Journal of Marine Science and Engineering

17 pages, 5016 KB

Open AccessArticle

Development and Application of a Polar Ice-Based Ecological Observation Buoy

by Xing Han, Guoxuan Liu, Liwei Kou and Yinke Dou

J. Mar. Sci. Eng. 2025, 13(12), 2387; https://doi.org/10.3390/jmse13122387 - 16 Dec 2025

Addressing the current situation where in situ observations in the Arctic primarily target physical and a few biogeochemical parameters, leaving a gap in systematic direct observation of biological populations beneath sea ice, this study developed a polar ice-based ecological observation buoy system. Building [...] Read more.

Addressing the current situation where in situ observations in the Arctic primarily target physical and a few biogeochemical parameters, leaving a gap in systematic direct observation of biological populations beneath sea ice, this study developed a polar ice-based ecological observation buoy system. Building upon conventional meteorological and oceanographic hydrographic sensors, this system innovatively integrates an underwater imaging module and key technologies such as machine learning-based automatic fish target recognition and reliable dual-channel satellite data transmission in polar environments. Its successful deployment during the 2025 15th Chinese National Arctic Research Expedition verified the system’s stability. During the initial one-month operation period (designed for a monitoring cycle of not less than one year), the data return rates for conventional and image data reached 100% and 96.8%, respectively, achieving quasi-real-time continuous observation of physical and ecological parameters at the air–sea interface in the Arctic Ocean, and it is capable of acquiring not only physical parameters but also visual observations of under-ice fauna. The system successfully acquired and transmitted images containing suspected biological targets and reference objects, providing the first in situ, image-based biological observation dataset for the central Arctic Ocean. This work establishes a new methodological capability for direct ecological monitoring, offering essential equipment support for quantifying biological presence, studying population dynamics, and informing evidence-based polar ecosystem governance. Full article

(This article belongs to the Section Marine Ecology)

20 pages, 1618 KB

Open AccessArticle

Effect of Following Current on the Hydroelastic Behavior of a Floating Ice Sheet near an Impermeable Wall

by Sarat Chandra Mohapatra, Pouria Amouzadrad and C. Guedes Soares

J. Mar. Sci. Eng. 2025, 13(12), 2386; https://doi.org/10.3390/jmse13122386 - 16 Dec 2025

Abstract

A theoretical model of the interaction between a following current and a semi-infinite floating ice sheet under compressive stress near a vertical impermeable wall is developed, within the scope of linear water wave theory, to study the hydroelastic behavior. The conceptual framework defining [...] Read more.

A theoretical model of the interaction between a following current and a semi-infinite floating ice sheet under compressive stress near a vertical impermeable wall is developed, within the scope of linear water wave theory, to study the hydroelastic behavior. The conceptual framework defining the buoyant ice structure incorporates the tenets of elastic beam theory. The associated fluid dynamics are governed by strict adherence to the potential flow paradigm. To resolve the undetermined parameters appearing in the Fourier series decomposition of the potential functions, investigators systematically apply higher-order criteria detailing the coupling relationships between modes. The current results are compared with a specific case of results available in the literature, and the convergence analysis of the analytical solution is made for computational accuracy. Further, the free edge conditions are applied at the edge of the floating ice sheet, and the effects of current speed, compressive stress, the thickness of the ice sheet, flexural rigidity, water depth on the strain, displacements, reflection wave amplitude, and the horizontal force on the rigid vertical wall are analyzed in detail. It is found that the higher values of the following current heighten the strain, displacements, reflection amplitude, and force on the wall. The study’s outcomes are considered to benefit not just cold region design applications but also the engineering of resilient floating structures for oceanic and offshore environments, and to the design of marine structures. Full article

(This article belongs to the Section Ocean Engineering)

24 pages, 5537 KB

Open AccessArticle

Research on Subsea Cluster Layout Optimization Method Considering Three-Dimensional Terrain Constraints

by Weizheng An, Wenze Liu, Xiaohui Song, Yingying Wang, Qiang Ma, Yangqing Lin and Yiyang Xue

J. Mar. Sci. Eng. 2025, 13(12), 2385; https://doi.org/10.3390/jmse13122385 - 16 Dec 2025

Abstract

Seabed topography is a key factor affecting the layout of underwater production systems. Developing a more scientific, intelligent, and integrated layout optimization method is the key to optimizing the layout of underwater production systems. To address the challenge of acquiring a more scientific, [...] Read more.

