Journal of Marine Science and Engineering

19 pages, 20423 KB

Open AccessArticle

Spherical Gravity Inversion Reveals Crustal Structure and Microplate Tectonics in the Caribbean Sea

by Feiyu Zhao, Chunrong Zhan, Junling Pei, Yumin Chen, Mengxue Dai, Bin Hu, Lifu Hou, Zixi Ning and Rongrong Xu

J. Mar. Sci. Eng. 2026, 14(1), 109; https://doi.org/10.3390/jmse14010109 - 5 Jan 2026

Viewed by 474

Abstract

As a convergent zone of multiple plates, the Caribbean Sea and its adjacent areas have experienced a complex tectonic evolution process and are characterized by prominent microplate development. This region provides a natural laboratory for studying the formation mechanism of continental margins, the [...] Read more.

As a convergent zone of multiple plates, the Caribbean Sea and its adjacent areas have experienced a complex tectonic evolution process and are characterized by prominent microplate development. This region provides a natural laboratory for studying the formation mechanism of continental margins, the evolution process of ocean basins, and the tectonics of microplates. However, the crustal structure and microplate tectonics in this region remain unclear due to limitations of conventional planar gravity inversion methods, which neglect the Earth’s curvature in large-scale areas, as well as the uneven coverage of regional seismic networks. To precisely delineate the crustal structure and microplate boundaries in the Caribbean Sea region, this study employs a nonlinear gravity inversion method based on a spherical coordinate system. By utilizing GOCO06s satellite gravity data, ETOPO1 topographic data, and the CRUST1.0 crustal model, we performed inversion calculations for the Moho depth in the Caribbean Sea and its adjacent regions and systematically analyzed the crustal structure and microplate tectonic characteristics of the region. The results indicate that the gravity inversion method in the spherical coordinate system has good applicability in complex tectonic regions. The inversion results show that the Moho depth in the study area generally presents a spatial distribution pattern of “shallow in the central part and deep in the surrounding areas”. Among them, the Moho depth is the largest (>39 km) at the junction of the Northern Andes and the South American Plate, while it is relatively shallow (<6 km) in regions such as the Cayman Trough, the Colombian Basin, and the Venezuelan Basin. Based on the Moho undulation, gravity anomalies, and topographic features, this study divides the Caribbean Sea and its adjacent areas into 22 microplates and identifies three types of microplates, including oceanic, continental, and accretionary. Among them, there are 10 microplates with oceanic crust, 6 with continental crust, and 5 with accretionary crust, while the Northern Andes Microplate exhibits a mixed type. The crustal structure characteristics revealed in this study support the Pacific origin model of the Caribbean Plate, indicating that most of the plate is a component of the ancient Pacific Plate with standard oceanic crust properties. Locally, the Caribbean Large Igneous Province developed due to hotspot activity, and the subsequent eastward drift and tectonic wedging processes collectively shaped the complex modern microplate tectonic framework of this region. This study not only reveals the variation pattern of crustal thickness in the Caribbean Sea region but also provides new geophysical evidence for understanding the lithospheric structure and microplate evolution mechanism in the area. Full article

(This article belongs to the Special Issue Advances in Ocean Plate Motion and Seismic Research)

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17 pages, 14002 KB

Open AccessArticle

Modeling of High-Precision Sea Surface Geomagnetic Field in the Northern South China Sea Based on PSO-BP Neural Network

by Hongjie Chen, Guiqian Wu, Haopeng Chen, Chuang Xu and Chunhong Wu

J. Mar. Sci. Eng. 2026, 14(1), 108; https://doi.org/10.3390/jmse14010108 - 5 Jan 2026

Viewed by 387

Abstract

In existing regional geomagnetic field modeling, the smoothness of basic functions and the insufficient data constraints in marginal regions lead to the omission of detail features and extrapolation oscillations. To address these limitations and develop a high-precision marine regional geomagnetic field model, we [...] Read more.

In existing regional geomagnetic field modeling, the smoothness of basic functions and the insufficient data constraints in marginal regions lead to the omission of detail features and extrapolation oscillations. To address these limitations and develop a high-precision marine regional geomagnetic field model, we develop a back propagation neural network (BPNN) method enhanced by particle swarm optimization (PSO). The PSO-BPNN method has the ability of adaptive learning and could extract local features. By combining the magnetic field data measured by ships with the previous model data, a high-precision geomagnetic field model of the northern South China Sea (SCS) is developed. The fitting error of the PSO-BPNN model is 18.05 nT, which is 16% and 20.1% lower than those of the traditional Legendre Polynomial (LP) and Taylor Polynomial (TP) models, respectively. The proposed PSO-BPNN model demonstrates superior robustness and higher accuracy, while retaining more magnetic signals of small geological bodies. Full article

(This article belongs to the Section Physical Oceanography)

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27 pages, 3321 KB

Open AccessArticle

An Anchorage Decision Method for the Autonomous Cargo Ship Based on Multi-Level Guidance

by Wei Zhu, Junmin Mou, Yixiong He, Xingya Zhao, Guoliang Li and Bing Wang

J. Mar. Sci. Eng. 2026, 14(1), 107; https://doi.org/10.3390/jmse14010107 - 5 Jan 2026

Viewed by 298

Abstract

The advancement of autonomous cargo ships requires dependable anchoring operations, which present significant challenges stemming from reduced maneuverability at low speeds and vulnerability to anchorage disturbances. This study systematically investigates these operational constraints by developing anchoring decision-making methodologies. Safety anchorage areas were quantitatively [...] Read more.

The advancement of autonomous cargo ships requires dependable anchoring operations, which present significant challenges stemming from reduced maneuverability at low speeds and vulnerability to anchorage disturbances. This study systematically investigates these operational constraints by developing anchoring decision-making methodologies. Safety anchorage areas were quantitatively defined through integration of ship specifications and environmental parameters. An available anchor position identification method based on grid theory, integrated with an anchorage allocation mechanism to determine optimal anchorage selection, was employed. A multi-level guided anchoring trajectory planning algorithm was developed through practical anchoring. This algorithm was designed to facilitate the scientific calculation of turning and stopping guidance points, with the objective of guiding a cargo ship to navigate towards the designated anchorage while maintaining specified orientation. An integrated autonomous anchoring system was established, encompassing perception, decision-making, planning, and control modules. System validation through digital simulations demonstrated robust performance under complex sea conditions. This study establishes theoretical foundations and technical frameworks for enhancing autonomous decision-making and safety control capabilities of intelligent ships during anchoring operations. Full article

(This article belongs to the Special Issue Advancements in Maritime Safety and Risk Assessment)

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19 pages, 2688 KB

Open AccessArticle

Framework for the Development of a Process Digital Twin in Shipbuilding: A Case Study in a Robotized Minor Pre-Assembly Workstation

by Ángel Sánchez-Fernández, Elena-Denisa Vlad-Voinea, Javier Pernas-Álvarez, Diego Crespo-Pereira, Belén Sañudo-Costoya and Adolfo Lamas-Rodríguez

J. Mar. Sci. Eng. 2026, 14(1), 106; https://doi.org/10.3390/jmse14010106 - 5 Jan 2026

Viewed by 671

Abstract

This article proposes a framework for the development of process digital twins (DTs) in the shipbuilding sector, based on the ISO 23247 standard and structured around the achievement of three levels of digital maturity. The framework is demonstrated through a real pilot cell [...] Read more.

