temporally. In our study, beaked whales were present all year round at six deep-water (>1000 m) sites, but no clicks were detected at the shallow-water (~70 m) site. No seasonal or diurnal patterns of beaked whale clicks were identified. Full article

(This article belongs to the Special Issue Advances in Ecological Modelling of Marine Mammal Habitats of Importance)

► Show Figures

Figure 1

16 pages, 3414 KiB

Open AccessArticle

Underwater Side-Scan Sonar Target Detection: An Enhanced YOLOv11 Framework Integrating Attention Mechanisms and a Bi-Directional Feature Pyramid Network

by Junhui Zhu, Houpu Li, Min Liu, Guojun Zhai, Shaofeng Bian, Ye Peng and Lei Liu

J. Mar. Sci. Eng. 2025, 13(5), 926; https://doi.org/10.3390/jmse13050926 - 8 May 2025

Abstract

Underwater target detection is pivotal for marine exploration, yet it faces significant challenges because of the inherent complex underwater environment. Sonar images are generally degraded by noise, exhibit low resolution, and lack prominent target features, making the extraction of useful feature information from [...] Read more.

Underwater target detection is pivotal for marine exploration, yet it faces significant challenges because of the inherent complex underwater environment. Sonar images are generally degraded by noise, exhibit low resolution, and lack prominent target features, making the extraction of useful feature information from blurred and complex backgrounds particularly challenging. These limitations hinder highly accurate autonomous target detection in sonar imagery. To address these issues, this paper proposes the ABFP-YOLO model, which was designed to enhance the accuracy of underwater target detection. Specifically, the bi-directional feature pyramid network (BiFPN) structure is integrated into the model to efficiently fuse the features of different scales, significantly improving the capability of the network to recognize targets of varying scales, especially small targets in complex scenarios. Additionally, an attention module is incorporated to enhance feature extraction from blurred images, thereby boosting the detection accuracy of the model. To validate the proposed model’s effectiveness, extensive comparative and ablation experiments were conducted on two datasets. The experimental results demonstrate that the ABFP-YOLO model achieves mean average precision (mAP0.5) scores of 0.988 and 0.866, indicating its superior performance in target detection tasks within complex underwater environments. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

21 pages, 5470 KiB

Open AccessArticle

YOLO-LPSS: A Lightweight and Precise Detection Model for Small Sea Ships

by Liran Shen, Tianchun Gao and Qingbo Yin

J. Mar. Sci. Eng. 2025, 13(5), 925; https://doi.org/10.3390/jmse13050925 - 8 May 2025

Abstract

The accurate detection of small ships based on images or vision is critical for many scenarios, like maritime surveillance, port security, and navigation safety. However, achieving accurate detection for small ships is a challenge for cost-efficiency models; while the models could meet this [...] Read more.

The accurate detection of small ships based on images or vision is critical for many scenarios, like maritime surveillance, port security, and navigation safety. However, achieving accurate detection for small ships is a challenge for cost-efficiency models; while the models could meet this requirement, they have unacceptable computation costs for real-time surveillance. We propose YOLO-LPSS, a novel model designed to significantly improve small ship detection accuracy with low computation cost. The characteristics of YOLO-LPSS are as follows: (1) Strengthening the backbone’s ability to extract and emphasize features relevant to small ship objects, particularly in semantic-rich layers. (2) A sophisticated, learnable method for up-sampling processes is employed, taking into account both deep image information and semantic information. (3) Introducing a post-processing mechanism in the final output of the resampling process to restore the missing local region features in the high-resolution feature map and capture the global-dependence features. The experimental results show that YOLO-LPSS outperforms the known YOLOv8 nano baseline and other works, and the number of parameters increases by only 0.33 M compared to the original YOLOv8n while achieving 0.796 and 0.831 AP^50:95 in classes consisting mainly of small ship targets (the bounding box of the target area is less than 5% of the image resolution), which is 3–5% higher than the vanilla model and recent SOTA models. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

17 pages, 12491 KiB

Open AccessArticle

Hydrodynamic Analysis of Combined Offshore Wind Turbine and Net Cage Under Finite-Depth Waves

by Bin Wang, Mingfu Tang, Zhenqiang Jiang and Guohai Dong

J. Mar. Sci. Eng. 2025, 13(5), 924; https://doi.org/10.3390/jmse13050924 - 8 May 2025

Viewed by 34

Abstract

Offshore wind turbines are subjected to long-term wave loads, which shorten their service life. Marine aquaculture cages are common structures in the ocean engineering field. Therefore, investigating the hydrodynamic characteristics of combined wind turbine and cage facilities under wave loads is crucial. This [...] Read more.