Seabed topography is a key factor affecting the layout of underwater production systems. Developing a more scientific, intelligent, and integrated layout optimization method is the key to optimizing the layout of underwater production systems. To address the challenge of acquiring a more scientific, intelligent, and integrated optimization method, this paper proposes a multi-level integrated optimization model that incorporates three-dimensional seabed topography, obstacle areas, target locations, pipeline paths, and manifold connection relationships, with the primary objective of minimizing total investment cost. A hybrid algorithm combining H-MOPSO (Hierarchical Multi-Objective Particle Swarm Optimization) with K-means-ILP clustering, dynamic programming, and TEWA* pathfinding is raised to collaboratively solve for the global optimal layout, achieving a coupled “target grouping-manifold connection-path optimization” design. Based on the actual oilfield seabed topography and target data, this paper carries out case analysis and algorithm comparison experiments. The results show that the optimization method in this paper can significantly improve the layout economy and cost accuracy under the premise of meeting the engineering constraints. Among them, the PLEM parallel connection method reduces the pipeline laying cost by 25.72% and the overall layout investment cost by 5.39% compared with the traditional manifold series scheme. Full article

(This article belongs to the Section Geological Oceanography)

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33 pages, 1246 KB

Open AccessReview

Predicting Coastal Flooding and Overtopping with Machine Learning: Review and Future Prospects

by Moeketsi L. Duiker, Victor Ramos, Francisco Taveira-Pinto and Paulo Rosa-Santos

J. Mar. Sci. Eng. 2025, 13(12), 2384; https://doi.org/10.3390/jmse13122384 - 16 Dec 2025

Abstract

Flooding and overtopping are major concerns in coastal areas due to their potential to cause severe damage to infrastructure, economic activities, and human lives. Traditional methods for predicting these phenomena include numerical and physical models, as well as empirical formulations. However, these methods [...] Read more.

Flooding and overtopping are major concerns in coastal areas due to their potential to cause severe damage to infrastructure, economic activities, and human lives. Traditional methods for predicting these phenomena include numerical and physical models, as well as empirical formulations. However, these methods have limitations, such as the high computational costs, reliance on extensive field data, and reduced accuracy under complex conditions. Recent advances in machine learning (ML) offer new opportunities to improve predictive capabilities in coastal engineering. This paper reviews ML applications for coastal flooding and overtopping prediction, analyzing commonly used models, data sources, and preprocessing techniques. Several studies report that ML models can match or exceed the performance of traditional approaches, such as empirical EurOtop formulas or high-fidelity numerical models, particularly in controlled laboratory datasets where numerical models are computationally intensive and empirical methods show larger estimation errors. However, their advantages remain task- and data-dependent, and their generalization and interpretability may lag behind physics-based methods. This review also examines recent developments, such as hybrid approaches, real-time monitoring, and explainable artificial intelligence, which show promise in addressing these limitations and advancing the operational use of ML in coastal flooding and overtopping prediction. Full article

(This article belongs to the Special Issue Coastal Disaster Assessment and Response—2nd Edition)

19 pages, 4114 KB

Open AccessArticle

Assessment of Short-Term Sediment Deposition Patterns Along the Palamós Submarine Canyon (NW Mediterranean) Using ²³⁴Th

by Maria Sierks, Sarah Paradis, Montserrat Roca-Martí, Viena Puigcorbé and Pere Puig

J. Mar. Sci. Eng. 2025, 13(12), 2383; https://doi.org/10.3390/jmse13122383 - 16 Dec 2025

Abstract

Sedimentary dynamics in the Palamós Canyon are influenced by river inputs and storm resuspension, as well as by bottom trawling on the canyon flanks. In this study, we estimate recent sediment deposition patterns along the canyon axis using the excess activity concentration of [...] Read more.

Sedimentary dynamics in the Palamós Canyon are influenced by river inputs and storm resuspension, as well as by bottom trawling on the canyon flanks. In this study, we estimate recent sediment deposition patterns along the canyon axis using the excess activity concentration of the short-lived radiotracer ²³⁴Th (half-life of 24.1 days). Sediment cores were obtained at various locations along the canyon axis from a depth of approximately 800 m to 2100 m in June 2023 and August 2024. Excess ²³⁴Th (²³⁴Th_xs) was detected in all sampled sites with variable penetration depths (0.5–3.5 cm). ²³⁴Th_xs-derived estimations of mixing rates decreased downcanyon from up to 15.6 cm² y⁻¹ at the canyon head (~800 m) to negligible mixing at the canyon mouth (~2100 m). ²³⁴Th_xs inventories, a proxy of recent sediment deposition, were high (1800–3490 Bq m⁻²) at the canyon head and at the upper canyon (~1400 m) close to fishing grounds and decreased downcanyon (82–694 Bq m⁻²) at the lower canyon (~1800 m) and canyon mouth. Inventories varied 2-fold across years presumably attributed to enhanced riverine and bottom trawling sediment fluxes. Similar ²³⁴Th-derived sediment deposition patterns can be found in submarine canyons worldwide, highlighting the value of this radiotracer for sedimentary dynamics studies in such complex environments. Full article

