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Volume 14
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J. Mar. Sci. Eng., Volume 14, Issue 8 (April-2 2026) – 73 articles

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28 pages, 7294 KB  
Article
Nighttime Encounter Situation Recognition for Unmanned Surface Vessels Based on Images of Vessel Navigation Lights
by Ruoyun Huang, Xiang Zheng, Jianhua Wang, Gongxing Wu, Yu Tian and Yining Tian
J. Mar. Sci. Eng. 2026, 14(8), 761; https://doi.org/10.3390/jmse14080761 - 21 Apr 2026
Viewed by 342
Abstract
To address the limitations of existing perception methods for nighttime encounter situation recognition of unmanned surface vessels (USVs), this study proposes an image-based method for navigation-light recognition and encounter situation recognition. In accordance with the International Regulations for Preventing Collisions at Sea (COLREGs), [...] Read more.
To address the limitations of existing perception methods for nighttime encounter situation recognition of unmanned surface vessels (USVs), this study proposes an image-based method for navigation-light recognition and encounter situation recognition. In accordance with the International Regulations for Preventing Collisions at Sea (COLREGs), a parameterized 3D geometric model of vessel navigation lights and encounter scenario models is established. Based on the camera imaging principle, a dataset of navigation-light images under various encounter situations is generated through simulation experiments. By analyzing the variation patterns of navigation-light images in different encounter situations, a feature vector composed of area-domain and azimuth-domain features is constructed, and an encounter situation recognition method is developed accordingly. To mitigate the effects of water reflections and interfering light sources in real images, a navigation-light image-processing method is designed for the stable extraction of feature parameters. Simulation results show that the classification accuracy ranges from 96.6% to 98.3% at different distance conditions. In field experiments conducted with a small USV under a three-light configuration, the proposed method achieves a navigation-light recognition accuracy of 96.2% and an encounter situation recognition accuracy of 94.94%. The proposed method provides an interpretable and lightweight complementary visual solution for nighttime encounter situation recognition, complementing existing nighttime perception technologies. Full article
(This article belongs to the Section Ocean Engineering)
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26 pages, 4573 KB  
Article
Feasibility of Wave Energy Converters in the Azores Under Climate Change Scenarios
by Marta Gonçalves, Mariana Bernardino and Carlos Guedes Soares
J. Mar. Sci. Eng. 2026, 14(8), 760; https://doi.org/10.3390/jmse14080760 - 21 Apr 2026
Viewed by 330
Abstract
The wave energy resource along the Azores coast is evaluated for the present (1990–2019) and future (2030–2059) periods using the third-generation wave model WAVEWATCH III, forced by winds and sea-ice cover from the RCP8.5 EC-Earth integration dynamically downscaled with the Weather Research and [...] Read more.
The wave energy resource along the Azores coast is evaluated for the present (1990–2019) and future (2030–2059) periods using the third-generation wave model WAVEWATCH III, forced by winds and sea-ice cover from the RCP8.5 EC-Earth integration dynamically downscaled with the Weather Research and Forecasting model. The results indicate that the region is characterized by a high-energy wave climate, with mean wave power values typically ranging between 30 and 40 kW/m. A statistical comparison between the two periods shows a moderate reduction in wave energy potential under future conditions, with strong spatial variability. The performance of four wave energy converters (AquaBuoy, Wavestar, Oceantec, and Atargis) is analyzed, revealing significant differences in energy production and capacity factor depending on device–site matching. A techno-economic evaluation is performed by estimating the LCOE, accounting for capital expenditure, operational costs, device lifetime, and annual energy production (AEP). The results demonstrate that economic performance is primarily driven by energy production rather than capital cost alone, and that wave energy exploitation in the Azores remains viable under near-future climate conditions. Full article
(This article belongs to the Section Marine Energy)
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22 pages, 45694 KB  
Article
Visual Localization for Deep-Sea Mining Vehicles During Operation
by Yangrui Cheng, Bingkun Wang, Xiaojun Zhuo, Kai Liu and Yingjie Guan
J. Mar. Sci. Eng. 2026, 14(8), 759; https://doi.org/10.3390/jmse14080759 - 21 Apr 2026
Viewed by 386
Abstract
Deep-sea mining operations demand continuous, drift-free positioning over multi-day missions—a requirement that traditional acoustic dead-reckoning systems struggle to meet due to cumulative error accumulation and frequent DVL bottom-lock loss in sediment plume environments. Inspired by Google Cartographer’s 2D grid mapping paradigm, we present [...] Read more.
Deep-sea mining operations demand continuous, drift-free positioning over multi-day missions—a requirement that traditional acoustic dead-reckoning systems struggle to meet due to cumulative error accumulation and frequent DVL bottom-lock loss in sediment plume environments. Inspired by Google Cartographer’s 2D grid mapping paradigm, we present a prior map-based visual localization framework that decouples offline mapping from real-time localization, fundamentally eliminating drift through absolute image registration against pre-built seabed mosaics. By integrating adaptive keyframe selection, Multi-Scale Retinex (MSR) enhancement, and the AD-LG deep feature matching architecture, our system constructs globally consistent seabed maps for absolute positioning. The framework leverages deformable convolutions and LightGlue to effectively mitigate challenges such as low texture and non-rigid distortion. Quantitative validation on tank simulation datasets demonstrates significant superiority over IMU-only and standard fusion schemes; qualitative deployment on real Pacific CCZ imagery confirms near-real-time operational feasibility on an embedded Jetson Orin NX platform. This system establishes visual navigation as a viable backup to acoustic systems, addressing a critical gap in deep-sea mining vehicle autonomy. Full article
(This article belongs to the Special Issue Advances in Underwater Positioning and Navigation Technology)
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31 pages, 6994 KB  
Article
Coordinated Vessel Arrival Time Prediction and Berth Allocation Optimization for Efficient Port Operations
by Peng Fei, Wu Ning, Kecheng Li, Xiyao Xu, Xiumin Chu and Chenguang Liu
J. Mar. Sci. Eng. 2026, 14(8), 758; https://doi.org/10.3390/jmse14080758 - 21 Apr 2026
Viewed by 482
Abstract
Uncertainty in vessel arrival times can substantially reduce the efficiency of berth planning in port operations. To address this issue, this study proposes a unified, data-driven, predict-then-optimize framework that explicitly links vessel arrival time (VAT) prediction with downstream continuous berth allocation optimization. In [...] Read more.
Uncertainty in vessel arrival times can substantially reduce the efficiency of berth planning in port operations. To address this issue, this study proposes a unified, data-driven, predict-then-optimize framework that explicitly links vessel arrival time (VAT) prediction with downstream continuous berth allocation optimization. In the prediction stage, heterogeneous maritime data, including port call records, AIS trajectories, and vessel physical characteristics, are integrated to construct VAT prediction models. In the optimization stage, the predicted VAT is embedded into a continuous berth allocation problem (BAP) model to support berth scheduling decisions. To better reflect real operations, a two-stage evaluation framework is further developed, in which berth plans generated from estimated arrival times (ETAs) or predicted VATs are re-evaluated under realized actual arrival times while preserving the original temporal and spatial service order. Experimental results show that the proposed framework improves VAT prediction accuracy substantially, reducing the MAE and RMSE from 4.795 h and 7.255 h for the vessel-reported ETAs to 2.844 h and 4.934 h, respectively. More importantly, the predicted-VAT-based BAP consistently outperforms the ETA-based benchmark, yielding an overall 35.96% reduction in objective value across tested scenarios. These findings demonstrate that improved VAT prediction can be effectively translated into meaningful operational gains in berth allocation. Full article
(This article belongs to the Special Issue Artificial Intelligence and Its Applications in Intelligent Ship Navigation)
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38 pages, 3949 KB  
Article
Research on Trajectory Tracking Control of USV Based on Disturbance Observation Compensation
by Jiadong Zhang, Hongjie Ling, Wandi Song, Anqi Lu, Changgui Shu and Junyi Huang
J. Mar. Sci. Eng. 2026, 14(8), 757; https://doi.org/10.3390/jmse14080757 - 21 Apr 2026
Viewed by 366
Abstract
To address trajectory-tracking degradation of unmanned surface vehicles (USVs) in constrained waters caused by model uncertainty, strong environmental disturbances, and actuator limitations, this paper proposes a robust disturbance-observer-based optimization model predictive control method. First, a nonlinear tracking error model is established for a [...] Read more.