Offshore wind turbines are subjected to long-term wave loads, which shorten their service life. Marine aquaculture cages are common structures in the ocean engineering field. Therefore, investigating the hydrodynamic characteristics of combined wind turbine and cage facilities under wave loads is crucial. This study employs a porous medium model to analyze the hydrodynamic behavior of a fixed wind turbine base integrated with cages under finite-depth wave conditions. First, the transmission coefficients of waves passing through cages at different positions were examined under varying cage solidity conditions. The results indicate that the cages minimally affect wave height in regions close to the cage group. Subsequently, the wave forces acting on the fixed wind turbine base behind the cages were analyzed under different solidity and wave height conditions. The variation curves of the drag coefficient and inertia coefficient were obtained for solidity values ranging from 0.3 to 0.6 and Keulegan–Carpenter (KC) numbers between 1 and 4. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

18 pages, 6095 KiB

Open AccessArticle

Influence of Viscous Effects on Mooring Buoy Motion

by Yunmiao Li, Jian Zhou, Heping Wang and Chenxu Wang

J. Mar. Sci. Eng. 2025, 13(5), 923; https://doi.org/10.3390/jmse13050923 - 7 May 2025

Viewed by 31

Abstract

Field observations revealed that a mooring buoy rapidly drifts in a reciprocating motion along an arcuate path between two extreme positions. When the anchor point is considered the origin and viewed from an aerial perspective, this movement resembles a pendulum. The implications of [...] Read more.

Field observations revealed that a mooring buoy rapidly drifts in a reciprocating motion along an arcuate path between two extreme positions. When the anchor point is considered the origin and viewed from an aerial perspective, this movement resembles a pendulum. The implications of this motion for data acquisition efficiency prompted our inquiry into this phenomenon. The comparative analysis of the model’s different movements under wave-only, current-only, and wave–current conditions demonstrates that currents are the source inducing this pendulum-like motion. To investigate the mechanism of this current-driven motion, the flow field around the buoy was visualized through numerical simulations. Specifically, the CFD results aligned with the field data and confirmed that periodic vortex shedding induces oscillatory forces, which dominate the rapid reciprocating movement. The findings emphasize the significant impact of fluid viscosity and the resulting vortex effects on the motion characteristics of buoys. They can provide a foundation for addressing more applied problems of data error-correcting and trajectory predictions. Full article

(This article belongs to the Special Issue Application of Advanced Technologies in Maritime Safety—Second Edition)

► Show Figures

Figure 1

29 pages, 19185 KiB

Open AccessArticle

An AIS-Based Study to Estimate Ship Exhaust Emissions Using Spatio-Temporal Approach

by Akhahenda Whitney Khayenzeli, Woo-Ju Son, Dong-June Jo and Ik-Soon Cho

J. Mar. Sci. Eng. 2025, 13(5), 922; https://doi.org/10.3390/jmse13050922 - 7 May 2025

Viewed by 27

Abstract

The global shipping industry facilitates the movement of approximately 80% of goods across the world but accounts for nearly 3% of total greenhouse gas (GHG) emissions every year, and other pollutants. One challenge in reducing shipping emissions is understanding and quantifying emission characteristics. [...] Read more.

The global shipping industry facilitates the movement of approximately 80% of goods across the world but accounts for nearly 3% of total greenhouse gas (GHG) emissions every year, and other pollutants. One challenge in reducing shipping emissions is understanding and quantifying emission characteristics. A detailed method for calculating shipping emissions should be applied when preparing exhaust gas inventory. This research focused on quantifying CO₂, NO_x, and SO_x emissions from tankers, containers, bulk carriers, and general cargo in the Republic of Korea using spatio-temporal analysis and maritime big data. Using the bottom-up approach, this study calculates vessel emissions from the ship engines while considering the fuel type and operation mode. It leveraged the Geographic Information System (GIS) to generate spatial distribution maps of vessel exhausts. The research revealed variability in emissions according to ship types, sizes, and operational modes. CO₂ emissions were dominant, totaling 10.5 million tons, NO_x 179,355.2 tons, and SO_x 32,505.1 tons. Tankers accounted for about 43.3%, containers 33.1%, bulk carriers 17.3%, and general cargo 6.3%. Further, emissions in hoteling and cruising were more significant than during maneuvering and reduced speed zones (RSZs). This study contributes to emission databases, providing a basis for the establishment of targeted emission control policies. Full article

(This article belongs to the Special Issue Smart and Low Carbon Emission-Oriented Maritime Traffic Management and Controlling)

► Show Figures

Figure 1

16 pages, 31769 KiB

Open AccessArticle

Orbital-Scale Modulation of the Middle Miocene Third-Order Eustatic Sequences from the Northern South China Sea

by Haichun Xu, Nan Wu, Xinyan Xu, Bo Yu and Ke Xu

J. Mar. Sci. Eng. 2025, 13(5), 921; https://doi.org/10.3390/jmse13050921 - 7 May 2025

Viewed by 20

Abstract

The Miocene Hanjiang Formation (HJF) is a remarkable exploration target in the Pearl River Mouth Basin (PRMB). However, challenges such as bias in current sequence stratigraphic schemes, limitations in high-resolution stratigraphic schemes, and incomplete understanding of genetic mechanisms may present obstacles for refining [...] Read more.