(This article belongs to the Section Marine Environmental Science)

27 pages, 1143 KB

Open AccessArticle

Assessing the Resilience of Specialized Terminals Within Coastal Port Transportation Systems: An Improved RBOP Method

by Qi Tian, Kun Du and Yumei Liang

J. Mar. Sci. Eng. 2025, 13(12), 2382; https://doi.org/10.3390/jmse13122382 - 16 Dec 2025

Abstract

Specialized terminals in coastal ports play an increasingly important role in maritime transport. To enhance the resilience of specialized terminals, it is vital to increase their ability to maintain a certain level of function under various emergencies. This effort is fundamental to ensuring [...] Read more.

Specialized terminals in coastal ports play an increasingly important role in maritime transport. To enhance the resilience of specialized terminals, it is vital to increase their ability to maintain a certain level of function under various emergencies. This effort is fundamental to ensuring the handling efficiency of coastal ports and the stability of the shipping network. In this paper, from the perspective of the coastal port transportation system, we developed a resilience evaluation framework considering micro-level, meso-level, and macro-level influencing factors on specialized terminals. To evaluate the comprehensive resilience of the specialized terminal, we quantitatively calculated each evaluation indicator and proposed an improved Ranking Based on Optimal Points (RBOP) method. The application results were obtained from a study on specialized container terminals at eight hub ports in coastal China. The improved RBOP method takes into account both the current status and future development trends of specialized terminals. As a result, compared with TOPSIS, VIKOR, Multi-MOORA, and WASPAS, the ranking results of the improved RBOP and the latest method (i.e., WASPAS) are the closest, which only differ in the seventh and eighth ranking, while the outcomes of the improved RBOP align more closely with expert expectations. The proposed method enables the resilience evaluation of specialized terminals from a holistic perspective of the coastal port transportation system. This helps port managers identify bottlenecks in the resilience of specialized terminals and can enhance the efficiency and stability of port operations. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

38 pages, 5630 KB

Open AccessArticle

A New Methodology for Coastal Erosion Risk Assessment—Case Study: Calabria Region

by Giuseppina Chiara Barillà, Giuseppe Barbaro, Giandomenico Foti and Giuseppe Mauro

J. Mar. Sci. Eng. 2025, 13(12), 2381; https://doi.org/10.3390/jmse13122381 - 16 Dec 2025

Abstract

The coastal environment is a dynamic system shaped by both natural processes and human activities. In recent decades, increasing anthropogenic pressure and climate change—manifested through sea-level rise and more frequent extreme events—have accelerated coastal retreat, highlighting the need for improved management strategies and [...] Read more.

The coastal environment is a dynamic system shaped by both natural processes and human activities. In recent decades, increasing anthropogenic pressure and climate change—manifested through sea-level rise and more frequent extreme events—have accelerated coastal retreat, highlighting the need for improved management strategies and standardized tools for coastal risk assessment. Existing approaches remain highly heterogeneous, differing in structure, input data, and the range of factors considered. To address this gap, this study proposes an index-based methodology of general validity designed to quantify coastal erosion risk through the combined analysis of hazard, vulnerability, and exposure factors. The approach was developed for multi-scale and multi-risk applications and implemented across 54 representative sites along the Calabrian coast in southern Italy, demonstrating strong adaptability and robustness for regional-scale assessments. Results reveal marked spatial variability in coastal risk, with the Tyrrhenian sector exhibiting the highest values due to the combined effects of energetic wave conditions and intense anthropogenic pressure. The proposed framework can be easily integrated into open-access GIS platforms to support evidence-based planning and decision-making, offering practical value for public administrations and stakeholders, and providing a flexible, accessible tool for integrated coastal risk management. Full article

(This article belongs to the Special Issue Climate Change Impacts on Hydrodynamic and Morphodynamic Coastal Processes)

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22 pages, 15811 KB

Open AccessTechnical Note

A Low-Cost, Open-Source, Multi-Purpose Autonomous Surface Vehicle

by Thomaz Augusto Kras Benatti, Emerson Martins de Andrade, Maicon Rodrigo Correa, Felipe da Silva Lopes, João Paulo Machado dos Santos Bernardino, Joel Sena Sales, Jr. and Antonio Carlos Fernandes

J. Mar. Sci. Eng. 2025, 13(12), 2380; https://doi.org/10.3390/jmse13122380 - 16 Dec 2025

Abstract

Autonomous surface vehicles (ASVs) have played a crucial role in various areas, including oceanographic research, environmental monitoring, and asset inspection. However, the high cost and proprietary nature of many platforms limit accessibility. Thus, this work introduces a low-cost, fully open-source ASV platform designed [...] Read more.

