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Time Series Changes of Surficial Sediments on Eastern Ship Shoal, Louisiana Shelf
Attentive Neural Processes for Few-Shot Learning Anomaly-Based Vessel Localization Using Magnetic Sensor Data
CAD Model Reconstruction by Generative Design of an iQFoil Olympic Class Foiling Windsurfing Wing
Determining the Minimum Detection Limit of Methane Hydrate Using Associated Alpha Particle Technique
Novel Hybrid Aquatic–Aerial Vehicle to Survey in High Sea States: Initial Flow Dynamics on Dive and Breach

Journal Description

Journal of Marine Science and Engineering

Journal of Marine Science and Engineering is an international, peer-reviewed, open access journal on marine science and engineering, published monthly online by MDPI. The Australia New Zealand Marine Biotechnology Society (ANZMBS) is affiliated with JMSE and their members receive discounts on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed with Scopus, SCIE (Web of Science), Ei Compendex, GeoRef, Inspec, AGRIS, and other databases.
Journal Rank: JCR - Q2 (Engineering, Marine) / CiteScore - Q2 (Ocean Engineering)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 15.6 days after submission; acceptance to publication is undertaken in 1.9 days (median values for papers published in this journal in the first half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Journal Clusters of Water Resources: Water, Journal of Marine Science and Engineering, Hydrology, Resources, Oceans, Limnological Review, Coasts.

Impact Factor: 2.8 (2024); 5-Year Impact Factor: 2.8 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2077-1312

Latest Articles

13 pages, 413 KB

Open AccessEditorial

Advances in Innovative Solutions for Ship Energy Efficiency

by Nikos Themelis

J. Mar. Sci. Eng. 2025, 13(11), 2103; https://doi.org/10.3390/jmse13112103 (registering DOI) - 4 Nov 2025

The shipping sector is central to global trade, carrying about 80–90% of goods worldwide, but it also represents one of the hardest-to-abate industries from an environmental perspective [...] Full article

(This article belongs to the Special Issue Advances in Innovative Solutions for Ship Energy Efficiency)

20 pages, 2237 KB

Open AccessArticle

Exploring Time-Series Deep Learning Models for Ship Fuel Consumption Prediction

by Xiao Chen, Xiaosheng Liu, Yuxia Luo and Xiangming Zeng

J. Mar. Sci. Eng. 2025, 13(11), 2102; https://doi.org/10.3390/jmse13112102 (registering DOI) - 4 Nov 2025

The fuel consumption of ships is an important component of shipping operation costs and also a significant source of greenhouse gas emissions. Accurate fuel consumption prediction is of great significance for optimizing the energy efficiency management of ships, reducing operating costs, and minimizing [...] Read more.

The fuel consumption of ships is an important component of shipping operation costs and also a significant source of greenhouse gas emissions. Accurate fuel consumption prediction is of great significance for optimizing the energy efficiency management of ships, reducing operating costs, and minimizing environmental pollution. In addition, we have also observed that the fuel consumption data of ships usually have a strong temporal correlation. Therefore, in order to study whether the time-series factors of ship fuel data are helpful for SFC prediction and the performance of various deep learning models in ship fuel consumption prediction, this paper proposes three classes of models for comparative study: RNN-based models, attention-based models such as Transformer and Informer, which are applied to the field of ship fuel consumption for the first time, and RNN–attention mixed models. The experimental results show that there is indeed a lag in ship navigation data, and the processing of time-series data is of great significance for fuel consumption prediction. Moreover, we have found that on real ship operation datasets, Informer is the best-performing model with 1.46 and 0.969 for MSE and

R^{2}

scores. The prediction performance of Informer is significantly better than that of other methods, which provides a new direction for future ship fuel consumption prediction. Full article

(This article belongs to the Special Issue Advanced Research on the Sustainable Maritime Transportation (2nd Edition))

18 pages, 2647 KB

Open AccessArticle

Deploying Neural Networks at Sea: Condition Monitoring of the Ropes on the Amerigo Vespucci

by Letizia Rosseti, Mattia Frascio, Massimiliano Avalle and Francesco Grella

J. Mar. Sci. Eng. 2025, 13(11), 2101; https://doi.org/10.3390/jmse13112101 (registering DOI) - 4 Nov 2025

Monitoring the condition of ropes aboard historic ships is crucial for both safety and preservation. This study introduces a portable, low-cost imaging device designed for deployment on the Italian training ship Amerigo Vespucci, enabling autonomous acquisition of high-quality images of onboard ropes. The [...] Read more.