The Miocene Hanjiang Formation (HJF) is a remarkable exploration target in the Pearl River Mouth Basin (PRMB). However, challenges such as bias in current sequence stratigraphic schemes, limitations in high-resolution stratigraphic schemes, and incomplete understanding of genetic mechanisms may present obstacles for refining hydrocarbon exploration strategies. This study integrates gamma ray (GR) logging data, lithological variations, sequence stratigraphy, and cyclostratigraphy to delineate connections between sequence stratigraphy and astronomical forcing. The analysis utilizes gamma-ray logging data from boreholes LFA (1250–1960 m) and LFB (1070–1955 m) in the HJF. We constructed an absolute astronomical time scale anchored at the HJF’s top boundary (10.221 ± 0.4 Ma), identifying 6 third-order sequences through detailed analysis. Notably, 18 long-eccentricity cycles (405 kyr) and distinctive 1.2-Myr obliquity modulation signals were detected in the stratigraphic record. Our study demonstrates distinct connection between third-order sequence boundaries and the 1.2-Myr obliquity cycles, congruent with both global eustatic sea-level fluctuations and regional sea-level changes in the PRMB. The integration of cyclostratigraphic methods with sequence stratigraphic analysis proves particularly valuable for objective stratigraphic subdivision and understanding third-order sequence evolution in the divergent continental margin settings of the South China Sea. This approach enhances temporal resolution on a regional scale while revealing astronomical forcing mechanisms governing sedimentary cyclicity. Full article

(This article belongs to the Special Issue Recent Developments and Advances in Geological Oceanography and Ocean Observation in the Pacific Ocean and Its Marginal Basins—2nd Edition)

► Show Figures

Figure 1

6 pages, 166 KiB

Open AccessEditorial

Autonomous Marine Vehicle Operations—2nd Edition

by Xiao Liang, Rubo Zhang and Xingru Qu

J. Mar. Sci. Eng. 2025, 13(5), 920; https://doi.org/10.3390/jmse13050920 - 7 May 2025

Viewed by 6

Abstract

In recent years, the field of autonomous marine vehicles has undergone remarkable advancements, with unmanned surface vehicles (USVs) and unmanned underwater vehicles (UUVs) demonstrating transformative potential for oceanographic exploration and marine applications [...] Full article

(This article belongs to the Special Issue Autonomous Marine Vehicle Operations—2nd Edition)

18 pages, 1986 KiB

Open AccessArticle

Underwater Time Delay Estimation Based on Meta-DnCNN with Frequency-Sliding Generalized Cross-Correlation

by Meiqi Ji, Xuerong Cui, Juan Li, Lei Li and Bin Jiang

J. Mar. Sci. Eng. 2025, 13(5), 919; https://doi.org/10.3390/jmse13050919 - 7 May 2025

Viewed by 10

Abstract

In underwater signal processing, accurate time delay estimation (TDE) is of crucial importance for ensuring the reliability of data transmission. However, the complex propagation of sound waves and strong noise interference in the underwater environment make this task extremely challenging. Especially under the [...] Read more.

In underwater signal processing, accurate time delay estimation (TDE) is of crucial importance for ensuring the reliability of data transmission. However, the complex propagation of sound waves and strong noise interference in the underwater environment make this task extremely challenging. Especially under the condition of low signal-to-noise ratio (SNR), the existing methods based on cross-correlation and deep learning struggle to meet requirements. Aiming at this core issue, this paper proposed an innovative solution. Firstly, a multi-sub-window reconstruction is performed on the frequency-sliding generalized colorboxpinkcross-correlation (FS-GCC) matrix between signals to capture the time delay characteristics from different frequency bands and conduct the enhancement and extraction of features. Then, the grayscale image corresponding to the generated FS-GCC matrix is used, and the multi-level noise features are extracted by the multi-layer convolution of denoising convolutional neural network (DnCNN), effectively suppressing the noise and improving the estimation accuracy. Finally, the model-agnostic meta-learning (MAML) framework is introduced. Through training tasks under various SNR conditions, the model is enabled to possess the ability to quickly adapt to new environments, and it can achieve the desired estimation accuracy even when the number of underwater training samples is limited. Simulation validation was conducted under the NOF and NCS underwater acoustic channels, and results demonstrate that our proposed approach exhibits lower estimation errors and greater stability compared with existing methods under the same conditions. This method enhances the practicality and robustness of the model in complex underwater environments, providing strong support for the efficient and stable operation of underwater sensor networks. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

32 pages, 10189 KiB

Open AccessArticle

NSMO-Based Adaptive Finite-Time Command-Filtered Backstepping Speed Controller for New Energy Hybrid Ship PMSM Propulsion System

by Dan Zhang, Suijun Xiao, Hongfen Bai, Diju Gao and Baonan Wang

J. Mar. Sci. Eng. 2025, 13(5), 918; https://doi.org/10.3390/jmse13050918 - 7 May 2025

Viewed by 18

Abstract

In the context of the new energy hybrid ship propulsion system (NE-HSPS), the parameters of the rotor speed, torque, and current of the permanent magnet synchronous motor (PMSM) are susceptible to environmental variations and unmodeled disturbances. Conventional nonlinear controllers (e.g., backstepping, PI, and [...] Read more.