To address trajectory-tracking degradation of unmanned surface vehicles (USVs) in constrained waters caused by model uncertainty, strong environmental disturbances, and actuator limitations, this paper proposes a robust disturbance-observer-based optimization model predictive control method. First, a nonlinear tracking error model is established for a 3-DOF USV by incorporating environmental loads, parametric perturbations, and unmodeled dynamics into the kinematic and dynamic equations. Based on this model, a prediction model suitable for model predictive control is derived through linearization and discretization. Then, to estimate complex unknown disturbances online, a robust disturbance observer integrating a radial basis function neural network (RBFNN) with an adaptive sliding-mode mechanism is developed, enabling real-time approximation and compensation of lumped disturbances in the surge and yaw channels. Furthermore, to overcome actuator saturation caused by the direct superposition of feedforward compensation and feedback control in conventional composite strategies, a dynamic constraint reconstruction mechanism is introduced. By feeding the observer-generated compensation signal back into the MPC optimizer, the feasible control region is updated online so that the total control input satisfies both magnitude and rate constraints of the propulsion system. Theoretical analysis based on Lyapunov theory proves the uniform ultimate boundedness of the observation errors and neural-network weight estimation errors, while input-to-state stability theory is employed to establish closed-loop stability. Comparative simulations under sinusoidal trajectories, time-varying curvature paths, and large-maneuver turning conditions demonstrate that the proposed method significantly improves tracking accuracy, disturbance rejection capability, and control feasibility under severe disturbances and parameter mismatch. Full article
(This article belongs to the Section Ocean Engineering)
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25 pages, 29575 KB  
Article
An Adaptive Receiver-Grid Parameter Optimization Method for BELLHOP Based on Bathymetric and Sound-Speed-Profile Features
by Zhichao Lv, Kexin Zhang, Chuanhe Tan, Junjie Chen, Fei Yu, Jialong Chen and Zongwei Liu
J. Mar. Sci. Eng. 2026, 14(8), 756; https://doi.org/10.3390/jmse14080756 - 21 Apr 2026
Viewed by 312
Abstract
Ray-based models have been extensively applied in underwater acoustic propagation modeling because of their favorable physical interpretability and engineering practicality. Nevertheless, in complex ocean environments, conventional acoustic propagation models still face several limitations, including low computational efficiency, empirically determined grid settings, and inadequate [...] Read more.
Ray-based models have been extensively applied in underwater acoustic propagation modeling because of their favorable physical interpretability and engineering practicality. Nevertheless, in complex ocean environments, conventional acoustic propagation models still face several limitations, including low computational efficiency, empirically determined grid settings, and inadequate local refinement capability, which restrict their application in high-accuracy and high-efficiency simulations. To address these limitations, an adaptive receiver-grid construction method for the BELLHOP model is proposed in this study. The method adaptively adjusts receiver-grid spacings by using seafloor bathymetric features and sound-speed-profile gradient characteristics as the primary driving factors. Specifically, local grid refinement is introduced in the receiver-grid region of critical acoustic propagation areas, whereas relatively coarse grids are employed in non-critical regions, thereby improving acoustic-field resolution while reducing the overall computational cost. Simulation results show that the proposed method effectively improves the transmission-loss computation efficiency and spatial resolution of the BELLHOP model in complex ocean environments, thus providing a practical approach for rapid and high-precision underwater acoustic propagation modeling. Full article
(This article belongs to the Special Issue Marine Modelling and Environmental Statistics—2nd Edition)
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15 pages, 5200 KB  
Article
A KNN-Multiplicative Score Approach for Blade Impact Fault Detection of Tidal Current Turbines
by Lei Ren, Tianzhen Wang and Christophe Claramunt
J. Mar. Sci. Eng. 2026, 14(8), 755; https://doi.org/10.3390/jmse14080755 - 21 Apr 2026
Viewed by 307
Abstract
Blade impact faults degrade power generation quality, if not detected in time, may lead to turbine malfunction or even complete failure. Moreover, the accuracy of blade impact fault detection in tidal current turbine (TCT) is significantly affected by variations in flow velocity and [...] Read more.
Blade impact faults degrade power generation quality, if not detected in time, may lead to turbine malfunction or even complete failure. Moreover, the accuracy of blade impact fault detection in tidal current turbine (TCT) is significantly affected by variations in flow velocity and tidal flow period. To solve this problem, a self-adaptive detection method based on stator current signals and k-nearest neighbor-multiplicative score (KNN-MS) is proposed. The method first employs the KNN algorithm to characterize local feature distributions. Then, robustness under unstable flow conditions is improved through variance-based weighting. Finally, a cumulative multiplicative scoring mechanism is proposed to amplify and quantify fault-related anomaly indicators. The experimental results show that the proposed method achieves high diagnostic accuracy and stability across steady, periodic, and variable-period flow scenarios. Full article
(This article belongs to the Section Ocean Engineering)
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16 pages, 3140 KB  
Article
Comparative Temporal Analysis of Demographic and Morphometric Traits in Patella ferruginea
by Paolo Marras, A. Cossu, A. Ruiu, A. Santonastaso and Mario De Luca
J. Mar. Sci. Eng. 2026, 14(8), 754; https://doi.org/10.3390/jmse14080754 - 21 Apr 2026
Viewed by 434
Abstract
This study presents the results of monitoring the endangered gastropod Patella ferruginea within a Marine Protected Area in Sardinia. A detailed map of the species distribution was created, and individual density and population structure were analysed by comparing data collected during monitoring campaigns [...] Read more.
This study presents the results of monitoring the endangered gastropod Patella ferruginea within a Marine Protected Area in Sardinia. A detailed map of the species distribution was created, and individual density and population structure were analysed by comparing data collected during monitoring campaigns in 2014, 2018, and 2023. A total of 206, 203, and 109 individuals were recorded in 2014, 2018, and 2023, respectively. In 2014 and 2018, 24 and 26 specimens with a maximum diameter of ≥6 cm were observed, while in 2023, only 11 individuals reached this size, with a single specimen measuring 6.5 cm. Linear density showed an average reduction of approximately 37% in the latest campaign compared to the previous one. The coastline under analysis was divided into five sectors based on the degree of protection and exposure to prevailing winds. The overall decline of approximately 50% in the population indicates a decrease affecting all size classes, although it is more pronounced in the larger size classes. Furthermore, analyses of spatial structure using the Minimum Spanning Tree (MST), Clark and Evans’ R index, and Nearest Neighbour Distance (NND) indicate a dispersed distribution already in 2018, which became more pronounced in 2023. These results indicate that current protection measures within the MPA may not be sufficient to ensure long-term population stability, suggesting that conservation strategies for this species should be assessed on a site-specific basis. Full article
(This article belongs to the Special Issue How Marine Environment Changes Affect Marine Organism's Responses)
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16 pages, 2817 KB  
Article
Characterization and Dynamics of the Beach Transition Zone: Insights from Southwestern Rhode Island, U.S.A.
by Bess Points and John P. Walsh
J. Mar. Sci. Eng. 2026, 14(8), 753; https://doi.org/10.3390/jmse14080753 - 20 Apr 2026
Viewed by 355
Abstract
Oceanfront relief varies along coastlines and serves as the first barrier to wave and surge damage. However, forecasted increases in storm frequency and sea levels are anticipated to enhance coastal erosion, potentially weakening this protection. The land–sea transition is variable along the New [...] Read more.