Monitoring the condition of ropes aboard historic ships is crucial for both safety and preservation. This study introduces a portable, low-cost imaging device designed for deployment on the Italian training ship Amerigo Vespucci, enabling autonomous acquisition of high-quality images of onboard ropes. The device, built around a Raspberry Pi 3 and enclosed in a 3D-printed protective case, allows the crew to label the state of ropes using colored markers and capture standardized visual data. From 207 collected recordings, a curated and balanced dataset was created through frame extraction, blur filtering using Laplacian variance, and image preprocessing. This dataset was used to train and evaluate convolutional neural networks (CNNs) for binary classification of rope conditions. Both custom CNN architectures and pre-trained models (MobileNetV2 and EfficientNetB0) were tested. Results show that color images outperform grayscale in all cases, and that EfficientNetB0 achieved the best performance, with 97.74% accuracy and an F1-score of 0.9768. The study also compares model sizes and inference times, confirming the feasibility of real-time deployment on embedded hardware. These findings support the integration of deep learning techniques into field-deployable inspection tools for preventive maintenance in maritime environments. Full article

(This article belongs to the Section Ocean Engineering)

35 pages, 5117 KB

Open AccessArticle

Impact of Fluid Sloshing on BOG Generation in Type B LNG Tanks During Ship Emergency Stops

by Haikang Zhao, Gang Wu, Jiachen Chen, Xigang Pu, Sicong Wang, Yuhao Yuan and Ang Sun

J. Mar. Sci. Eng. 2025, 13(11), 2100; https://doi.org/10.3390/jmse13112100 (registering DOI) - 4 Nov 2025

The safe and efficient transport of Liquefied Natural Gas (LNG) is critically dependent on understanding fluid dynamics within cargo tanks, which directly influence structural integrity and operational safety. Study employs the Volume of Fluid (VOF) method to simulate fluid sloshing and phase change [...] Read more.

The safe and efficient transport of Liquefied Natural Gas (LNG) is critically dependent on understanding fluid dynamics within cargo tanks, which directly influence structural integrity and operational safety. Study employs the Volume of Fluid (VOF) method to simulate fluid sloshing and phase change dynamics in Type B LNG cargo tanks during emergency stop conditions. The transient simulations employ a time step of 5 × 10⁻³ s, a model with 46,840 grids, and the analysis focuses on impact forces on tank walls, their dependence on filling levels. Results show that the flow disturbance caused by vessel rolling increases BOG generation fluctuations by approximately 35%. Sloshing significantly increases BOG generation, particularly after a 10 s relaxation period, as the initial shock enhances heat transfer and mixing, accelerating vapor production. Original components of LNG are sensitive to BOG generation and impact forces on the front bulkhead are significantly higher than on the rear, with peak impacts occurring. The filling rate is a critical parameter influencing fluid dynamics and safety in LNG transportation. Impact magnitude increases with fill level up while at about 80% it declines; impact timing shortens at higher fill ratios. A BOG generation mechanism in which microscale turbulence and ongoing thermal imbalance govern the kinetics of evaporation phase transitions was proposed. It was discovered that the impact forces and BOG production exhibit rise–fall–rise patterns driven by impact dynamics, condensation, and evaporation processes. The findings highlight the critical role of fluid sloshing in affecting tank safety and operational efficiency, offering insights into designing more resilient LNG cargo tanks and optimizing transportation safety and economy. Full article

(This article belongs to the Special Issue Advanced Studies in Ship Fluid Mechanics)

16 pages, 1901 KB

Open AccessArticle

Risk Assessment Framework for Structural Failures of Polar Ship Under Ice Loads

by Kai Sun, Xiaodong Chen, Shunying Ji and Haitian Yang

J. Mar. Sci. Eng. 2025, 13(11), 2099; https://doi.org/10.3390/jmse13112099 - 4 Nov 2025

For polar ships, navigation in ice-covered regions can lead to high risk to structural safety. To study the structural risk induced by ice loads, a risk assessment framework is proposed based on a probabilistic analysis. The fatigue failure probability is derived with the [...] Read more.

For polar ships, navigation in ice-covered regions can lead to high risk to structural safety. To study the structural risk induced by ice loads, a risk assessment framework is proposed based on a probabilistic analysis. The fatigue failure probability is derived with the first-order second-moment (FOSM) method. Typical ice load cases are extracted as a joint probability distribution of ice thickness and ship speed, based on shipboard measurements. Equivalent fatigue stresses for each case are calculated using a coupled discrete element method (DEM) and finite element method (FEM), and fatigue failure probabilities are obtained via linear cumulative damage theory. The ultimate strength failure probability is derived from the reliability theory. The probabilistic distribution of load-carrying capacity for the bow structure, determined by the moment estimation method, is used as the structural resistance, while the ice load distribution identified from shipboard monitoring is treated as the external load. Considering both the likelihood and consequence of failure, a risk matrix is constructed to assess structural failure risk. Inspection and maintenance intervals are then proposed according to the assessed risk levels. This approach offers a quantitative basis for structural risk management, supporting safe navigation and efficient maintenance planning for polar ships. Full article

(This article belongs to the Section Ocean Engineering)

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23 pages, 6239 KB

Open AccessArticle

Numerical and Experimental Investigation of New Concrete Armor Unit Maya

by Angela Di Leo, Anna Sansanelli, Luigi Pratola, Valentino Paolo Berardi and Fabio Dentale

J. Mar. Sci. Eng. 2025, 13(11), 2098; https://doi.org/10.3390/jmse13112098 - 4 Nov 2025

The subject of the present work is the study of the phenomena of the interaction between wave motion and coastal defense structures for a new type of reinforcement unit in concrete armor blocks (C.A.U.)—named “MAYA”. The performance of single-layer MAYA armor, reproduced in [...] Read more.