In the context of the new energy hybrid ship propulsion system (NE-HSPS), the parameters of the rotor speed, torque, and current of the permanent magnet synchronous motor (PMSM) are susceptible to environmental variations and unmodeled disturbances. Conventional nonlinear controllers (e.g., backstepping, PI, and sliding mode) encounter challenges related to response speed, interference immunity, and vibration jitter. These challenges stem from the inherent uncertainties in perturbations and the limitations of the traditional nonlinear controllers. In this paper, a novel Adaptive Finite-Time Command-Filtered Backstepping Controller (AFTCFBC) is proposed, featuring a faster response time and the elimination of overshoot. The proposed controller is a significant advancement in the field, addressing the computational complexity of backstepping control and reducing the maximum steady-state error of the control output. The novel controller incorporates a Nonlinear Finite-Time Command Filter (NFTCF) adapted to the variation in motor speed. Secondly, a novel Nonlinear Sliding Mode Observer (NSMO) is proposed based on the designed nonlinear sliding mode gain function (φ(S_w)) to estimate the load disturbance of the electric propulsion system. The Uncertainty Parameter-Adaptive law (UPAL) is designed based on Lyapunov theory to improve the robust performance of the system. The construction of a simulation model of a hybrid ship PMSM under four distinct working conditions, including constant speed and constant torque, the lifting and lowering of speed, loading and unloading, and white noise interference, is presented. The results of this study demonstrate a significant reduction in speed-tracking overshoot to zero, a substantial decrease in integral squared error by 90.15%, and a notable improvement in response time by 18.6%. Full article

(This article belongs to the Topic Advanced Operation, Control, and Planning of Intelligent Energy Systems)

► Show Figures

Figure 1

15 pages, 1930 KiB

Open AccessArticle

A Data Cleaning Method for the Identification of Outliers in Fishing Vessel Trajectories Based on a Geocoding Algorithm

by Li Zhang and Weifeng Zhou

J. Mar. Sci. Eng. 2025, 13(5), 917; https://doi.org/10.3390/jmse13050917 - 6 May 2025

Viewed by 95

Abstract

In modern fishery management, fishing vessel trajectory data are used to monitor and analyze fishing vessel activities. However, trajectory data are often of low quality, probably due to environmental factors, equipment failures, signal loss and operation errors, leading to numerous outliers in these [...] Read more.

In modern fishery management, fishing vessel trajectory data are used to monitor and analyze fishing vessel activities. However, trajectory data are often of low quality, probably due to environmental factors, equipment failures, signal loss and operation errors, leading to numerous outliers in these data. These outliers not only undermine the credibility of the data but also negatively affect the subsequent data mining and decision-making. In this study, a data cleaning method for the identification of outlier points in fishing vessel trajectories based on the Geohash geocoding algorithm is given, which involves several key steps: obtaining and preprocessing the raw trajectory data; generating the corresponding Geohash codes for each ship position based on its latitude and longitude; calculating the reachable distance considering the time interval between the current point and the following points and their speeds; querying the neighborhood of the current point based on the reachable distance; and obtaining all Geohash codes of the reachable areas of the fishing vessels within the time interval as the reachable range grid set of the current position. The reachable range grid set of the current position is compared with the reachable range grid sets of the previous point identified as normal and the next point in the fishing vessel trajectory. If there is no intersection, it is determined that the current fishing vessel position is an outlier, and this point will be excluded. The method proposed in this study is able to effectively identify outliers in trajectory data, achieving efficient and effective trajectory data cleaning and improving the accuracy and reliability of the data. Full article

(This article belongs to the Special Issue Management and Control of Ship Traffic Behaviours)

► Show Figures

Figure 1

31 pages, 18555 KiB

Open AccessArticle

Fast Non-Dominated Sorting Tuna Swarm Optimization Algorithm (FNS-TSO): Time-Energy-Impact Multi-Objective Optimization of Underwater Manipulator Trajectories

by Xingyao Wang, Yanjun Liu, Gang Xue, Fagang Bai and Shuting Huang

J. Mar. Sci. Eng. 2025, 13(5), 916; https://doi.org/10.3390/jmse13050916 - 6 May 2025

Viewed by 57

Abstract

To achieve time–energy–impact multi-objective optimization in the trajectory control of underwater manipulators, this paper proposes a Fast Non-Dominated Sorting Tuna Swarm Optimization algorithm (FNS-TSO). The algorithm integrates a fast non-dominated sorting mechanism into the Tuna Swarm Optimization algorithm, improves initialization through Optimal Latin [...] Read more.