Oceanfront relief varies along coastlines and serves as the first barrier to wave and surge damage. However, forecasted increases in storm frequency and sea levels are anticipated to enhance coastal erosion, potentially weakening this protection. The land–sea transition is variable along the New England coast, USA, and this variability has produced a range of coastal morphologies that can vary over short distances. It is important to track the beach transition zone to better understand transformations of the system and related hazard risks. A combination of field and computer-based methods was used to evaluate the beach transition zone of southwestern Rhode Island to determine alongshore variability and dynamics. More specifically, a decadal-scale study was conducted to examine changes in morphology from 2011 to 2022, and a short-term study at South Kingstown Town Beach examined changes from November 2023 to January 2024 using time-series drone-derived elevations. Classification of over 500 cross-shore transects illustrated the dominance of sedimentary shorelines, with smaller areas of rocky outcrops and hardening. Analysis of four different years (2011, 2014, 2018, and 2022) determined that beaches with dune morphology were the most common type of transition zone (41–47% of the transects) and transects with a high bank upland were the next most frequent class (34–41%). Following Hurricane Sandy in 2012, a 6% decrease in the number of dune-classified transects was measured; however, one-third of those recovered dune morphology by 2022. The greatest beach transformations over the short-term study occurred in response to strong storms in the 2023–2024 winter season, during which lateral beach movement (erosion) exceeded 15 m in portions of South Kingstown Town Beach. Dune erosion was accompanied by overwash flooding and deposition, and the area remained low-lying and thus vulnerable to future impacts. The beach transition zone classification and insights from this research will be informative for future planning by coastal communities by determining at-risk shorelines based on underlying geology and the stability of morphological features. Full article
(This article belongs to the Special Issue Marine and Coastal Processes in a Changing Climate)
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14 pages, 1809 KB  
Article
Sub-Basin Variability of Dissolved and Particulate Barium in the Mediterranean Sea: Insights into Ba Cycling Horizons and Remineralization Processes
by Stéphanie Jacquet and Francisca Martinez Ruiz
J. Mar. Sci. Eng. 2026, 14(8), 752; https://doi.org/10.3390/jmse14080752 - 20 Apr 2026
Viewed by 359
Abstract
This study investigated sub-basin variability in dissolved (dBa)–excess particulate (Baxs) barium relationships and Ba flux patterns across the western and central Mediterranean Sea during late spring 2017 (PEACETIME cruise). The dBa concentrations increased from ~35 nmol L−1 near the surface [...] Read more.
This study investigated sub-basin variability in dissolved (dBa)–excess particulate (Baxs) barium relationships and Ba flux patterns across the western and central Mediterranean Sea during late spring 2017 (PEACETIME cruise). The dBa concentrations increased from ~35 nmol L−1 near the surface to ~70 nmol L−1 at 2500 m, consistent with the relatively weak vertical dBa gradient typical of the Mediterranean. Depth profiles of dBa showed distributions consistent with Baxs dynamics associated with organic matter remineralization at mesopelagic depths (100–1000 m). Baxs exhibited basin-dependent maxima, with lower (<300 pM) depth-weighted average concentrations confined to the upper mesopelagic in the Tyrrhenian and Ionian basins and higher (up to 650 pM) and deeper concentrations (to ~1000 m) in the Algero–Provençal basin, suggesting contrasted remineralization horizon structures. A simplified steady-state 1-D approach yielded first-order mesopelagic dBa removal fluxes of ~0.3 ± 0.1 µmol m−2 d−1 in the Algero–Provençal basin to 1.7 ± 1.0 µmol m−2 d−1 in the Ionian basin, consistent with previous estimates obtained from a coupled dBa and parametric optimum multiparameter approach. Together, these paired dissolved and particulate Ba observations refined the Mediterranean Ba cycle framework and provided additional geochemical constraints for interpreting mesopelagic carbon remineralization processes. Full article
(This article belongs to the Section Chemical Oceanography)
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21 pages, 2691 KB  
Article
Wave Blocking in the Hydroelastic Response of a Floating Flexible Platform Under Compression Using Timoshenko–Mindlin Beam Theory
by Pouria Amouzadrad, Sarat Chandra Mohapatra and C. Guedes Soares
J. Mar. Sci. Eng. 2026, 14(8), 751; https://doi.org/10.3390/jmse14080751 - 20 Apr 2026
Viewed by 338
Abstract
A hydroelastic theoretical model is formulated, and an analytical solution is obtained to investigate the interaction between wave-opposing current loading with compression and a moored floating flexible platform within the framework of Timoshenko–Mindlin beam theory based on the linearized wave and small structural [...] Read more.
A hydroelastic theoretical model is formulated, and an analytical solution is obtained to investigate the interaction between wave-opposing current loading with compression and a moored floating flexible platform within the framework of Timoshenko–Mindlin beam theory based on the linearized wave and small structural response. By employing the matching technique and orthogonal mode-coupling relation, the closed-form analytical solutions for structural displacement, as well as shear force and bending moment, are obtained. The wave blocking and buckling limit in the presence of compressive force against an opposing current is determined via group and phase velocities from the dispersion relation in the context of the Timoshenko–Mindlin beam theory. Further, the combined influence of opposing current, compressive loading, and key structural design parameters on the hydroelastic response are examined. The results demonstrate that opposing currents and compressive forces can significantly alter the hydroelastic response, highlighting their critical role in structural engineering analysis. The current analysis provides a comprehensive analytical framework that can support the design and optimization of floating flexible platforms in the presence of opposing currents and compressive loads in complex marine environments. Full article
(This article belongs to the Section Ocean Engineering)
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16 pages, 5635 KB  
Article
Integrated Ecological and Molecular Assessment of a Crown-of-Thorns Seastar (Acanthaster planci) Outbreak in the Gulf of Oman (UAE)
by Eleonora Concari, Enrico Montalbetti, Davide Maggioni, Alison Landes, Paolo Galli, Davide Seveso and John Henrik Stahl
J. Mar. Sci. Eng. 2026, 14(8), 750; https://doi.org/10.3390/jmse14080750 - 20 Apr 2026
Viewed by 548
Abstract
Outbreaks of crown-of-thorns sea stars (CoTS) threaten coral reef integrity and biodiversity, yet local dynamics and short-term responses to control remain insufficiently described. This study characterised an outbreaking Acanthaster population in two specific sites of the coast of Khor Fakkan (Gulf of Oman, [...] Read more.