The subject of the present work is the study of the phenomena of the interaction between wave motion and coastal defense structures for a new type of reinforcement unit in concrete armor blocks (C.A.U.)—named “MAYA”. The performance of single-layer MAYA armor, reproduced in a 1:20 Froude-scaled physical model, has been investigated in terms of hydraulic behavior and wave run-up, reflection, and overtopping. The results have been compared to classic literature formulations, numerical results of the same type of structure reproduced at full scale, and other artificial blocks. A new approach for the prediction of the reflection coefficient based on dimensional analysis was proposed in a previous study, and a newly derived empirical equation was also tested for numerical result validation. The structures were numerically modeled and reproduced using an innovative approach by overlapping individual three-dimensional elements of a new type of block “Maya”, Accropode and Tetrapod and a fine computational grid was fitted to provide enough computational nodes within the flow paths. The hydraulic behavior of the novel block was numerically evaluated, and its potential was assessed in comparison to other existing blocks. This was achieved by reproducing and analyzing the structures using a RANS approach. The numerical approach, which was validated by experimental results, enables the analysis of various design solutions in a shorter amount of time while ensuring the accuracy of the results. Additionally, the preliminary analysis showed the potential of the novel block, which allows for a reduction in construction and manufacturing costs while also demonstrating superior hydrodynamic performance in some cases. Full article

(This article belongs to the Section Ocean Engineering)

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14 pages, 4260 KB

Open AccessArticle

Structural Integrity Evaluation of a Modular 15-Ton Class Barge Under Still Water and Wave-Induced Loads

by Changhyun Lee, Juneyoung Kim and Jaemin Lee

J. Mar. Sci. Eng. 2025, 13(11), 2097; https://doi.org/10.3390/jmse13112097 - 4 Nov 2025

Modular barges are increasingly applied in inland and nearshore operations for their transportability and flexible assembly, yet the reliability of their connections remains insufficiently studied. This study presents a finite element analysis of a 15-ton-class modular barge in service, focusing on bolted and [...] Read more.

Modular barges are increasingly applied in inland and nearshore operations for their transportability and flexible assembly, yet the reliability of their connections remains insufficiently studied. This study presents a finite element analysis of a 15-ton-class modular barge in service, focusing on bolted and interlocking joints under still-water and wave-induced loads. A detailed three-dimensional model with explicit contacts was developed, and four load cases combined hydrostatic and deck loads with longitudinal and transverse crest/trough scenarios. Results showed that the highest stresses occurred in central stiffeners and lower interlocking joints, but all were below allowable limits, ensuring adequate safety margins. Bolted joints exhibited low stress, confirming their robustness and redundancy within the hybrid system. By analyzing an operating barge under realistic conditions, this study demonstrates the structural adequacy of the modular concept and provides a basis for future guidelines and larger modular floating platforms. Full article

(This article belongs to the Special Issue Wave Excitation Loads and Structural Assessment in Maritime and Offshore Engineering)

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21 pages, 4928 KB

Open AccessArticle

System Identification and Robust Control Method for Magnetic Bearings in Ship Propulsion Shaft Systems

by Feng Xiong, Tianqi Yin, Neng Zhang, Wenhao Xu and Yan Li

J. Mar. Sci. Eng. 2025, 13(11), 2096; https://doi.org/10.3390/jmse13112096 - 4 Nov 2025

In the field of rotating machinery, such as marine propulsion shafting, magnetic bearing-supported propulsion systems have garnered significant attention due to their non-mechanical contact advantages. To address the problem that the design of magnetic bearing controllers, based on theoretical models, neglects the dynamic [...] Read more.

In the field of rotating machinery, such as marine propulsion shafting, magnetic bearing-supported propulsion systems have garnered significant attention due to their non-mechanical contact advantages. To address the problem that the design of magnetic bearing controllers, based on theoretical models, neglects the dynamic characteristics of practical components like power amplifiers and displacement sensors, making it difficult to achieve ideal performance in practical applications, this paper proposes a control method for Hybrid Magnetic Bearings (HMBs) that combines a time-domain identification model with robust control. The method first models the power amplifier, HMB, and displacement sensor as an equivalent single system and obtains its high-precision transfer function model by performing system identification on its time-domain data using the least squares method. Based on this foundation, a PID controller is designed using the loop-shaping method to enhance the system’s robustness and control performance. Both simulations and experiments on an HMB test rig confirmed the controller’s effectiveness. The system showed excellent levitation, dynamic stability, and disturbance rejection, with experimental results closely matching simulations. The experimental results are consistent with the simulation results. This method provides a practical and feasible technical approach for enhancing the control performance of magnetic bearing-supported propulsion shafting. Full article

(This article belongs to the Section Ocean Engineering)

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19 pages, 7033 KB

Open AccessArticle

Implications of Flume Simulation for the Architectural Analysis of Shallow-Water Deltas: A Case Study from the S Oilfield, Offshore China

by Lixin Wang, Ge Xiong, Yanshu Yin, Wenjie Feng, Jie Li, Pengfei Xie, Xun Hu and Xixin Wang

J. Mar. Sci. Eng. 2025, 13(11), 2095; https://doi.org/10.3390/jmse13112095 - 3 Nov 2025

The shallow-water delta-front reservoir in Member II of the Oligocene Dongying Formation (Ed2), located in an oilfield within the Bohai Bay Basin, is a large-scale composite sedimentary system dominated by subaqueous distributary channels and mouth bars. Within this system, reservoir sand bodies exhibit [...] Read more.