Autonomous surface vehicles (ASVs) have played a crucial role in various areas, including oceanographic research, environmental monitoring, and asset inspection. However, the high cost and proprietary nature of many platforms limit accessibility. Thus, this work introduces a low-cost, fully open-source ASV platform designed to support a wide range of applications, from academic research to community-driven monitoring projects, bridging the existing gap between low-cost prototyping and naval architecture-based ASV development. Featuring a modular 2 m hull design, the vehicle integrates off-the-shelf components and open-source software to ensure affordability, flexibility, and ease of replication. Field tests were conducted on Ilha do Fundão (Fundão Island), located within the campus of the Federal University of Rio de Janeiro (UFRJ), Brazil. All design files and code are released on GitHub (version 1.0.0) to encourage adoption and collaborative improvement. Full article

(This article belongs to the Special Issue Unmanned Surface Vessels (USVs): Technology, Applications and Regulatory Landscapes)

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22 pages, 5581 KB

Open AccessArticle

Evaluating Model-Simulated Monthly Sea Levels During 1993–2023 in the Northwest Atlantic: Influence of Model Resolution and Data Assimilation

by Li Zhai, Youyu Lu, Xianmin Hu and Frédéric Dupont

J. Mar. Sci. Eng. 2025, 13(12), 2379; https://doi.org/10.3390/jmse13122379 - 16 Dec 2025

Abstract

This study evaluates monthly sea levels during 1993–2023 from four ocean models using tide gauge and altimeter data in the Northwest Atlantic with its shelf seas, including the Gulf of Maine, Scotian Shelf, Gulf of St. Lawrence, and the Newfoundland and Labrador Shelf. [...] Read more.

This study evaluates monthly sea levels during 1993–2023 from four ocean models using tide gauge and altimeter data in the Northwest Atlantic with its shelf seas, including the Gulf of Maine, Scotian Shelf, Gulf of St. Lawrence, and the Newfoundland and Labrador Shelf. The evaluation is carried out for four different aspects: the multi-decadal mean and linear trend, seasonal cycle, and the de-trended and de-seasonalized anomalies. Overall, the high-resolution model with advanced data assimilation (GLORYS12v1) possesses skills in all four aspects. The other three models show different discrepancies in reproducing the observed sea level variations relative to GLORYS12v1. They possess low or no skills for the timing (despite reasonable standard deviations) of sea level anomalies at time scales longer than 20 months along the coast, and at all time scales on the shelf, over the shelf break, and in the deep ocean. Without data assimilation, the models with high and medium resolutions show biases in the time-mean sea levels in the Labrador Sea that can be attributed to the simulated stronger and weaker deep convection (deeper and shallower mixed layer depth), respectively. The medium-resolution model, using a different data assimilation approach than GLORYS12v1, shows biases in the seasonal amplitude and multi-decadal trends. Full article

(This article belongs to the Special Issue Marine Modelling and Environmental Statistics in Honor of Professor Keith Thompson)

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39 pages, 26945 KB

Open AccessArticle

Deep Learning-Based Prediction of Ship Roll Motion with Monte Carlo Dropout

by Gi-yong Kim, Chaeog Lim, Sang-jin Oh, In-hyuk Nam, Yu-mi Lee and Sung-chul Shin

J. Mar. Sci. Eng. 2025, 13(12), 2378; https://doi.org/10.3390/jmse13122378 - 15 Dec 2025

Abstract

Accurate prediction of ship roll motion is essential for safe and autonomous navigation. This study presents a deep learning framework that estimates both roll motion and epistemic uncertainty using Monte Carlo (MC) Dropout. Two architectures, a Long Short-Term Memory (LSTM) network and a [...] Read more.

Accurate prediction of ship roll motion is essential for safe and autonomous navigation. This study presents a deep learning framework that estimates both roll motion and epistemic uncertainty using Monte Carlo (MC) Dropout. Two architectures, a Long Short-Term Memory (LSTM) network and a Transformer encoder, were trained on HydroD–Wasim simulations covering various sea states, speeds, and damage conditions, and validated with real voyage data from two ferries, showing complementary performance, where LSTM achieved higher accuracy and Transformer provided more reliable confidence intervals. Model performance was evaluated by mean squared error (MSE), prediction interval coverage probability (PICP), and prediction interval normalized average width (PINAW). The LSTM achieved lower MSE, showing superior deterministic accuracy, while the Transformer produced higher PICP and wider PINAW, indicating more reliable uncertainty estimation. Results confirm that MC Dropout effectively quantifies epistemic uncertainty, improving the reliability of deep learning–based ship motion forecasting for intelligent maritime operations. Full article

(This article belongs to the Special Issue Machine Learning for Prediction of Ship Motion)

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19 pages, 1739 KB

Open AccessArticle

Intelligent Prediction of Sea Level in the South China Sea Using a Hybrid SSA-LSTM Model

by Huiling Zhang, Hang Yang, Wenbo Hong, Hongbo Dai, Guotao Zhang and Changqing Li

J. Mar. Sci. Eng. 2025, 13(12), 2377; https://doi.org/10.3390/jmse13122377 - 15 Dec 2025

Abstract

As an important marginal sea in the western Pacific, sea-level changes in the South China Sea not only respond to global warming but are also regulated by regional ocean dynamics and climate modes, exerting profound impacts on the socioeconomic development and engineering safety [...] Read more.