This article proposes a framework for the development of process digital twins (DTs) in the shipbuilding sector, based on the ISO 23247 standard and structured around the achievement of three levels of digital maturity. The framework is demonstrated through a real pilot cell developed at the Innovation and Robotics Center of NAVANTIA—Ferrol shipyard, incorporating various cutting-edge technologies such as robotics, artificial intelligence, automated welding, computer vision, visual inspection, and autonomous vehicles for the manufacturing of minor pre-assembly components. Additionally, the study highlights the crucial role of discrete event simulation (DES) in adapting traditional methodologies to meet the requirements of Process digital twins. By addressing these challenges, the research contributes to bridging the gap in the current state of the art regarding the development and implementation of Process digital twins in the naval sector. Full article

(This article belongs to the Special Issue Artificial Intelligence Technology and Application in Marine Science and Engineering)

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26 pages, 1160 KB

Open AccessArticle

Identifying the Importance of Key Performance Indicators for Enhanced Maritime Decision-Making to Avoid Navigational Accidents

by Antanas Markauskas and Vytautas Paulauskas

J. Mar. Sci. Eng. 2026, 14(1), 105; https://doi.org/10.3390/jmse14010105 - 5 Jan 2026

Viewed by 508

Abstract

Despite ongoing advances in maritime safety research, ship accidents persist, with significant consequences for human life, marine ecosystems, and port operations. Because many accidents occur in or near ports, assessing a vessel’s ability to enter or depart safely remains critical. Although ports apply [...] Read more.

Despite ongoing advances in maritime safety research, ship accidents persist, with significant consequences for human life, marine ecosystems, and port operations. Because many accidents occur in or near ports, assessing a vessel’s ability to enter or depart safely remains critical. Although ports apply local navigational rules, safety criteria could be strengthened by adopting more adaptive and data-informed approaches. This study presents a mathematical framework that links Key Performance Indicators (KPIs) to a Ship Risk Profile (SRP) for collision/contact/grounding risk indication. Expert-based KPI importance weights were derived using the Average Rank Transformation into Weight method in linear (ARTIW-L) and nonlinear (ARTIW-N) forms and aggregated into a nominal SRP. Using routinely monitored KPIs largely drawn from the Baltic and International Maritime Council and Port State Control/flag-related measures, the results indicate that critical equipment and systems failures and human/organisational factors—particularly occupational health and safety and human resource management deficiencies—are the most influential contributors to the normalised accident-risk index. The proposed framework provides port authorities and maritime stakeholders with an interpretable basis for more proactive risk-informed decision-making and targeted safety improvements. Full article

(This article belongs to the Special Issue Advancements in Maritime Safety and Risk Assessment)

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21 pages, 4796 KB

Open AccessArticle

Experimental and Theoretical Study on the Stability of Submarine Cable Covered by Articulated Concrete Mattresses on Flat Hard Seabed Under the Action of Currents

by Ke Chen, Huakun Wang, Chiyuan Xu, Dawei Guan, Guokai Yuan, Chengyu Liu, Hongqing Wang and Can Zheng

J. Mar. Sci. Eng. 2026, 14(1), 104; https://doi.org/10.3390/jmse14010104 - 5 Jan 2026

Viewed by 424

Abstract

The safe and stable operation of submarine cables is a critical issue in offshore wind power engineering. This study presents an experimental and theoretical study on the stability of submarine cable protected by a sleeve (SCPS) with Articulated Concrete Mattresses (ACMs) protection on [...] Read more.

The safe and stable operation of submarine cables is a critical issue in offshore wind power engineering. This study presents an experimental and theoretical study on the stability of submarine cable protected by a sleeve (SCPS) with Articulated Concrete Mattresses (ACMs) protection on a flat hard seabed under current conditions. The instability modes of the SCPS–ACMs were identified, and the effects of the number of spans, cover spacing, and ACMs length on the critical instability velocity were investigated. The experimental results indicate that the primary instability mode of the SCPS–ACMs is the overall slip mode. An increase in cover spacing enlarges the exposure scale of the SCPS in the flow environment, thereby reducing the critical velocity. Employing at least two spans effectively mitigates the boundary effect induced by the flow past the SCPS at its ends, thus ensuring the reliability of the experimental model. The critical velocity is fundamentally determined by the dimensionless parameter—the ACMs coverage ratio (incorporating both the ACMs length and cover spacing). Based on the experimental results and force analysis, a theoretical equation reflecting the intrinsic relationship between the ACMs’ cover spacing and critical velocity was established. Key parameters in the equation, such as the friction coefficient, hydrodynamic coefficients (including the lift coefficient and drag coefficient), and weight distribution coefficients, were determined. Finally, the theoretical results were validated against the experimental data, showing a good agreement and verifying the reliability of the theoretical formula. The findings of this research can provide crucial support for the optimal design of ACMs protection schemes for submarine cables on the hard seabed. Full article

(This article belongs to the Special Issue Celebrating the 110th Anniversary of Hohai University: Invited Papers for Coastal Engineering)

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18 pages, 7623 KB

Open AccessReview

Natural Fracturing in Marine Shales: From Qualitative to Quantitative Approaches

by Chen Zhang, Yuhan Huang, Huadong Chen and Zongquan Hu

J. Mar. Sci. Eng. 2026, 14(1), 99; https://doi.org/10.3390/jmse14010099 - 4 Jan 2026

Viewed by 495

Abstract

Natural fractures in marine shales are crucial storage spaces and migration pathways for oil and gas, making the study of their formation mechanisms and distribution patterns essential for hydrocarbon exploration and development. This review systematically evaluates the progress in natural fracture studies, transitioning [...] Read more.

Natural fractures in marine shales are crucial storage spaces and migration pathways for oil and gas, making the study of their formation mechanisms and distribution patterns essential for hydrocarbon exploration and development. This review systematically evaluates the progress in natural fracture studies, transitioning from qualitative to quantitative approaches, with a focus on the genetic mechanisms, distribution patterns, and methodological advancements of fracture types. The review finds that: (1) Integrated “geological-geophysical-dynamic” analyses significantly improve the prediction accuracy of tectonic fracture networks compared to traditional stress-field models. Bedding-parallel fracture development is primarily controlled by the interplay between diagenetic evolution and in situ stress, with their critical opening conditions now being quantifiable; (2) Crucially, the application of micro-scale in situ techniques (e.g., Laser Ablation Inductively Coupled PlasmaMass Spectrometer, laser C-O isotope analysis, carbonate U-Pb dating) has successfully decoded the geochemical signatures and absolute timing of fracture fillings, revealing multiple episodes of fluid activity directly tied to hydrocarbon migration. (3) The combined application of multiple techniques holds promise for deepening the understanding of the coupling mechanisms between fractures. The combined application of these techniques provides a robust framework for deciphering the coupling mechanisms between fracture dynamic evolution and hydrocarbon migration, offering critical insights for future exploration. Full article

(This article belongs to the Topic Formation Mechanism and Quantitative Evaluation of Deep to Ultra-Deep High-Quality Reservoirs)

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16 pages, 4374 KB

Open AccessArticle

Development and Laboratory Validation of a Real-Time Quantitative PCR Assay for Rapid Detection and Quantification of Heterocapsa bohaiensis

by Mengfan Cai, Ruijia Jing, Yiwen Zhang and Jingjing Zhan

J. Mar. Sci. Eng. 2026, 14(1), 98; https://doi.org/10.3390/jmse14010098 - 4 Jan 2026

Viewed by 265

Abstract

Heterocapsa bohaiensis is an emerging harmful dinoflagellate increasingly reported from coastal regions of the Pacific. However, an available molecular assay offering rapid and sensitive detection is still lacking. This study developed a SYBR Green real-time quantitative PCR (qPCR) assay for the identification and [...] Read more.