The shallow-water delta-front reservoir in Member II of the Oligocene Dongying Formation (Ed2), located in an oilfield within the Bohai Bay Basin, is a large-scale composite sedimentary system dominated by subaqueous distributary channels and mouth bars. Within this system, reservoir sand bodies exhibit significant thickness, complex internal architecture, poor injection–production correspondence during development, and an ambiguous understanding of remaining oil distribution. To enhance late-stage development efficiency, it is imperative to deepen the understanding of the genesis and evolution of the subaqueous distributary channel–mouth bar system, analyze the internal reservoir architecture, and clarify sand body connectivity relationships. Based on sedimentary physical modeling experiments, integrated with core, well logging, and seismic data, this study systematically reveals the architectural characteristics and spatial stacking patterns of the mouth bar reservoirs using Miall’s architectural element analysis method. The results indicate that the study area is dominated by sand-rich, shallow-water delta front deposits, which display a predominantly coarsening-upward character. The main reservoir units are mouth bar sand bodies (accounting for 30%), with a vertical stacking thickness ranging from 3 to 20 m, and they exhibit lobate distribution patterns in plan view. Sedimentary physical modeling reveals the formation mechanism and stacking patterns of these sand-rich, thick sand bodies. Upon entering the lake, the main distributary channel unloads its sediment, forming accretionary bodies. The main channel then bifurcates, and a new main channel forms in the subsequent unit, which transports sediment away and initiates a new phase of deposition. Multi-phase deposition ultimately builds large-scale lobate complexes composed of channel–mouth bar assemblages. These complexes exhibit internal architectural styles, including channel–channel splicing, channel–bar splicing, and bar–bar splicing. Reservoir architecture analysis demonstrates that an individual distributary channel governs the formation of an individual lobe, whereas multiple distributary channels control the development of composite lobes. These lobes are laterally spliced and vertically superimposed, exhibiting a multi-phase progradational stacking pattern. Dynamic production data analysis validates the reliability of this reservoir architecture classification. This research elucidates the genetic mechanisms of thick sand bodies in delta fronts and establishes a region-specific reservoir architecture model. This study clarifies the spatial distribution of mudstone interlayers and preferential flow pathways within the composite sand bodies. It provides a geological basis for optimizing injection–production strategies and targeting residual oil during the ultra-high water-cut stage. The findings offer critical guidance for the efficient development of shallow-water delta front reservoirs. Full article

(This article belongs to the Section Geological Oceanography)

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29 pages, 4097 KB

Open AccessArticle

Global Fixed-Time Target Enclosing Tracking Control for an Unmanned Surface Vehicle Under Unknown Velocity States and Actuator Saturation

by Xinjie Han, Guanglu Ma, Yunsheng Fan, Dongdong Mu, Feng Sun, Linlong Shi and Hongbiao Li

J. Mar. Sci. Eng. 2025, 13(11), 2094; https://doi.org/10.3390/jmse13112094 - 3 Nov 2025

This paper presents a global fixed-time control framework to address the target circumnavigation tracking problem of underactuated unmanned surface vehicles (USV) under unknown velocity states, lumped uncertainties, and actuator saturation. At the core of this approach is a novel fixed-time target-enclosing line-of-sight (FTTELOS) [...] Read more.

This paper presents a global fixed-time control framework to address the target circumnavigation tracking problem of underactuated unmanned surface vehicles (USV) under unknown velocity states, lumped uncertainties, and actuator saturation. At the core of this approach is a novel fixed-time target-enclosing line-of-sight (FTTELOS) guidance law, designed to generate the desired heading angle and surge velocity. To estimate unknown velocities, external disturbances, and unmeasured system states, a set of fixed-time observers is constructed, consisting of a velocity observer, a disturbance observer, and a high-dimensional extended state observer (HFTESO). Moreover, to enhance robustness and effectively tackle actuator saturation, the control scheme incorporates a fixed-time sliding mode controller, a dynamic auxiliary system, and a fixed-threshold event-triggered mechanism. Simulation results using SimuNPS demonstrate that the proposed method enables rapid and smooth target circumnavigation, with all system errors converging to an arbitrarily small neighborhood of the origin within a fixed time. Theoretical analysis and simulation studies confirm the effectiveness and robustness of both the FTTELOS guidance law and the integrated control strategy. Quantitatively, compared with the traditional target-enclosing line-of-sight (TELOS) method, the proposed FTTELOS reduces the convergence time of the distance error

δ_{e}

from 13.64 s to 10.22 s and the angular error

ϕ_{e}

from 10.46 s to 7.52 s, demonstrating a significant improvement in convergence speed and overall control performance. Full article