As an important marginal sea in the western Pacific, sea-level changes in the South China Sea not only respond to global warming but are also regulated by regional ocean dynamics and climate modes, exerting profound impacts on the socioeconomic development and engineering safety of coastal regions. To address the widespread issues of low accuracy and robustness in existing sea-level prediction models when handling nonlinear, multi-scale sequences, as well as the complexity of sea-level change mechanisms in the South China Sea, this study constructs a hybrid model combining Singular Spectrum Analysis and Long Short-Term Memory neural networks (SSA-LSTM). The coral skeletal oxygen isotope ratio (δ¹⁸O) used in this study is a key indicator for characterizing the marine environment, defined as the per mille difference in the ¹⁸O/¹⁶O ratio of a sample relative to a standard. Based on coral δ¹⁸O data from the South China Sea, the sea level from 1850 to 2015 is reconstructed. SSA is then applied to decompose the sea-level data into trend and periodic components. The trend component, accounting for 37.03%, and components 2 to 11, containing major periodic information, are extracted to reconstruct the sea-level series. The reconstructed series retains 95.89% of the original information. The trend component is modeled through curve fitting, while the periodic components are modeled using an LSTM neural network. Optimal hyperparameters for the LSTM are determined through parameter sensitivity analysis. An integrated SSA-LSTM model is constructed to predict sea level in the South China Sea, and its predictions are compared with those from a Singular Spectrum Analysis-Autoregressive Integrated Moving Average (SSA-ARIMA) model. The results indicate that from 1850 to 2015, sea level in the South China Sea exhibits periodic fluctuations with a significant overall upward trend. Specifically, the growth rate from 1921 to 1940 reaches 5.49 mm/yr. Predictions from the SSA-LSTM model are significantly higher than those from the SSA-ARIMA model. The SSA-LSTM model projects that from 2016 to 2035, sea level in the South China Sea will continue to rise at a fluctuating rate of 0.75 mm/yr, with a cumulative rise of approximately 15 mm. This study provides a novel methodology for investigating the mechanisms of sea-level change in the South China Sea and offers a scientific basis for coastal risk management. Full article

(This article belongs to the Section Physical Oceanography)

35 pages, 1545 KB

Open AccessReview

Local Scour Around Tidal Stream Turbine Foundations: A State-of-the-Art Review and Perspective

by Ruihuan Liu, Ying Li, Qiuyang Yu and Dongzi Pan

J. Mar. Sci. Eng. 2025, 13(12), 2376; https://doi.org/10.3390/jmse13122376 - 15 Dec 2025

Abstract

Local scour around support structures has remained a critical barrier to tidal stream turbine deployment in energetic marine channels since loss of embedment and bearing capacity has undermined stability and delayed commercialization. This review identifies key mechanisms, practical implications, and forward-looking strategies related [...] Read more.

Local scour around support structures has remained a critical barrier to tidal stream turbine deployment in energetic marine channels since loss of embedment and bearing capacity has undermined stability and delayed commercialization. This review identifies key mechanisms, practical implications, and forward-looking strategies related to local scour. It highlights that rotor operation, small tip clearance, and helical wakes can significantly intensify near-bed shear stress and erosion relative to monopile foundations without turbine rotation. Scour behavior is compared across monopile, tripod, jacket, and gravity-based foundations under steady flow, reversing tides, and combined wave and current conditions, revealing their influence on depth and morphology. The review further assesses coupled interactions among waves, oscillatory currents, turbine-induced flow, and seabed response, including sediment transport, transient pore pressure, and liquefaction risk. Advances in prediction methods spanning laboratory experiments, high-fidelity simulations, semi-empirical models, and data-driven techniques are synthesized, and mitigation strategies are evaluated across passive, active, and eco-integrated approaches. Remaining challenges and specific research needs are outlined, including array-scale effects, monitoring standards, and integration of design frameworks. The review concludes with future directions to support safe, efficient, and sustainable turbine deployment. Full article

(This article belongs to the Special Issue Marine Renewable Energy and Environment Evaluation)

29 pages, 15509 KB

Open AccessArticle

Machine Learning for Wind Pattern Estimation at Data-Scarce Coastal Ports: A Comparative Study Using Real Measurements

by Anastasios Giannopoulos, Aikaterini Karditsa, Maria Hatzaki and Panagiotis Trakadas

J. Mar. Sci. Eng. 2025, 13(12), 2375; https://doi.org/10.3390/jmse13122375 - 15 Dec 2025

Abstract

Accurate wind information is essential for safe and efficient port operations, yet many small and medium-sized coastal ports lack dense meteorological instrumentation. This paper presents a data-driven framework for wind speed prediction at such ports by leveraging long-term historical measurements from nearby reference [...] Read more.