Heterocapsa bohaiensis is an emerging harmful dinoflagellate increasingly reported from coastal regions of the Pacific. However, an available molecular assay offering rapid and sensitive detection is still lacking. This study developed a SYBR Green real-time quantitative PCR (qPCR) assay for the identification and quantification of H. bohaiensis. Species-specific primers (F: 5′-CCATCGAACCAGAACTCCGT-3′; R: 5′-AGTGTAGTGCACCGCATGTC-3′) were designed and the assay was optimized and evaluated using laboratory cultures for specificity, sensitivity, and quantitative performance. Primer screening and melt-curve analysis confirmed that the selected primer pair produced a single, specific amplification peak for H. bohaiensis, with no cross-reactivity observed in non-target species (Chlorella pyrenoidosa, Phaeocystis globosa, Skeletonema costatum, Alexandrium tamarense) or mixed algal communities. The standard curve displayed strong linearity (R² = 0.9868) and a high amplification efficiency (102.5%). The limit of detection (LOD) was approximately 2–3 cells per reaction, as determined from 24 replicates of 5-cell equivalents and verified at ~2.7-cell equivalents. This sensitivity was comparable to or exceeded that reported for assays targeting other HABs forming dinoflagellates. Quantitative results derived from the qPCR assay closely matched microscopic cell counts, with a relative error of 10.79%, falling within the acceptable threshold for phytoplankton surveys. In summary, this study established and validates a species-specific qPCR assay for H. bohaiensis under controlled laboratory conditions. The method shows strong potential for incorporation into HAB monitoring programs, early-warning systems, and future ecological investigations of this emerging species. Full article

(This article belongs to the Topic Recent Advances in Harmful Algal Blooms in Freshwater and Marine Systems)

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33 pages, 21972 KB

Open AccessArticle

Wave Attenuation Performance of a Floating Breakwater Integrated with Flexible Wave-Dissipating Structures

by Xianlin Jia, Su Guo, Kangjie Wang, Sai Fu, Xintong Yu and Wei Peng

J. Mar. Sci. Eng. 2026, 14(1), 97; https://doi.org/10.3390/jmse14010097 - 4 Jan 2026

Viewed by 399

Abstract

This study develops a two-dimensional numerical model to investigate the hydrodynamic performance of a floating breakwater coupled with flexible wave-dissipating structures (FWDS). The model integrates the immersed boundary method with a finite element structural solver, enabling accurate simulation of fluid–structure interactions under wave [...] Read more.

This study develops a two-dimensional numerical model to investigate the hydrodynamic performance of a floating breakwater coupled with flexible wave-dissipating structures (FWDS). The model integrates the immersed boundary method with a finite element structural solver, enabling accurate simulation of fluid–structure interactions under wave excitation. Validation against benchmark cases, including cantilever beam deflection and flexible vegetation under waves, confirms the model’s reliability. Parametric analyses were conducted to examine the influence of the elastic modulus and height of the FWDS on wave attenuation efficiency. Results show that structural flexibility plays a crucial role in modifying wave reflection, transmission, and dissipation characteristics. A lower elastic modulus enhances energy dissipation through large deformation and vortex generation, while higher stiffness promotes reflection with reduced dissipation. Increasing the height of the FWDS improves overall wave attenuation but exhibits diminishing returns for long-period waves. The findings highlight that optimized flexibility and geometry can effectively enhance the energy-dissipating capacity of floating breakwaters. This study provides a theoretical basis for the design and optimization of hybrid floating breakwaters integrating flexible elements for coastal and offshore wave energy mitigation. Full article

(This article belongs to the Special Issue Numerical Analysis and Modeling of Floating Structures)

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25 pages, 13731 KB

Open AccessArticle

Improved Integral Sliding Mode Control for AUV Trajectory Tracking Based on Deep Reinforcement Learning

by Ruizhi Zhang, Zongsheng Wang, Hongyu Li, Weizhuang Ma, Xiaodong Liu and Jia Liu

J. Mar. Sci. Eng. 2026, 14(1), 103; https://doi.org/10.3390/jmse14010103 - 4 Jan 2026

Viewed by 341

Abstract

Trajectory tracking control of autonomous underwater vehicles (AUVs) faces challenges in complex nearshore environments due to model uncertainties and external environmental disturbances. Traditional control methods often rely on expert knowledge and manual parameter tuning, which limit the adaptability of AUVs to structural variations [...] Read more.

Trajectory tracking control of autonomous underwater vehicles (AUVs) faces challenges in complex nearshore environments due to model uncertainties and external environmental disturbances. Traditional control methods often rely on expert knowledge and manual parameter tuning, which limit the adaptability of AUVs to structural variations and changing operating conditions. Moreover, inappropriate parameter selection in conventional sliding mode control may induce high-frequency chattering, degrading control accuracy and operational efficiency. To address these issues, this paper proposes an improved integral sliding mode control (IISMC) strategy integrated with deep reinforcement learning (DRL). In the proposed framework, DRL is employed to adaptively tune key controller parameters, including the sliding surface coefficients and reaching law gains, while preserving the analytical structure of the IISMC scheme. This adaptive tuning mechanism effectively suppresses chattering and enhances robustness against uncertainties and disturbances. Numerical simulation results demonstrate that the proposed DRL-assisted IISMC method achieves improved disturbance rejection capability, higher trajectory tracking accuracy, and smoother control performance compared with conventional sliding mode control (SMC) approaches under identical operating conditions. Full article

(This article belongs to the Section Ocean Engineering)

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31 pages, 7259 KB

Open AccessArticle

Fixed-Time Robust Path-Following Control for Underwater Snake Robots with Extended State Observer and Event-Triggering Mechanism

by Qingqing Shi, Jing Liu and Xiao Han

J. Mar. Sci. Eng. 2026, 14(1), 102; https://doi.org/10.3390/jmse14010102 - 4 Jan 2026

Viewed by 287

Abstract

Aiming at the robust path-following control problem of underwater snake robot (USR) systems subject to modeling uncertainties and time-varying external disturbances, this paper proposes a robust path-following control algorithm based on a fast fixed-time extended state observer (FTESO). First, a fixed-time stability framework [...] Read more.

Aiming at the robust path-following control problem of underwater snake robot (USR) systems subject to modeling uncertainties and time-varying external disturbances, this paper proposes a robust path-following control algorithm based on a fast fixed-time extended state observer (FTESO). First, a fixed-time stability framework with a shorter settling time than existing systems is introduced, and a novel extended state observation system based on the fixed-time stability framework is constructed. Subsequently, by combining the disturbance estimates from the proposed observer with a nonsingular fast fixed-time path-following controller, a robust fixed-time path-following controller is developed. This control strategy incorporates a dynamic event-triggering mechanism, which accomplishes the path-following task while conserving computational resources. The fixed-time convergence of the closed-loop control system is rigorously proved using Lyapunov stability theory. Furthermore, a novel head joint suppression function is designed to reduce the probability of losing the tracking target. Simulation results demonstrate that, compared with conventional control methods, the proposed approach exhibits superior tracking performance and enhanced disturbance rejection capability in complex underwater environments. Full article

(This article belongs to the Section Ocean Engineering)

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17 pages, 3971 KB

Open AccessArticle

A Hybrid LSTM-UDP Model for Real-Time Motion Prediction and Transmission of a 10,000-TEU Container Ship

by Qizhen Yu, Xiyu Liao, Jun Xu, Yicheng Lian and Zhanyang Chen

J. Mar. Sci. Eng. 2026, 14(1), 101; https://doi.org/10.3390/jmse14010101 - 4 Jan 2026

Viewed by 280

Abstract

For various specialized maritime operations, predicting the future motion responses of structures is essential. For example, ship-borne helicopter landings require a predictable time frame of 6 to 8 s, while avoiding risks during ship navigation in waves calls for a 15-s prediction window. [...] Read more.