(This article belongs to the Special Issue New Technologies in Autonomous Ship Navigation)

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27 pages, 4245 KB

Open AccessArticle

Numerical Analysis of Impact-Freezing and Spreading Dynamics of Supercooled Saline Droplets on Offshore Wind Turbine Blades Using the VOF–Enthalpy–Porosity Method

by Guanyu Chen, Huan Xia, Xu Bai, Daolei Wu and Baolong Lin

J. Mar. Sci. Eng. 2025, 13(11), 2093; https://doi.org/10.3390/jmse13112093 - 3 Nov 2025

The impact-freezing phenomenon of supercooled saline droplets on cold surfaces poses a serious threat to the operational stability and structural integrity of offshore wind turbines. Compared to freshwater droplets, numerical models for analyzing the impact-freezing behavior of saline droplets typically involve complex physical [...] Read more.

The impact-freezing phenomenon of supercooled saline droplets on cold surfaces poses a serious threat to the operational stability and structural integrity of offshore wind turbines. Compared to freshwater droplets, numerical models for analyzing the impact-freezing behavior of saline droplets typically involve complex physical mechanisms, resulting in high computational costs. This study employs a simplified two-dimensional axisymmetric numerical model that integrates the Volume of Fluid (VOF) method with the enthalpy–porosity approach, enabling rapid analysis of the saline droplet impact-freezing process under marine environmental conditions. The model is validated by comparing the spreading factor curve of saline droplets with a salinity of 35‰ against existing experimental data. Results show that the salinity corresponding to the peak relative deviation shifts with varying impact parameters, depending on the competition between impact dynamics and solidification. Furthermore, the maximum spreading factor decreases with increasing supercooling degree and contact angle but increases with higher Weber number. These findings provide useful correction parameters for improving existing droplet motion and icing prediction models. Full article

(This article belongs to the Special Issue Advances in Marine Engineering Hydrodynamics, 2nd Edition)

26 pages, 1627 KB

Open AccessArticle

Optimization of Energy Replenishment for Inland Electric Ships Considering Multi-Technology Adoption and Partial Replenishment

by Siqing Guo, Yubing Wang, Mingyuan Yue, Lei Dai, Sidun Fang, Shenxi Zhang and Hao Hu

J. Mar. Sci. Eng. 2025, 13(11), 2092; https://doi.org/10.3390/jmse13112092 - 3 Nov 2025

While battery-powered propulsion represents a promising pathway for inland waterway freight, its widespread adoption is hindered by range anxiety and high investment costs. Strategic energy replenishment has emerged as a critical and cost-effective solution to extend voyage endurance and mitigate these barriers. This [...] Read more.

While battery-powered propulsion represents a promising pathway for inland waterway freight, its widespread adoption is hindered by range anxiety and high investment costs. Strategic energy replenishment has emerged as a critical and cost-effective solution to extend voyage endurance and mitigate these barriers. This paper introduces a novel approach to optimize energy replenishment strategies for inland electric ships that considers the possibility of adopting multiple technologies (charging and battery swapping) and partial replenishment. The proposed approach not only identifies optimal replenishment ports but also determines the technology to employ and the corresponding amount of energy to replenish for each operation, aimed at minimizing total replenishment costs. This problem is formulated as a mixed-integer linear programming model. A case study of a 700-TEU electric container ship operating on two routes along the Yangtze River validates the effectiveness of the proposed approach. The methodology demonstrates superior performance over existing approaches by significantly reducing replenishment costs and improving solution feasibility, particularly in scenarios with tight schedules and limited technology availability. Furthermore, a sensitivity analysis examines the impacts of key parameters, offering valuable strategic insights for industry stakeholders. Full article

(This article belongs to the Special Issue Advanced Research on the Sustainable Maritime Transportation (2nd Edition))

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27 pages, 1584 KB

Open AccessArticle

Physics-Informed Dynamics Modeling: Accurate Long-Term Prediction of Underwater Vehicles with Hamiltonian Neural ODEs

by Xiang Jin, Zeyu Lyu, Jiayi Liu and Yu Lu

J. Mar. Sci. Eng. 2025, 13(11), 2091; https://doi.org/10.3390/jmse13112091 - 3 Nov 2025

Accurately predicting the long-term behavior of complex dynamical systems is a central challenge for safety-critical applications like autonomous navigation. Mechanistic models are often brittle, relying on difficult-to-measure parameters, while standard deep learning models are black boxes that fail to generalize, producing physically inconsistent [...] Read more.

