Journal of Marine Science and Engineering

20 pages, 21577 KB

Open AccessArticle

Regulating Thermal Performance and Emission Characteristics of a Large-Bore Two-Stroke Marine Diesel Engine Fueled with Methyl Decanoate/Diethyl Ether Blends: A Full-Cylinder CFD Study

by Shiye Wang, Peiyuan Wang, Jianghua Sui and Haopeng Chen

J. Mar. Sci. Eng. 2026, 14(14), 1347; https://doi.org/10.3390/jmse14141347 - 22 Jul 2026

Viewed by 253

Abstract

A full-cylinder CFD model was developed to investigate methyl decanoate (MD)/diethyl ether (DEE) blends in a MAN B&W 7S80ME-C9 two-stroke diesel engine at 75% load. The model retained the multi-injector configuration, asymmetric spray development, scavenging and exhaust processes, and in-cylinder combustion of the [...] Read more.

A full-cylinder CFD model was developed to investigate methyl decanoate (MD)/diethyl ether (DEE) blends in a MAN B&W 7S80ME-C9 two-stroke diesel engine at 75% load. The model retained the multi-injector configuration, asymmetric spray development, scavenging and exhaust processes, and in-cylinder combustion of the 800 mm-bore engine. Four equal-energy cases, MD100, MD95, MD90, and MD85, were considered, with DEE energy fractions of 0%, 5%, 10%, and 15%. DEE blending regulated spray evaporation, mixture formation, heat-release phasing, and expansion work conversion. Increasing the DEE fraction enhanced evaporation and gas-phase mixing, but stronger mixing did not necessarily improve thermal performance. The peak-pressure trend differed from the net indicated work trend, indicating that work output was governed more by pressure evolution during expansion than by peak pressure alone. MD90 maintained stronger post-injection heat release and a more favorable equivalence-ratio distribution, thereby achieving the highest net indicated work, 6.70% higher than MD100. Although MD90 showed a high mean temperature, it produced the lowest NO and NO₂ emissions because NO_X formation depended on the local coupling of temperature, oxygen availability, equivalence ratio, and residence time. The CO₂ level was lowest for MD100 among the four fuel cases. At 75% load, MD90 provided a favorable balance among heat-release phasing, net indicated work, and emission control across the four investigated fuel cases. Full article

(This article belongs to the Section Ocean Engineering)

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24 pages, 3049 KB

Open AccessArticle

Formation Collision Avoidance Control of Underactuated Surface Vessels Under Input Constraints

by Xiaoming Xia, Yiming Jia, Zhiyang Zhang and Zhaolie Tang

J. Mar. Sci. Eng. 2026, 14(14), 1346; https://doi.org/10.3390/jmse14141346 - 22 Jul 2026

Viewed by 229

Abstract

In this paper, the collision-avoidance formation control problem for underactuated surface vessels (USVs) subject to input constraints is investigated. The input constraints include both input amplitude saturation and input rate saturation. A controller based on barrier Lyapunov functions (BLFs) is developed for the [...] Read more.

In this paper, the collision-avoidance formation control problem for underactuated surface vessels (USVs) subject to input constraints is investigated. The input constraints include both input amplitude saturation and input rate saturation. A controller based on barrier Lyapunov functions (BLFs) is developed for the considered system. First, a disturbance observer is designed to compensate for environmental disturbances and model uncertainties that degrade system performance. Second, an auxiliary dynamic system is introduced to handle input amplitude saturation and input rate saturation. To guarantee connectivity preservation and collision avoidance within the formation, the distance errors and angle errors are transformed using BLFs. Based on the transformed errors and the disturbance observer, a BLF-based anti-saturation controller is then constructed. Lyapunov stability analysis proves that all signals in the closed-loop system are bounded. Finally, simulation results demonstrate that the proposed method can achieve collision-free formation control under both input amplitude saturation and input rate saturation, and verify that the control system achieves fast convergence, small tracking errors, and collision avoidance while satisfying the input magnitude and rate constraints. Full article

(This article belongs to the Section Ocean Engineering)

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30 pages, 10197 KB

Open AccessArticle

Autonomous Approach and Stable Tracking of Dynamic Target for Intelligent Ship Using Recurrent Soft Actor-Critic

by Zixuan Qiu, Shaosong Min and Cong Liu

J. Mar. Sci. Eng. 2026, 14(14), 1345; https://doi.org/10.3390/jmse14141345 - 22 Jul 2026

Viewed by 181

Abstract

Dynamic target tracking is a challenging task for autonomous ships due to the continuous variation of relative motion states and the requirement for coordinated control of position, heading, and speed. This paper proposes a task-oriented continuous decision-making framework based on Soft Actor-Critic (SAC) [...] Read more.

Dynamic target tracking is a challenging task for autonomous ships due to the continuous variation of relative motion states and the requirement for coordinated control of position, heading, and speed. This paper proposes a task-oriented continuous decision-making framework based on Soft Actor-Critic (SAC) reinforcement learning for the autonomous approach and stable following of dynamic target vessels. A finite-history-enhanced SAC framework is developed by incorporating LSTM-based sequence encoding into the policy and value networks to capture recent evolution patterns of target motion and own-ship maneuvering responses. Furthermore, a sector-annular tracking region defined by distance and relative bearing constraints is constructed and a multi-component reward function is designed to integrate distance convergence, heading adjustment, region maintenance, speed matching, and control smoothness into policy learning. Simulation experiments under straight-line motion, curved motion, and randomized initial conditions demonstrate that the proposed SAC-LSTM method achieves improved task completion capability and control quality compared with SAC, PPO, and DDPG under the same task settings. Compared with standard SAC, SAC-LSTM improves the average success rate by 7.5 percentage points, reduces the average episode length by approximately 22.0%, and decreases the average heading error by approximately 35.5%. Additional sequence-length analysis, reward-component ablation, and multi-level disturbance tests further validate the effectiveness of the proposed design. The results indicate that the proposed method provides an effective solution for continuous decision-making in dynamic target tracking tasks. Full article

(This article belongs to the Section Ocean Engineering)

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24 pages, 5234 KB

Open AccessArticle

Refined Prediction of Strain-Softening Parameters of Marine Soft Clay Using Cyclic T-Bar Penetration Tests

by Yujian Sun, Qinglai Fan, Cunzhong Sun, Zhaoxia Lin and Yunrui Han

J. Mar. Sci. Eng. 2026, 14(14), 1344; https://doi.org/10.3390/jmse14141344 - 22 Jul 2026

Viewed by 256

Abstract

T-bar penetrometers are widely utilized for measurements of strength characteristics of soft clay in offshore field investigations and laboratory tests. To obtain strain-softening parameters of marine soft clay, it is necessary to conduct cyclic T-bar tests below the critical penetration depth. Therefore, this [...] Read more.

T-bar penetrometers are widely utilized for measurements of strength characteristics of soft clay in offshore field investigations and laboratory tests. To obtain strain-softening parameters of marine soft clay, it is necessary to conduct cyclic T-bar tests below the critical penetration depth. Therefore, this study conducted CEL large-deformation finite-element analyses to simulate the entire penetration process of T-bar in strain-softening soils. An equation for predicting the critical penetration depth is proposed, taking into account both the amount and the rate of strength reduction of clay. The numerical results indicate that the minimum depth for initiating the pull-out phase of the cyclic test is the full-flow penetration depth plus three times the T-bar diameter, which ensures that the surrounding soil remains in a full-flow mechanism throughout the cyclic test. Moreover, a refined resistance degradation model is proposed, which corrects a defect in the existing model, which is that when the number of cycles is equal to N₉₅, the predicted result of the model does not reach 95% degradation in penetration resistance. Then, an estimation method for strain-softening parameters of soft clay is developed. The method based on the refined resistance degradation model is verified by comparing the estimated values with the numerical simulation results in this paper and the available test data. Full article

(This article belongs to the Section Geological Oceanography)

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17 pages, 3846 KB

Open AccessArticle

Cross–Spectrum–Based Shallow Water Retrieval Using High–Resolution C–Band Miniaturized SAR Satellites

by Lingfeng Zhou, Quankun Li, Liangsheng Li, Xupu Geng and Xiao-Hai Yan

J. Mar. Sci. Eng. 2026, 14(14), 1343; https://doi.org/10.3390/jmse14141343 - 22 Jul 2026

Viewed by 267

Abstract

Topographic and geomorphic information provides an essential basis for human development and utilization of natural resources, disaster prevention and mitigation, ecological environment protection, and scientific research. Among spaceborne remote sensing approaches, Synthetic Aperture Radar (SAR) stands out due to its ability to actively [...] Read more.