For various specialized maritime operations, predicting the future motion responses of structures is essential. For example, ship-borne helicopter landings require a predictable time frame of 6 to 8 s, while avoiding risks during ship navigation in waves calls for a 15-s prediction window. In this work, a real-time prediction method of future ship motions using the Long Short-Term Memory Neural Network (LSTM) is introduced. A direct multi-step output approach is used to continually update with the most recent data for prediction. This method can model the nonlinear time series of ship motions leveraging LSTM’s capabilities, and User Datagram Protocol (UDP) is used between devices to achieve low-latency data transfer. The performance of this framework is demonstrated and validated through multi-degree-of-freedom motion simulations of a 10,000-TEU container ship model in random waves. The results show that all the values of R² in the four cases are greater than 0.7, and the maximum and minimum values of R² correspond to predictable time scales of 6 s in Case I and 10 s in Case IV, respectively. This indicates that combining LSTM neural networks with the UDP protocol allows for accurate and efficient predictions and data transmission, and the calculating accuracy of the method decreases as the predictable time scale increases. Full article

(This article belongs to the Special Issue Intelligent Solutions for Marine Operations)

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17 pages, 2509 KB

Open AccessArticle

Parametric Study on the Dynamic Response of a Barge-Jacket Coupled System During Transportation

by Ruilong Shi, Xiaolan Zhang, Yanhui Xia, Ben He, Zhihong Zhang and Jianhua Zhang

J. Mar. Sci. Eng. 2026, 14(1), 100; https://doi.org/10.3390/jmse14010100 - 4 Jan 2026

Viewed by 335

Abstract

As offshore wind farms expand into deeper waters, the safe transportation of large jacket foundations presents a significant engineering challenge. This study utilizes the SESAM 2022 software suite, based on three-dimensional potential flow theory, to conduct a coupled numerical simulation and parametric analysis [...] Read more.

As offshore wind farms expand into deeper waters, the safe transportation of large jacket foundations presents a significant engineering challenge. This study utilizes the SESAM 2022 software suite, based on three-dimensional potential flow theory, to conduct a coupled numerical simulation and parametric analysis of a barge-jacket system. Finite element models of the barge and jacket are established, with mesh convergence verified. The influences of key parameters including wave frequencies (0.4–1.6 rad/s), wave directions (0–180°), forward speeds (0–8 knots) and jacket arrangement (vertical/horizontal) on the six degrees of freedom (6-DOF) dynamic responses of the coupled system are systematically investigated. Based on the observed response characteristics, optimized transportation configurations and practical engineering recommendations are proposed. The findings consolidate previous scattered parametric results into a single, repeatable SESAM-based benchmark data set, offering a reference against which future nonlinear or time-domain models can be validated. Furthermore, this work establishes a systematic parametric basis and offers practical guidance for assessing the safety of offshore wind turbine (OWT) foundation transportation in deep-water environments. Full article

(This article belongs to the Special Issue Advanced Studies in Marine Structures)

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16 pages, 2700 KB

Open AccessArticle

Spatio-Temporal Distribution of Setipinna taty Resources Using a Zero-Inflated Model in the Offshore Waters of Southern Zhejiang, China

by Xiaoxue Liu, Wen Ma, Jin Ma, Chunxia Gao, Weifeng Chen and Jing Zhao

J. Mar. Sci. Eng. 2026, 14(1), 96; https://doi.org/10.3390/jmse14010096 - 3 Jan 2026

Viewed by 294

Abstract

Effective fishery management in coastal waters requires accurate assessments of species–environment relationships, particularly in data-rich but zero-inflated contexts (i.e., datasets with an excess of zero catches). Here, we used fishery-independent trawl survey data collected from 2018 to 2019 in the offshore waters of [...] Read more.

Effective fishery management in coastal waters requires accurate assessments of species–environment relationships, particularly in data-rich but zero-inflated contexts (i.e., datasets with an excess of zero catches). Here, we used fishery-independent trawl survey data collected from 2018 to 2019 in the offshore waters of southern Zhejiang Province of China to investigate the spatio-temporal distribution of Setipinna taty (scaly hairfin anchovy) and its environmental determinants. Given the high frequency of zero catches, we fitted both zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) models and selected the best-performing approach using the Akaike information criterion (AIC). Cross-validation indicated that the ZINB model (RMSE: 199.1, R²; 0.25) outperformed ZIP model (RMSE: 239.4, R²; 0.23). Temperature, depth, and salinity were key predictors of S. taty abundance, which generally occurred at depths of 20–40 m and salinities of 26–34 psu. We then applied the optimal ZINB model to predict S. taty distributions in spring, summer, and autumn of 2020. The predictions indicated a summer peak in abundance and a nearshore-to-offshore decreasing gradient, and were broadly consistent with the spatial distribution trends observed in the 2020 survey data. The highest predicted densities were located in nearshore areas off Wenzhou and Taizhou, west of 122° E. By clarifying the key environmental factors shaping S. taty distribution and applying zero-inflated count models to account for an excess of zero catches, which occur more frequently than expected under standard negative binomial models, this study provides an improved basis for effective conservation and sustainable utilization of S. taty resources in the southern offshore waters of Zhejiang; nevertheless, predictive performance could be further improved by incorporating additional environmental and biotic covariates together with extended spatio-temporal data. Full article

(This article belongs to the Section Marine Ecology)

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43 pages, 9757 KB

Open AccessArticle

Rayleigh Quotient Eigenvalue-Based Array Beamforming Optimization for Targeted Angular Energy Concentration in Underwater Acoustic Energy Transfer

by Zhongzheng Liu, Tao Zhang, Yuhang Li, Xin Zhao, Yulong Xing, Nahid Mahmud and Yanzhang Geng

J. Mar. Sci. Eng. 2026, 14(1), 95; https://doi.org/10.3390/jmse14010095 - 3 Jan 2026

Viewed by 291

Abstract

Underwater acoustic energy transmission (UAET) is critical for sustaining long-term operations of underwater platforms, but its efficiency is constrained by the limited aperture of underwater receivers—requiring acoustic energy to be concentrated within a pre-defined target angular domain. Existing array-weighting methods face inherent limitations: [...] Read more.