Accurately predicting the long-term behavior of complex dynamical systems is a central challenge for safety-critical applications like autonomous navigation. Mechanistic models are often brittle, relying on difficult-to-measure parameters, while standard deep learning models are black boxes that fail to generalize, producing physically inconsistent predictions. Here, we introduce a physics-informed framework that learns the continuous-time dynamics of an Autonomous Underwater Vehicle (AUV) by discovering its underlying energy landscape. We embed the structure of Port-Hamiltonian mechanics into a neural ordinary differential equation (NODE) architecture, learning not to imitate trajectories but rather to identify the system’s Hamiltonian and its constituent physical matrices from observational data. Geometric consistency is enforced by representing rotational dynamics on the SE(3) manifold, preventing numerical error accumulation. Experimental validation reveals a stark performance divide. While a state-of-the-art black-box model matches our accuracy in simple, interpolative maneuvers, its predictions fail catastrophically under complex controls. Quantitatively, our physics-informed model maintained a mean 10 s position error of a mere 3.3 cm, whereas the black-box model’s error diverged to 5.4 m—an over 160-fold performance gap. This work establishes that the key to robust, generalizable models lies not in bigger data or deeper networks but in the principled integration of physical laws, providing a clear path to overcoming the brittleness of black-box models in critical engineering simulations. Full article

(This article belongs to the Section Ocean Engineering)

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17 pages, 6537 KB

Open AccessArticle

Diagenetic Barite Growths in the Mixing Zone of a Carbonate Coastal Aquifer

by Fernando Sola, Malva Mancuso and Ángela Vallejos

J. Mar. Sci. Eng. 2025, 13(11), 2090; https://doi.org/10.3390/jmse13112090 - 3 Nov 2025

Mixing zones in carbonate coastal aquifers are dynamic interfaces where freshwater and seawater converge, triggering complex biogeochemical processes. This study investigates diagenetic barite (BaSO₄) precipitation within such a mixing zone in the dolomitic aquifer of the Sierra de Gádor (SE Spain). [...] Read more.

Mixing zones in carbonate coastal aquifers are dynamic interfaces where freshwater and seawater converge, triggering complex biogeochemical processes. This study investigates diagenetic barite (BaSO₄) precipitation within such a mixing zone in the dolomitic aquifer of the Sierra de Gádor (SE Spain). Three sectors were analyzed: two active mixing zones—one associated with submarine discharge and the other affected by marine intrusion—and an uplifted, fossilized Pleistocene mixing zone. Mineralogical, petrographic, and geochemical analyses reveal extensive dissolution of the dolomitic bedrock, forming polygonal voids and fracture-controlled porosity, frequently covered by Fe and Mn oxides. Barite crystals were identified exclusively in the Fe oxide precipitates at depths where 80% of seawater is reached. The saturation index for barite in groundwater suggests near-equilibrium conditions across the fresh–brackish–saline transition; however, barite precipitation is localized where Fe oxides act as a geochemical barrier, concentrating Ba and enabling nucleation. SEM imaging shows well-formed euhedral barite crystals up to 100 µm in size. This form of crystallization would be similar to the marine diagenetic barite formation models involving organic matter degradation and Ba remobilization, translated to a coastal aquifer setting in this study. Trace metal analyses show significant enrichment of Pb (up to 20 wt%) and other elements (Zn, Ni, and Co), suggesting potential for ore-forming processes if redox conditions shift. This work proposes a conceptual model for diagenetic barite formation in coastal aquifers, emphasizing the role of Fe and Mn oxides as reactive substrates in metal cycling at the land–sea interface. Full article

(This article belongs to the Special Issue Marine Karst Systems: Hydrogeology and Marine Environmental Dynamics)

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21 pages, 5924 KB

Open AccessArticle

An Affordable Wave Glider-Based Magnetometry System for Marine Magnetic Measurement

by Siyuan Ma, Can Li and Xiujun Sun

J. Mar. Sci. Eng. 2025, 13(11), 2089; https://doi.org/10.3390/jmse13112089 - 3 Nov 2025

Marine magnetic surveys are vast and time-consuming, and researchers have long been seeking an economical mode for large-area data acquisition. A towed magnetic measurement system was developed based on the motion characteristics of the wave glider. By modifying the SeaSPY2 magnetometer, a twin-body [...] Read more.

Marine magnetic surveys are vast and time-consuming, and researchers have long been seeking an economical mode for large-area data acquisition. A towed magnetic measurement system was developed based on the motion characteristics of the wave glider. By modifying the SeaSPY2 magnetometer, a twin-body towed configuration was developed, in which an S-shaped towing cable mitigates motion-induced impacts from the platform, and a high-precision GNSS positioning module was integrated into the system. Sea trials were conducted in the coastal waters near Qingdao. The results indicated that the system achieved an average cruising speed of 0.56 m/s, with the towed body’s pitch and roll angles controlled within ±5° and ±1°, respectively. The dynamic noise was measured at 0.0639 nT (Level 1), and the internal consistency for repeated survey lines and cross lines was 1.832 nT and 1.956 nT, respectively, meeting the requirements of marine magnetic survey standards. The system offers unmanned operation, zero carbon emissions, and a minimal environmental footprint, and long endurance, supporting applications such as nearshore exploration, mapping in sensitive marine areas, and underwater magnetic target detection. The research provides a novel unmanned technological solution for deep-sea magnetic surveys and lays the foundation for low-cost, cluster-based operations. Full article

(This article belongs to the Section Ocean Engineering)

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30 pages, 19955 KB

Open AccessArticle

Adaptive Sampling of Marine Submesoscale Features Using Gaussian Process Regression with Unmanned Platforms

by Wenbo Wang, Haibo Tang, Wei Song, Shuangshuang Fan and Dongxiao Wang

J. Mar. Sci. Eng. 2025, 13(11), 2088; https://doi.org/10.3390/jmse13112088 - 3 Nov 2025

Submesoscale processes, characterized by strong vertical velocities that generate sea surface temperature (SST) fronts as well as O(1) Rossby number (Ro), are critical to ocean mixing and biogeochemical transport, yet their observation is hampered by cost and spatial limitations. Hence, this study [...] Read more.

