Journal of Marine Science and Engineering

22 pages, 10308 KB

Open AccessArticle

Local Spatial Attention Transformer with First-Order Difference for Sea Level Anomaly Field Forecast: A Regional Study in the East China Sea

by Yuting Wang, Hui Chen, Lifang Jiang, Qiyan Ji, Juan Li, Jianxin Wang and Guoqing Han

J. Mar. Sci. Eng. 2026, 14(1), 54; https://doi.org/10.3390/jmse14010054 (registering DOI) - 28 Dec 2025

Abstract

Accurate prediction of regional sea level anomaly (SLA) is critical for coastal hazard early warning, navigation safety, and infrastructure protection in economically active marginal seas such as the East China Sea (ECS), yet complex multiscale air–sea dynamics still make SLA forecasting challenging. This [...] Read more.

Accurate prediction of regional sea level anomaly (SLA) is critical for coastal hazard early warning, navigation safety, and infrastructure protection in economically active marginal seas such as the East China Sea (ECS), yet complex multiscale air–sea dynamics still make SLA forecasting challenging. This study proposes a Local Spatial Attention Transformer Network (LSATrans-Net) for short-term regional SLA prediction in the ECS, which incorporates a Local Spatial Attention mechanism designed for regional ocean processes and employs a first-order difference preprocessing strategy to reduce error accumulation induced by data non-stationarity. The LSATrans-Net outperforms ConvLSTM, BiLSTM, and CNN-Transformer in 7-day prediction experiments, with an RMSE of 0.017 m and a PCC of 0.984, with particularly strong forecasting skill in the ECS-Kuroshio and eddy-active regions. LSATrans-Net provides an efficient and physically interpretable framework for high-precision short-term SLA forecasting in dynamically complex marine regions, and offers reliable technical support for coastal disaster prevention and operational ocean forecasting systems. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

24 pages, 1632 KB

Open AccessArticle

Research on Risk Assessment and Prevention–Control Measures for Immersed Tunnel Construction in 100 m-Deep Water Environments

by Haiyang Xu, Zhengzhong Qiu, Sudong Xu, Liuyan Mao and Zebang Cui

J. Mar. Sci. Eng. 2026, 14(1), 53; https://doi.org/10.3390/jmse14010053 (registering DOI) - 27 Dec 2025

Abstract

With the rapid development of cross-sea infrastructure, the immersed tube method has been increasingly applied to deep-water immersed-tube tunnel construction. However, when the construction depth reaches the scale of one hundred meters, issues such as high hydrostatic pressure, complex hydrological conditions, and limited [...] Read more.

With the rapid development of cross-sea infrastructure, the immersed tube method has been increasingly applied to deep-water immersed-tube tunnel construction. However, when the construction depth reaches the scale of one hundred meters, issues such as high hydrostatic pressure, complex hydrological conditions, and limited construction windows significantly elevate project risks. Against this backdrop, this study systematically reviews relevant domestic and international research findings in the context of 100-m-deep water environments and constructs a comprehensive risk index system covering the construction processes of the WBS breakdown system based on the WBS-RBS decomposition method within the HSE framework. A risk index weighting analysis combines quantitative and qualitative analysis, categorizing the indicators into qualitative and quantitative categories. Quantitative analysis employs threshold determination and the LEC method; qualitative analysis utilizes expert surveys and the G1 method. Ultimately, a model that combines multiple methods for a 100-m-deep water environment, integrating subjective expertise and objective data, is developed. On this basis, multi-level prevention and control measures are proposed for hundred-meter-deep water-immersed tube construction. The results demonstrate that the proposed system can effectively identify key risk sources under deep-water conditions and provide practical countermeasures, offering significant guidance for ensuring construction safety and engineering quality in hundred-meter immersed-tube tunnel projects. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

12 pages, 2050 KB

Open AccessArticle

Past and Future Changes in Sea Ice in the Sea of Okhotsk: Analysis Using the Future Ocean Regional Projection Dataset

by Daichi Narita and Shinsuke Iwasaki

J. Mar. Sci. Eng. 2026, 14(1), 52; https://doi.org/10.3390/jmse14010052 (registering DOI) - 26 Dec 2025

Abstract

Although subject to annual fluctuations, sea ice in the Sea of Okhotsk has decreased to a maximum extent at a rate of approximately 3.4% per decade since the 1970s. Thus far, few studies have focused on projections of sea ice in the Sea [...] Read more.