Accurate wind information is essential for safe and efficient port operations, yet many small and medium-sized coastal ports lack dense meteorological instrumentation. This paper presents a data-driven framework for wind speed prediction at such ports by leveraging long-term historical measurements from nearby reference stations. Focusing on a real-world case study at the Chalkida port in Greece, the framework integrates both deterministic and Machine Learning (ML) models trained on historical wind patterns of archived wind data from four surrounding locations. We examine both short- and long-horizon prediction periods, using recently acquired wind measurements at the target port for model validation. Deterministic baselines include simple and weighted averaging schemes, while supervised ML methods, such as Multiple Linear Regression, Decision Trees, Support Vector Regression, Random Forests, and Gradient Boosting, are trained to capture complex spatiotemporal patterns. Experimental results highlight that ensemble-based ML models, particularly Gradient Boosting, achieve superior accuracy in short-term forecasting, while the optimal predictor varies with the forecast horizon. The proposed approach enables the deployment of virtual wind stations in data-scarce ports and can be periodically updated to dynamically select the most suitable model, thereby supporting climate adaptation strategies, localized wind monitoring, and operational planning without requiring dense local instrumentation. Full article

(This article belongs to the Section Coastal Engineering)

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32 pages, 1308 KB

Open AccessArticle

A Q-Learning-Based Link-Aware Routing Protocol for Underwater Wireless Sensor Networks

by Xinyang Li, Yanbo Wu, Min Zhu and Jie Ren

J. Mar. Sci. Eng. 2025, 13(12), 2374; https://doi.org/10.3390/jmse13122374 - 14 Dec 2025

Abstract

In Underwater Wireless Sensor Networks (UWSNs) with mobile nodes, the mobility of the nodes leads to dynamic changes in the network topology. Thus, pre-established routing paths may become invalid and next-hop nodes may be unavailable due to link disruptions. This implies that routing [...] Read more.

In Underwater Wireless Sensor Networks (UWSNs) with mobile nodes, the mobility of the nodes leads to dynamic changes in the network topology. Thus, pre-established routing paths may become invalid and next-hop nodes may be unavailable due to link disruptions. This implies that routing decisions for mobile UWSNs that do not account for changes in the connectivity state of communication links cannot guarantee reliable packet delivery. In this study, a Q-learning-based link-aware routing (QLAR) protocol designed for mobile UWSNs is proposed. The proposed QLAR protocol introduces the Link Expiration Time (LET) into the reward function of the Q-learning algorithm as a critical decision metric, thereby guiding the agent to prioritize more stable communication links with longer expected lifetime. In addition, multiple decision metrics are dynamically predicted and updated by actively perceiving and acquiring information from neighbor nodes through periodic control packet interactions. To achieve a balance among these metrics, the Entropy Weight Method (EWM) is employed to adaptively adjust their weights in response to real-time network conditions. Comprehensive simulation results demonstrate that QLAR outperforms existing routing protocols in terms of various performance metrics under different scenarios. Full article

(This article belongs to the Special Issue Underwater Acoustic Communication and Marine Robot Networks)

29 pages, 4363 KB

Open AccessArticle

Study on the Influence of 3D Printing Material Filling Patterns on Marine Photovoltaic Performance

by Huiling Zhang, Shengqing Zeng, Yining Zhang, Sixing Guo, Huaxian Feng and Dapeng Zhang

J. Mar. Sci. Eng. 2025, 13(12), 2373; https://doi.org/10.3390/jmse13122373 - 14 Dec 2025

Abstract

With the rapid development of offshore photovoltaic (PV) systems, PV support structures have become a critical component in offshore PV installations. The material properties of these structures significantly influence the safety and reliability of the entire system. 3D printing technology, leveraging its advantages [...] Read more.