To achieve time–energy–impact multi-objective optimization in the trajectory control of underwater manipulators, this paper proposes a Fast Non-Dominated Sorting Tuna Swarm Optimization algorithm (FNS-TSO). The algorithm integrates a fast non-dominated sorting mechanism into the Tuna Swarm Optimization algorithm, improves initialization through Optimal Latin Hypercubic Sampling (OLHS) to enhance population distribution uniformity, and incorporates a nonlinear dynamic weight to refine the spiral foraging strategy, thereby strengthening algorithmic robustness. To verify FNS-TSO’s effectiveness, we conducted comparative evaluations using standard test functions against three established algorithms: Multi-Objective Particle Swarm Optimization (MOPSO), Multi-Objective Jellyfish Search Optimization (MOJSO), and the Non-Dominated-Sorting Genetic Algorithm (NSGA-II). Results demonstrate superior overall performance, particularly regarding convergence speed and solution diversity, with solution set distributions showing enhanced uniformity. In practical implementation, we applied FNS-TSO to the multi-objective optimization of an underwater manipulator using quintic spline curves for trajectory planning. Simulation outcomes reveal respective reductions of 11.03% in total operation time, 19.02% in energy consumption, and 24.69% in mechanical impacts, with the optimized manipulator achieving stable point-to-point motion transitions. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

16 pages, 13077 KiB

Open AccessArticle

Effect of Blade Number on Tip Vortex Cavitation of Propeller

by Yanan Wang, Yang Xiao, Bin Fang, Wen Li, Chuanzhi Duan, Weipeng Zhang and Jian Hu

J. Mar. Sci. Eng. 2025, 13(5), 915; https://doi.org/10.3390/jmse13050915 - 6 May 2025

Viewed by 73

Abstract

Tip vortex cavitation not only impacts the hydrodynamic performance of a propeller but also results in vibrations, noise, and erosion. In this study, the effect of blade number on propeller tip vortex cavitation is investigated using computational fluid dynamics (CFD) methods. Numerical simulation [...] Read more.

Tip vortex cavitation not only impacts the hydrodynamic performance of a propeller but also results in vibrations, noise, and erosion. In this study, the effect of blade number on propeller tip vortex cavitation is investigated using computational fluid dynamics (CFD) methods. Numerical simulation is performed regarding four model propellers with blade numbers varying from one to four. These propellers have the same blade geometry as the E779A propeller. Large eddy simulation (LES) and the Schnerr–Sauer cavitation model are used to solve tip vortex cavitation with local mesh refinement according to the spiral tip vortex trajectory. The hydrodynamic performance and tip cavitation of the propellers are solved and analyzed to reveal the fluid mechanism of tip vortex formation. The effect of blade number on wake velocity and wake vorticity is discussed. Numerical analysis showed that the increase in blade number leads to a reduction in the thrust and torque of a single blade, although the total thrust and torque of all blades increased. The present study takes new insights to the suppression of tip vortex cavitation, which benefits propeller design. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

15 pages, 6419 KiB

Open AccessArticle

Sediment Resuspension in the Yellow River Subaqueous Delta During Gale Events

by Jingjing Qi, Siyu Liu, Lulu Qiao, Xingyu Xu, Jianing Li, Haonan Li and Guangxue Li

J. Mar. Sci. Eng. 2025, 13(5), 914; https://doi.org/10.3390/jmse13050914 - 6 May 2025

Viewed by 86

Abstract

During winter, strong winds and waves significantly enhance sediment resuspension in the Yellow River Delta. Based on the continuous and high-resolution data on water levels, wave heights, current velocities, and echo intensities collected by the Acoustic Doppler Current Profiler at different depths (5 [...] Read more.

During winter, strong winds and waves significantly enhance sediment resuspension in the Yellow River Delta. Based on the continuous and high-resolution data on water levels, wave heights, current velocities, and echo intensities collected by the Acoustic Doppler Current Profiler at different depths (5 m and 12 m) in the northern Yellow River Delta simultaneously, this study investigated the sediment resuspension during gale events and tranquil conditions. In deeper waters (12 m), the suspended sediment volume concentration (SSVC) showed a strong correlation with current speed (r = 0.74), while in shallower waters (5 m), the SSVC correlated more closely with wave height (r = 0.72). The thorough analysis of gale events revealed that the maximum wave heights during northwest gales were 23.80% and 34.59% lower than that during northeast gales at deep and shallow stations, respectively, primarily due to the longer wind fetch associated with northeast gales. Conversely, the maximum current velocities during northwest gales were 10.34% and 37.31% higher than that during northeast gales at deep and shallow stations. In deeper waters, the maximum wave–current induced shear stress

$(τ_{c w}$ ) and SSVC during northwest gales were 30.38% and 3.70% higher than those during northeast gales, highlighting current-driven resuspension. In contrast, in shallower waters, the maximum

$τ_{c w}$ and SSVC during northeast gales were 47.35% and 4.94% higher than those during northwest gales, underscoring the dominance of wave-induced resuspension. Full article

(This article belongs to the Section Coastal Engineering)

► Show Figures

Figure 1

30 pages, 12300 KiB

Open AccessArticle

VIOS-Net: A Multi-Task Fusion System for Maritime Surveillance Through Visible and Infrared Imaging

by Junquan Zhan, Jiawen Li, Langtao Wu, Jiahua Sun and Hui Yin

J. Mar. Sci. Eng. 2025, 13(5), 913; https://doi.org/10.3390/jmse13050913 - 6 May 2025

Viewed by 101

Abstract

Automatic ship monitoring models leveraging image recognition have become integral to regulatory applications within maritime management, with multi-source image co-monitoring serving as the primary method for achieving comprehensive, round-the-clock surveillance. Despite their widespread use, the existing models predominantly train each data source independently [...] Read more.