Although subject to annual fluctuations, sea ice in the Sea of Okhotsk has decreased to a maximum extent at a rate of approximately 3.4% per decade since the 1970s. Thus far, few studies have focused on projections of sea ice in the Sea of Okhotsk. This study focused on sea ice in the Sea of Okhotsk and examined its past and future characteristics using a climate projection dataset termed the Future Ocean Regional Projection dataset. Historical sea ice areas have been reported to be larger than satellite observations, and some data contain biases of approximately double the actual value. Therefore, a simple bias correction was performed based on the ratio of historical to satellite observation sea-ice areas, and the bias was corrected. Furthermore, we performed future projections using two bias-corrected scenarios (RCP2.6 and RCP8.5). Results revealed that for the future analysis period of 2006–2100, sea ice loss would be approximately 12.3 (10² km²/year) under RCP2.6 and approximately 37.3 (10² km²/year) under RCP8.5, indicating that under both scenarios, there would be almost no sea ice in the southern Sea of Okhotsk between 2071 and 2100. The results of this study provide useful information for researchers to predict sea ice in related physical fields. Full article

(This article belongs to the Section Ocean Engineering)

27 pages, 3223 KB

Open AccessArticle

Development of an Initial Burial Rate Estimation Simulator for Bottom-Contact Mines and a Reinforcement Learning-Based Mine-Laying Route Optimization Method

by Su Hwan Kim, Young Seo Park and Se Won Kim

J. Mar. Sci. Eng. 2026, 14(1), 51; https://doi.org/10.3390/jmse14010051 (registering DOI) - 26 Dec 2025

Abstract

In modern naval operations, the strategic value of naval mines has been increasingly emphasized, highlighting the need for intelligent and efficient deployment strategies. This study proposes integrated framework that combines mine burial rate estimation with reinforcement learning-based optimization to generate mine-laying routes that [...] Read more.

In modern naval operations, the strategic value of naval mines has been increasingly emphasized, highlighting the need for intelligent and efficient deployment strategies. This study proposes integrated framework that combines mine burial rate estimation with reinforcement learning-based optimization to generate mine-laying routes that maximize burial effectiveness. An initial burial rate estimation simulator was developed using environmental factors such as sediment bulk density and shear strength estimated from sediment type and mean grain size to predict the burial rates of bottom-contact mines. The simulator was integrated into reinforcement learning frameworks—Deep Q-Network (DQN), and proximal policy optimization (PPO). The reinforcement learning methods were trained to autonomously explore the environment and generate routes that strategically utilize high burial regions while satisfying navigational constraints. Experimental results demonstrate that the reinforcement learning methods consistently generated routes with higher average burial rates while requiring significantly shorter computation time compared with the A* algorithm. These findings suggest that reinforcement learning, when coupled with environmental modeling, provides a practical and scalable strategy for improving the effectiveness, concealment, and autonomy of naval mine-laying operations. Full article

(This article belongs to the Special Issue Advanced Research on Path Planning for Intelligent Ships)

32 pages, 8885 KB

Open AccessArticle

Autonomous Navigation and Automated Control for a Small Balancing Hydrofoil Craft

by Tiziano Wehrli and Thomas Bräunl

J. Mar. Sci. Eng. 2026, 14(1), 50; https://doi.org/10.3390/jmse14010050 (registering DOI) - 26 Dec 2025

Abstract

Hydrofoil vessels have recently re-gained interest, presenting a more efficient and comfortable alternative to regular vessels. However, research in hydrofoils is limited by the high cost and complexity of developing a complete vessel to use for experimental testing. This paper presents a novel [...] Read more.

Hydrofoil vessels have recently re-gained interest, presenting a more efficient and comfortable alternative to regular vessels. However, research in hydrofoils is limited by the high cost and complexity of developing a complete vessel to use for experimental testing. This paper presents a novel low-cost, small autonomous hydrofoil that can be used to research different hydrofoil hardware and configurations, control routines for autonomous balancing while foiling, and autonomous driving algorithms for hydrofoil crafts. A modular design with low-cost, off-the-shelf electronics is proposed and developed. Three independent PID control loops were implemented and validated, enabling the boat to remain stable in a foilborne state. An onboard GPS was used to implement autonomous driving, allowing the boat to navigate between GPS waypoints in a river. Experimental testing of the vessel indicated suitability as a low-cost, easy-to-modify, and easy-to-use hydrofoil test bed. Future research should focus on aspects of the mechanical design, investigating new control methodologies to improve performance, and investigating the efficiency gains and feasibility of performing long-range autonomous missions. Full article

(This article belongs to the Special Issue Advances in the Decision-Making and Control of Autonomous Marine Vehicles)

48 pages, 23944 KB

Open AccessReview

Tsunamites Versus Tempestites: A Comprehensive Review from the Precambrian to Recent Times

by Mohamed Amine Doukani, José Madeira, Linda Satour and Sérgio P. Ávila

J. Mar. Sci. Eng. 2026, 14(1), 49; https://doi.org/10.3390/jmse14010049 (registering DOI) - 26 Dec 2025

Abstract

Insight regarding the overall geological history of tsunamis and their impacts requires information gained from preserved deposits. Although recent decades have seen a rise in tsunami deposit studies overall, most reviews focus on specific time intervals, such as the Paleozoic, the K–Pg boundary, [...] Read more.