Underwater acoustic energy transmission (UAET) is critical for sustaining long-term operations of underwater platforms, but its efficiency is constrained by the limited aperture of underwater receivers—requiring acoustic energy to be concentrated within a pre-defined target angular domain. Existing array-weighting methods face inherent limitations: traditional window-based techniques optimize mainlobe–sidelobe trade-offs rather than target-specific energy concentration, while intelligent algorithms suffer from high computational cost, quasi-optimality, and poor reproducibility. To address these gaps, this study proposes an array beam energy aggregation optimization method based on Rayleigh quotient eigenvalues for UAET. First, a rigorous mathematical model of the acoustic energy concentration problem was established: by defining a target-domain energy operator matrix

R_{Θ}

with a Toeplitz–sinc structure (Hermitian positive definite), the energy-focusing problem was transformed into a tractable linear algebra problem. Second, the optimization objective of maximizing target-domain energy was formulated as a generalized Rayleigh quotient maximization problem, where the optimal amplitude weights correspond to the eigenvector of the maximum eigenvalue of

R_{Θ}

—solved via Cholesky whitening and eigenvalue decomposition to ensure theoretical optimality and low computational complexity. Comprehensive validations were conducted via simulations and underwater physical experiments. Simulations on 1D uniform linear arrays and 2D 4-layer circular ring arrays showed that the proposed method outperformed traditional weighting methods and PSO in target angular energy concentration: for the 16-element linear array, its energy radiation efficiency in the 30° domain was 14% higher than classical methods (Blackman weighting). Underwater physical tests further confirmed its superiority: for the 4-layer circular ring array at 1 m, the acoustic energy efficiency in the 30° target domain reached 21.5% higher than Blackman weighting. Additionally, the method exhibited strong adaptivity (dynamic weight adjustment with target angular width) and scalability (performance improvement with array size), meeting UAET’s real-time and reliability requirements. This work provides a theoretically optimal and engineering-feasible solution for directional acoustic energy transfer in underwater environments, offering valuable insights for UAET system design. Full article

(This article belongs to the Section Ocean Engineering)

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18 pages, 20589 KB

Open AccessArticle

Parametrization of Seabed Liquefaction for Nonlinear Waves

by Mantang Zeng, Titi Sui, Musheng Yang and Li Peng

J. Mar. Sci. Eng. 2026, 14(1), 94; https://doi.org/10.3390/jmse14010094 - 3 Jan 2026

Viewed by 243

Abstract

In actual marine environments, significant nonlinear changes occur during wave propagation toward the nearshore, resulting in noticeable wave asymmetry. This leads to substantial differences in seabed response and liquefaction compared to conditions under linear waves. This study employs numerical simulations to investigate the [...] Read more.

In actual marine environments, significant nonlinear changes occur during wave propagation toward the nearshore, resulting in noticeable wave asymmetry. This leads to substantial differences in seabed response and liquefaction compared to conditions under linear waves. This study employs numerical simulations to investigate the liquefaction depth of the seabed under nonlinear wave loading. Building upon existing liquefaction prediction formulas, a more widely applicable seabed liquefaction prediction formula is derived through dimensional analysis and the least squares method. The proposed formula provides a better fit to the numerically simulated values and significantly reduces prediction errors. Based on waveform analysis, a parametric method is established. By integrating the liquefaction prediction formula, this method allows rapid estimation of the maximum seabed liquefaction depth on a sloped beach under random wave action. The calculated results show that the prediction formula closely matches the numerical simulation results. Full article

(This article belongs to the Section Coastal Engineering)

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18 pages, 9766 KB

Open AccessArticle

The Influence of Shell-Sand Mixing on the Dynamic Response of the Seabed Foundation in Front of a Slope Breakwater

by Titi Sui, Tianyu Lv, Musheng Yang and Hang Zhu

J. Mar. Sci. Eng. 2026, 14(1), 93; https://doi.org/10.3390/jmse14010093 - 3 Jan 2026

Viewed by 318

Abstract

Shell-sand mixing, as a novel technique for coastal protection and seabed improvement, holds broad application prospects. However, the underlying mechanism of its influence on the wave-induced dynamic response of the seabed beneath slope breakwaters remains unclear. In this study, physical model experiments were [...] Read more.

Shell-sand mixing, as a novel technique for coastal protection and seabed improvement, holds broad application prospects. However, the underlying mechanism of its influence on the wave-induced dynamic response of the seabed beneath slope breakwaters remains unclear. In this study, physical model experiments were conducted in a wave flume to analyze the effects of shell-sand mixing on the amplitude of pore water pressure in front of the breakwater and the vertical attenuation coefficient of the seabed. The results indicate that the amplitude of pore water pressure decreased by up to 46.5% after the application of shell-sand mixing. As the mixing ratio of shell-sand increased, the vertical attenuation coefficient of pore pressure initially rose and then stabilized. When the shell-sand mixing ratio reached 15%, the average vertical attenuation coefficient of pore pressure had already stabilized. Furthermore, this paper established an empirical formula for the pore pressure response of shell-sand mixed seabed in front of slope breakwaters, applicable to sandy seabeds. The correlation coefficient

R^{2}

between the predicted values from the formula and the measured data reached 0.881. This research provides a scientific basis for the engineering application and improvement evaluation of shell-sand mixing. The study also assessed the application of shell-sand mixing technology along the West African coast, with results indicating that the Western Sahara region is the most suitable area for implementing this technique. Full article

(This article belongs to the Section Coastal Engineering)

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16 pages, 7504 KB

Open AccessArticle

Geological Characteristics and a New Simplified Method to Estimate the Long-Term Settlement of Dredger Fill in Tianjin Nangang Region

by Jinke Yuan, Zuan Pei and Jie Chen

J. Mar. Sci. Eng. 2026, 14(1), 92; https://doi.org/10.3390/jmse14010092 - 2 Jan 2026

Viewed by 366

Abstract

Long-term settlement of dredger fill presents substantial challenges to infrastructure stability, particularly in coastal areas such as Tianjin Nangang, where liquefied natural gas (LNG) pipelines are vulnerable to deformation caused by differential settlements. This study investigates the geological properties and long-term settlement characteristics [...] Read more.

Long-term settlement of dredger fill presents substantial challenges to infrastructure stability, particularly in coastal areas such as Tianjin Nangang, where liquefied natural gas (LNG) pipelines are vulnerable to deformation caused by differential settlements. This study investigates the geological properties and long-term settlement characteristics of dredger fill in the Tianjin Nangang coastal zone and develops a simplified predictive model for long-term settlement. Comprehensive laboratory analyses, including field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD) and mercury intrusion porosimetry (MIP), revealed a porous, flaky microstructure dominated by quartz and calcite, with mesopores (0.03–0.8 µm) constituting over 80% of total pore volume. A centrifuge modelling test conducted at 70 g acceleration simulated accelerated settlement behavior, demonstrating that approximately 70% of settlements occured within the initial year. The study proposes an enhanced hyperbolic model for long-term settlement prediction, which shows excellent correlation with experimental results. The findings underscore the high compressibility and low shear strength of dredger fill, highlighting the necessity for specific mitigation measures to ensure infrastructure integrity. This research establishes a simplified yet reliable methodology for settlement estimation, providing valuable practical guidance for coastal land reclamation projects. Full article

(This article belongs to the Section Coastal Engineering)

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23 pages, 58132 KB

Open AccessArticle

Integrated Rock Physics-Based Interpretation of Time-Lapse Seismic Data for Residual Oil Detection in Offshore Waterflooded Reservoirs

by Haoyuan Li, Xuri Huang, Sheng Yang, Xiaoqing Cui, Yibin Li and Ran Yang

J. Mar. Sci. Eng. 2026, 14(1), 91; https://doi.org/10.3390/jmse14010091 - 2 Jan 2026

Viewed by 292

Abstract

Accurate characterization of fluid distribution in offshore waterflooded oilfields has been challenging due to complex heterogeneity and the limitations of traditional interpretation tools, which often cannot integrate multi-scale datasets such as core samples, well logs, and seismic surveys. This study addresses these challenges [...] Read more.