Submesoscale processes, characterized by strong vertical velocities that generate sea surface temperature (SST) fronts as well as O(1) Rossby number (Ro), are critical to ocean mixing and biogeochemical transport, yet their observation is hampered by cost and spatial limitations. Hence, this study proposes an adaptive sampling framework for unmanned surface vehicles (USVs) that integrates Gaussian process regression (GPR) with submesoscale physical characteristics for efficient, targeted sampling. Three composite-kernel GPR models are developed to predict SST, zonal velocity U, and meridional velocity V, providing predictive fields to support adaptive path planning. A robust coupled gradient indicator (CGI) is further introduced to identify SST frontal zones, where the maximum CGI values are used to select candidate waypoints. Connecting these waypoints yields adaptive paths aligned with frontal structures, while a Ro threshold (0.5–2) automatically triggers spiral-intensive sampling to collect more useful data. Simulation results show that the planned paths effectively capture SST gradient and submesoscale dynamics. The final environment reconstruction achieved the desired accuracy after model retraining, and deployment analysis informs optimal platform deployment. Overall, the proposed framework couples environmental prediction, adaptive path planning, and intelligent sampling, offering an effective strategy for advancing the observation of submesoscale ocean processes. Full article

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

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18 pages, 4476 KB

Open AccessArticle

Storm Surge Dynamics and Mechanisms in the Macao Cross Tidal Channel

by Li Li, Boshuai Zhang, Jiayi Guo, Ye Zhu, Zhiguo He and Yuezhang Xia

J. Mar. Sci. Eng. 2025, 13(11), 2087; https://doi.org/10.3390/jmse13112087 - 3 Nov 2025

Storm surge dynamics in coastal zones and estuaries are complex, driven by coupled oceanic and terrestrial interactions that enhance the risk of coastal disasters. This study investigates storm surge characteristics and mechanisms in the Macao Cross Tidal Channel (MCTC), located in the Macao [...] Read more.

Storm surge dynamics in coastal zones and estuaries are complex, driven by coupled oceanic and terrestrial interactions that enhance the risk of coastal disasters. This study investigates storm surge characteristics and mechanisms in the Macao Cross Tidal Channel (MCTC), located in the Macao Sea Area (MSA). A tide-surge coupled numerical model was established using the unstructured grid Finite Volume Community Ocean Model (FVCOM). The model was rigorously validated against tide gauge data from Typhoon Hato, demonstrating strong performance, with a skill score of 0.95 and a correlation coefficient exceeding 0.94. The spatiotemporal characteristics and mechanisms of storm surge dynamics in the MCTC were elucidated. The results show that the MCTC’s complex geometry induces a geometric funneling effect, which substantially amplifies the storm surge compared with adjacent locations in the estuary and open sea. During the typhoon period, coastal geomorphology affects winds, tide levels, currents, and waves, which in turn spatially and temporally modulate the storm surge. Wind is the primary driver, but its effect is modulated by nonlinear interactions with waves, including enhanced bottom friction and wave set-down. In isolation, the wind-induced component contributed approximately 106% of the peak total surge. This overestimation quantitatively highlights the critical role of nonlinear interactions, where wave-enhanced bottom friction acts as a major energy sink, and wave set-down directly suppresses the water level at the channel entrance. The individual peak contributions from atmospheric pressure and wave were approximately 5% and 17%, respectively, but these peaks occurred out of phase with the storm surge. Energy transformation analysis based on the Bernoulli principle revealed a distinct conversion from potential to kinetic energy in the constricted transverse waterway, while the longitudinal waterway exhibited a more gradual energy change. These findings enhance the mechanistic understanding of storm surges in complex, constricted estuaries and can inform targeted strategies for coastal hazard mitigation in the Macao region. Full article

(This article belongs to the Section Physical Oceanography)

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18 pages, 4845 KB

Open AccessFeature PaperArticle

A Complexity-Aware Course–Speed Model Integrating Traffic Complexity Index for Nonlinear Crossing Waters

by Eui-Jong Lee, Hyun-Suk Kim and Yongung Yu

J. Mar. Sci. Eng. 2025, 13(11), 2086; https://doi.org/10.3390/jmse13112086 - 1 Nov 2025

We propose a complexity-aware extension of the Course–Speed (CS) model that integrates an AIS-derived Traffic Complexity Index (TCI) based on change in speed (ΔV) and course (Δθ) to quantify maneuvering complexity in nonlinear crossing waters. The framework consists of: [...] Read more.