Insight regarding the overall geological history of tsunamis and their impacts requires information gained from preserved deposits. Although recent decades have seen a rise in tsunami deposit studies overall, most reviews focus on specific time intervals, such as the Paleozoic, the K–Pg boundary, the Quaternary, or historical and recent events, while others concentrated on particular depositional settings, including lacustrine, offshore, or onshore environments. This review paper provides a comprehensive synthesis of tsunami deposits spanning the geological record from the Precambrian to recent times based on a global compilation of onshore, offshore, and lacustrine examples. Selections from the available evidence is traced from the oldest known tsunamites in the Archaean through major extinction boundaries such as the K–Pg, to the well-preserved Holocene and historical deposits. The findings indicate that while the fundamental sedimentological signatures of tsunamis have remained broadly consistent over geological time, their recognition in ancient strata remains challenging due to difficulty in differentiating between storm deposits (tempestites) and other high-energy facies. A central aspect of this review is the critical assessment of diagnostic criteria proposed to differentiate tsunamites from tempestites. By using a multidisciplinary approach, integrating sedimentological, paleontological, geochemical, and geomorphological evidence in palaeotsunami research, this review provides a detailed framework to improve the confidence in identifying tsunami deposits. This, in turn, enhances palaeotsunami reconstructions, which are valuable for advancing hazard assessment along vulnerable coastlines. Full article

(This article belongs to the Special Issue Feature Review Papers in Geological Oceanography)

27 pages, 5112 KB

Open AccessArticle

A Lightweight and Low-Cost Underwater Localization System Based on Visual–Inertial–Depth Fusion for Net-Cage Cleaning Robots

by Chuanyu Geng, Junhua Chen and Hao Li

J. Mar. Sci. Eng. 2026, 14(1), 48; https://doi.org/10.3390/jmse14010048 (registering DOI) - 26 Dec 2025

Abstract

Net-cage aquaculture faces challenges from biofouling, which reduces water exchange and threatens structural integrity. Automated cleaning robots provide an alternative to human divers but require effective, low-cost localization. Conventional acoustic–inertial systems are expensive and complex, while vision-only or IMU-based methods suffer from drift [...] Read more.

Net-cage aquaculture faces challenges from biofouling, which reduces water exchange and threatens structural integrity. Automated cleaning robots provide an alternative to human divers but require effective, low-cost localization. Conventional acoustic–inertial systems are expensive and complex, while vision-only or IMU-based methods suffer from drift in turbid, low-texture waters. This paper presents a lightweight Visual–Inertial–Depth (VID) fusion framework for underwater net-cage cleaning robots. Built on the VINS-Fusion system the method estimates scene scale using optical flow and stereo matching, and incorporates IMU pre-integration for high-frequency motion prediction. A pressure-based depth factor constrains Z-axis drift, and reflective-anchor initialization ensures global alignment. The system runs in real time on a Jetson Orin NX with ROS. Experiments in air, tank, pool, and ocean settings demonstrate its robustness. In controlled environments, the mean anchor coordinate error (ACE) was 0.05–0.16 m, and loop-closure drift (LCD) was ≤0.5 m per 5 m. In ocean trials, turbulence and biofouling led to drift (LCD 1.32 m over 16.05 m, 8.3%), but IMU and depth cues helped maintain vertical stability. The system delivers real-time, cost-effective localization in structured underwater cages and offers insights for improvements in dynamic marine conditions. Full article

(This article belongs to the Section Ocean Engineering)

► Show Figures

Figure 1

21 pages, 4525 KB

Open AccessArticle

The Effect of Density Difference on the Sedimentation Dynamics of Two Spherical Particles in Side-by-Side and Tandem Configurations

by Da Hui, Xiang Ji, Baizhuang Chen, Mingfu Tang and Lixin Xu

J. Mar. Sci. Eng. 2026, 14(1), 47; https://doi.org/10.3390/jmse14010047 (registering DOI) - 26 Dec 2025

Abstract

Complex fluid–particle interactions are ubiquitous in natural environments and engineering applications, with their underlying mechanisms often attributed to interparticle attraction and repulsion. To understand the interaction mechanism between the dual particles, this study examines the setting process of dual particles using the Immersed [...] Read more.