With the rapid development of offshore photovoltaic (PV) systems, PV support structures have become a critical component in offshore PV installations. The material properties of these structures significantly influence the safety and reliability of the entire system. 3D printing technology, leveraging its advantages such as rapid prototyping, complex structure manufacturing, and high material utilization, holds broad application prospects in the field of offshore PV. However, the infill pattern of 3D printing materials can significantly affect their mechanical properties. Marine PV systems require extremely high resistance to wave action, tensile strength, and torsional performance, while offshore PV support structures need sufficient compressive capacity. Therefore, this study aims to investigate how different infill patterns affect the compressive properties of 3D printed materials, thereby optimizing material selection and printing processes for offshore PV applications. Through experimental design, a variety of common infill patterns were selected. Universal testing machines and torsion testing machines were used to conduct systematic tests on compressive strength, elastic modulus, and compressive fracture strain. The results showed that different infill patterns have a significant impact on compressive properties, among which the honeycomb infill exhibited the best overall mechanical performance, effectively enhancing load-bearing capacity and stability. Based on the experimental results, appropriate infill configurations and material combinations for different components of offshore PV systems were proposed. The feasibility of optimizing 3D printing processes to improve the overall performance of offshore PV structures was further explored. The findings of this study not only provide a theoretical basis for material selection and process optimization in 3D printing for offshore PV systems but also offer important references for promoting the application of 3D printing technology in this field. Full article

(This article belongs to the Special Issue Structural Modelling, Safety Assessment, and Advanced Material Application of Marine Structures)

20 pages, 6578 KB

Open AccessArticle

Investigating the Genesis and Migration Mechanisms of Subsea Shallow Gas Using Carbon Isotopic and Lithological Constraints: A Case Study from Hangzhou Bay, China

by Linqi Ji, Zhongxuan Chen, Sheng Song, Taojun Hu and Xianghua Lai

J. Mar. Sci. Eng. 2025, 13(12), 2372; https://doi.org/10.3390/jmse13122372 - 14 Dec 2025

Abstract

This study addresses the challenge of data scarcity in research on the migration patterns of shallow gas in submarine sediments. Taking the northern Hangzhou Bay area of the East China Sea as an example, we integrate borehole core geophysical surveys and geochemical data [...] Read more.

This study addresses the challenge of data scarcity in research on the migration patterns of shallow gas in submarine sediments. Taking the northern Hangzhou Bay area of the East China Sea as an example, we integrate borehole core geophysical surveys and geochemical data to elucidate the migration and fractionation mechanisms of shallow biogenic gas. A three-zone conceptual model—“disturbed zone–active zone–residual zone”—dominated by lithology-controlled migration is established, revealing the dominant roles of gas escape, mixing-homogenization, and adsorption fractionation in heterogeneous sedimentary systems. The results show that high-permeability sand layers can act as adsorption-fractionation windows, causing significant enrichment in δ¹³C-CH₄ (–57.4‰). We propose an analytical framework of “zonal verification–mechanism tracing”, which overcomes the limitations of traditional Rayleigh fractionation models and enables accurate interpretation of gas migration patterns in heterogeneous systems using limited data such as δ¹³C-CH₄ and CH₄ concentration. This provides a new paradigm for engineering surveys and risk assessment in low-data-density contexts. The findings indicate that the shallow seepage zone poses low engineering risks, while the residual zone serves as an indicator of depleted gas reservoirs. The proposed analytical approach can be extended to preliminary submarine engineering surveys and hazard assessments in other regions. Full article

(This article belongs to the Section Geological Oceanography)

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26 pages, 6020 KB

Open AccessArticle

Numerical Investigation of Maneuvering Characteristics for a Submarine Under Horizontal Stern Plane Deflection in Vertical Plane Straight-Line Motion

by Binbin Zou, Yingfei Zan, Ruinan Guo, Shuaihang Wang, Zhenzhong Jin and Qiang Xu

J. Mar. Sci. Eng. 2025, 13(12), 2371; https://doi.org/10.3390/jmse13122371 - 14 Dec 2025

Abstract

The maneuverability of a submarine in the vertical plane is a key indicator of navigation safety. However, existing studies typically evaluate maneuvering performance based on hydrodynamic coefficients, often neglecting the flow-field evolution induced by different steering strategies. In this study, a high-fidelity numerical [...] Read more.

The maneuverability of a submarine in the vertical plane is a key indicator of navigation safety. However, existing studies typically evaluate maneuvering performance based on hydrodynamic coefficients, often neglecting the flow-field evolution induced by different steering strategies. In this study, a high-fidelity numerical model for the vertical-plane motion of the DARPA SUBOFF submarine is established using the Reynolds-Averaged Navier–Stokes (RANS) method and validated against benchmark data. Unlike traditional analyses that employ a fixed rudder angle, this work systematically compares three steering strategies with continuously varying rudder angles—trapezoidal, step, and linear steering—examining their motion responses, hydrodynamic performance, and unsteady flow-field evolution. The results show that, although step steering produces the fastest response with the strongest transient characteristics, it also triggers pronounced flow separation and significant unsteady effects. Linear steering yields a smoother but the weakest motion response, with reduced rudder effectiveness and a noticeable lag effect. In contrast, trapezoidal steering maintains a stable flow field around the submarine, with uniformly concentrated vorticity distribution, ensuring smooth and safe motion and achieving a favorable balance between response speed and flow stability. The findings provide theoretical reference for research on submarine vertical-plane steering motion, rudder-angle control, and flow-field stability. Full article