Accurate characterization of fluid distribution in offshore waterflooded oilfields has been challenging due to complex heterogeneity and the limitations of traditional interpretation tools, which often cannot integrate multi-scale datasets such as core samples, well logs, and seismic surveys. This study addresses these challenges by developing an integrated interpretation workflow based on a calibrated rock physical fluid substitution model. The model, constrained by low-frequency laboratory measurements and elastic parameters from well logs, is used to assess the impact of fluid variations on core elastic properties and to ensure physical consistency across core, log, and seismic data scales. Key findings demonstrate that the calibrated model effectively detects impedance changes caused by water injection and accurately identifies remaining oil deposits. When applied to time-lapse seismic interpretation and reservoir numerical simulation, the model proves valuable for guiding infill well placement and optimizing development strategies in mature offshore reservoirs. Additionally, this approach provides a robust framework for integrating multi-source data, thereby enhancing the reliability of reservoir characterization in waterflooded wells. Full article

(This article belongs to the Topic Advanced Technology for Oil and Nature Gas Exploration)

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24 pages, 31783 KB

Open AccessArticle

Investigation of Edge Scour and Undermining Process of Conical Structure Around a Monopile

by Jinming Tu, Fan Yang, Chi Yu and Fuming Wang

J. Mar. Sci. Eng. 2026, 14(1), 90; https://doi.org/10.3390/jmse14010090 - 2 Jan 2026

Viewed by 253

Abstract

The scour protection performance of the conical structure under different slope angles, α, was investigated through numerical simulations. By solving the Navier–Stokes (N–S) equations, using the Renormalization Group (RNG) k–ε turbulence model and the Meyer-Peter and Müller (MPM) sediment transport [...] Read more.

The scour protection performance of the conical structure under different slope angles, α, was investigated through numerical simulations. By solving the Navier–Stokes (N–S) equations, using the Renormalization Group (RNG) k–ε turbulence model and the Meyer-Peter and Müller (MPM) sediment transport formula, the scour protection performance, undermining process, and the flow field around the devices were fully analyzed at different slope angles. The findings indicate that the conical scour protection provides effective protection against scour damage. As the slope angle increases, greater scour depth is observed around the structure. A critical slope angle was identified between 30° and 40°, slope angle effects are obvious below the threshold; otherwise, it minimized. Undermining is the main cause of failure of such stiff scour protection, mainly driven by flow contraction and sand sliding. Upstream undermining beneath the structure is more pronounced, while the downstream undermining is largely related to the near-bed flow separation point. The critical undermining point (CUP) is proposed based on the undermining curve to distinguish the undermining state, which is critical in scour protection and structural stability. Full article

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

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16 pages, 2799 KB

Open AccessArticle

Coupling Effect of the Bottom Type-Depth Configuration on the Sonar Detection Range in Seamount Environments

by Xiaofang Sun, Shisong Zhang, Feiyu Chen and Pingbo Wang

J. Mar. Sci. Eng. 2026, 14(1), 89; https://doi.org/10.3390/jmse14010089 - 2 Jan 2026

Viewed by 335

Abstract

Seabed topography exerts a profound influence on underwater acoustic propagation, and the coupling effect between bottom acoustic properties and the source–receiver geometric configuration remains insufficiently quantified, particularly in seamount shielding scenarios. To address this gap, in this study, the BELLHOP ray model was [...] Read more.

Seabed topography exerts a profound influence on underwater acoustic propagation, and the coupling effect between bottom acoustic properties and the source–receiver geometric configuration remains insufficiently quantified, particularly in seamount shielding scenarios. To address this gap, in this study, the BELLHOP ray model was integrated with Earth topography 1 (ETOPO1) topographic data and Hybrid Coordinate Ocean Model (HYCOM) hydrological data for seamounts east of Taiwan. Transmission loss (TL) of 300 Hz sound waves was simulated across four typical bottom types (rock, coarse sand, silt, and clay) under varying source depths (50–1000 m) and receiver depths (50–500 m). The maximum sonar detection range was delineated using an 80 dB TL threshold as the criterion for effective detection. The key findings reveal that the bottom properties are the primary factors that reduce the detection range: the maximum detection range over rock bottom exceeds that over clay by more than 8-fold. Notably, a shallow source–shallow receiver configuration mitigates the acoustic shadow effect induced by seamounts, whereas deep receiver deployment (≥500 m) diminishes the discriminative impact of bottom types on the propagation behavior. Furthermore, a segmented empirical prediction formula was established, which reconciles both the physical mechanisms (e.g., bottom reflection-absorption and seamount shielding) and engineering applicability. This formula provides a robust theoretical basis for evaluating sonar performance in complex seabed topography settings, thereby facilitating optimized underwater detection strategies in seamount-dominated marine environments. Full article

(This article belongs to the Section Ocean Engineering)

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37 pages, 11112 KB

Open AccessArticle

Adaptive Dynamic Prediction-Based Cooperative Interception Control Algorithm for Multi-Type Unmanned Surface Vessels

by Yuan Liu, Bowen Tang, Lingyun Lu, Zhiqing Bai, Guoxing Li, Shikun Geng and Xirui Xu

J. Mar. Sci. Eng. 2026, 14(1), 88; https://doi.org/10.3390/jmse14010088 - 2 Jan 2026

Viewed by 535

Abstract

In the dynamic marine environment, the high mobility of intrusion targets, complex interference, and insufficient multi-vessel coordination accuracy pose significant challenges to the cooperative interception mission of multiple unmanned surface vehicles (USVs). This paper proposes an adaptive dynamic prediction-based cooperative interception control algorithm [...] Read more.

In the dynamic marine environment, the high mobility of intrusion targets, complex interference, and insufficient multi-vessel coordination accuracy pose significant challenges to the cooperative interception mission of multiple unmanned surface vehicles (USVs). This paper proposes an adaptive dynamic prediction-based cooperative interception control algorithm and establishes a “mission planning—anti-interference control—phased coordination” system. Specifically, it ensures interception accuracy through threat-level-oriented target assignment and extended Kalman filter multi-step prediction, offsets environmental interference by separating the cooperative encirclement and anti-interference modules using an improved Two-stage architecture, and optimizes the movement of nodes to form a stable blockade through the “target navigation—cooperative encirclement” strategy. Simulation results show that in a 1000 m × 1000 m mission area, the node trajectory deviation is reduced by 40% and the heading angle fluctuation is decreased by 50, compared with the limit cycle encirclement algorithm, the average interception time is shortened by 15% and the average final distance between the intrusion target and the guarded target is increased by 20%, when the target attempts to escape, the relevant collision rates are all below 0.3%. The TFMUSV framework ensures the stable optimization of the algorithm and significantly improves the efficiency and reliability of multi-USV cooperative interception in complex scenarios. This paper provides a highly adaptable technical solution for practical tasks such as maritime security and anti-smuggling. Full article

(This article belongs to the Section Ocean Engineering)

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26 pages, 12124 KB

Open AccessArticle

MF-GCN: Multimodal Information Fusion Using Incremental Graph Convolutional Network for Ship Behavior Anomaly Detection

by Ruixin Ma, Jinhao Zhang, Weizhi Nie, Naiming Ge, Hao Wen and Aoxiang Liu

J. Mar. Sci. Eng. 2026, 14(1), 87; https://doi.org/10.3390/jmse14010087 - 1 Jan 2026

Viewed by 286

Abstract

Ship behavior anomaly detection is critical for intelligent perception and early warning in complex inland waterways, where single-source sensing (e.g., AIS-only or vision-only) is often fragile under occlusion, illumination variation, and signal noise. This study proposes MF-GCN, a multimodal (heterogeneous) information fusion framework [...] Read more.