We propose a complexity-aware extension of the Course–Speed (CS) model that integrates an AIS-derived Traffic Complexity Index (TCI) based on change in speed (ΔV) and course (Δθ) to quantify maneuvering complexity in nonlinear crossing waters. The framework consists of: (i) data preprocessing and gating to ensure navigationally valid AIS samples; (ii) CS index computation using distribution-aware statistics; (iii) TCI estimation from variability in speed and course along intersecting flows; and (iv) an integrated CS–TCI for interpretable mapping and ranking. Using one year of AIS data from a high-density crossing area near the Korean coast, we show that the integrated index reveals crossing hotspots and small-vessel maneuvering burdens that are not captured by spatial regularity metrics alone. The results remain robust across reasonable parameter ranges (e.g., speed filter and σ-based weighting), and they align with operational observations in vessel traffic services (VTS). The proposed CS–TCI offers actionable decision support for port and coastal operations by jointly reflecting traffic smoothness and complexity; it can complement collision-risk screening and efficiency-oriented planning (e.g., energy and emission considerations). The approach is readily transferable to other crossing waterways and can be integrated with real-time monitoring to prioritize control actions in complex marine traffic environments. Full article

(This article belongs to the Section Ocean Engineering)

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19 pages, 2835 KB

Open AccessArticle

Description and Phylogenetic Analysis of Two New Species, Trissonchulus sinensis sp. nov. and Metachromadora sinica sp. nov. (Nematoda) from the South China Sea

by Jing Sun, Ruobing Bai and Yong Huang

J. Mar. Sci. Eng. 2025, 13(11), 2085; https://doi.org/10.3390/jmse13112085 - 1 Nov 2025

Two new species of free-living marine nematodes from mangrove wetlands of Beihai, Guangxi province in China, are described and illustrated. Trissonchulus sinensis sp. nov. is characterized by a head continuous with the body, an amphidial fovea pouch-shaped, pharynx expanding gradually but not forming [...] Read more.

Two new species of free-living marine nematodes from mangrove wetlands of Beihai, Guangxi province in China, are described and illustrated. Trissonchulus sinensis sp. nov. is characterized by a head continuous with the body, an amphidial fovea pouch-shaped, pharynx expanding gradually but not forming a posterior bulb, spicules sclerotized, blade-shaped, slightly curved ventrally, proximal part enlarged with a prominent central septum, posterior part slender and handle-like; gubernaculum small, composed of two distally connected sheet-like structures with tooth-like ends, and lacking apophysis. Metachromadora sinica sp. nov. is characterized by a cuticle that is finely annulated, labial sensilla papilliform, cephalic setae four in number, amphideal fovea loop-shaped, exhibiting a double-contoured appearance, pharyngeal bulb well-developed, internal cuticular lumen tripartite, lateral epidermal ridges present, spicules slender with an enlarged capitulum, gubernaculum boat-shaped, precloacal supplements absent, tail conical with two setose protuberances, three pairs of subventral preanal setae, and a pair of papillae situated anterior to the anus. Nearly full-length SSU sequences and D2-D3 of LSU sequences are provided for the new species. Phylogenetic analysis of SSU provided support for the current classification status of the two new species. In the SSU phylogenetic tree, the family Ironidae was recovered as a separate monophyletic clade. However, the phylogenetic relationships within the family Desmodoridae were complicated, and the subfamilies Desmodorinae and Spiriniinae were polyphyletic. A comprehensive taxonomic approach combining morphological observations and molecular phylogeny construction would be particularly valuable in a more robust nematode taxonomy. Full article

(This article belongs to the Section Marine Biology)

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13 pages, 1282 KB

Open AccessArticle

Multi-Objective Optimization for PTO Damping of Floating Offshore Wind–Wave Hybrid Systems Under Extreme Conditions

by Suchun Yang, Shuo Zhang, Fan Zhang, Xianzhi Wang and Dongsheng Qiao

J. Mar. Sci. Eng. 2025, 13(11), 2084; https://doi.org/10.3390/jmse13112084 - 1 Nov 2025

Floating offshore wind–wave hybrid systems, as a novel structural form integrating floating wind turbine foundations and WECs, can effectively enhance the efficiency of renewable energy utilization when properly designed. A numerical model is established to investigate the dynamic responses of a wind–wave hybrid [...] Read more.

Floating offshore wind–wave hybrid systems, as a novel structural form integrating floating wind turbine foundations and WECs, can effectively enhance the efficiency of renewable energy utilization when properly designed. A numerical model is established to investigate the dynamic responses of a wind–wave hybrid system comprising a semi-submersible FOWT and PA wave energy converters. The optimal damping values of the PTO system for the wind–wave hybrid system are determined based on an NSGA-II. Subsequently, a comparative analysis of dynamic responses is carried out for the PTO system with different states: latching, fully released, and optimal damping. Under the same extreme irregular wave conditions, the pitch motion of the FOWT with optimal damping is reduced to 71% and 50% compared to the latching and fully released states, respectively. The maximum mooring line tension in the optimal damping state is similar to that in the fully released state, but nearly 40% lower than in the latching state. This optimal control strategy not only sustains power generation but also enhances structural stability and efficiency compared to traditional survival strategies, offering a promising approach for cost-effective offshore wind and wave energy utilization. Full article

(This article belongs to the Special Issue Optimized Design of Offshore Wind Turbines)

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