Outbreaks of crown-of-thorns sea stars (CoTS) threaten coral reef integrity and biodiversity, yet local dynamics and short-term responses to control remain insufficiently described. This study characterised an outbreaking Acanthaster population in two specific sites of the coast of Khor Fakkan (Gulf of Oman, United Arab Emirates) to resolve species identity, population composition, prey selection and the effects of targeted removals. All sequenced individuals clustered in two related haplotypes belonging to the species Acanthaster planci. Benthic surveys showed moderate live-coral cover, dominated by massive Porites sp. colonies. Moreover, the observations of 139 preyed colonies revealed pronounced genus-level selectivity, with branching and complex morphologies suffering disproportionately and massive forms largely avoided. However, the selection of massive Plesiastrea and Favites genera as preferred coral prey might suggest a shift towards less preferred coral in the CoTS diet, posing a severe threat to coral reefs’ integrity. Intensive removal reduced the local density, up to 86%, and provided substantial short-term relief, but continued monitoring is required to secure long-term reef resilience. Full article
(This article belongs to the Special Issue Coral Reefs in a Changing World: Disturbance, Recovery, and Resilience)
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51 pages, 3316 KB  
Article
Improving Quay Crane Productivity and Delay Management in Conventional Container Terminals Using Artificial Intelligence Tools
by George-Cosmin Partene, Florin Nicolae, Florin Postolache and Sorin Ionescu
J. Mar. Sci. Eng. 2026, 14(8), 749; https://doi.org/10.3390/jmse14080749 - 19 Apr 2026
Viewed by 777
Abstract
This study proposes an integrated artificial intelligence-based framework for modeling and predicting quay crane productivity and operational delays in conventional container terminals, addressing key limitations in the existing port analytics literature. The research introduces a novel dual-mode machine learning architecture that explicitly separates [...] Read more.
This study proposes an integrated artificial intelligence-based framework for modeling and predicting quay crane productivity and operational delays in conventional container terminals, addressing key limitations in the existing port analytics literature. The research introduces a novel dual-mode machine learning architecture that explicitly separates retrospective prediction (forecast mode) from pre-operational decision support (decision mode), addressing a critical gap in existing literature where predictive models are rarely aligned with real-world informational constraints. The framework is applied to a high-resolution, real-world dataset comprising ship-level operations over a three-year period (2023–2025), incorporating a structured representation of 27 delay types and multiple resource allocation variables. A multi-indicator modeling strategy is employed, simultaneously analyzing four productivity metrics (RQCP, GMPH, WBMPH and NMPH), thus allowing for a systematic comparison of their structural sensitivities to delays, congestion, and equipment utilization. The results reveal a clear hierarchy of predictability and operational behavior: structurally driven indicators such as RQCP and GMPH exhibit high predictive stability, while delay-sensitive indicators such as NMPH display greater variability, reflecting real-time operational disruptions. The consistent model performance in forecasting and decision-making indicates significant predictive value in pre-operational variables, endorsing its utility for uncertain decision-making. Sensitivity analysis reveals a critical nonlinear congestion threshold affecting predictive accuracy under extreme operational strain. Employing a combination of multi-indicator productivity modeling, structured delay classification, and ensemble learning within an integrated analytical framework, this research enhances both methodological and practical insights into port operations, aiding in merging predictive analytics with operational decision-making in container terminals to enhance resource allocation, delay handling, and container terminal efficiency. Full article
(This article belongs to the Special Issue Artificial Intelligence Technology and Application in Marine Science and Engineering)
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33 pages, 1538 KB  
Article
A Parallel STPA–FTA Risk Assessment Framework for Maritime Autonomous Surface Ships: Development and Case Study Application
by Konstantinos Voutzoulidis and Ioannis Tigkas
J. Mar. Sci. Eng. 2026, 14(8), 748; https://doi.org/10.3390/jmse14080748 - 19 Apr 2026
Viewed by 445
Abstract
Maritime Autonomous Surface Ships (MASS) introduce new safety challenges associated with complex cyber–physical systems, distributed control architectures, and remote supervisory operation. Traditional maritime risk assessment approaches primarily focus on component failures and historical accident data and may therefore be insufficient for capturing interaction-driven [...] Read more.
Maritime Autonomous Surface Ships (MASS) introduce new safety challenges associated with complex cyber–physical systems, distributed control architectures, and remote supervisory operation. Traditional maritime risk assessment approaches primarily focus on component failures and historical accident data and may therefore be insufficient for capturing interaction-driven hazards arising in autonomous vessel systems. This study develops a parallel and architecturally synchronized risk assessment framework integrating System-Theoretic Process Analysis (STPA) and Fault Tree Analysis (FTA) for the safety assessment of MASS. Within the proposed framework, both analyses evolve concurrently within a shared system architecture, enabling explicit traceability between hazards, unsafe control actions, causal scenarios, failure events, and accident propagation pathways. The framework is demonstrated through a case study of a Degree of Autonomy 3 short-sea freight vessel operating in a high-density North Sea traffic environment. The integrated analysis identifies dominant accident pathways related to perception degradation, communication disturbance, authority coordination conflicts, maneuver execution deviations, and incorrect collision-risk assessment. The results illustrate how the framework supports structured safety assessment of MASS while preserving traceability between systemic control deficiencies and accident propagation mechanisms. Full article
(This article belongs to the Special Issue Advancements in Autonomous Systems for Complex Maritime Operations)
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21 pages, 4181 KB  
Article
Dynamic Response and Multi-Objective Optimization of Lazy-Wave Dynamic Cables for Large-Capacity Floating Wind Turbines in Shallow Water
by Mingda Ma and Yangyang Gao
J. Mar. Sci. Eng. 2026, 14(8), 747; https://doi.org/10.3390/jmse14080747 - 18 Apr 2026
Viewed by 308
Abstract
Dynamic cables, serving as the critical link between floating wind turbines and submarine cables, are subjected to significant tension fluctuations and bending deformations under environmental loading. While deep-water systems have been widely studied, investigations of large-capacity wind turbines in shallow water environments remain [...] Read more.
Dynamic cables, serving as the critical link between floating wind turbines and submarine cables, are subjected to significant tension fluctuations and bending deformations under environmental loading. While deep-water systems have been widely studied, investigations of large-capacity wind turbines in shallow water environments remain limited. This study establishes a coupled numerical model of an IEA 15 MW floating wind turbine and its dynamic cable system at a water depth of 50 m. The platform’s six-degree-of-freedom motions were calculated under 0°, 90°, and 180° loading directions, followed by a systematic analysis of lazy-wave dynamic cable response characteristics. Results indicate that platform motions and dynamic cable responses are strongly direction-dependent in shallow water, with the 0° loading direction identified as the governing design case due to peak curvature and tension levels. Analysis reveals that the touchdown point location is the primary driver of tension response, while cable length increments predominantly influence bending. Utilizing these insights, a multi-objective fitness function was integrated with a Particle Swarm Optimization (PSO) algorithm. The optimized configuration significantly reduced peak curvature and total cable length, providing a theoretical framework and engineering guidance for the design of high-capacity floating wind systems in shallow-water regions. Full article
(This article belongs to the Section Ocean Engineering)
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21 pages, 3568 KB  
Article
Asymmetric Deep Co-Training Framework Using a Shape Context Descriptor for Reservoir Prediction: A Case Study from the Yinggehai Basin, South China Sea
by Xuanang Li, Jiao Xue and Hanming Gu
J. Mar. Sci. Eng. 2026, 14(8), 746; https://doi.org/10.3390/jmse14080746 - 18 Apr 2026
Viewed by 277
Abstract
The scarcity and incompleteness of well-log data pose a critical challenge to deep learning-based reservoir prediction. To address this small-sample problem and improve prediction quality, we propose a novel semi-supervised asymmetric deep co-training framework integrated with a shape context descriptor. This method leverages [...] Read more.