Topographic and geomorphic information provides an essential basis for human development and utilization of natural resources, disaster prevention and mitigation, ecological environment protection, and scientific research. Among spaceborne remote sensing approaches, Synthetic Aperture Radar (SAR) stands out due to its ability to actively transmit and receive microwave signals, enabling high spatial coverage, all–weather, and all–day observation. With the rapid development of miniaturized satellite constellations, high–revisit and high–resolution SAR data have become more accessible, offering unprecedented opportunities for dynamic ocean observation. However, existing SAR–based bathymetry methods based on power–spectrum analysis are susceptible to sea–spike noise and 180° directional ambiguity, limiting their accuracy in shallow coastal waters. To address these limitations, a Cross–Spectrum–based Wave Ray Tracking bathymetry retrieval algorithm (CS–WRT) is developed using high–resolution imagery from mini–SAR constellations including HiSea–1 and Chaohu–1. The method incorporates cross–spectrum analysis into a localized wave ray tracking framework to effectively suppress sea–spike noise and accurately extract shallow–water wave vectors. Applied to six SAR images over the Taiwan Strait, CS–WRT consistently outperformed the power–spectrum approach in coastal environments. In the Jinjiang coastal region, comparison with Electronic Navigational Chart (ENC) data yielded a root mean square error of 2.22 m, a mean absolute percentage error of 7.06%, and a Pearson correlation coefficient of 0.84. Analysis of the shoaling slope parameter k further revealed that stronger wave shoaling effects correlate with improved retrieval accuracy, suggesting its potential as a diagnostic indicator of retrieval reliability. Full article

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16 pages, 4609 KB

Open AccessArticle

Theoretical Analysis and Optimal Design of Underwater Towed Body Dynamic Stability

by Junhao Chen and Linfeng Chen

J. Mar. Sci. Eng. 2026, 14(14), 1342; https://doi.org/10.3390/jmse14141342 - 22 Jul 2026

Viewed by 247

Abstract

This study presents the analysis of towed stability and the optimization design method for an underwater towed body, aiming to design a towing system with high stability, good hydrodynamic performance and a high degree of safety and reliability. By proposing analytical models for [...] Read more.

This study presents the analysis of towed stability and the optimization design method for an underwater towed body, aiming to design a towing system with high stability, good hydrodynamic performance and a high degree of safety and reliability. By proposing analytical models for both the static and dynamic behavior of the towing system, the influence of the structural characteristics on the motion of the towed body were determined. The Computational Fluid Dynamics (CFD) method was employed to conduct hydrodynamic numerical simulations of the towed body, obtaining precise hydrodynamic coefficients. The optimization design of the towed body’s center of gravity and cable connecting point position was carried out. The simulation results systematically revealed the influence of towing speed and cable length on the dynamic behavior of the towed body. With the speed increasing from 4 kN to 20 kN the depth of the towed body reduces from 277.0 m to 90.6 m, the tension of the cable inreases from 11.5 kN to 171.85 kN. At a towing speed of 20 kN, the optimized towed body stay at an averaged pitch angle of

{6.82}^{°}

with very small roll angles. This research provides theoretical and numerical analyzing approach for the design of high-performance underwater towed bodies. Full article

(This article belongs to the Section Ocean Engineering)

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38 pages, 6405 KB

Open AccessArticle

Linear Stability of Sand Ridges in Three-Dimensional Models: The Role of Mass Conservation and Velocity Shear

by Gaoyang Li

J. Mar. Sci. Eng. 2026, 14(14), 1341; https://doi.org/10.3390/jmse14141341 - 22 Jul 2026

Viewed by 243

Abstract

Depth-averaged 2D models have shown considerable success at predicting the presence of tidal sand ridges in the nearshore environment while only requiring minimal efforts of parameter tuning. 3D models, on the other hand, fail to predict the growth of coarse-grain sand waves unless [...] Read more.

Depth-averaged 2D models have shown considerable success at predicting the presence of tidal sand ridges in the nearshore environment while only requiring minimal efforts of parameter tuning. 3D models, on the other hand, fail to predict the growth of coarse-grain sand waves unless unrealistic assumptions on eddy viscosity are applied. When a vertically varying eddy viscosity profile is adopted in the model, sand waves will invariably be the fastest growing mode unless suspended load dominates, which contradicts observations. Through both numerical and analytical approaches, this paper will show that the residual circulation in the vertical plane due to mass continuity and vertical shear is a possible underlying mechanism that accounts for the dominant growth of sand waves. The strength of this residual circulation is proportional to the shear of the tidal velocity. A consequence is that sand ridges are more likely to develop in certain models with a small slip parameter in the bottom boundary condition (hence, less shear in tidal velocity), and such a parameter choice often, though not necessarily, leads to stronger mixing due to model configurations. Hence, sand waves are favoured in coastal seas due to the strong shear of the tidal current. The above findings suggest that there could be some unresolved processes that cause a transition in the bedform-building mechanism, which eventually inhibits the growth of sand waves and promotes the growth of sand ridges. Full article

(This article belongs to the Section Geological Oceanography)

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13 pages, 1239 KB

Open AccessArticle

The Development and Application of a Continuous Monitoring System for Environmental Radioactivity

by Stylianos Alexakis and Christos Tsabaris

J. Mar. Sci. Eng. 2026, 14(14), 1340; https://doi.org/10.3390/jmse14141340 - 22 Jul 2026

Viewed by 269

Abstract

This study presents the development and application of a continuous monitoring system to operate in hybrid mode for the atmospheric and oceanic environments. The developed system integrates a smart version of the underwater in situ sensor named KATERINA to a stationary platform in [...] Read more.

This study presents the development and application of a continuous monitoring system to operate in hybrid mode for the atmospheric and oceanic environments. The developed system integrates a smart version of the underwater in situ sensor named KATERINA to a stationary platform in order to operate as a real-time communication tool. The data are transferred using a mobile telephony network and the power is generated for all modules by a solar panel. The system is applied for a period of around six months in different seasons to detect and identify gradients of environmental radioactivity in the atmosphere. The system observed gamma-ray emitters during dry and wet periods, exhibiting enhanced radon progenies during wet periods as identified in the acquired spectra. Moreover, the gross gamma-ray intensity depends on the radon progenies and is used as a tracer to interpret rainfall events in a qualitative manner. The background gamma-ray spectra during dry periods for different seasons are also discussed in terms of seasonality. The correlation of gamma-ray intensity rate with the rainfall rate is also studied for the wet periods, providing a R² value of around 75%. Full article

(This article belongs to the Section Marine Pollution)

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26 pages, 6327 KB

Open AccessArticle

Numerical Investigation of the Lateral Loading Behaviour of Plate–Monopile Hybrid Foundations in Clay

by Yukun Ma, Subhamoy Bhattacharya, Haoyuan Liu, Kai Wen, Chuanjie Xu and Liang Cui

J. Mar. Sci. Eng. 2026, 14(14), 1339; https://doi.org/10.3390/jmse14141339 - 21 Jul 2026

Viewed by 231

Abstract

Plate–monopile hybrid foundations, as a potential alternative to monopiles, have demonstrated promising potential in enhancing load-bearing capacity and structural stability. To investigate its load transfer mechanisms and pile–soil interaction in clay, numerical models are developed under varying undrained shear strength (Su), pile diameter [...] Read more.