Ship behavior anomaly detection is critical for intelligent perception and early warning in complex inland waterways, where single-source sensing (e.g., AIS-only or vision-only) is often fragile under occlusion, illumination variation, and signal noise. This study proposes MF-GCN, a multimodal (heterogeneous) information fusion framework based on an Incremental Graph Convolutional Network (IGCN) to detect and warn anomalous ship behaviors by jointly modeling AIS, video imagery, LiDAR point clouds, and water level signals. We first extract modality-specific features and enforce temporal–spatial consistency via timestamp and geo-referencing alignment, then construct an evolving graph in which nodes represent multimodal features and edges encode temporal dependency and semantic similarity. MF-GCN integrates a Semantic Clustering-based GCN (S-GCN) to inject historical semantic context and an Attentive Fusion-based GCN (A-GCN) to learn dynamic cross-modal correlations using multi-head attention. Experiments on our constructed real-world datasets demonstrate that MF-GCN achieves accuracies of 93.8%, 93.8%, and 93.3% with F1-scores of 93.6%, 93.6%, and 93.3% for ship deviation warning, bridge-crossing warning, and inter-ship collision warning, respectively, consistently outperforming representative baselines. These results verify the effectiveness of the proposed method for robust multimodal anomaly detection and early warning in inland-waterway scenarios. Full article

(This article belongs to the Special Issue Emerging Computational Methods in Intelligent Marine Vehicles)

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33 pages, 5065 KB

Open AccessArticle

Delay-Compensated EKF and Adaptive Delay Threshold Weighting for AUV–MDS Docking

by Han Yan and Shuxue Yan

J. Mar. Sci. Eng. 2026, 14(1), 86; https://doi.org/10.3390/jmse14010086 - 1 Jan 2026

Viewed by 403

Abstract

This study tackles real-time state estimation for autonomous underwater vehicle (AUV)–mobile docking station (MDS) cooperation over low-bandwidth, high-latency, jitter-dominated acoustic links, with the goal of turning delayed/out-of-sequence measurements (OOSM) into consistent and informative constraints without sacrificing online operation. We propose an integrated scheme [...] Read more.

This study tackles real-time state estimation for autonomous underwater vehicle (AUV)–mobile docking station (MDS) cooperation over low-bandwidth, high-latency, jitter-dominated acoustic links, with the goal of turning delayed/out-of-sequence measurements (OOSM) into consistent and informative constraints without sacrificing online operation. We propose an integrated scheme centered on a delay-compensated extended Kalman filter (DC-EKF): a ring buffer enables backward updates and forward replay so that OOSM are absorbed strictly at their physical timestamps; a data-driven delay threshold is learned from “effective information gain” combined with normalized estimation error squared (NEES) filtering; and dynamic confidence, derived from innovation statistics, delay, and signal-to-noise ratio (SNR) proxies, scales the measurement noise to adapt fusion weights. Simulations show the learned delay threshold converges to about 6.4 s (final 6.35 s), error spikes are suppressed, and the overall position root-mean-square error (RMSE) is 5.751 m; across the full data stream, 1067 station measurements were accepted and 30 rejected, and the fusion weights shifted smoothly from inertial measurement unit (IMU)-dominant to station-dominant (≈0.16/0.84) over time. On this basis, a cooperative augmented EKF (Co-Aug-EKF) is added as a lightweight upper layer for unified-frame cooperative estimation, further improving relative consistency. The results indicate that the framework reliably maps delayed acoustic measurements into closed-loop useful information, significantly enhancing estimator stability and docking readiness, while remaining practical to deploy and readily extensible. Full article

(This article belongs to the Topic Advanced Technologies and Applications for Unmanned Systems)

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36 pages, 2483 KB

Open AccessReview

Machine Learning Applications in Fuel Reforming for Hydrogen Production in Marine Propulsion Systems

by Yexin Chen, Xinyu Liu, Xu Liu, Hao Lu and Ziqin Wang

J. Mar. Sci. Eng. 2026, 14(1), 85; https://doi.org/10.3390/jmse14010085 - 31 Dec 2025

Viewed by 823

Abstract

In the context of the shipping industry’s transition towards low-carbon solutions, hydrogen energy exhibits substantial application potential in marine propulsion systems. Fuel reforming for hydrogen production represents one of the key technologies for efficient hydrogen production in maritime applications. Nevertheless, this process involves [...] Read more.

In the context of the shipping industry’s transition towards low-carbon solutions, hydrogen energy exhibits substantial application potential in marine propulsion systems. Fuel reforming for hydrogen production represents one of the key technologies for efficient hydrogen production in maritime applications. Nevertheless, this process involves complex multi-scale reaction mechanisms, challenges in catalyst design, and difficulties in system optimization. This paper conducts a comprehensive review of the recent progress in the application of machine learning in fuel reforming hydrogen production technology. In the realm of catalysts, machine learning has expedited the design of efficient catalysts via high-throughput screening, performance prediction, and active site regulation. In reaction modeling, machine learning has facilitated the development of multi-scale kinetic models, enhancing the interpretability and predictive accuracy of reaction pathways. Regarding equipment and system optimization, machine learning has enabled innovations in reactor design, collaborative optimization of process parameters, and intelligent system control. This review aims to provide theoretical foundations and practical guidance for the technological development of ship propulsion systems. Moreover, it explores the future directions for the deep integration of machine learning and hydrogen energy technologies, thereby promoting the low-carbon and intelligent transformation of the shipping industry. Full article

(This article belongs to the Special Issue Advanced Technologies for New (Clean) Energy Ships—2nd Edition)

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42 pages, 12068 KB

Open AccessArticle

Geochemical and Radiometric Assessment of Romanian Black Sea Shelf Waters and Sediments: Implications for Anthropogenic Influence

by Irina Catianis, Mihaela Mureșan, Tatiana Begun, Adrian Teacă, Andra Bucșe, Florina Rădulescu, Florina Macau, Naliana Lupașcu, Daniela Florea, Florentina Fediuc, Sorin Ujeniuc, Radu Seremet, Silvia Ise, Iulian Andreicovici and Ana Bianca Pavel

J. Mar. Sci. Eng. 2026, 14(1), 84; https://doi.org/10.3390/jmse14010084 - 31 Dec 2025

Viewed by 598

Abstract

The Northwestern Black Sea shelf, strongly influenced by Danube discharge and coastal activities, provides an effective setting for separating lithogenic controls from localized anthropogenic inputs. We applied a multi-proxy geochemical–radiometric approach to Romanian shelf waters and surface sediments. A CTD–Rosette was used to [...] Read more.