The scarcity and incompleteness of well-log data pose a critical challenge to deep learning-based reservoir prediction. To address this small-sample problem and improve prediction quality, we propose a novel semi-supervised asymmetric deep co-training framework integrated with a shape context descriptor. This method leverages abundant unlabeled seismic data as well as complementary information on related physical properties. Specifically, we introduce a shape context descriptor to encode seismic waveform morphology and spatial context, thereby improving the lateral continuity and interpretability of predictions while mitigating issues inherent in the sequence-to-point paradigm, wherein three-dimensional seismic data are used as input and a single target point is predicted. To overcome data limitations, a sliding-window resampling strategy is employed to expand the training samples. For co-training, we design an asymmetric dual-task architecture wherein one model performs porosity regression while the other conducts reservoir type classification, thereby enabling synergistic learning. The proposed framework is validated using real three-dimensional seismic data from the Yinggehai Basin in the South China Sea through ablation experiments. The results demonstrate superior performance in prediction accuracy, spatial consistency, and training stability compared to baseline methods. Full article
(This article belongs to the Topic Advanced Technology for Oil and Nature Gas Exploration)
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21 pages, 11810 KB  
Article
ANN-Based Fuse Time–Current Characteristic Coordination for Short-Circuit Protection in Shipboard DC Integrated Power System
by Changkun Zhang, Xin Dong, Yinhuang Mao, Rongquan Yun, Weiqiang Liao, Chenghan Luo, Yao Chen, Yilong Wang and Wanneng Yu
J. Mar. Sci. Eng. 2026, 14(8), 745; https://doi.org/10.3390/jmse14080745 - 18 Apr 2026
Viewed by 271
Abstract
To meet the dual requirements of selectivity and rapidity in fuse-based short-circuit protection for shipboard DC Integrated Power Systems (DC IPS), this paper proposes a novel coordination method. This approach employs an artificial neural network (ANN) to map the inherent time–current characteristic (TCC) [...] Read more.
To meet the dual requirements of selectivity and rapidity in fuse-based short-circuit protection for shipboard DC Integrated Power Systems (DC IPS), this paper proposes a novel coordination method. This approach employs an artificial neural network (ANN) to map the inherent time–current characteristic (TCC) curves of all fuses onto a unified time–current coordinate plane. Protection selectivity is then evaluated based on the relative positions of these curves, and by prioritizing fuses with shorter operating times, both selectivity and rapid fault clearance are achieved. Furthermore, through a mathematical analysis of the current relationships between faulted and non-faulted distribution circuits, the ANN is formulated to require only current and time data while maintaining robustness to moderate variations in short-circuit transition resistance. The effectiveness of the proposed method is validated using DC IPS cases of a hybrid passenger vessel and a pure electric sightseeing vessel. Compared with conventional coordination methods, the proposed method simultaneously accounts for the TCCs of protective devices and the influence of transition resistance on short-circuit current behavior. The case study results demonstrate that the proposed method achieves both selective and rapid protection, and shows strong potential for broader application in the coordination of multi-source DC power systems. Full article
(This article belongs to the Section Ocean Engineering)
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35 pages, 6664 KB  
Article
Dynamic Modeling and Integrated Optimization Design of a Biomimetic Skipping Plate for Hybrid Aquatic–Aerial Vehicle
by Fukui Gao, Wei Yang, Lei Yu, Zhe Zhang, Wenhua Wu and Xinlin Li
J. Mar. Sci. Eng. 2026, 14(8), 744; https://doi.org/10.3390/jmse14080744 - 18 Apr 2026
Viewed by 368
Abstract
A hybrid aquatic–aerial vehicle (HAAV) is a novel type of aircraft capable of both aerial flight and underwater navigation. Inspired by the swan’s gliding and landing motion on water surfaces, this study investigates the dynamic modeling and integrated optimization design of an HAAV [...] Read more.
A hybrid aquatic–aerial vehicle (HAAV) is a novel type of aircraft capable of both aerial flight and underwater navigation. Inspired by the swan’s gliding and landing motion on water surfaces, this study investigates the dynamic modeling and integrated optimization design of an HAAV equipped with a biomimetic skipping plate. By comprehensively accounting for the aerodynamic, impact, hydrodynamic, and frictional forces during the water entry process, a dynamic model for the HAAV’s gliding water entry is established. The reliability of the model is verified through comparisons between numerical simulations and theoretical predictions. Parametric modeling of the skipping plate’s configuration and layout is performed to analyze the influence of different parameters on the water entry dynamics. With the objectives of minimizing the overload and pitch angle variation, a hybrid infilling strategy based on a radial basis function neural network (RBFNN) surrogate model is constructed to improve optimization efficiency. This is combined with a quantum-behaved particle swarm optimization (QPSO) algorithm to conduct the multi-objective optimization of the biomimetic plate, thereby obtaining its optimal configuration and layout parameters. The results demonstrate that the established dynamic model is effective and can accurately capture the kinematic characteristics of the gliding water entry process. The error between the peak load and the pitch angle variation is less than 5%. Compared with the direct QPSO algorithm, the proposed method reduces the number of model evaluations by 66.7%, the computational time by 52.1%, and the optimal solution response value by 12.01%, demonstrating strong potential for engineering applications. Full article
(This article belongs to the Special Issue Dynamics, Control, and Design of Bionic Underwater Vehicles)
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21 pages, 3679 KB  
Article
Interannual Wave Climate Variability and Its Role in the Shoreline Evolution of a Barrier Island in Southeastern Brazil
by Filipe Galiforni-Silva, Carlos Roberto de Paula Junior, Léo Costa Aroucha, Paulo Henrique Gomes de Oliveira Sousa and Eduardo Siegle
J. Mar. Sci. Eng. 2026, 14(8), 743; https://doi.org/10.3390/jmse14080743 - 18 Apr 2026
Viewed by 372
Abstract
Sandy shorelines respond to variability in boundary conditions over a wide range of time and spatial scales. While recent studies show that climate modes may affect shoreline evolution at interannual scales, such relationships remain unclear in the South Atlantic Ocean. Here, we investigate [...] Read more.
Sandy shorelines respond to variability in boundary conditions over a wide range of time and spatial scales. While recent studies show that climate modes may affect shoreline evolution at interannual scales, such relationships remain unclear in the South Atlantic Ocean. Here, we investigate whether climate mode-driven variability in wave climate influences shoreline evolution using Ilha Comprida, a barrier island on the southeastern Brazilian coast, as a case study. Offshore wave conditions from the ERA5 reanalysis were analyzed over the last four decades and propagated to the nearshore using wave modeling. Shoreline change was quantified from satellite-derived shoreline positions, and relationships with interannual climate modes were evaluated using climate indices. Results show that the wave climate is bimodal and dominated by swell, with strong seasonality and no significant long-term trend in storminess. The El Niño–Southern Oscillation (ENSO) influences wave energy and extremes, with La Niña phases associated with higher wave power without a change in wave direction. No significant signal of the Southern Annular Mode (SAM) was found. At the coast, shoreline evolution is controlled by long-term sediment redistribution driven by alongshore transport gradients. ENSO-related shoreline signals are weak and spatially limited, occurring only in lower Empirical Orthogonal Function (EOF) modes of variability. These results suggest that, at Ilha Comprida, ENSO mainly modulates episodic wave-driven events rather than long-term shoreline patterns, emphasizing the need to distinguish between short-term energetic variability and longer-term morphodynamic response. This distinction is important for coastal management because even where climate modes do not produce persistent long-term shoreline trends due to site-specific aspects, they may still modulate event-scale risk, which can vary independently of the long-term average shoreline behavior. Full article
(This article belongs to the Special Issue Learning from Geomorphological Adaptation of Coasts at Different Time Scales (2nd Edition))
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23 pages, 2201 KB  
Article
Benthic Hydroid Assemblages in the South Adriatic: Spatiotemporal Patterns and Life-Cycle Plasticity in Stylactis inermis
by Ivona Onofri, Davor Lučić, Marijana Hure and Barbara Gangai Zovko
J. Mar. Sci. Eng. 2026, 14(8), 742; https://doi.org/10.3390/jmse14080742 - 17 Apr 2026
Viewed by 361
Abstract
We investigated the biodiversity and spatiotemporal dynamics of benthic hydroids at two contrasting eastern South Adriatic sites: exposed, oligotrophic Lokrum Island and sheltered, nutrient-enriched Bistrina Bay. A total of 54 hydroid taxa were recorded, with substantially higher richness at Lokrum (42 taxa) than [...] Read more.