Complex fluid–particle interactions are ubiquitous in natural environments and engineering applications, with their underlying mechanisms often attributed to interparticle attraction and repulsion. To understand the interaction mechanism between the dual particles, this study examines the setting process of dual particles using the Immersed Boundary-Lattice Boltzmann Method (IB-LBM), with a focus on the effect of the density difference between particles. Two typical configurations—tandem and side-by-side—are considered in the analysis. In the tandem configuration, when

ρ_{L P} / ρ_{T P} < 1

, the TP inevitably kisses the LP due to its greater settling velocity, thus initiating the classical drafting-kissing-tumbling phenomenon. As the density of the TP further increases, the attractive effect exerted by the LP on the TP becomes weak. Conversely, when

ρ_{L P} / ρ_{T P} > 1

, kissing between two particles is mainly determined by the density of LP. Whether kissing occurs between the two particles depends on a critical value

ρ_{L P} / ρ_{T P} = 1.2 : 1.14

. Although the LP’s attraction to the TP strengthens with increasing LP density, beyond this certain threshold, this attraction becomes insufficient for the TP to catch up with the LP. In a side-by-side configuration with two particles of different densities, their interaction evolves from initial attraction to subsequent repulsion. This phenomenon is not observed in pairs of particles with identical density. Moreover, with increasing density difference between the particles, the attractive effect from the higher-density particle on the lower-density one strengthens, whereas the repulsive interaction between them gradually weakens. When the particle density ratio reaches

1.4 : 1.14

, the lateral migration of the particles becomes very small; although they still interact with each other, the effect becomes extremely weak. This work systematically elucidates the influence of density disparity on particle interaction, providing insights into understanding more complex multiparticle system dynamics. Full article

(This article belongs to the Special Issue CFD Applications in Ship and Offshore Hydrodynamics (2nd Edition))

► Show Figures

Figure 1

25 pages, 103370 KB

Open AccessArticle

NeRF-Enhanced Visual–Inertial SLAM for Low-Light Underwater Sensing

by Zhe Wang, Qinyue Zhang, Yuqi Hu and Bing Zheng

J. Mar. Sci. Eng. 2026, 14(1), 46; https://doi.org/10.3390/jmse14010046 (registering DOI) - 26 Dec 2025

Abstract

Marine robots operating in low illumination and turbid waters require reliable measurement and control for surveying, inspection, and monitoring. This paper present a sensor-centric visual–inertial simultaneous localization and mapping (SLAM) pipeline that combines low-light enhancement, learned feature matching, and NeRF-based dense reconstruction to [...] Read more.

Marine robots operating in low illumination and turbid waters require reliable measurement and control for surveying, inspection, and monitoring. This paper present a sensor-centric visual–inertial simultaneous localization and mapping (SLAM) pipeline that combines low-light enhancement, learned feature matching, and NeRF-based dense reconstruction to provide stable navigation states. A lightweight encoder–decoder with global attention improves signal-to-noise ratio and contrast while preserving feature geometry. SuperPoint and LightGlue deliver robust correspondences under severe visual degradation. Visual and inertial data are tightly fused through IMU pre-integration and nonlinear optimization, producing steady pose estimates that sustain downstream guidance and trajectory planning. An accelerated NeRF converts monocular sequences into dense, photorealistic reconstructions that complement sparse SLAM maps and support survey-grade measurement products. Experiments on AQUALOC sequences demonstrate improved localization stability and higher-fidelity reconstructions at competitive runtime, showing robustness to low illumination and turbidity. The results indicate an effective engineering pathway that integrates underwater image enhancement, multi-sensor fusion, and neural scene representations to improve navigation reliability and mission effectiveness in realistic marine environments. Full article

(This article belongs to the Special Issue Intelligent Measurement and Control System of Marine Robots)

► Show Figures

Figure 1

22 pages, 12700 KB

Open AccessArticle

An Adaptive Path Planning Algorithm for USV in Complex Waterways: SA-Bi-APF-RRT*

by Sixian Li, Ke Chen, Dongfang Li, Jieyu Xian, Tieli Lyu, Yimeng Li, Hong Zhu and Maohua Xiao

J. Mar. Sci. Eng. 2026, 14(1), 45; https://doi.org/10.3390/jmse14010045 - 25 Dec 2025

Abstract

In recent years, the RRT* algorithm has been widely applied in industrial fields because of its asymptotic optimality. However, the traditional RRT* algorithm exhibits limitations in terms of convergence speed and quality of generated paths, and its path exploration capability in complex environments [...] Read more.

In recent years, the RRT* algorithm has been widely applied in industrial fields because of its asymptotic optimality. However, the traditional RRT* algorithm exhibits limitations in terms of convergence speed and quality of generated paths, and its path exploration capability in complex environments remains inadequate. To address these issues, this study proposes a self-adaptive bidirectional APF-RRT* (SA-Bi-APF-RRT*) algorithm. Specifically, a hierarchical node expansion mechanism is established, enabling dynamic adjustment of the new node expansion strategy. Furthermore, a bidirectional artificial potential field (APF) guidance strategy is introduced to enhance obstacle avoidance performance. An obstacle range density evaluation module, which autonomously adjusts APF parameters according to the density distribution of surrounding obstacles, is then incorporated. Additionally, the algorithm integrates a segmented greedy approach with Bézier curve fitting techniques to achieve simultaneous optimization of path length and smoothness, while ensuring path safety. Finally, the proposed algorithm is compared against RRT*, GB-RRT*, Bi-RRT*, APF-RRT*, and Bi-APF-RRT*, demonstrating superior adaptability and efficiency in environments characterized by low iteration counts and high obstacle density. Results indicate that the SA-Bi-APF-RRT* algorithm constitutes a promising optimization solution for USVs path planning tasks. Full article