The Northwestern Black Sea shelf, strongly influenced by Danube discharge and coastal activities, provides an effective setting for separating lithogenic controls from localized anthropogenic inputs. We applied a multi-proxy geochemical–radiometric approach to Romanian shelf waters and surface sediments. A CTD–Rosette was used to quantify nutrients, chlorophyll-a, TOC, and TN. Dissolved metals and PAHs were measured in seawater, while surface sediments were analyzed for CaCO₃, TOC, trace metals, and γ-emitting radionuclides. Multivariate statistics (PCA/FA) were used to resolve the dominant environmental controls. Summer stratification was characterized by the bottom-layer maxima of PO₄³⁻, SiO₄⁴⁻, and NH₄⁺ and a pronounced subsurface chlorophyll-a maximum at 12–16 m. Surface-water Σ16PAH ranged from 134 to 347 ng L⁻¹ and was dominated by low-molecular-weight compounds, with episodic nearshore enrichment in high-molecular-weight species. In sediments, CaCO₃ ranged from 7.6 to 29.9% and TOC from 0.11 to 0.96%. Trace metals were generally low. Pb and Hg peaked at nearshore station S23, whereas mean Ni (38.88 ppm) slightly exceeded the 35 ppm guideline, consistent with natural Fe/Mn-oxide association. PCA/FA identified a terrigenous axis (Fe-Al-Ti-V-Ni-Cr), a carbonate axis (CaCO₃; Sr where available), and an anthropogenic factor (Pb, Hg, HMW-PAHs). γ-spectrometry provided a compatible radiometric baseline that supports the multi-proxy interpretation. Full article

(This article belongs to the Section Marine Environmental Science)

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21 pages, 12880 KB

Open AccessArticle

Effects of Cross-Linked Structure of Sodium Alginate on Electroosmotic Dewatering and Reinforcement for Coastal Soft Soil

by Guoqiang Wu, Lingwei Zheng, Xunli Zhang, Guanyu Chen, Shangqi Ge, Yuanhong Yu and Xinyu Xie

J. Mar. Sci. Eng. 2026, 14(1), 83; https://doi.org/10.3390/jmse14010083 - 31 Dec 2025

Viewed by 255

Abstract

The reinforcement of high-water-content, low-permeability soft soils presents a critical challenge in marine and coastal engineering. While electroosmotic dewatering is a promising technique, its widespread application is often hindered by issues such as high energy consumption and limited strength gain. However, the specific [...] Read more.

The reinforcement of high-water-content, low-permeability soft soils presents a critical challenge in marine and coastal engineering. While electroosmotic dewatering is a promising technique, its widespread application is often hindered by issues such as high energy consumption and limited strength gain. However, the specific mechanisms by which marine-derived biopolymers modify soil properties and microstructure to enhance electroosmotic efficiency and significantly improve the post-treatment bearing capacity remain insufficiently understood. To address this gap, this study investigates the use of Sodium Alginate (SA) to enhance the electroosmotic dewatering performance of coastal soft soil. Laboratory experiments were conducted using carbon felt electrodes with varying SA mass fractions (0.0%, 0.2%, 0.5%, and 1.0%). The study integrated macroscopic monitoring with Scanning Electron Microscopy (SEM) to evaluate the electroosmotic efficiency and mechanical property evolution. The results demonstrate that the cross-linked structure of SA gel effectively bridges soil particles and fills inter-granular pores, significantly increasing the liquid limit (from 32.34% to 49.15% at 1.0% SA) and mitigating soil cracking. This microstructural alteration enhanced electrical conductivity and accelerated drainage; the average water content reduction increased from 12.78% (0.0% SA) to 20.86% (1.0% SA). Notably, the 0.5% SA treatment improved the average bearing capacity to approximately 86 kPa (about 7 times that of 0.0% SA) with only a 21% increase in the energy consumption coefficient. This study confirms that utilizing SA for electroosmotic reinforcement effectively modifies soil properties to provide a marine solution for coastal soft soil foundation treatment. Full article

(This article belongs to the Section Coastal Engineering)

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36 pages, 5570 KB

Open AccessArticle

Evolving Collective Intelligence for Unmanned Marine Vehicle Swarms: A Federated Meta-Learning Framework for Cross-Fleet Planning and Control

by Yuhan Ye, Hongjun Tian, Yijie Yin, Yuhan Zhou, Yang Xiong, Zi Wang, Yaojiang Liu, Zinan Nie, Zitong Zhang, Yichen Wang and Jingyu Sun

J. Mar. Sci. Eng. 2026, 14(1), 82; https://doi.org/10.3390/jmse14010082 - 31 Dec 2025

Viewed by 290

Abstract

The development of robust autonomous maritime systems is fundamentally constrained by the “data silo” problem, where valuable operational data from disparate fleets remain isolated due to privacy concerns, severely limiting the scalability of general-purpose navigation intelligence. To address this barrier, we propose a [...] Read more.

The development of robust autonomous maritime systems is fundamentally constrained by the “data silo” problem, where valuable operational data from disparate fleets remain isolated due to privacy concerns, severely limiting the scalability of general-purpose navigation intelligence. To address this barrier, we propose a novel Federated Meta-Transfer Learning (FMTL) framework that enables collaborative evolution of unmanned surface vehicle (USV) swarms while preserving data privacy. Our hierarchical approach orchestrates three synergistic stages: (1) transfer learning pre-trains a universal “Sea-Sense” foundation model on large-scale maritime data to establish fundamental navigation priors; (2) federated learning enables decentralized fleets to collaboratively refine this model through encrypted gradient aggregation, forming a distributed cognitive network; (3) meta-learning allows for rapid personalization to individual vessel dynamics with minimal adaptation trials. Comprehensive simulations across heterogeneous fleet distributions demonstrate that our federated model achieves a 95.4% average success rate across diverse maritime scenarios, significantly outperforming isolated specialist models (63.9–73.1%), while enabling zero-shot performance of 78.5% and few-shot adaptation within 8–12 episodes on unseen tasks. This work establishes a scalable, privacy-preserving paradigm for collective maritime intelligence through swarm-based learning. Full article

(This article belongs to the Special Issue Unmanned Marine Vehicles: Perception, Planning, Control and Swarm—2nd Edition)

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34 pages, 5124 KB

Open AccessArticle

A Deep Ship Trajectory Clustering Method Based on Feature Embedded Representation Learning

by Yifei Liu, Zhangsong Shi, Bing Fu, Jiankang Ke, Huihui Xu and Xuan Wang

J. Mar. Sci. Eng. 2026, 14(1), 81; https://doi.org/10.3390/jmse14010081 - 31 Dec 2025

Viewed by 248

Abstract

Trajectory clustering is of great significance for identifying behavioral patterns and vessel types of non-cooperative ships. However, existing trajectory clustering methods suffer from limitations in extracting cross-spatiotemporal scale features and modeling the coupling relationship between positional and motion features, which restricts clustering performance. [...] Read more.

Trajectory clustering is of great significance for identifying behavioral patterns and vessel types of non-cooperative ships. However, existing trajectory clustering methods suffer from limitations in extracting cross-spatiotemporal scale features and modeling the coupling relationship between positional and motion features, which restricts clustering performance. To address this, this study proposes a deep ship trajectory clustering method based on feature embedding representation learning (ERL-DTC). The method designs a Temporal Attention-based Multi-scale feature Aggregation Network (TA-MAN) to achieve dynamic fusion of trajectory features from micro to macro scales. A Dual-feature Self-attention Fusion Encoder (DualSFE) is employed to decouple and jointly represent the spatiotemporal position and motion features of trajectories. A two-stage optimization strategy of “pre-training and joint training” is adopted, combining contrastive loss and clustering loss to jointly constrain the embedding representation learning, ensuring it preserves trajectory similarity relationships while being adapted to the clustering task. Experiments on a public vessel trajectory dataset show that for a four-class task (K = 4), ERL-DTC improves ACC by approximately 14.1% compared to the current best deep clustering method, with NMI and ARI increasing by about 28.9% and 30.2%, respectively. It achieves the highest Silhouette Coefficient (SC) and the lowest Davies-Bouldin Index (DBI), indicating a tighter and more clearly separated cluster structure. Furthermore, its inference efficiency is improved by two orders of magnitude compared to traditional point-matching-based methods, without significantly increasing runtime due to model complexity. Ablation studies and parameter sensitivity analysis further validate the necessity of each module design and the rationality of hyperparameter settings. This research provides an efficient and robust solution for feature learning and clustering of vessel trajectories across spatiotemporal scales. Full article

(This article belongs to the Section Ocean Engineering)

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