We investigated the biodiversity and spatiotemporal dynamics of benthic hydroids at two contrasting eastern South Adriatic sites: exposed, oligotrophic Lokrum Island and sheltered, nutrient-enriched Bistrina Bay. A total of 54 hydroid taxa were recorded, with substantially higher richness at Lokrum (42 taxa) than at Bistrina (24 taxa). Assemblage composition differed markedly between sites, confirming that local environmental conditions are a primary determinant of community structure, while shallow sublittoral assemblages showed the greatest temporal variability due to seasonally short-lived athecate species. The shared seasonal partitioning at both sites suggests that temperature-mediated life-cycle timing is a key structuring mechanism, and the sharp summer decline in richness underscores the need for multi-seasonal sampling. Laboratory observations of Stylactis inermis from Torre del Serpe near Otranto revealed notable life-cycle plasticity, with detached short-lived eumedusoids reverting to a sessile stolonal stage. This trait may promote persistence under fluctuating conditions while reducing field detectability. Together, these results provide the first seasonal, depth-stratified ecological baseline for monitoring eastern South Adriatic benthic communities under environmental and anthropogenic change. Full article
(This article belongs to the Section Marine Ecology)
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5 pages, 164 KB  
Editorial
Feature Review Papers in Geological Oceanography
by Markes E. Johnson
J. Mar. Sci. Eng. 2026, 14(8), 741; https://doi.org/10.3390/jmse14080741 - 17 Apr 2026
Viewed by 351
Abstract
Linkages between modern environments that host a panoply of complex ecosystems and their ancient counterparts preserved in the rock record are indispensable to our understanding and appreciation of the world we occupy [...] Full article
(This article belongs to the Special Issue Feature Review Papers in Geological Oceanography)
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17 pages, 1597 KB  
Article
Interpretation of the Preconsolidation Stress in Soft Clay Using the One-Dimensional Consolidation Test
by Dae-Jin Gwak, Kwangpil Park, Bum-Hee Jo and Sung-Ha Baek
J. Mar. Sci. Eng. 2026, 14(8), 740; https://doi.org/10.3390/jmse14080740 - 17 Apr 2026
Viewed by 459
Abstract
This study explores interpretation methods for determining the preconsolidation stress from one-dimensional consolidation test results. Twelve reconstituted clay specimens with targeted preconsolidation stresses of 60 and 120 kPa were prepared using commercial kaolinite and marine clays collected from coastal regions of South Korea. [...] Read more.
This study explores interpretation methods for determining the preconsolidation stress from one-dimensional consolidation test results. Twelve reconstituted clay specimens with targeted preconsolidation stresses of 60 and 120 kPa were prepared using commercial kaolinite and marine clays collected from coastal regions of South Korea. Five representative interpretation methods were applied, and the influence of maximum applied stress levels of 320, 640, and 1280 kPa was evaluated. The results indicate that the estimated preconsolidation stress varies considerably depending on both the interpretation method and the maximum applied stress, particularly for rounded compression curves with gradually changing virgin compression slopes. To address these limitations, a new interpretation approach is proposed. The method utilizes the rebound slope obtained from an unload–reload cycle and defines the virgin compression line through linear regression without identifying the recompression–virgin compression boundary. The proposed method demonstrated reduced sensitivity to the maximum applied stress and provided more reproducible estimates for rounded compression curves, although further validation using natural clays considering sample disturbance effects is required. Full article
(This article belongs to the Special Issue Marine Geotechnical Applications in Marine Structures)
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28 pages, 2111 KB  
Article
Simulation-Based Safety Evaluation of Mixed Traffic with Autonomous Vehicles in Seaports
by Jingwen Wang, Anastasia Feofilova, Yadong Wang, Jixiao Jiang and Mengru Shao
J. Mar. Sci. Eng. 2026, 14(8), 739; https://doi.org/10.3390/jmse14080739 - 16 Apr 2026
Viewed by 582
Abstract
The increasing deployment of autonomous vehicles in port logistics requires safety assessment methods that remain valid in mixed traffic environments. This study evaluates the safety of mixed automated guided vehicle (AGV) and human-driven vehicle (HDV) traffic in a seaport terminal connected to an [...] Read more.
The increasing deployment of autonomous vehicles in port logistics requires safety assessment methods that remain valid in mixed traffic environments. This study evaluates the safety of mixed automated guided vehicle (AGV) and human-driven vehicle (HDV) traffic in a seaport terminal connected to an external urban road network. A microscopic traffic model was developed in AIMSUN Next to represent gate areas, internal roads, storage-yard access, berth interfaces, and external container-truck traffic. HDVs were modeled using a Gipps-based car-following model, whereas AGVs were represented through an Adaptive Cruise Control framework. Vehicle trajectories were exported to the Surrogate Safety Assessment Model (SSAM), where Time-to-Collision (TTC) and Post-Encroachment Time (PET) were used to detect and classify conflicts. Six staged fleet-composition scenarios were evaluated in 36 simulation runs, ranging from fully human-driven operation to full automation. Total conflicts decreased from 89 in the fully human-driven scenario to 43 in the fully automated scenario (−51.7%), while rear-end conflicts decreased from 70 to 30 (−57.1%). Crossing conflicts remained relatively stable across scenarios. At the same time, mean TTC decreased from 0.80 to 0.24 s and mean PET from 1.57 to 0.38 s, indicating tighter but more coordinated interactions under automated control. These results show that automation improves longitudinal safety performance in port traffic, but also that conventional TTC and PET thresholds calibrated for human-driven traffic may not be directly applicable to automated port operations. Automation-sensitive surrogate safety criteria are therefore needed for seaport mixed-traffic evaluation. Full article
(This article belongs to the Special Issue Deep Learning Applications in Port Logistics Systems)
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20 pages, 7422 KB  
Article
MAAT: A Marine-Aware Adaptive Tracker for Robust and Real-Time Multi-Object Tracking in Maritime Environments
by Xinjie Han, Qi Han, Yunsheng Fan and Dongdong Mu
J. Mar. Sci. Eng. 2026, 14(8), 738; https://doi.org/10.3390/jmse14080738 - 16 Apr 2026
Viewed by 410
Abstract
Multi-object tracking (MOT) is a key technology for enabling autonomous navigation of unmanned surface vehicle (USV) as it provides continuous perception of surrounding maritime targets and supports navigation decision-making. However, videos acquired on maritime platforms typically suffer from challenges such as platform-induced jitter [...] Read more.
Multi-object tracking (MOT) is a key technology for enabling autonomous navigation of unmanned surface vehicle (USV) as it provides continuous perception of surrounding maritime targets and supports navigation decision-making. However, videos acquired on maritime platforms typically suffer from challenges such as platform-induced jitter and nonlinear object motion, which significantly degrade tracking performance. To address these challenges, this paper builds upon ByteTrack by incorporating an adaptive Kalman filtering scheme and proposing a density-aware association strategy, resulting in a novel tracker termed the Marine-Aware Adaptive Tracker (MAAT). Specifically, an adaptive Kalman filter is introduced to increase the contribution of high-confidence detections during the state update process, thereby enhancing the stability and robustness of state estimation. Furthermore, to better mitigate the frequent identity switches caused by severe platform jitter from the USV observation platform, a density-aware association strategy is proposed. This strategy dynamically adjusts the composition of the cost matrix according to the density of high-confidence targets, enabling more reliable data association under varying scene conditions. Finally, the proposed tracking algorithm is evaluated against several state-of-the-art methods on the Singapore Maritime Dataset. It achieves competitive performance, attaining 44.37 MOTA and 43.857 IDF1. Moreover, MAAT operates in real time, running at 41.4 FPS. The experimental results demonstrate that MAAT is capable of performing accurate and real-time multi-object tracking in dynamic maritime environments with surface fluctuations, thereby providing effective technical support for intelligent maritime surveillance applications. Full article
(This article belongs to the Special Issue New Technologies in Autonomous Ship Navigation)
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23 pages, 5645 KB  
Article
A Theoretical Limit on Power Absorption in Variable-Shape Buoy Wave Energy Converters
by Mohammed Atallah and Ossama Abdelkhalik
J. Mar. Sci. Eng. 2026, 14(8), 737; https://doi.org/10.3390/jmse14080737 - 16 Apr 2026
Viewed by 325
Abstract
Despite the significant potential of ocean wave energy, the high cost of the generated power remains a major challenge. This highlights the need for innovative conceptual designs that enhance energy conversion while maintaining comparable implementation and installation costs. Recently, the concept of Variable-Shape [...] Read more.
Despite the significant potential of ocean wave energy, the high cost of the generated power remains a major challenge. This highlights the need for innovative conceptual designs that enhance energy conversion while maintaining comparable implementation and installation costs. Recently, the concept of Variable-Shape Buoy Wave Energy Converters (VSB WECs) was introduced that uses flexible buoy material. While many studies have demonstrated the improved performance of VSB WECs compared to Fixed-Shape Buoy Wave Energy Converters (FSB WECs) through numerical simulations, analytical validation is essential to support these findings. This paper presents an analytical derivation of the theoretical limit of power absorption for VSB WECs using the complex-conjugate criteria for the heave motion. In this study, a multi-degree-of-freedom (multi-DoF) VSB WEC model is developed using a thin spherical shell representation, incorporating Rayleigh–Ritz and Love approximations under the assumptions of small deformations and axisymmetric vibration. Hydrodynamic coefficients are computed using a Boundary Element Method (BEM) software. The variation in the theoretical power absorption limit with Young’s modulus is analyzed across a range of elastic materials. As a validation step, the derived theoretical limit criterion is applied to the standard reduced-order single-DoF model of an FSBWEC, successfully yielding the exact theoretical limit reported in the literature. Full article
(This article belongs to the Special Issue Exploitation and Optimization of Ocean Energy Conversion Infrastructure)
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20 pages, 5815 KB  
Article
Astronomically Constrained Palaeoclimate Reconstruction and Drivers of Organic Carbon Burial: Evidence from the Lower Eocene Wenchang Formation, Eastern Yangjiang Sag
by Rui Han, Shangfeng Zhang, Xinwei Qiu, Yaning Wang, Gaoyang Gong and Chengcheng Zhang
J. Mar. Sci. Eng. 2026, 14(8), 736; https://doi.org/10.3390/jmse14080736 - 16 Apr 2026
Viewed by 557
Abstract
Sub-sag 21 in the eastern Yangjiang Sag, Pearl River Mouth Basin, South China, contains a thick lacustrine source-rock interval within the lower Wenchang Formation and is a major exploration target on the northern margin of the South China Sea. However, the timing of [...] Read more.
Sub-sag 21 in the eastern Yangjiang Sag, Pearl River Mouth Basin, South China, contains a thick lacustrine source-rock interval within the lower Wenchang Formation and is a major exploration target on the northern margin of the South China Sea. However, the timing of deposition during the early to middle Eocene remains poorly constrained, and the applicability of quantitative palaeoclimate reconstruction methods in low-latitude lacustrine basins requires further evaluation. In this study, we analyzed mudstones from the lower Wenchang Formation in Well E1. Using cyclostratigraphic constraints, we applied AstroGeoFit to construct an astronomically tuned age model, and combined palynological coexistence analysis with geochemical weathering proxies and linear–regression calibration to quantitatively reconstruct and cross-validate mean annual temperature and mean annual precipitation. Within this time-calibrated framework, we further quantified organic-carbon burial to evaluate the relationship between palaeoclimate evolution and organic-matter enrichment. The AstroGeoFit results indicate that the top of the lower Wenchang Formation in Well E1 is constrained to 44.563 Ma, and that the studied succession spans 50.249–44.563 Ma. Palynological coexistence analysis identifies three palaeoclimate phases within this interval. Method evaluation shows that the temperature reconstruction based on major-element geochemistry agrees well with the pollen-based temperature record, whereas one precipitation reconstruction based on weathering proxies shows the most robust agreement and stability relative to the pollen-based precipitation record. Reconstructed mean annual temperature ranges from 10.77 to 22.20 °C, and reconstructed mean annual precipitation ranges from 1188.27 to 1871.89 mm. Correlation analyses on the tuned timescale show that precipitation is more strongly associated than temperature with organic-matter accumulation parameters, including total organic carbon and organic carbon accumulation rate, indicating that organic carbon burial in the eastern Yangjiang Sag lake basin was mainly controlled by hydrological forcing. During the Early Eocene Climatic Optimum, carbon burial in low-latitude lakes was, therefore, not a simple response to elevated temperature, but instead reflected the integrated effects of precipitation, runoff, stratification, material supply, transport, and preservation. The evolutionary sequence further suggests that early high productivity was diluted by rapid sedimentation, reducing total organic carbon; subsequent cooling, lake deepening, and strengthened stratification enhanced organic matter preservation; and finally, tectonic subsidence together with regional humidification promoted the development and long-term preservation of high-quality lacustrine source rocks. Full article
(This article belongs to the Section Geological Oceanography)
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21 pages, 15046 KB  
Article
Prediction of Sound Speed Profiles Under Disturbance of Strong Internal Solitary Waves Using Bidirectional Long Short-Term Memory Network
by Hong Yin, Ke Qu, Han Wang and Guangming Li
J. Mar. Sci. Eng. 2026, 14(8), 735; https://doi.org/10.3390/jmse14080735 - 15 Apr 2026
Viewed by 410
Abstract
Time-series machine learning models represented by long short-term memory (LSTM) networks provide an effective way to obtain high-precision sound speed profiles (SSPs) quickly and at low cost, which can meet the practical application requirements of underwater sonar systems. However, in sea areas with [...] Read more.
Time-series machine learning models represented by long short-term memory (LSTM) networks provide an effective way to obtain high-precision sound speed profiles (SSPs) quickly and at low cost, which can meet the practical application requirements of underwater sonar systems. However, in sea areas with frequent strong internal solitary waves, the large-amplitude sound speed anomalies caused by them will seriously interfere with model learning in the form of strong outlier features, resulting in a sharp drop in SSP prediction accuracy and significant degradation of the generalization stability and robustness of the model. To address this problem, this paper proposes a time-series SSP prediction method based on a bidirectional long short-term memory (Bi-LSTM) network. First, Empirical Orthogonal Function (EOF) decomposition is used to realize the low-dimensional feature representation of SSPs, and then the bidirectional time-series feature capture capability of Bi-LSTM is used to predict the SSP sequence with large disturbances caused by strong internal solitary waves. Multiple groups of comparative experiments based on the measured temperature chain data in the continental slope area of the South China Sea show that the Bi-LSTM model has a significant improvement in prediction accuracy and robustness compared with the classical LSTM model. Among them, the Bi-LSTM model with EOF decomposition achieves a correlation coefficient of 0.995 and an average Root Mean Square Error (RMSE) as low as 0.387 m/s. Under the condition of internal solitary wave disturbance, the classical LSTM is difficult to effectively capture the large abrupt change in sound speed, while the proposed Bi-LSTM model can still achieve accurate prediction of the SSP in the disturbance section, and has both the feature recognition and evolution prediction capabilities for the strongly nonlinear internal solitary wave process. This method provides effective technical support for the rapid and large-scale reconstruction of the sound speed field under the disturbance of strong internal solitary waves. Full article
(This article belongs to the Section Ocean Engineering)
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25 pages, 2881 KB  
Article
Feasibility Analysis of Underwater Vehicle Detection Based on Homogeneous Ellipsoidal Hull Model Using Gravity Gradient
by Hexing Zheng, Jinguo Liu and Haitao Gu
J. Mar. Sci. Eng. 2026, 14(8), 734; https://doi.org/10.3390/jmse14080734 - 15 Apr 2026
Viewed by 427
Abstract
In recent years, as underwater vehicles continue to improve their noise reduction capabilities, sonar-based detection has faced significant challenges, and non-acoustic detection has become a research focus. Gravity gradient detection, owing to its excellent concealment and anti-interference capability, is regarded as an important [...] Read more.
In recent years, as underwater vehicles continue to improve their noise reduction capabilities, sonar-based detection has faced significant challenges, and non-acoustic detection has become a research focus. Gravity gradient detection, owing to its excellent concealment and anti-interference capability, is regarded as an important non-acoustic means for underwater target detection. Based on the structural characteristics of an underwater vehicle, this paper establishes a homogeneous ellipsoidal hull (HEH) model composed of two similar rotating ellipsoids. This model assumes that the mass of an underwater vehicle is completely uniformly distributed over the outer hull. Analytical formulas for the gravity anomaly and gravity gradient anomaly generated by this model are derived, and their spatial distribution characteristics are analyzed. Furthermore, based on the HEH model, the feasibility underwater vehicle detection using the vertical gravity gradient component is analyzed. Results show that when the accuracy of the gravity gradiometer reaches 10−4 E, the detection distance for a large underwater vehicle with a displacement of 18,750 t can reach 570 m. Full article
(This article belongs to the Special Issue Advanced Modeling and Intelligent Control of Marine Vehicles)
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30 pages, 2640 KB  
Article
Environment-Aware Optimal Placement and Dynamic Reconfiguration of Underwater Robotic Sonar Networks Using Deep Reinforcement Learning
by Qiming Sang, Yu Tian, Jin Zhang, Yuyang Xiao, Zhiduo Tan, Jiancheng Yu and Fumin Zhang
J. Mar. Sci. Eng. 2026, 14(8), 733; https://doi.org/10.3390/jmse14080733 - 15 Apr 2026
Viewed by 390
Abstract
Underwater dynamic target detection, classification, localization, and tracking (DCLT) is central to maritime surveillance and monitoring and increasingly relies on distributed AUV-based robotic sonar networks operating in passive listening and, when required, cooperative multistatic modes. Achieving a robust performance in realistic oceans remains [...] Read more.
Underwater dynamic target detection, classification, localization, and tracking (DCLT) is central to maritime surveillance and monitoring and increasingly relies on distributed AUV-based robotic sonar networks operating in passive listening and, when required, cooperative multistatic modes. Achieving a robust performance in realistic oceans remains challenging, because sensor placement must adapt to time-varying acoustic conditions and target priors while preserving acoustic communication connectivity, and because frequent reconfiguration under dynamic currents makes classical large-scale planning computationally expensive. This paper presents an integrated deep reinforcement learning (DRL)-based framework for passive-stage sonar placement and dynamic reconfiguration in distributed AUV networks. First, we cast placement as a constructive finite-horizon Markov decision process (MDP) and train a Proximal Policy Optimization (PPO) agent to sequentially build a collision-free layout on a discretized surveillance grid. The terminal reward is formulated to jointly optimize the environment-aware detection performance, computed from BELLHOP-based transmission loss models, and global network connectivity, quantified using algebraic connectivity. Second, to enable time-critical reconfiguration, we estimate flow-aware motion costs for all AUV–destination pairs using a PPO with a Long Short-Term Memory (LSTM) trajectory policy trained for partial observability. The learned policy can be deployed onboard, allowing each AUV to refine its path online using locally sensed currents, improving robustness to ocean-model uncertainty. The resulting cost matrix is solved via an efficient zero-element assignment method to obtain the optimal one-to-one reassignment. In the reported simulation studies, the proposed Sequential PPO placement method achieves a final reward 16–21% higher than Particle Swarm Optimization (PSO) and 2–3.7% higher than the Genetic Algorithm (GA), while the proposed PPO + LSTM planner reduces average travel time by 30.44% compared with A*. The proposed closed-loop architecture supports frequent re-optimization, scalable fleet operation, and a seamless transition to communication-supported cooperative multistatic tracking after detection, enabling efficient, adaptive DCLT in dynamic marine environments. Full article
(This article belongs to the Section Ocean Engineering)
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27 pages, 2909 KB  
Article
Integrated Spatial Planning as a Framework for Climate Adaptation in Coastal and Marine Systems
by Francisco Javier Córdoba-Donado, Vicente Negro-Valdecantos, Gregorio Gómez-Pina, Juan J. Muñoz-Pérez and Luis Juan Moreno-Blasco
J. Mar. Sci. Eng. 2026, 14(8), 732; https://doi.org/10.3390/jmse14080732 - 15 Apr 2026
Viewed by 548
Abstract
Coastal socio-ecological systems are increasingly exposed to the combined pressures of climate change, land-use intensification, hydrological alterations and expanding infrastructure networks. These pressures interact across the land–catchment–lagoon–sea continuum, generating complex feedbacks that challenge traditional planning instruments, which remain sectoral and fragmented. The Mar [...] Read more.
Coastal socio-ecological systems are increasingly exposed to the combined pressures of climate change, land-use intensification, hydrological alterations and expanding infrastructure networks. These pressures interact across the land–catchment–lagoon–sea continuum, generating complex feedbacks that challenge traditional planning instruments, which remain sectoral and fragmented. The Mar Menor (SE Spain), a semi-enclosed Mediterranean lagoon affected by intensive agriculture, urbanisation, hydrological modifications and recurrent extreme climatic events, exemplifies this systemic vulnerability. Existing planning frameworks—local urban plans, regional territorial plans, river basin management plans, maritime spatial plans and lagoon-specific strategies—operate independently, each addressing only a fragment of the system and none integrating climate change as a structuring axis. This article introduces Integrated Spatial Planning (ISP) as a novel territorial–climatic framework designed to overcome these limitations. ISP integrates climate forcing, land uses, catchment processes, lagoon dynamics, marine conditions, critical infrastructures, intermodal and energy corridors and multilevel governance into a single analytical structure. A central component of the methodology is a four-zone multilevel zoning system that connects municipal, regional, basin, marine and EEZ planning domains within a unified territorial–climatic logic. The ISP matrix is applied to the Mar Menor to produce the first holistic diagnosis of the system. Results reveal strong land–sea–catchment interactions, high climatic exposure, vulnerable infrastructures and structural governance fragmentation. The matrix exposes systemic incompatibilities and vulnerabilities that remain invisible in sectoral planning instruments. The discussion demonstrates how ISP clarifies the roles and responsibilities of each governance level, supports multilevel coherence and integrates critical infrastructures and intermodal corridors into climate-resilient planning. ISP reframes climate change as the organising principle of territorial planning and provides a replicable, scalable methodology for coastal socio-ecological systems facing accelerating climate pressures. The Mar Menor case illustrates the urgent need for integrated territorial–climatic governance and positions ISP as a scientifically robust and operationally viable pathway for long-term adaptation and resilience. Full article
(This article belongs to the Special Issue Marine Climate Models and Environmental Dynamics)
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