Automatic ship monitoring models leveraging image recognition have become integral to regulatory applications within maritime management, with multi-source image co-monitoring serving as the primary method for achieving comprehensive, round-the-clock surveillance. Despite their widespread use, the existing models predominantly train each data source independently or simultaneously train multiple sources without fully optimizing the integration of similar information. This approach, while capable of all-weather detection, results in the underutilization of data features from related sources and unnecessary repetition in model training, leading to excessive time consumption. To address these inefficiencies, this paper introduces a novel multi-task learning framework designed to enhance the utilization of data features from diverse information sources, thereby reducing training time, lowering costs, and improving recognition accuracy. The proposed model, VIOS-Net, integrates the advantages of both visible and infrared data sources to meet the challenges of all-weather, all-day ship monitoring under complex environmental conditions. VIOS-Net employs a Shared Bottom network architecture, utilizing both shared and specific feature extraction modules at the model’s lower and upper layers, respectively, to optimize the system’s recognition capabilities and maximize data utilization efficiency. The experimental results demonstrate that VIOS-Net achieves an accuracy of 96.20% across both visible and infrared spectral datasets, significantly outperforming the baseline ResNet-34 model, which attained accuracies of only 4.86% and 9.04% in visible and infrared data, respectively. Moreover, VIOS-Net reduces the number of parameters by 48.82% compared to the baseline, achieving optimal performance in multi-spectral ship monitoring. Extensive ablation studies further validate the effectiveness of the individual modules within the proposed framework. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

15 pages, 6083 KiB

Open AccessArticle

Investigation of 1,3-Diketone and Nano-Copper Additives for Enhancing Boundary Lubrication Performance

by Jingsi Wang, Dezhi Teng, Jiawei Fan, Xi Zhang, Qihang Cui, Ke Li and Pay Jun Liew

J. Mar. Sci. Eng. 2025, 13(5), 912; https://doi.org/10.3390/jmse13050912 - 4 May 2025

Viewed by 276

Abstract

In this work, 1,3-diketone synthesized via the Claisen condensation method and nano-copper particles modified by the Brust–Schiffrin method were added into a commercial marine medium-speed diesel engine cylinder piston oil to evaluate their effects on boundary lubrication performance. Friction and wear tests conducted [...] Read more.

In this work, 1,3-diketone synthesized via the Claisen condensation method and nano-copper particles modified by the Brust–Schiffrin method were added into a commercial marine medium-speed diesel engine cylinder piston oil to evaluate their effects on boundary lubrication performance. Friction and wear tests conducted on CKS-coated piston ring and cast-iron cylinder liner samples demonstrated significant reductions in both friction and wear with the addition of 1,3-diketone and nano-copper particles. Compared to the original oil without additives, the friction force was reduced by up to 16.7%, while the wear of the piston ring and cylinder liner was decreased by up to 21.6% and 15.1% at 150 °C, respectively. A worn surface analysis indicated that the addition of 1,3-diketone and functionalized nano-copper particles influenced the depolymerization and tribo-chemical reactions of the anti-wear additive ZDDP (zinc dialkyldithiophosphate) in the original engine oil. This modification enhanced the oil’s anti-friction and anti-wear properties, offering valuable insights into the development of eco-friendly lubricants for energy-efficient systems. Full article

► Show Figures

Figure 1

28 pages, 4871 KiB

Open AccessArticle

Three-Dimensional Spatio-Temporal Slim Weighted Generative Adversarial Imputation Network: Spatio-Temporal Silm Weighted Generative Adversarial Imputation Net to Repair Missing Ocean Current Data

by Yiwan Yue, Juan Li, Yu Zhang, Meiqi Ji, Jingyao Zhang and Rui Ma

J. Mar. Sci. Eng. 2025, 13(5), 911; https://doi.org/10.3390/jmse13050911 - 4 May 2025

Viewed by 223

Abstract

Three-dimensional ocean observation is the foundation for accurately predicting ocean information. Although ocean observation sensor arrays can obtain internal data, their deployment is difficult, costly, and prone to component failures and environmental noise, resulting in discontinuous data. To address the severe missing data [...] Read more.