Plate–monopile hybrid foundations, as a potential alternative to monopiles, have demonstrated promising potential in enhancing load-bearing capacity and structural stability. To investigate its load transfer mechanisms and pile–soil interaction in clay, numerical models are developed under varying undrained shear strength (Su), pile diameter (D), and plate-to-pile diameter ratio (R). Through comparative analyses within different parameters configurations, the load-bearing capacity, pile deflection, bending moment and shear force distributions are systematically examined. The results indicate that: (1) Su, D and R are all positively correlated with the load-bearing capacity of the hybrid foundation, which can be expressed as the superposition of the monopile capacity and a quadratic function of R; (2) with increasing R, load transfer shifts from deep to shallow soil, accompanied by an upward pivot shift; increasing D causes a downward shift, more pronounced in weak soils; (3) for small-diameter hybrid foundation, the bending moment decreases progressively with increasing R, while for large-diameter, a stage-dependent response is observed, characterised by local moment concentration near the mudline within a certain range of R; (4) the shear force exhibits a double-peak pattern; increasing R strengthens the shallow peak and weakens the deep one, while increasing D localises the distribution near the mudline. Full article

(This article belongs to the Section Ocean Engineering)

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22 pages, 3656 KB

Open AccessArticle

Decoupling Causality from Correlation in Port Operations: A Small-Sample DML Approach for Sea–Rail Intermodal Systems

by Panfeng Hao, Li Wang, Xiaoning Zhu and Jiayu Liu

J. Mar. Sci. Eng. 2026, 14(14), 1338; https://doi.org/10.3390/jmse14141338 - 21 Jul 2026

Viewed by 279

Abstract

Container sea–rail intermodal transport is pivotal to the low-carbon transformation of global supply chains. However, traditional performance evaluation systems are prone to circular reasoning fallacies due to the nesting of input and output indicators and frequently suffer from spurious regression when analyzing high-dimensional [...] Read more.

Container sea–rail intermodal transport is pivotal to the low-carbon transformation of global supply chains. However, traditional performance evaluation systems are prone to circular reasoning fallacies due to the nesting of input and output indicators and frequently suffer from spurious regression when analyzing high-dimensional macro time series under small-sample constraints. To address these endogeneity and attribution challenges, this study proposes a four-step progressive causal inference framework. Taking Tianjin Port—a pioneering hub of China’s “road-to-rail” freight restructuring policy—as the empirical subject, we use quarterly operational data covering a complete cycle from 2017Q1 to 2024Q4. First, we construct a strictly exogenous high-quality development index based on turnover efficiency, logistics cost reduction, and carbon emission mitigation, which completely isolates scale input factors. Second, from an initial pool of 35 operational and macroeconomic indicators, 17 candidate variables are rigorously pre-screened according to statistical consistency and logistics system theory. Third, an adaptive Double Machine Learning (DML) model integrated with leave-one-out cross-fitting is applied to disentangle complex collinearity among variables. The results show that DML effectively eliminates confounding noise, accurately identifies 15 true causal drivers, and excludes spurious correlations such as redundant macro-infrastructure investment. Furthermore, a causally weighted composite index reveals that the intermodal system exhibits strong resilience to global supply chain fluctuations and has undergone a four-stage evolution. Its development momentum has fundamentally shifted from extensive scale expansion to a refined mode driven by the synergy of efficiency and service quality. This study provides a robust methodological paradigm for port performance evaluation and targeted decision support for resource allocation. Full article

(This article belongs to the Special Issue Sustainable Maritime Transport, Ports, Supply Chain Intelligence, and Marine Environmental Engineering)

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20 pages, 16269 KB

Open AccessArticle

Structural Response of Stiffened Panels Under Repeated Impacts from Rigid and Ice Hammers: An Experimental and Numerical Study

by Nan Zhao, Yuwen Xu, Fei Li, Tongqiang Yu and Kun Liu

J. Mar. Sci. Eng. 2026, 14(14), 1337; https://doi.org/10.3390/jmse14141337 - 21 Jul 2026

Viewed by 263

Abstract

Repeated-impact tests were carried out on a typical stiffened panel using both a wedge-shaped ice indenter and, for comparison, a rigid steel indenter under identical conditions. The tests were performed on a drop-weight impact system under a mass-loaded configuration, and the impact force, [...] Read more.

Repeated-impact tests were carried out on a typical stiffened panel using both a wedge-shaped ice indenter and, for comparison, a rigid steel indenter under identical conditions. The tests were performed on a drop-weight impact system under a mass-loaded configuration, and the impact force, deformation response, and failure characteristics were recorded. Numerical simulations were additionally conducted to analyze the structural response and damage evolution. Progressive permanent deformation was observed under both impact types, whereas ice impact produced stronger fluctuations and a more scattered peak-force history. The differences between the two impact modes are clarified, providing a reference for the impact-resistant design and safety assessment of ships designed for ice-covered water. Full article

(This article belongs to the Special Issue Advanced Analysis of Ship and Offshore Structures)

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30 pages, 26269 KB

Open AccessArticle

Numerical Analysis of the Hydrodynamic Performance of a Connected Offshore Floating Photovoltaic Platform Array

by Yuan Zhang, Xudong Wang, Peng Xu, Xinxin Lyu, Zhaode Zhang and Zhanbin Meng

J. Mar. Sci. Eng. 2026, 14(14), 1336; https://doi.org/10.3390/jmse14141336 - 20 Jul 2026

Viewed by 354

Abstract

Offshore floating photovoltaic (FPV) platforms have attracted attention as a promising approach for expanding solar energy utilization in marine environments. However, the hydrodynamic behavior of connected FPV arrays and the associated mooring response under realistic offshore conditions remain insufficiently understood. In this study, [...] Read more.

Offshore floating photovoltaic (FPV) platforms have attracted attention as a promising approach for expanding solar energy utilization in marine environments. However, the hydrodynamic behavior of connected FPV arrays and the associated mooring response under realistic offshore conditions remain insufficiently understood. In this study, a numerical model of a connected offshore FPV platform array designed for the East China Sea is established using frequency-domain hydrodynamic analysis and time-domain simulations. The effects of module spacing and connector configuration are first examined for a twin-float system, and the optimized connection scheme is then applied to a 4 × 4 array. The motion responses, air-gap variation, and mooring performance of the array are evaluated under operational and extreme sea states. The results show that the surge response of the array is governed by an edge amplification effect under operational conditions, whereas the array tends to exhibit a more coordinated, quasi-rigid-body response as environmental loading increases. The heave response is influenced by wave shielding among adjacent units, while the pitch motion is strongly synchronized by the spring–damper connection system. The air-gap and mooring analyses indicate that the platform maintains sufficient freeboard and mooring safety margins under the considered sea states. These findings provide useful guidance for the preliminary design and safety assessment of connected offshore FPV arrays. Full article

(This article belongs to the Topic Marine Energy)

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16 pages, 2603 KB

Open AccessArticle

A Variational Dispersion Mode Decomposition Approach to Extracting Normal-Mode Interference Spectra from Broadband Acoustic Intensity Measurements

by Wei Gao and Guocheng Gao

J. Mar. Sci. Eng. 2026, 14(14), 1335; https://doi.org/10.3390/jmse14141335 - 20 Jul 2026

Viewed by 227

Abstract

The primary objective of separating normal-mode interference spectra (NMISs) is to extract more fine-grained coherent structures between different pairs of modes in a shallow water sound field. However, NMISs generally exhibit nonlinear phase frequency and amplitude frequency relationships in one-dimensional broadband sound intensity [...] Read more.

The primary objective of separating normal-mode interference spectra (NMISs) is to extract more fine-grained coherent structures between different pairs of modes in a shallow water sound field. However, NMISs generally exhibit nonlinear phase frequency and amplitude frequency relationships in one-dimensional broadband sound intensity measurements, which poses a challenge for effective separation. To address the difficulty arising from the nonlinearity of NMISs, this study presents a variational dispersion mode decomposition (VDMD) method. An innovation of VDMD is to incorporate the physical model of NMISs into the framework of Variational Nonlinear Chirp Mode Decomposition (VNCMD). First, it utilizes the waveguide invariant and the interference frequency factor to characterize the phase function of NMISs. Second, this parameterization of the nonlinear phase function provides an analytical expression for the gradient of the objective function in the variational optimization processing of VNCMD, thereby improving the efficiency of its iterative search and enabling accurate extraction of NMISs. Finally, experimental results from a Yellow Sea trial demonstrate that the separated NMISs agree well with the reference modes, validating the effectiveness of our proposed method. Full article

(This article belongs to the Section Ocean Engineering)

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26 pages, 3294 KB

Open AccessArticle

Beyond Nuclear Norm: Adversarial Spectral Distribution Alignment for Cross-Domain Underwater Object Recognition

by Yun Zhang and Lei Song

J. Mar. Sci. Eng. 2026, 14(14), 1334; https://doi.org/10.3390/jmse14141334 - 20 Jul 2026

Viewed by 265

Abstract

Cross-domain underwater object recognition is essential for intelligent visual monitoring in marine ranching, yet domain shift caused by varying water conditions and imaging devices severely degrades model performance. Existing adversarial domain adaptation methods align feature distributions to mitigate domain shift, but they often [...] Read more.

Cross-domain underwater object recognition is essential for intelligent visual monitoring in marine ranching, yet domain shift caused by varying water conditions and imaging devices severely degrades model performance. Existing adversarial domain adaptation methods align feature distributions to mitigate domain shift, but they often fail to preserve the fine-grained discriminative structure required for distinguishing visually similar marine species. Discriminator-free adversarial domain adaptation constrains only the sum of singular values, leading to projection distortion, thereby degrading target discriminability. We observe that the discriminative structure of the source domain is encoded in the singular value distribution of classifier outputs, and aligning this distribution across domains, rather than its sum, preserves discriminability during knowledge transfer. Based on this insight, we propose Adversarial Spectral Distribution Alignment (ASDA). ASDA consists of Spectral Distribution Alignment (SDA), which minimizes the Wasserstein distance between source and target singular value distributions, and a Dynamic Feature Queue (DFQ) with an adaptive length schedule that provides stable spectral distribution estimates across mini-batches. By enforcing singular value ratio consistency across all principal directions, SDA achieves fine-grained alignment, which reduces domain discrepancy while preserving discriminative features. Experimental results on two underwater image datasets demonstrate that ASDA outperforms existing domain adaptation methods. Full article

(This article belongs to the Section Marine Aquaculture)

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37 pages, 8632 KB

Open AccessReview

A Review of Medium–Long-Term Wind Energy Projection

by Yi Lai, Chong-Wei Zheng, Feng Zhang, Lei Wang and Hong Cheng

J. Mar. Sci. Eng. 2026, 14(14), 1333; https://doi.org/10.3390/jmse14141333 - 20 Jul 2026

Viewed by 245

Abstract

Reliable medium–long-term wind energy projection is essential in the planning, financing, and operation of large-scale offshore wind development. This study classified projection methods into three categories: statistical/empirical and climate-signal-driven methods, dynamical models with reanalysis and regional downscaling, and machine/deep learning and hybrid methods [...] Read more.

Reliable medium–long-term wind energy projection is essential in the planning, financing, and operation of large-scale offshore wind development. This study classified projection methods into three categories: statistical/empirical and climate-signal-driven methods, dynamical models with reanalysis and regional downscaling, and machine/deep learning and hybrid methods for bias correction, downscaling, and direct data-driven projection. Then, this study reviewed the technical framework, representative studies, and comparative strengths and limitations. The main finding was that the state of the art increasingly converged on “dynamical simulation plus statistical or machine learning correction”. Next, seven main bottlenecks, along with the countermeasures, were systematically presented: (i) difficult data quality control and insufficient observational representativeness, especially offshore; (ii) divergent, even contradictory, conclusions for the same region across data sources and research groups; (iii) large uncertainty in extrapolating 10 m winds to the continually rising turbine hub height; (iv) difficulty in quantifying and communicating non-stationarity and uncertainty to decision-makers; (v) engineering conversion errors from projected “wind resource” to deliverable “electricity”; (vi) systematic biases in the marine atmospheric boundary layer, strong winds, and extreme conditions; and (vii) unresolved reliability, interpretability, and out-of-distribution generalization of AI models. Correspondingly, three mutually reinforcing strands of countermeasures were proposed: first, strengthening the observational and benchmarking foundation through unified, open, quality-controlled observation networks with data-provenance standards and shared reference datasets and intercomparison protocols; second, advancing physics–data integration and uncertainty quantification through hybrid and physics-informed correction, regime-specific bias correction of boundary-layer and extreme-wind errors, and probabilistic frameworks that delivered and clearly communicated credible intervals; and third, closing the resource-to-electricity gap by embedding power-curve convolution, wake-loss modeling, and availability and technology derating into the projection workflow, with the aim of improving medium–long-term wind energy projection accuracy. Full article

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

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28 pages, 6968 KB

Open AccessArticle

Multi-Objective Ship Route and Speed Optimization Under Time-Varying Marine Environments Based on NSGA-II

by Junyi Wang, Shaojie Guo and Yihua Liu

J. Mar. Sci. Eng. 2026, 14(14), 1332; https://doi.org/10.3390/jmse14141332 - 20 Jul 2026

Viewed by 276

Abstract

Efficient ship voyage planning under time-varying marine environments is important for reducing fuel consumption, improving operational efficiency, and maintaining navigational safety. This study proposes an NSGA-II-based multi-objective ship route and speed optimization method that jointly optimizes intermediate waypoint positions and segment speeds. A [...] Read more.

Efficient ship voyage planning under time-varying marine environments is important for reducing fuel consumption, improving operational efficiency, and maintaining navigational safety. This study proposes an NSGA-II-based multi-objective ship route and speed optimization method that jointly optimizes intermediate waypoint positions and segment speeds. A three-objective framework is developed to minimize fuel consumption, voyage time, and a navigational safety index. Static navigational data are used for feasibility checking, while time-varying wind, wave, and current fields are matched with route segments according to their positions and sailing times. An Extra Trees-based fuel consumption model and a multi-factor safety index evaluation model are embedded into the segment-level evaluation process, and joint waypoint–speed encoding, grouped genetic operators, and constraint handling are incorporated into the NSGA-II framework. A case study on the Busan–Ningbo route shows that the proposed method generates a well-distributed Pareto non-dominated solution set and reveals clear trade-offs among the three objectives. The TOPSIS-based recommended route achieves a fuel consumption of 43.468 t, a voyage time of 34.599 h, and a safety index value of 0.830. Compared with the A* baseline route, the proposed method reduces fuel consumption, voyage time, safety index value, and route length by 5.08%, 3.52%, 20.61%, and 5.65%, respectively. Comparisons with the original NSGA-II and CMOPSO further show that the proposed method improves Pareto solution quality and route smoothness among the multi-objective optimization methods. Results from two representative oceanic route scenarios further demonstrate that the proposed framework can generate feasible Pareto solution sets and recommended routes under different voyage conditions. These results indicate that the proposed method can provide feasible, smooth, and balanced route–speed solutions for voyage optimization under complex marine conditions. Full article

(This article belongs to the Section Ocean Engineering)

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23 pages, 15884 KB

Open AccessArticle

ARGO-Net: An Adaptive Receptive-Field and Geometry-Oriented Network for Lightweight Ship Detection in Complex Maritime Scene

by Jing Qu, Qiang Zhou, Bimeng Zhang, Yude Zhu and Kai Chen

J. Mar. Sci. Eng. 2026, 14(14), 1331; https://doi.org/10.3390/jmse14141331 - 20 Jul 2026

Viewed by 201

Abstract

Deploying robust ship detectors in real-world maritime environments is severely bottlenecked by the dual challenges of strictly constrained computational resources and complex background interferences, such as dense berthing, wake patterns, and SAR speckle. To solve these problems, we propose ARGO-Net, a highly efficient [...] Read more.

Deploying robust ship detectors in real-world maritime environments is severely bottlenecked by the dual challenges of strictly constrained computational resources and complex background interferences, such as dense berthing, wake patterns, and SAR speckle. To solve these problems, we propose ARGO-Net, a highly efficient architecture tailored for multi-modal maritime detection. At its core, ARGO-Net extracts physically meaningful and highly discriminative features through three targeted innovations. First, a Background Suppression and Reconstruction Module (BSRM) is developed to mitigate irregular coastal clutter and speckle in the frequency domain, reconstructing resilient spatial representations. Second, to capture the intrinsic morphological properties of ships, the High-Resolution Preserving Feature Network (HRPFN) employs geometry-oriented strip convolutions alongside an adaptive scale mechanism, effectively preserving the structural continuity of elongated hulls across extreme scale variations. Finally, a Semantic–Detail Alignment Fusion (SDAF) module is introduced to resolve cross-level spatial mismatches, ensuring that deep semantic context precisely informs low-level boundary localization. Extensive evaluations on the SeaShips and SSDD benchmarks highlight the exceptional efficiency–accuracy balance of ARGO-Net. With a marginal footprint of merely 2.3 M parameters and 6.9 G FLOPs, ARGO-Net achieves 97.9%/75.4% (mAP@50/mAP@50:95) on SeaShips and 99.5%/79.3% on SSDD. The proposed framework demonstrates that integrating background-aware feature reconstruction with geometry-driven fusion yields state-of-the-art localization precision without compromising lightweight deployability. Full article

(This article belongs to the Section Ocean Engineering)

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25 pages, 12036 KB

Open AccessArticle

Spatio-Temporal Analysis and Multiscale Identification of Global Bulk Carrier Accident Blackspots

by Zhanzhu Li, Xiaohua Cao, Jin Chen and Hua Zhou

J. Mar. Sci. Eng. 2026, 14(14), 1330; https://doi.org/10.3390/jmse14141330 - 20 Jul 2026

Viewed by 287

Abstract

Bulk carriers play a critical role in global dry bulk transportation, and their safe operation is closely related to commodity supply chains, port continuity, and maritime governance. However, bulk carrier accidents are unevenly distributed across maritime space, and existing maritime blackspot studies are [...] Read more.

Bulk carriers play a critical role in global dry bulk transportation, and their safe operation is closely related to commodity supply chains, port continuity, and maritime governance. However, bulk carrier accidents are unevenly distributed across maritime space, and existing maritime blackspot studies are often limited by single-scale density estimation, unconstrained planar smoothing, and insufficient consideration of temporal persistence. These limitations make it difficult to distinguish robust accident-prone waters from scale-sensitive or temporally unstable hotspots. To address this problem, this study proposes a constrained multiscale consensus framework for identifying and interpreting global bulk carrier accident blackspots. The framework first screens and standardizes global maritime accident records to extract valid bulk carrier accident samples. It then constructs an ocean-constrained equal-area analysis grid and estimates severity-weighted accident intensity under multiple Gaussian smoothing bandwidths. Scale-specific hotspots are further extracted through threshold-based segmentation and minimum-area filtering, and a consensus persistence rule is developed to classify core, secondary, and transition blackspots. Finally, threshold sensitivity analysis, bootstrap resampling, time-window comparison, lifecycle classification, accident-type stratification, and severity-weighted versus frequency-only comparison are conducted to evaluate the robustness and interpretability of the identified blackspots. Based on 38,139 raw accident records, the empirical analysis retained 1441 cleaned bulk carrier accidents from 2015 to 2023 and identified 87 core consensus blackspots, covering approximately 8.06 million km² and containing 863 accidents. These blackspots are mainly concentrated in major coastal shipping regions, and the proposed framework provides a reproducible and geographically constrained basis for global maritime blackspot identification. Full article

(This article belongs to the Section Ocean Engineering)

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23 pages, 5903 KB

Open AccessArticle

Dynamic Response Analysis of Floating Offshore Wind Turbines During Towing Operations

by Jianan Wu, Kuankuan Wu, Liangmao Lin, Haorui Si, Binghao Zhao and Dayong Zhang

J. Mar. Sci. Eng. 2026, 14(14), 1329; https://doi.org/10.3390/jmse14141329 - 20 Jul 2026

Viewed by 292

Abstract

Floating offshore wind turbines (FOWTs) have become an important structural configuration for deep-water offshore wind energy development. However, existing studies have mainly focused on towing experience for conventional offshore structures and static stability assessment, while a systematic understanding of the multi-body coupled dynamic [...] Read more.

Floating offshore wind turbines (FOWTs) have become an important structural configuration for deep-water offshore wind energy development. However, existing studies have mainly focused on towing experience for conventional offshore structures and static stability assessment, while a systematic understanding of the multi-body coupled dynamic response characteristics and hazardous response factors of large-scale FOWTs under combined wind, wave, and current loads remains limited. To address the insufficient understanding of critical hazardous response indicators in existing studies, a 10 MW semi-submersible floating wind turbine was investigated in this study. Variations in environmental loads, towline constraints, and FOWT responses during towing were incorporated into a multi-body coupled analysis framework, and the key hazardous response indicators governed by different dominant environmental factors were identified. The results indicate that increasing wind speed significantly amplifies the pitch response, with the extreme pitch angle reaching approximately −7.17° under the 24 m/s wind condition. Variations in current velocity have limited influence on response amplitudes. Wave height has the most pronounced effect on heave motion and nacelle acceleration. Under the 6.5 m wave height condition, their extreme values reach approximately −1.37 m and 1.15 m/s², respectively. Under the single-tug towing configuration, the 45° and 90° environmental directions induce pronounced lateral and yaw offsets, indicating insufficient path-keeping capability under unfavorable environmental directions. Comprehensive analysis demonstrates that pitch motion should be regarded as the primary hazardous response indicator under high wind speed conditions, while nacelle acceleration and heave motion require particular attention under high wave height conditions. Full article

(This article belongs to the Section Ocean Engineering)

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20 pages, 4074 KB

Open AccessArticle

Pore-Scale Imaging of CO₂–Water Displacement: Experimental Insights from Microfluidics

by Jiaxun Xu, Yijun Shen, Yi Hong, Zhao Lu and Shiguo Wu

J. Mar. Sci. Eng. 2026, 14(14), 1328; https://doi.org/10.3390/jmse14141328 - 20 Jul 2026

Viewed by 267

Abstract

Geological storage of carbon dioxide (CO₂) in deep-sea formations represents a pivotal strategy for mitigating atmospheric CO₂ levels, where storage security and efficacy are fundamentally governed by the pore-scale seepage behavior of CO₂. However, the microscopic displacement mechanisms [...] Read more.

Geological storage of carbon dioxide (CO₂) in deep-sea formations represents a pivotal strategy for mitigating atmospheric CO₂ levels, where storage security and efficacy are fundamentally governed by the pore-scale seepage behavior of CO₂. However, the microscopic displacement mechanisms of CO₂–water two-phase flow under the characteristic high-pressure, low-temperature conditions of the deep sea remain inadequately understood. This study employed a self-developed high-pressure microfluidic experimental platform (0–30 MPa, 4–50 °C) to systematically investigate the CO₂ displacement process in porous media. The effects of injection rate (0.001–5 mL/min) and system pressure (1, 5, and 10 MPa) on displacement patterns, front stability, and final saturation were quantified. The results demonstrate that injection rate is the primary controller of displacement stability: high rates (≥0.1 mL/min) induce viscous fingering and lower final saturation, whereas low rates (≤0.05 mL/min) promote stable, piston-like displacement. Crucially, elevated pressure exerts a profound stabilizing effect, effectively suppressing fingering instabilities and enhancing final gas saturation (up to 0.544 at 10 MPa). This work elucidates the synergistic regulatory mechanism between injection rate and confining pressure, providing essential pore-scale experimental evidence for optimizing injection parameters to achieve efficient and secure CO₂ storage in deep-sea reservoirs. Full article

(This article belongs to the Special Issue Advanced Studies of Hydrate-Bearing Marine Sediments)

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30 pages, 11156 KB

Open AccessArticle

Coupled Aero-Hydro-Elastic Response Analysis of 16 MW Semi-Submersible and TLP Floating Wind Turbines

by Kangzhe Li, Jinghong Shang, Liang Liu, Xuliang Han, Xing Zheng and Guangyuan Cheng

J. Mar. Sci. Eng. 2026, 14(14), 1327; https://doi.org/10.3390/jmse14141327 - 20 Jul 2026

Viewed by 328

Abstract

This study investigates the dynamic performance characteristics of 16 MW-class floating wind turbines supported by semi-submersible and tension leg platform (TLP) concepts, with the aim of providing guidance for platform selection. High-fidelity coupled aero-hydro-servo-elastic models were developed in OpenFAST for both floating platform [...] Read more.

This study investigates the dynamic performance characteristics of 16 MW-class floating wind turbines supported by semi-submersible and tension leg platform (TLP) concepts, with the aim of providing guidance for platform selection. High-fidelity coupled aero-hydro-servo-elastic models were developed in OpenFAST for both floating platform configurations. Dynamic simulations were carried out under operational conditions for five wind–wave inflow directions with aligned environmental loading. The responses of the floating systems were comprehensively evaluated in terms of platform six-degree-of-freedom motions, tower structural behavior, blade aeroelastic loads, and aerodynamic performance. The results show that the TLP configuration provides enhanced hydrodynamic stability, reduced platform motions, and improved aerodynamic efficiency compared with the semi-submersible platform. In contrast, the semi-submersible configuration exhibits lower aeroelastic loading levels. Furthermore, platform-induced hydrodynamic excitations significantly amplify the elastic responses of both the tower and blades, leading to noticeable variations in aerodynamic performance. These findings provide useful insights into the design and selection of next-generation large-scale floating wind turbine platforms. Full article

(This article belongs to the Section Ocean Engineering)

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30 pages, 21174 KB

Open AccessArticle

Experimental, Numerical, and Analytical Investigation on the Crashworthiness of U-Shaped Stiffened Hull Plates Under Wedge-Shaped Impact

by Yue Tang, Shuai Zong, Lejun Shen and Jiangtao Zhai

J. Mar. Sci. Eng. 2026, 14(14), 1326; https://doi.org/10.3390/jmse14141326 - 20 Jul 2026

Viewed by 244

Abstract

The crashworthiness of stiffened hull plates is essential for improving ship safety under collision and grounding loads. In this study, the impact resistance and energy-absorption mechanism of a U-shaped stiffened hull plate subjected to a wedge-shaped impact are investigated through drop-weight tests, nonlinear [...] Read more.

The crashworthiness of stiffened hull plates is essential for improving ship safety under collision and grounding loads. In this study, the impact resistance and energy-absorption mechanism of a U-shaped stiffened hull plate subjected to a wedge-shaped impact are investigated through drop-weight tests, nonlinear finite-element simulations, and analytical derivations. The experimental results show that the specimen experiences local indentation of the face plate, folding of the U-shaped stiffener webs, and crack propagation along the stiffener direction. The maximum residual deformation reaches 112 mm, and the failure mode is governed by the combined effect of face-plate stretching, web folding, and tearing near the contact or welded region. A finite-element model is established in ABAQUS and validated against the experimental deformation mode and force–indentation response. Furthermore, an analytical model based on the plastic upper-bound theorem is proposed to predict the instantaneous structural resistance. The total resistance is decomposed into contributions from the face plate, inclined webs, cap plate, and the tearing correction term. The analytical prediction agrees reasonably with the experimental and numerical results, with a peak collision force of approximately 620 kN at an indentation depth of about 124.5 mm. The proposed method provides a practical reference for rapid resistance prediction and crashworthy design of U-shaped stiffened hull plates. Full article

(This article belongs to the Special Issue Advanced Analysis of Ship and Offshore Structures)

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16 pages, 4909 KB

Open AccessArticle

Deep-Sea Vector Geomagnetic Observations from a Mooring Platform: Instrument Demonstration and Geophysical Data Quality

by Xianfeng Li, Chenguang Liu, Qingjie Zhou and Yang Sun

J. Mar. Sci. Eng. 2026, 14(14), 1325; https://doi.org/10.3390/jmse14141325 - 20 Jul 2026

Viewed by 279

Abstract

Despite their importance for constraining lithospheric magnetization models, tracking secular variation in oceanic regions, and improving global geomagnetic field representations, long-term vector geomagnetic data from deep-sea environments remain scarce. In this study, we developed a three-axis fluxgate magnetometer mounted on a deep-sea mooring [...] Read more.

Despite their importance for constraining lithospheric magnetization models, tracking secular variation in oceanic regions, and improving global geomagnetic field representations, long-term vector geomagnetic data from deep-sea environments remain scarce. In this study, we developed a three-axis fluxgate magnetometer mounted on a deep-sea mooring platform to acquire continuous vector data at 580 m depth in the Western Pacific Ocean and assessed its performance through a 48 h observatory comparison and a 20-day at-sea trial. During the observatory test, the magnetometer achieved an instrumental accuracy of 0.2 nT (characterized under stable observatory conditions) and a noise floor of 0.09 nT, with Pearson correlations of 93.76–94.13% against reference scalar magnetometers. In the sea trial, the attitude-corrected, vector-synthesized total field agreed with two co-deployed Sentinel magnetometers at 230 m and 380 m depths, yielding Pearson correlations of 94.33% and 94.59%, respectively. All instruments coherently recorded diurnal variations with a peak-to-peak amplitude of approximately 50 nT. The inter-depth differences in mean total field—35,353 nT at 230 m, 35,337 nT at 380 m, and 35,285 nT at 580 m—are primarily attributable to uncalibrated instrument baselines, with secondary contributions from residual attitude correction errors. These results demonstrate that mooring platforms can support multi-depth vector geomagnetic observations over deployment timescales of weeks to months, providing a pathway toward spatially distributed deep-sea geomagnetic field monitoring. Full article

(This article belongs to the Special Issue Ocean Observations, Second Edition)

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23 pages, 6365 KB

Open AccessArticle

Stable Incremental Underwater Object Detection via Adaptive Representation Routing and Topology-Preserved Replay

by Shaodong Zhang, Feng Tian, Haiyang Yao, Jinhao Shi and Yongsheng Yan

J. Mar. Sci. Eng. 2026, 14(14), 1324; https://doi.org/10.3390/jmse14141324 - 19 Jul 2026

Viewed by 304

Abstract

Incremental object detection (IOD) is critical for autonomous underwater perception, where detectors deployed on long-duration underwater platforms must continuously adapt to evolving marine environments while retaining previously learned recognition and localization capabilities. However, underwater IOD is particularly challenging because visual degradation, small-object ambiguity, [...] Read more.

Incremental object detection (IOD) is critical for autonomous underwater perception, where detectors deployed on long-duration underwater platforms must continuously adapt to evolving marine environments while retaining previously learned recognition and localization capabilities. However, underwater IOD is particularly challenging because visual degradation, small-object ambiguity, background dominance, rare-class dilution, and non-stationary data distributions jointly cause structure instability in incremental representations. Existing response-based distillation methods, such as elastic response distillation (ERD), mainly preserve output-level responses and often rely on rigid backbone updating and static optimization strategies, making them insufficient for maintaining hierarchical representation stability under degraded and imbalanced underwater observations. To address these limitations, we propose a structure-stable underwater IOD framework that jointly regulates representation update, replay topology, and optimization dynamics within a unified stability–plasticity formulation. Specifically, Structure-Adaptive Residual Routing (SARR) replaces binary layer freezing with adaptive residual paths, task-aware gradient routing, and semantic-sensitive update gates, enabling parameter-efficient incremental representation routing. Topology-Aware Semantic Replay (TASR) maintains class prototypes, teacher-guided relation matrices, and decision-boundary anchor samples to preserve the neighborhood topology of rare old classes in the feature manifold. Uncertainty-Aware Plasticity–Stability Feedback (UPSF) dynamically adjusts classification and localization distillation strengths according to old-class forgetting risk, new-class learning difficulty, and localization uncertainty. Extensive experiments on UTDAC2020 and DUO demonstrate that the proposed method outperforms representative distillation- and transformer-based IOD baselines in most incremental settings. In particular, our method achieves 30.7% AP on UTDAC2020 under the 2 + 2 setting and narrows the gap to full-data training, validating the effectiveness of structure-stable representation evolution for robust incremental underwater object detection. Full article

(This article belongs to the Section Marine Environmental Science)

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28 pages, 16959 KB

Open AccessArticle

A Study on the Dynamic Ultimate Bearing Capacity of Box Girders Under Combined Hydrostatic Pressure and Whipping-Type Dynamic Bending Loads

by Jucheng Wang, Yongjun Wang, Jianji Tang, Kun Liu, Jiaxia Wang and Yonghao He

J. Mar. Sci. Eng. 2026, 14(14), 1323; https://doi.org/10.3390/jmse14141323 - 19 Jul 2026

Viewed by 261

Abstract

Hydrodynamic actions on ships may excite hull-girder whipping and generate short-duration global dynamic bending effects in the structure. To investigate the dynamic ultimate bearing capacity of box girders under such hydrodynamically induced whipping-type dynamic bending loads, a simplified box-girder structural segment is studied [...] Read more.

Hydrodynamic actions on ships may excite hull-girder whipping and generate short-duration global dynamic bending effects in the structure. To investigate the dynamic ultimate bearing capacity of box girders under such hydrodynamically induced whipping-type dynamic bending loads, a simplified box-girder structural segment is studied in this paper. A nonlinear dynamic finite element model is established under the combined action of hydrostatic pressure and equivalent whipping-type dynamic bending loads. Instead of directly applying localized slamming pressure, opposite rotational velocities with equal magnitudes are prescribed at the end reference points to equivalently represent the global bending response associated with whipping. This treatment allows the load-carrying characteristics and failure behavior of the box girder under transient dynamic bending to be examined. Geometric nonlinearity, material nonlinearity, the Cowper–Symonds strain-rate effect, and initial geometric imperfections are considered in the model. Stochastic finite element analysis and Monte Carlo simulation are further used to evaluate the influence of the randomness of Young’s modulus and loading strain rate on the probability distribution of the dynamic ultimate bearing capacity and structural reliability. The results show that the dynamic ultimate bearing capacity of the box girder increases with increasing strain rate, while its sensitivity to the strain rate decreases markedly when the strain rate exceeds 2.306 s⁻¹. A larger initial geometric imperfection amplitude leads to a more evident reduction in the ultimate capacity. The reliability analysis shows that an increase in the mean load effect significantly increases the failure probability; when the mean load effect is lower than the mean ultimate bending moment, an increase in the load standard deviation reduces structural reliability. This study provides a fundamental numerical reference for predicting the dynamic ultimate bearing capacity and conducting probabilistic safety assessment of box-girder structures subjected to whipping-type global dynamic bending. Full article

(This article belongs to the Section Ocean Engineering)

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19 pages, 9708 KB

Open AccessArticle

A BASM-Integrated LLM Reasoning Method for Multidimensional Vessel Anomaly Attribution and Decision Support

by Yongfeng Suo, Fangfang Luo and Tao Zhang

J. Mar. Sci. Eng. 2026, 14(14), 1322; https://doi.org/10.3390/jmse14141322 - 19 Jul 2026

Viewed by 195

Abstract

The attribution of anomalous vessel behaviors is crucial for maritime traffic supervision and safety decision-making. However, existing approaches often lack the capability to systematically interpret multidimensional anomaly features and reveal their underlying behavioral mechanisms, limiting the transparency and practical value of anomaly attribution. [...] Read more.

The attribution of anomalous vessel behaviors is crucial for maritime traffic supervision and safety decision-making. However, existing approaches often lack the capability to systematically interpret multidimensional anomaly features and reveal their underlying behavioral mechanisms, limiting the transparency and practical value of anomaly attribution. To address these challenges, we propose a multidimensional anomalous vessel behavior attribution and decision-support framework based on large language models (LLMs). Specifically, the framework first employs Behavioral Anomaly Semantic Mapping (BASM) to transform multidimensional anomaly features into structured semantic units governed by logical constraints; it then leverages knowledge-guided reasoning (KGRP-PCoT) with LLMs to perform multi-step inference, enabling systematic attribution from low-level anomaly observations to high-level behavioral mechanisms. Experiments conducted on AIS data from the Wusongkou waters demonstrate that the proposed framework significantly outperforms traditional methods. Quantitative evaluations show that the framework achieves a BLEU-4 score of 0.91 and a BERTScore of 0.98 when integrated with advanced LLMs like DeepSeek. Furthermore, the ablation study confirms that the proposed BASM and KGRP-PCoT mechanisms improve the BERTScore from approximately 0.86 to 0.98. It not only reveals the causal mechanisms underlying anomalous behaviors more accurately but also improves logical consistency and regulatory compliance, confirming its practical utility and decision-support value. Full article

(This article belongs to the Section Ocean Engineering)

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19 pages, 2631 KB

Open AccessArticle

A Manifold Alignment and Hierarchical Surrogate-Assisted Transfer Optimization Algorithm for Multi-UUV Shape Design

by Junyu Xiang, Xinjing Wang, Shengfa Wang, Guanghui Liu and Huachao Dong

J. Mar. Sci. Eng. 2026, 14(14), 1321; https://doi.org/10.3390/jmse14141321 - 19 Jul 2026

Viewed by 202

Abstract

In engineering practice, different requirements often give rise to distinct product designs. For the specific case of multi-UUVs, small-scale vehicles are typically designed with a rotational body shape to ensure superior hydrodynamic performance, whereas large-scale vehicles are often configured with a near-rectangular body [...] Read more.

In engineering practice, different requirements often give rise to distinct product designs. For the specific case of multi-UUVs, small-scale vehicles are typically designed with a rotational body shape to ensure superior hydrodynamic performance, whereas large-scale vehicles are often configured with a near-rectangular body shape to satisfy the demands of substantial payload capacity. These two tasks share a portion of common variables, while each also maintains its own task-specific variables. When each task is optimized independently, redundant computational efforts are incurred and inherent similarities among tasks remain unexploited, which frequently leads to suboptimal solutions. Typical multitask optimization algorithms assume completely heterogeneous tasks and therefore become inefficient when applied to this kind of partially heterogeneous problem. To address this, a manifold alignment and hierarchical surrogate-assisted transfer optimization algorithm (MAHSTO) is proposed in this work. In MAHSTO, an implicit knowledge transfer strategy is developed via manifold alignment. The design variables of both tasks are mapped onto a common low-dimensional latent space via manifold alignment, which enables implicit knowledge transfer across tasks. In addition, a hierarchical multisurrogate model with adaptive sampling is established. It comprises one shared global surrogate model that captures common trends across tasks and two task-specific surrogate models that focus on accurately fitting their respective tasks. Furthermore, an adaptive sampling criterion is adopted for different surrogate models to balance exploration and exploitation. Experiments on benchmark cases demonstrate that the proposed MAHSTO outperforms four state-of-the-art optimization algorithms, achieving the best performance in 58.3% of cases. Finally, MAHSTO is applied to the shape optimization of multi-UUVs. The results further verify its competitiveness in handling computationally expensive engineering problems. Full article

(This article belongs to the Special Issue Overall Design of Underwater Vehicles)

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18 pages, 8518 KB

Open AccessArticle

Acoustic-Intensity-Guided Local Grid-Refinement Sparse Bayesian Learning for Broadband Direction-of-Arrival Estimation Using a Single Acoustic Vector Sensor

by Weiyu Tan, Juan Hui, Zikai Wang and Wenwu Wang

J. Mar. Sci. Eng. 2026, 14(14), 1320; https://doi.org/10.3390/jmse14141320 - 19 Jul 2026

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Abstract

Broadband direction-of-arrival (DOA) estimation using a single acoustic vector sensor (AVS) is an important problem in passive underwater source localization and underwater acoustic signal processing, especially for compact underwater platforms and passive acoustic monitoring applications. However, conventional grid-based sparse Bayesian learning (SBL) may [...] Read more.

Broadband direction-of-arrival (DOA) estimation using a single acoustic vector sensor (AVS) is an important problem in passive underwater source localization and underwater acoustic signal processing, especially for compact underwater platforms and passive acoustic monitoring applications. However, conventional grid-based sparse Bayesian learning (SBL) may suffer from grid mismatch when the true bearing lies between adjacent predefined grid points. Although a dense grid can reduce this mismatch, it increases computational cost and dictionary coherence. To address this problem, this paper proposes an acoustic-intensity-guided local grid-refinement SBL method, termed AI-LGR-SBL. The pressure and particle-velocity channels are first used to construct acoustic intensity information and detect candidate source regions. The coarse bearing results then guide target-related spectral peak selection during SBL iterations, and local grid refinement is performed only around the selected directions. Simulations involving single-source and two-source scenarios show that AI-LGR-SBL yields sharper spatial spectra and lower estimation errors than conventional grid-based SBL. Compared with basic SBL, AI-LGR-SBL reduces the RMSE by approximately 10% in the low-SNR region and by 4–7% at relatively high SNRs. Compared with globally dense-grid SBL, it reduces the average runtime by approximately 47.3% and 43.6% in the single-source and equal-power two-source scenarios, respectively. Lake-trial data further demonstrate clear bearing–time trajectories and effective sub-grid peak refinement, supporting the feasibility of the proposed method for broadband underwater DOA estimation and passive source localization using a single AVS. Full article

(This article belongs to the Special Issue Advanced Research in Underwater Acoustic Signal Processing)

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30 pages, 13948 KB

Open AccessArticle

Encounter Scenario Generation and Simulation Based on a Wasserstein Generative Adversarial Network with Gradient Penalty for Autonomous Ships

by Jie Shi, Shengzheng Wang, Xiuzhi Chen, Xinwei Lin and Ranxuan Ke

J. Mar. Sci. Eng. 2026, 14(14), 1319; https://doi.org/10.3390/jmse14141319 - 18 Jul 2026

Viewed by 467

Abstract

Virtual testing is one of the key methods for evaluating the collision avoidance capabilities of autonomous ships, and test scenarios provide the fundamental basis for its implementation. However, generating test scenarios that are both diverse and physically realistic remains a significant challenge in [...] Read more.

Virtual testing is one of the key methods for evaluating the collision avoidance capabilities of autonomous ships, and test scenarios provide the fundamental basis for its implementation. However, generating test scenarios that are both diverse and physically realistic remains a significant challenge in this field. This paper proposes a ship encounter scenario generation and dynamic simulation method for encounter situations based on a Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP). Specifically, the proposed framework consists of a Collision Risk Index-guided-WGAN-GP (CRI-WGAN-GP) for initial encounter scenario generation and a Physics-Informed Conditional WGAN-GP (PI-CWGAN-GP) for dynamic encounter scenario simulation. In the first stage, the CRI-WGAN-GP is developed to generate initial encounter scenarios with collision-risk characteristics. The Collision Risk Index (CRI) is directly embedded into the discriminator of the WGAN-GP. This mechanism forces the latent space to learn risk correlations, enabling effective exploration of high-risk boundaries and generating test cases with collision risks for the target ship. In the second stage, the PI-CWGAN-GP is designed to generate sequential dynamic simulation scenarios conditioned on the current encounter situation. By incorporating constraints related to ship motion performance, the PI-CWGAN-GP ensures that the generated ship behaviors are physically realistic. The proposed method is experimentally evaluated based on scenario diversity and physical realism, and the experimental results demonstrate that the proposed method can generate initial scenarios with collision risks and simulate ship behavior in encounter situations. Compared to existing random sampling and general generative adversarial network methods, the proposed approach shows significant advantages in generating more realistic and high-risk scenarios. In addition, a stress-test analysis is conducted based on a real encounter scenario, with the historical own-ship trajectory replayed as a reference response. Since no specific collision-avoidance algorithm is exposed to the generated scenarios in closed loop, the evaluation is limited to examining the encounter pressure imposed by the generated target-ship behaviors. The results show that the generated counterpart scenarios reduce the original spatial and temporal safety margins and create more demanding encounter conditions. Full article

(This article belongs to the Special Issue Applications of Sensors and Artificial Intelligence Techniques in Ships)

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23 pages, 14865 KB

Open AccessArticle

Estuarine Salinity Inversion Using Acoustic Doppler Velocimetry (ADV): Methodology, Sensitivity and Environmental Modulations

by Yanhui Zhai, Pengxi Zhou, Huan Liu, Shengwen Liu and Mingli Zhao

J. Mar. Sci. Eng. 2026, 14(14), 1318; https://doi.org/10.3390/jmse14141318 - 18 Jul 2026

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Abstract

Retrieving the hydrophysical properties of water columns from acoustic backscatter signals is crucial for obtaining continuous and nonintrusive observations in estuarine environments. Utilizing the pulse coherent technology in the Acoustic Doppler Velocimeter (ADV), this study presents a methodology to estimate smoothed, low-frequency practical [...] Read more.

Retrieving the hydrophysical properties of water columns from acoustic backscatter signals is crucial for obtaining continuous and nonintrusive observations in estuarine environments. Utilizing the pulse coherent technology in the Acoustic Doppler Velocimeter (ADV), this study presents a methodology to estimate smoothed, low-frequency practical salinity in estuarine waters by integrating synchronized temperature and pressure datasets. Laboratory calibration experiments demonstrate that the Medwin formula achieves the highest inversion accuracy across a salinity range of 0 to 35 PSU, although data dispersion increases when salinity drops below 15 PSU. This methodology was further validated using field data, where acoustic intensity profiles were derived through multi-probe spatial averaging and quadratic polynomial fitting. Field application results show that a 300 min moving average filter extracts the lower frequency salt intrusion trend from turbulent noise, allowing the framework to track tidal-scale salinity variations with a low pass trend precision of ±3.07 PSU relative to reference instruments, whereas the raw unfiltered inversion exhibits a root-mean-square error (RMSE) of 5.68 PSU. The inversion performance is sensitive to ambient dynamics: the lowest error deviations occur within a moderate environmental window characterized by current velocities of 0.10–0.58 m/s and turbidities of 109.7–208.0 NTU. In contrast, the uncertainty increases during periods with higher velocities (up to 0.83 m/s) and severe turbidities (up to 278.1 NTU) or during slack water periods with current velocities below 0.10 m/s where the acoustic backscatter drops below 90 dB. These findings quantitatively define the environmental constraints for acoustic salinity estimations, providing a low-cost and non-intrusive methodological framework for recovering low-frequency salinity trends in dynamic estuaries. Full article

(This article belongs to the Section Ocean Engineering)

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