(This article belongs to the Section Ocean Engineering)

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24 pages, 2620 KB

Open AccessArticle

Study on the Effect of Column Form on the Dynamic Response of Semi-Submersible Truss-Type Fish Culture Platforms

by Kangyang Liang and Dapeng Zhang

J. Mar. Sci. Eng. 2025, 13(12), 2370; https://doi.org/10.3390/jmse13122370 - 13 Dec 2025

Abstract

To investigate the effect of column form on the hydrodynamic performance of semi-submersible truss fishery aquaculture platforms, this study focused on an active semi-submersible aquaculture platform located in the South China Sea. Three platform models featuring distinct column structures were established. Employing three-dimensional [...] Read more.

To investigate the effect of column form on the hydrodynamic performance of semi-submersible truss fishery aquaculture platforms, this study focused on an active semi-submersible aquaculture platform located in the South China Sea. Three platform models featuring distinct column structures were established. Employing three-dimensional potential flow theory and Morrison’s equations, numerical simulation methods were utilised to analyse the dynamic response of the three types of column platforms in both the frequency and time domains under wind, wave, and current action. Consequently, relevant conclusions regarding the influence of column form on the hydrodynamic performance of semi-submersible platforms were derived. The results show that: The quasi-elliptical column platform exhibits superior frequency-domain response characteristics, with the circular column platform following, while the square column platform demonstrates the poorest performance. When subjected to the combined effects of waves and currents, the circular column platform shows the most favourable time-domain dynamic response, with the quasi-elliptical column platform next, and the square column platform lagging behind. In contrast, under the combined influence of wind, waves, and currents, the quasi-elliptical column platform excels in time-domain dynamic response, followed by the square column platform, with the circular column platform being the least effective. These variations in time-frequency dynamic response characteristics among the three column platforms are attributed to their distinct structural forms. Full article

(This article belongs to the Special Issue Structural Modelling, Safety Assessment, and Advanced Material Application of Marine Structures)

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16 pages, 1682 KB

Open AccessArticle

Analysis of the Fatty Acid Desaturase Gene Family and Construction and Screening of High-EPA Transgenic Strains in Phaeodactylum tricornutum

by Wenjin He, Qingying Chen, Haoying Ye, Pingru Gao, Bina Wu, Wenchu Meng, Wenhui Zheng, Jianhua Shi and Haien Murong

J. Mar. Sci. Eng. 2025, 13(12), 2369; https://doi.org/10.3390/jmse13122369 - 13 Dec 2025

Abstract

Fatty acid desaturase (FAD) is a key enzyme that catalyzes the biosynthesis of polyunsaturated fatty acids (PUFAs) and is widely present in animals, plants and microorganisms. In this study, Phaeodactylum tricornutum was used as the material. Bioinformatics methods were employed to identify the [...] Read more.

Fatty acid desaturase (FAD) is a key enzyme that catalyzes the biosynthesis of polyunsaturated fatty acids (PUFAs) and is widely present in animals, plants and microorganisms. In this study, Phaeodactylum tricornutum was used as the material. Bioinformatics methods were employed to identify the FAD gene family within the entire genome of P. tricornutum. The genomic distribution, gene structure, conserved domains, phylogenetic relationships, and physicochemical properties of proteins were systematically analyzed. The results showed that a total of 15 FAD genes were identified in the genome of P. tricornutum, which could be classified into 4 subfamilies. These genes are unevenly distributed on the 11 chromosomes. Motif analysis predicted that motif1 and motif2 are not only highly conserved but also play a key role in the synthesis of unsaturated fatty acids. To verify the gene function, we transferred the exogenous Ptd5α gene into P. tricornutum. Through screening and verification, we successfully obtained three transgenic algal strains (5D1, 5D2, 5D3). Compared with the wild algal strain (WT), overexpression of the Ptd5α gene did not have a significant impact on the growth and development of P. tricornutum. Moreover, the total fatty acid content of the transgenic algal strain was significantly increased, and the proportion of EPA in the total fatty acids could be raised to over 30%. The results of this study lay an important foundation for in-depth analysis of the biological functions of the FAD gene family in P. tricornutum, and also provide experimental and theoretical basis for the large-scale industrial production of EPA using model microalgae. Full article

(This article belongs to the Section Marine Biology)

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Journal of Marine Science and Engineering

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