Three-dimensional ocean observation is the foundation for accurately predicting ocean information. Although ocean observation sensor arrays can obtain internal data, their deployment is difficult, costly, and prone to component failures and environmental noise, resulting in discontinuous data. To address the severe missing data problem in three-dimensional ocean flow fields, this paper proposes an unsupervised model: Three-dimensional Spatio-Temporal Slim Weighted Generative Adversarial Imputation Network (3D-STA-SWGAIN). This method integrates spatio-temporal attention mechanisms and Wasserstein constraints. The generator captures the three-dimensional spatial distribution and vertical profile dynamic patterns through the spatio-temporal attention module, while the discriminator introduces gradient penalty constraints to prevent gradient vanishing. The generator strives to generate data that conforms to the real ocean flow field, and the discriminator attempts to identify pseudo-ocean current data samples. Through the adversarial training of the generator and the discriminator, high-quality completed data are generated. Additionally, a spatio-temporal continuity loss function is designed to ensure the physical rationality of the data. Experiments show that on the three-dimensional flow field dataset of the South China Sea, compared with methods such as GAIN, under a 50% random missing rate, this method reduces the error by 37.2%. It effectively solves the problem that traditional interpolation methods have difficulty handling non-uniform missing and spatio-temporal correlations and maintains the spatio-temporal continuity of the current field’s three-dimensional structure. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

23 pages, 6499 KiB

Open AccessArticle

Enhancing Ocean Temperature and Salinity Reconstruction with Deep Learning: The Role of Surface Waves

by Xiaoyu Yu, Daling Li Yi and Peng Wang

J. Mar. Sci. Eng. 2025, 13(5), 910; https://doi.org/10.3390/jmse13050910 - 3 May 2025

Viewed by 245

Abstract

In oceanographic research, reconstructing the three-dimensional (3D) distribution of temperature and salinity is essential for understanding global climate dynamics, predicting marine environmental changes, and evaluating their impacts on ecosystems. While previous studies have largely concentrated on the effects of various modeling approaches on [...] Read more.

In oceanographic research, reconstructing the three-dimensional (3D) distribution of temperature and salinity is essential for understanding global climate dynamics, predicting marine environmental changes, and evaluating their impacts on ecosystems. While previous studies have largely concentrated on the effects of various modeling approaches on reconstructing oceanic variables, limited attention has been paid to the role of surface waves in reconstruction. This study, based on sea surface data, employs a deep learning-based neural network model, U-Net, to reconstruct 3D temperature and salinity across the North Pacific and Equatorial Pacific within the upper 200 m. The input of wave information includes the significant wave height (SWH), Langmuir number (La), and Langmuir enhancement factor (ε); the latter two indicate the strength of Langmuir turbulence, which promotes vertical mixing in the ocean surface layer and thereby affects profiles of temperature and salinity. The results indicate that incorporating wave information, particularly the La and ε, significantly enhances the model’s ability to reconstruct ocean temperature and salinity. This highlights the critical role of surface waves in enhancing the reconstruction of 3D ocean temperature and salinity. Full article

(This article belongs to the Special Issue Machine Learning Methodologies and Ocean Science)

► Show Figures

Figure 1

18 pages, 6257 KiB

Open AccessArticle

Submarine Groundwater Discharge in the Nice Airport Landslide Area

by Christoph Witt and Achim Kopf

J. Mar. Sci. Eng. 2025, 13(5), 909; https://doi.org/10.3390/jmse13050909 - 3 May 2025

Viewed by 210

Abstract

Natural radioactivity was measured and analyzed at the Nice Slope for over a month using radon daughters in order to trace groundwater movement from a coastal aquifer to a nearshore continental shelf. Such groundwater movement may have resulted in submarine groundwater discharge (SGD) [...] Read more.

Natural radioactivity was measured and analyzed at the Nice Slope for over a month using radon daughters in order to trace groundwater movement from a coastal aquifer to a nearshore continental shelf. Such groundwater movement may have resulted in submarine groundwater discharge (SGD) and potentially sediment weakening and slope failure. The relationship among major hydrological parameters (precipitation, Var discharge, groundwater level, salinity and water origin) in the area is demonstrated in this study. Time series analyses also helped to detect tidal fluctuations in freshwater input, highlighting the crucial role SGD plays in the slope stability of the still failure-prone Nice Slope, parts of which collapsed in a tsunamigenic submarine landslide in 1979. Earlier deployments of the underwater mass spectrometer KATERINA showed that SGD is limited to the region of the 1979 landslide scar, suggesting that the spatially heterogenous lithologies do not support widespread groundwater charging. The calculated volumetric activities from groundwater tracing isotopes revealed peaks up to ca. 150 counts ²¹⁴Bi, which is similar to those measured at other prominent SGD sites along the Mediterranean shoreline. Therefore, this rare long-term radioisotope dataset is a valuable contribution to the collaborative research at the Nice Slope and may not remain restricted to the unconfined landslide scar but may charge permeable sub-bottom areas nearby. Hence, it has to be taken into account for further slope stability studies. Full article

(This article belongs to the Special Issue Research Progress on Ocean Observations Technology and Information Systems)

► Show Figures

Figure 1

24 pages, 4894 KiB

Open AccessArticle

Improving Offshore Wind Speed Forecasting with a CRGWAA-Enhanced Adaptive Neuro-Fuzzy Inference System

by Yingjie Liu and Fahui Miao

J. Mar. Sci. Eng. 2025, 13(5), 908; https://doi.org/10.3390/jmse13050908 - 3 May 2025

Viewed by 131

Abstract

Accurate forecasting of offshore wind speed is crucial for the efficient operation and planning of wind energy systems. However, the inherently non-stationary and highly volatile nature of wind speed, coupled with the sensitivity of neural network-based models to parameter settings, poses significant challenges. [...] Read more.