(This article belongs to the Special Issue Advanced Research on Path Planning for Intelligent Ships)

► Show Figures

Figure 1

10 pages, 2022 KB

Open AccessArticle

Identification of a Ficolin-like Serum Lectin of the Common Carp as a Novel Homologue of Mammalian Microfibrillar-Associated Protein 4

by Michiyo Kimura, Tomonori Somamoto, Takahiro Nagasawa and Miki Nakao

J. Mar. Sci. Eng. 2026, 14(1), 44; https://doi.org/10.3390/jmse14010044 - 25 Dec 2025

Abstract

Serum lectins in vertebrates play crucial roles in innate immunity as recognition molecules for pathogen-associated molecular patterns (PAMPs). In mammals, two major lectins, mannose-binding lectin (MBL) and ficolin, both containing N-terminal collagen-like domains, activate the lectin pathway of complement. While MBL and ficolin [...] Read more.

Serum lectins in vertebrates play crucial roles in innate immunity as recognition molecules for pathogen-associated molecular patterns (PAMPs). In mammals, two major lectins, mannose-binding lectin (MBL) and ficolin, both containing N-terminal collagen-like domains, activate the lectin pathway of complement. While MBL and ficolin recognize distinct PAMPs, their counterparts in teleosts are less understood. To date, MBL and galactose-binding lectin (GalBL) have been identified in teleosts, but the presence of ficolin remains unclear. In this study, we purified a 31-kDa serum lectin from common carp that displayed carbohydrate-binding specificity similar to that of mammalian ficolin. Unexpectedly, this lectin lacked an N-terminal collagenous domain and showed the highest similarity to mammalian microfibril-associated glycoprotein 4 (MFAP4), suggesting that the lectin is distinct from fibulin. Biochemical analyses revealed that carp MFAP4-like lectin (MFAP4Lec) protein forms a hexamer in serum, specifically binds GlcNAc and GalNAc, and recognizes the fish pathogen Vibrio anguillarum. The binding was competitively inhibited by GlcNAc but not by EDTA, indicating Ca²⁺-independent recognition. These findings suggest that MFAP4Lec functions as a novel serum lectin in teleost fish, serving as a recognition molecule for bacterial pathogens in innate immunity. Full article

(This article belongs to the Section Marine Ecology)

► Show Figures

Figure 1

30 pages, 4360 KB

Open AccessArticle

Development of a Reinforcement Learning-Based Ship Voyage Planning Optimization Method Applying Machine Learning-Based Berth Dwell-Time Prediction as a Time Constraint

by Youngseo Park, Suhwan Kim, Jeongon Eom and Sewon Kim

J. Mar. Sci. Eng. 2026, 14(1), 43; https://doi.org/10.3390/jmse14010043 - 25 Dec 2025

Abstract

Global container shipping faces increasing pressure to reduce fuel consumption and greenhouse gas (GHG) emissions while still meeting strict port schedules under highly uncertain terminal operations and met-ocean conditions. However, most existing voyage-planning approaches either ignore real port operation variability or treat fuel [...] Read more.

Global container shipping faces increasing pressure to reduce fuel consumption and greenhouse gas (GHG) emissions while still meeting strict port schedules under highly uncertain terminal operations and met-ocean conditions. However, most existing voyage-planning approaches either ignore real port operation variability or treat fuel optimization and just-in-time (JIT) arrival as separate problems, limiting their applicability in actual operations. This study presents a data-driven just-in-time voyage optimization framework that integrates port-side uncertainty and marine environmental dynamics into the routing process. A dwell-time prediction model based on Gradient Boosting was developed using port throughput and meteorological–oceanographic variables, achieving a validation accuracy of R² = 0.84 and providing a data-driven required time of arrival (RTA) estimate. A Transformer encoder model was constructed to forecast fuel consumption from multivariate navigation and environmental data, and the model achieved a segment-level predictive performance with an R² value of approximately 0.99. These predictive modules were embedded into a Deep Q-Network (DQN) routing model capable of optimizing headings and speed profiles under spatially varying ocean conditions. Experiments were conducted on three container-carrier routes in which the historical AIS trajectories served as operational benchmark routes. Compared with these AIS-based baselines, the optimized routes reduced fuel consumption and CO₂ emissions by approximately 26% to 69%, while driving the JIT arrival deviation close to zero. The proposed framework provides a unified approach that links port operations, fuel dynamics, and ocean-aware route planning, offering practical benefits for smart and autonomous ship navigation. Full article

(This article belongs to the Special Issue Autonomous Ship and Harbor Maneuvering: Modeling and Control)

► Show Figures

Figure 1

15 pages, 2642 KB

Open AccessArticle

Study on Optimal Shaft Alignment of Propulsion Shafting System for Large Crude Oil Tanker Considering Ship Operating Conditions

by Jimin Lee and Yanggon Kim

J. Mar. Sci. Eng. 2026, 14(1), 42; https://doi.org/10.3390/jmse14010042 - 25 Dec 2025

Abstract

The alignment of the propulsion shafting system is crucial to ensuring the safe and efficient operation of ships. As ships grow in size and engine output increases, the complexity of propulsion systems also escalates, making precise alignment more challenging. Traditional methods often neglect [...] Read more.

The alignment of the propulsion shafting system is crucial to ensuring the safe and efficient operation of ships. As ships grow in size and engine output increases, the complexity of propulsion systems also escalates, making precise alignment more challenging. Traditional methods often neglect hull deformation caused by varying operational conditions, which can lead to uneven bearing loads, excessive vibrations, and potential bearing failures. This study addresses these challenges by analyzing the effects of hull deformation on bearing reaction forces in a large crude oil tanker. Shaft alignment analysis was conducted under six different loading conditions, ranging from dry docking to fully loaded states. The results indicated that hull deformation significantly alters the distribution of bearing loads along the propulsion shaft. Initial alignment, without considering hull deflection, showed satisfactory results, but when hull deformation was included, notable deviations in bearing loads emerged. These deviations pose risks of bearing overloads or underloads, which could accelerate wear or cause failure. To mitigate these risks, this study proposes an optimized bearing offset configuration, adjusting intermediate shaft bearings to maintain balanced loads across all conditions. The findings demonstrate that incorporating hull deformation data into shaft alignment improves the system’s reliability and safety, providing a foundation for better alignment practices for large vessels in varied operational conditions. Full article

(This article belongs to the Special Issue Advanced Design and Innovation for Sustainable Maritime Transport Systems)

► Show Figures

Figure 1

24 pages, 2941 KB

Open AccessArticle

Life Cycle Assessment of a Wave Cycloidal Rotor: Environmental Performance and Improvement Pathways

by Paula Bastos, Abel Arredondo-Galeana, Fiona Devoy-McAuliffe, Julia Fernandez Chozas, Paul Lamont-Kane and Pedro A. Vinagre

J. Mar. Sci. Eng. 2026, 14(1), 41; https://doi.org/10.3390/jmse14010041 - 25 Dec 2025

Abstract

Wave energy technology needs to be reliable, efficient, and environmentally sustainable. Therefore, life cycle assessment (LCA) is a critical tool in the design of marine renewable energy devices. However, LCA studies of floating type wave cycloidal rotors remain limited. This study builds on [...] Read more.

Wave energy technology needs to be reliable, efficient, and environmentally sustainable. Therefore, life cycle assessment (LCA) is a critical tool in the design of marine renewable energy devices. However, LCA studies of floating type wave cycloidal rotors remain limited. This study builds on previous work by assessing the cradle-to-grave environmental impacts of a cycloidal rotor wave farm, incorporating updated material inventories, site-dependent energy production, and lifetime extension scenarios. The farm with the steel cyclorotor configuration exhibits a carbon intensity of 21.4 g

{CO}_{2}

eq/kWh and an energy intensity of 344 kJ/kWh, which makes it a competitive technology compared to other wave energy converters. Alternative materials, such as aluminium and carbon fibre, yield mass reductions but incur higher embodied emissions. Site deployment strongly influences performance, with global warming potential reduced by up to 50% in high-power-density sites, while extending the operational lifetime from 25 to 30 years further reduces the impact by 17%. Overall, the results highlight the competitive environmental performance of floating wave cycloidal rotors and emphasize the importance of material selection, site selection, and lifetime extension strategies in reducing life cycle impacts. Full article

(This article belongs to the Section Marine Energy)

► Show Figures

Figure 1

27 pages, 12778 KB

Open AccessArticle

Oil Spill Trajectories and Beaching Risk in Brazil’s New Offshore Frontier

by Daniel Constantino Zacharias, Guilherme Landim Santos, Carine Malagolini Gama, Elienara Fagundes Doca Vasconcelos, Beatriz Figueiredo Sacramento and Angelo Teixeira Lemos

J. Mar. Sci. Eng. 2026, 14(1), 40; https://doi.org/10.3390/jmse14010040 - 25 Dec 2025

Abstract

The present study has applied a probabilistic oil spill modeling framework to assess the potential risks associated with offshore oil spills in the Foz do Amazonas sedimentary basin, a region of exceptional ecological importance and increasing geopolitical and socio-environmental relevance. By integrating a [...] Read more.

The present study has applied a probabilistic oil spill modeling framework to assess the potential risks associated with offshore oil spills in the Foz do Amazonas sedimentary basin, a region of exceptional ecological importance and increasing geopolitical and socio-environmental relevance. By integrating a large ensemble of simulations with validated hydrodynamic, atmospheric and wave-driven forcings, the analysis of said simulations has provided a robust and seasonally resolved assessment of oil drift and beaching patterns along the Guianas and the Brazilian Equatorial Margin. The model has presented a total of 47,500 simulations performed on 95 drilling sites located across the basin, using the Lagrangian Spill, Transport and Fate Model (STFM) and incorporating a six-year oceanographic and meteorological variability. The simulations have included ocean current fields provided by HYCOM, wind forcing provided by GFS and Stokes drift provided by ERA5. Model performance has been evaluated by comparisons with satellite-tracked surface drifters using normalized cumulative Lagrangian separation metrics and skill scores. Mean skill scores have reached 0.98 after 5 days and 0.95 after 10 days, remaining above 0.85 up to 20 days, indicating high reliability for short to intermediate forecasting horizons and suitability for probabilistic applications. Probabilistic simulations have revealed a pronounced seasonal effect, governed by the annual migration of the Intertropical Convergence Zone (ITCZ). During the JFMA period, shoreline impact probabilities have exceeded 40–50% along extensive portions of the French Guiana and Amapá state (Brazil) coastlines, with oil reaching the coast typically within 10–20 days. In contrast, during the JASO period, beaching probabilities have decreased to below 15%, accompanied by a substantial reduction in impact along the coastline and higher variability in arrival times. Although coastal exposure has been markedly reduced during JASO, a residual probability of approximately 2% of oil intrusion into the Amazonas river mouth has persisted. Full article

(This article belongs to the Special Issue Oil Transport Models and Marine Pollution Impacts)

► Show Figures

Figure 1

21 pages, 6298 KB

Open AccessArticle

Numerical Simulation Study on the Movement Characteristics of Plumes in Marine Mining

by Hui Li, Yicheng Zhang, Chaohui Nie, Yang Wang and Enjin Zhao

J. Mar. Sci. Eng. 2026, 14(1), 39; https://doi.org/10.3390/jmse14010039 - 24 Dec 2025

Abstract

The prediction of deep-sea mining sediment plumes is essential for assessing and mitigating the environmental impacts on vulnerable deep-sea ecosystems. In this paper, the numerical simulation method is adopted to predict the sediment plume transportation. Fluid dynamics are governed by the incompressible Navier–Stokes [...] Read more.

The prediction of deep-sea mining sediment plumes is essential for assessing and mitigating the environmental impacts on vulnerable deep-sea ecosystems. In this paper, the numerical simulation method is adopted to predict the sediment plume transportation. Fluid dynamics are governed by the incompressible Navier–Stokes equations, coupled with the Standard k–ε turbulence model to capture turbulent diffusion. The air–water free surface is tracked by a high-resolution Volume of Fluid (VOF) method. The pressure–velocity coupling utilizes the PISO algorithm. Sediment transport is governed by the advection–diffusion equation. The mathematical model is validated through experiments. There is a good consistency between the experiment results and the numerical results, which proves that the numerical method can be applied. The study calculates the diffusion range and characteristics of plumes under different free stream velocities, injection velocities and discharge densities. The results indicate that an increase in free stream velocity enhances the development of turbulence, but conversely restricts the expansion of the mixing zone between the plume and the ambient water. A greater injection velocity leads to a wider distribution range of the plume, while inhibiting the development of local turbulence. A higher plume discharge density results in a larger horizontal distribution range, while hindering the effective mixing between the plume and the ambient water body. Full article

(This article belongs to the Special Issue Deep-Sea Mineral Resource Development Technology and Equipment)

► Show Figures

Figure 1

15 pages, 1077 KB

Open AccessArticle

A Policy–Machine Learning Hybrid Approach to Evaluate Trap Mesh Selectivity: A Case Study on Pseudopleuronectes yokohamae

by Myungsung Koo and Inyeong Kwon

J. Mar. Sci. Eng. 2026, 14(1), 38; https://doi.org/10.3390/jmse14010038 - 24 Dec 2025

Abstract

A machine learning-based policy–utility framework was developed to assess trap mesh sizes (35–80 mm) in the Marbled Flounder fishery and reframe traditional selectivity analysis into a policy-oriented decision context. A utility function integrating catch per unit effort (CPUE), the immature proportion, and the [...] Read more.

A machine learning-based policy–utility framework was developed to assess trap mesh sizes (35–80 mm) in the Marbled Flounder fishery and reframe traditional selectivity analysis into a policy-oriented decision context. A utility function integrating catch per unit effort (CPUE), the immature proportion, and the bycatch ratio was constructed from experimental data collected in 2015–2016 and assessed under multiple policy weighting scenarios. Gradient boosting models trained on the 2016 data and validated with the 2015 data demonstrated strong predictive accuracy. The empirically optimized weighting set (α* = 0.79, β* = 2.36, and γ* = 0.79) produced high agreement between predicted and observed utilities (root mean square error ≈ 0.22; r = 0.901). Variable importance analysis identified the immature proportion as the main driver of utility variation; bycatch ratio and CPUE made smaller contributions. Scenario-based simulations showed a shift in the optimal mesh size, from 65 mm in 2015 to 80 mm in 2016, that reflects interannual changes to population size structure and bycatch composition. Policy regret analysis (comparing 65 mm to 80 mm) indicated consistently low regret (ΔU ≈ 0.12–0.15) and relative regret (<80%) values. This integrated utility–regret framework provides a dynamic, policy-relevant tool for linking trap selectivity information to management objectives. Full article

(This article belongs to the Special Issue Marine Fishing Gear and Aquacultural Engineering)

39 pages, 3145 KB

Open AccessArticle

WA-YOLO: Water-Aware Improvements for Maritime Small-Object Detection Under Glare and Low-Light

by Hongxin Sun, Hongguan Zhao, Zhao Liu, Guanyao Jiang and Jiansen Zhao

J. Mar. Sci. Eng. 2026, 14(1), 37; https://doi.org/10.3390/jmse14010037 - 24 Dec 2025

Abstract

Maritime vision systems for unmanned surface vehicles confront challenges in small-object detection, specular reflections and low-light conditions. This paper introduces WA-YOLO, a water-aware training framework that incorporates lightweight attention modules (ECA/CBAM) to enhance the model’s discriminative capacity for small objects and critical features, [...] Read more.

Maritime vision systems for unmanned surface vehicles confront challenges in small-object detection, specular reflections and low-light conditions. This paper introduces WA-YOLO, a water-aware training framework that incorporates lightweight attention modules (ECA/CBAM) to enhance the model’s discriminative capacity for small objects and critical features, particularly against cluttered water ripples and glare backgrounds; employs advanced bounding box regression losses (e.g., SIoU) to improve localization stability and convergence efficiency under wave disturbances; systematically explores the efficacy trade-off between high-resolution input and tiled inference strategies to tackle small-object detection, significantly boosting small-object recall (APS) while carefully evaluating the impact on real-time performance on embedded devices; and introduces physically inspired data augmentation techniques for low-light and strong-reflection scenarios, compelling the model to learn more robust feature representations under extreme optical variations. WA-YOLO achieves a compelling +2.1% improvement in mAP@0.5 and a +6.3% gain in APS over YOLOv8 across three test sets. When benchmarked against the advanced RT-DETR model, WA-YOLO not only surpasses its detection accuracy (0.7286 mAP@0.5) but crucially maintains real-time performance at 118 FPS on workstations and 17 FPS on embedded devices, achieving a superior balance between precision and efficiency. Our approach offers a simple, reproducible and readily deployable solution, with full code and pre-trained models publicly released. Full article

(This article belongs to the Section Ocean Engineering)

12 pages, 4170 KB

Open AccessArticle

Wind-Induced Seismic Noise and Stable Resonances Reveal Ice Shelf Thickness at Pine Island Glacier

by Yuqiao Chen, Peng Yan, Yuande Yang, David M. Holland and Fei Li

J. Mar. Sci. Eng. 2026, 14(1), 36; https://doi.org/10.3390/jmse14010036 - 24 Dec 2025

Abstract

Antarctic ice shelves regulate ice-sheet discharge and global sea-level rise, yet their rapid retreat underscores the need for new, low-cost monitoring tools. We analyze ambient seismic noise recorded by seismometers on the Pine Island Glacier ice shelf to characterize wind-induced signals and detect [...] Read more.

Antarctic ice shelves regulate ice-sheet discharge and global sea-level rise, yet their rapid retreat underscores the need for new, low-cost monitoring tools. We analyze ambient seismic noise recorded by seismometers on the Pine Island Glacier ice shelf to characterize wind-induced signals and detect persistent structural resonances. Power spectral analysis shows that wind sensitivity is strongly damped compared with bedrock sites: noise increases only 5–7 dB from 0 to 25 m s⁻¹ winds, versus a 42 dB increase at an inland bedrock station, reflecting the contrasted coupling environments of floating and grounded substrates. The horizontal-to-vertical spectral ratio (HVSR) spectrograms reveal two temporally stable peaks at ~2.2 Hz and ~4.3 Hz that persist across stations and remain independent of environmental forcing. Forward modeling indicates that these peaks correspond to S-wave resonances within the ice shelf. The inferred ice-water interface depth (~440 m) agrees with the Bedmap2 thickness estimate (466 m). This work demonstrates that HVSR provides an effective passive, single-station method for measuring ice shelf thickness. Full article

(This article belongs to the Section Marine Environmental Science)

► Show Figures

Figure 1

Journal Description

Journal of Marine Science and Engineering

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Further Information

Guidelines

MDPI Initiatives

Follow MDPI