Accurate forecasting of offshore wind speed is crucial for the efficient operation and planning of wind energy systems. However, the inherently non-stationary and highly volatile nature of wind speed, coupled with the sensitivity of neural network-based models to parameter settings, poses significant challenges. To address these issues, this paper proposes an Adaptive Neuro-Fuzzy Inference System (ANFIS) optimized by CRGWAA. The proposed CRGWAA integrates Chebyshev mapping initialization, an elite-guided reflection refinement operator, and a generalized quadratic interpolation strategy to enhance population diversity, adaptive exploration, and local exploitation capabilities. The performance of CRGWAA is comprehensively evaluated on the CEC2022 benchmark function suite, where it demonstrates superior optimization accuracy, convergence speed, and robustness compared to six state-of-the-art algorithms. Furthermore, the ANFIS-CRGWAA model is applied to short-term offshore wind speed forecasting using real-world data from the offshore region of Fujian, China, at 10 m and 100 m above sea level. Experimental results show that the proposed model consistently outperforms conventional and hybrid baselines, achieving lower MAE, RMSE, and MAPE, as well as higher R², across both altitudes. Specifically, compared to the original ANFIS-WAA model, the RMSE is reduced by approximately 45% at 10 m and 24% at 100 m. These findings confirm the effectiveness, stability, and generalization ability of the ANFIS-CRGWAA model for complex, non-stationary offshore wind speed prediction tasks. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

13 pages, 6743 KiB

Open AccessArticle

Weak Underwater Signals’ Detection by the Unwrapped Instantaneous Phase

by Aldo Vesnaver, Luca Baradello and Eleonora Denich

J. Mar. Sci. Eng. 2025, 13(5), 907; https://doi.org/10.3390/jmse13050907 - 3 May 2025

Viewed by 149

Abstract

In marine seismic surveys, weak signals can be overlaid by stronger signals or even random noise. Detecting these signals can be challenging, especially when they are close to each other or partially overlapping. Several normalization methods have already been proposed, but they often [...] Read more.

In marine seismic surveys, weak signals can be overlaid by stronger signals or even random noise. Detecting these signals can be challenging, especially when they are close to each other or partially overlapping. Several normalization methods have already been proposed, but they often lead to distortion. In this paper, we show that the unwrapped instantaneous phase of the associated analytical signal is an effective detection tool and validate it using synthetic and real data examples. This approach does not require user-defined parameters and therefore does not introduce personal bias in the results. We show that weak signals from submarine fluid plumes can be successfully detected by seismic surveys. These plumes can reveal anomalies in shallow sediments such as near-surface gas pockets and soft formations, which can severely affect offshore structures such as platforms and wind farms. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

17 pages, 11157 KiB

Open AccessArticle

A New Characterization Method for Dynamic Connectivity Field Between Injection and Production Wells in Offshore Reservoir

by Changchun Guo, Yuzhou Hu, Li Tao, Mengna Cheng, Fankun Meng, Hui Zhao and Fengshuang Du

J. Mar. Sci. Eng. 2025, 13(5), 906; https://doi.org/10.3390/jmse13050906 - 2 May 2025

Viewed by 134

Abstract

Connectivity between injection and production wells is critical for efficient oil production, especially in offshore reservoirs where the number of wells is limited. Though several methods for point-to-point connectivity have been developed, there is a lack of characterization methods for the dynamic connectivity [...] Read more.

Connectivity between injection and production wells is critical for efficient oil production, especially in offshore reservoirs where the number of wells is limited. Though several methods for point-to-point connectivity have been developed, there is a lack of characterization methods for the dynamic connectivity field, which describes connectivity for the whole reservoir. Based on the concept of pore-scale connectivity, this work proposes a multi-parameter integrated model to represent the connectivity field. The calculated connectivity is consistent with simulated streamlines between wells. Key influencing factors, including permeability heterogeneity, injection rate and viscosity ratio on the connectivity field, are systematically analyzed. The established method is then applied to construct the connectivity field in an offshore reservoir. First, a point cloud is applied to represent the reservoir characteristics. Then, the connection network is established, with parameters obtained from history matching. In this way, the point-to-point connectivity is transformed into a connectivity field. The connectivity between injection and production wells is validated by comparing with the on-site tracer test and measured allocation factor of water injection. This approach holds significant potential for enhancing the efficiency of water injection and optimizing offshore reservoir management. Full article

(This article belongs to the Section Marine Energy)

► Show Figures

Figure 1

Journal Menu

Journal Browser

J. Mar. Sci. Eng., Volume 13, Issue 5 (May 2025) – 111 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI