Journal of Marine Science and Engineering doi: 10.3390/jmse14171558

Authors: Utkarsh Bhardwaj

Reliability assessments of subsea systems are generally performed at two levels: structural reliability analysis of individual components and functional reliability analysis of the overall system using generic failure-rate databases. This study develops a component-to-system multi-scale framework that integrates these two levels for a subsea separation system operating at 3000 m water depth. At the component level, a Gaussian process regression (GPR) surrogate is developed from 474 finite element simulations of a vertical gravity separator. First-order reliability method (FORM) and Monte Carlo simulation (MCS) are then employed to assess the structural reliability, followed by a time-variant reliability analysis that accounts for corrosion effects. At the system level, the structural reliability model is integrated with functional failure rates through a Bayesian network that considers five equipment items and relevant risk-influencing factors. The surrogate model accurately predicts collapse pressure with an R2 value of 0.996. The intact separator achieves a reliability index of 4.55, satisfying the DNV high-safety-class target, with the structural failure mode contributing only 0.0034% of the separator failure rate. Under a corrosion rate of 0.4 mm/year, the reliability index decreases to 3.12 over a 25-year service period. The structural failure rate crosses the DNV medium-safety-class target of 10−4 per year at year 12, increasing the structural contribution to the overall system failure frequency to 0.33%. Sensitivity analysis indicates that initial ovality and wall thickness are the most influential parameters affecting structural reliability and should therefore be prioritized in design and integrity management strategies. The framework is demonstrated on this physics-consistent dataset; validation against independent nonlinear finite element analyses and experimental collapse data is identified as the necessary next step before the results are used for design.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161557

Authors: Yafei Ge Xiaoming Xia

This paper investigates a formation tracking problem for underactuated surface vessels (USVs) subject to collision avoidance and input saturation constraints. Many existing APF-based formation-control approaches formulate collision avoidance using a single reference point or an inter-center distance, which may provide insufficient geometric information during close-range maneuvers. To improve navigation safety, an elliptical disk-based collision avoidance mechanism is developed by introducing safety points at the bow, stern, port, and starboard sides of each USV, such that multiple characteristic-point distance constraints can be simultaneously enforced. To address unknown nonlinearities caused by model uncertainties and external disturbances, a neural network-based observer is designed to estimate unavailable velocity states and lumped disturbances. Distributed control laws are synthesized by integrating artificial potential functions (APFs), the observer, and a backstepping technique. Additional controllers are introduced to address the input saturation and underactuated issues while preserving the collision avoidance capability. Stability of the closed-loop system is rigorously established via Lyapunov theory. Simulation results demonstrate that the proposed approach achieves safer close-range maneuvering performance compared with conventional single-point methods.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161556

Authors: Yuqi Wu Yuanzheng Yang Hao Liang

This paper proposes an annular suction caisson specifically designed to reinforce in-service monopiles and upgrade existing offshore wind farms to accommodate larger-capacity wind turbines. During penetration of the annular suction caisson into clay, the existing monopile restricts the inward migration of soil into the internal space of the caisson, promoting upward soil displacement and consequently increasing the height of the soil plug formed inside the caisson. In addition, the strain-softening behavior causes varying degrees of strength degradation in the clay along the caisson wall. The softened zones extend approximately one caisson wall thickness on the inner side and 1.2 times the wall thickness on the outer side of the caisson. Both effects should be considered for accurately predicting the penetration resistance of annular suction caissons. Therefore, three-dimensional large-deformation finite element analyses were performed to investigate the penetration behavior of annular suction caissons in strain-softening clay. A comprehensive parametric study was conducted to quantify the soil plug heave and overall penetration resistance. Meanwhile, the soil flow mechanism at the caisson tip, the evolution of clay strength along the caisson wall, and the formation characteristics of the internal soil plug were systematically examined. Based on the numerical results, a theoretical approach was developed to evaluate the penetration resistance of annular suction caissons.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161555

Authors: Yan Wang Xupu Geng Yan Li Xiaohui Li Chenghan Luo Shaoping Shang Feng Zhang

Synthetic Aperture Radar (SAR) enables high-resolution sea-surface wind speed retrieval. However, the enhanced spatial resolution of SAR imagery introduces substantial challenges, from small-scale contamination sources that significantly degrade retrieval accuracy. Particularly in coastal regions, non-wind-related backscatter signals, such as ships and oil slicks, can severely bias wind speed estimates at sub-kilometer scales. In this study, the first-order moment (average, m1) and second-order moment (variance, m2) are computed from the normalized radar cross-section (NRCS) within sub-images of Sentinel-1 SAR data acquired in Interferometric Wide (IW) mode. Analysis reveals that clean-sea-surface signals in both VV and VH polarizations cluster around an approximately linear empirical trend, m2 = 2m1 + b, in the m1-m2 statistical feature space, whereas the examined contamination types deviate from this trend and occupy separable regions. Based on this characteristic, a quality-control framework is proposed for the systematic separation of clean sea surface from image noise (border noise and inter-swath stripe noise) and non-ocean targets (land contamination, bright targets, and dark spots). Validation using independent SAR data from the Taiwan Strait was conducted separately for native 10 m and height-adjusted 3 m buoy observations. For the native 10 m observations, the RMSE and MBE were essentially unchanged at 1.5 m/s and −0.3 m/s, respectively. For the height-adjusted nearshore observations, the RMSE decreased from 3.2 m/s to 2.1 m/s and the MBE changed from −1.5 m/s to −1.1 m/s.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161554

Authors: Ke Zhang Liujuan Xie Siyuan Ye Ken W. Krauss Lei He Xigui Ding Shixiong Yang Pan Zhou Zongmin Zhu Thomas J. Mozdzer Samantha K. Chapman Brian K. Sorrell Edward A. Laws Hans Brix

Although climate warming affects photosynthetic carbon sequestration in coastal wetland plants, the seasonality of this effect has not been assessed. We investigated the growth traits and photosynthetic properties of Phragmites australis by using open-top chambers (OTCs) to conduct a warming experiment in the coastal wetlands of the Yellow River Delta during a single growing season. The OTCs significantly elevated temperatures by ~1 °C across the growing season, and the effects of warming on stem diameter, net photosynthetic rate (Pn), and water use efficiency (WUE) were characterized by a significant month × warming interaction. Early-season carboxylation efficiency (φ) increased by 71%, but a significant late-season decline of Pn by 49% accompanied by a rise of intercellular CO2 concentrations (Ci) and decline of stomatal limitation (Ls) led to a seasonal shift from stomatal to non-stomatal (biochemical) limitation of growth. A consistent increase in plant height and Ci across all months and concomitant decrease in Ls indicated that the additive effects of warming were independent of phenological stage. The results revealed that the phenological mediation of warming responses is trait specific. Carbon cycle models should therefore adopt trait-specific parameterizations to accurately project the impact of the wetland carbon sink under future warming.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161553

Authors: Yaomin He Yimin Yang Zheng Li Liyuan Wang Jian Yang

Since heavy clutter seriously restricts the ability of radar to detect targets, it is significant to build the target detector under heavy clutter. For practical situations without the secondary data or prior knowledge of target and clutter, this paper proposes a polarization-space-time detector. First, a general radar model is constructed for multiple pulses, multiple arrays, and multiple polarizations. Based on the theory of ternary hypothesis, the secondary data free (SDF) GLRT detector is proposed, which can maintain the constant false alarm probability (CFAR) in inhomogeneous clutter. Then, this paper proposes a matrix transform operator and an adaptive detection method using sliding window. These two approaches do not need to know the steering vector of radar and the noncentral parameter of clutter in advance, so the SDF-GLRT detector can adapt to different application scenarios. In addition, this paper optimizes the polarization waveform of the radar system by constructing a projection matrix. This method yields closed-form solutions of the optimal polarization and worst polarization, rather than relying on numerical solution. Finally, the performances of the SDF-GLRT detector and three other detectors are compared by simulated and real data. The proposed SDF-GLRT maintains PFA of 5.4×10−3 and 2.6×10−3 on two IPIX datasets (#54 and #310) at a design PFA=10−3, whereas the other detectors deviate to 0.0249–0.7405. The optimal polarization yields a detection-probability gain of more than 0.22 over the worst polarization at SCR=0 dB.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161552

Authors: Jiaqi Guo Pengyang Song Hao Huang Xueen Chen

The Luzon Strait is a critical generation site for global internal tides. Their generation and propagation are significantly modulated by background currents, including the Kuroshio Current and mesoscale eddies. This study investigates nonlinear effects of these background currents on low-mode (modes 1–3) internal tides using a high-resolution numerical simulation. We apply the Taylor–Goldstein equation considering the Earth’s rotation and background currents to perform modal decomposition, and utilize a nonlinear internal tidal energy equation to quantify three crucial energy pathways: inter-modal energy conversion, nonlinear energy exchange with background currents, and nonlinear advection effects. Results demonstrate that while stationary mode-1 internal tides dominate in the generation region of the Luzon Strait, non-stationary energy increases significantly in the western and eastern propagation regions, driven largely by seasonal variability of the Kuroshio Current. Inter-modal energy conversion follows a cascade from lower to higher modes, with conversion efficiency increasing with mode number. Nonlinear exchanges between background currents and internal tides are one order of magnitude smaller than inter-modal conversions but exhibit a bidirectional transfer, where advection redistributes internal tidal energy within the eddy structures. This study provides a quantitative framework for understanding multiscale energy pathways of internal tides under complex ocean dynamics.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161551

Authors: Sharul Baggio Roslan Xin Wang Chunwee Ng

This paper reviews the application of Life Cycle Assessment (LCA), Life Cycle Cost Assessment (LCCA), and ship design optimisation methods and examines the extent to which these approaches have been integrated to support sustainable electric ship design. The main goal is to understand how these methods have been applied and where the key gaps remain. The review analyses current practices in environmental and cost assessments of ship systems and design, along with ship design optimisation methods aimed at improving energy efficiency and reducing emissions. Overall, the reviewed literature shows that LCA, LCCA, and ship design optimisation are generally applied as separate processes rather than parts of an integrated framework. Key gaps include the lack of models that account for time-varying costs, changes in technology and energy systems. Additionally, this paper highlights the need for integrated and adaptive frameworks, supported by open and standardised data and digital tools, to better connect environmental and economic considerations across a vessel’s life cycle, for more practical and sustainable ship design.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161550

Authors: Yongfei Zheng Guosun Zeng

Accurately forecasting waypoint-level tropical cyclone (TC) intensity, defined as the local wind speed at specific maritime route waypoints under TC influence, is crucial for navigation safety and voyage planning. Conventional studies mainly focus on the central intensity of TC systems and underutilize the complementary value of multimodal meteorological data with inconsistent sampling intervals. To address these challenges, this study proposes a multimodal-augmented conditional diffusion model (MADiff) for waypoint-level TC intensity prediction. To exploit the potential of multimodal inputs, we first design a temporal-adaptive dynamic convolution module (TDConv) to capture multi-timescale features, mitigating multimodal sampling discrepancies without rigid temporal alignment. Second, we develop a discriminative cross-fusion module (DisCF) to aggregate multi-timescale features across diverse modalities, quantifying multimodal heterogeneity and integrating valuable modality-specific features while suppressing noise interference. Fused features are fed into a diffusion model with physics-informed regularization to generate final intensity forecasts. Extensive experiments on four Western North Pacific datasets show that MADiff achieves average MAE and RMSE values of 2.08 kt and 2.37 kt, respectively, for 12 h intensity forecasting. Compared with the state-of-the-art baseline (TC-Clouds-DP), MADiff yields substantial performance improvements, reducing MAE by 16.3% and RMSE by 10.6% on average. This study provides an effective framework for fine-grained TC intensity forecasting, offering valuable insights for extreme marine weather early warning and intelligent navigation decision-making.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161548

Authors: Kaifeng Zhang Zhenhua Zhang

Ring-stiffened cylindrical shells are widely used as load-bearing components in submarine pressure-hull sections. Existing underwater explosion studies have mainly emphasized incident-face denting or global failure, leaving unresolved how circumferential shock-wave diffraction and internal structural load transfer produce different response sequences and plastic-strain accumulation at the incident, side, and rear faces. A mechanism-oriented underwater explosion model test was conducted using a 44 g TNT charge at a stand-off distance of 0.50 m, and a fluid–structure interaction model was established in MSC.Dytran using the general coupling method. The model incorporated the Cowper–Symonds strain-rate effect of 16MnR steel and was validated against the Cole empirical peak pressure and measured incident-face residual deformations. The calculated free-field peak pressure was 35.50 MPa, with an error of 0.65%, while the mean relative error of the six residual-deformation measurements was 13.50%. The shell plating between adjacent ring stiffeners exhibited higher velocity and acceleration peaks than the stiffeners, indicating the local constraint imposed by the ring stiffeners. The side-face nodes showed symmetric transverse expansion, and the corresponding elements exhibited no discernible equivalent plastic strain. The rear-face center displayed a delayed axial response, and its representative element reached a final equivalent plastic strain of approximately 1.32×10−3, compared with 0.40×10−3 for the incident-face element. These results identify distinct circumferential response modes and show that macroscopic motion amplitude is not simply correlated with local plastic deformation.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161549

Authors: Yuanting Ding Yi Liu Qiyi Du Jitao Yu

Long-term shoreline change on tropical islands is spatially heterogeneous, but alongshore contrasts remain insufficiently resolved. We quantified shoreline change along the 151.1 km eastern sandy coast of Hainan Island, China, from 1987 to 2025 using Landsat-derived visually interpreted shoreline proxies and the Digital Shoreline Analysis System across 1413 transects. The coast was broadly stable to accretional, with a mean linear regression rate (LRR) of 0.49 m/yr and a mean net shoreline movement (NSM) of 17.72 m. Under the uncertainty-aware classification, 28.0% of transects were stable, 42.1% accretional, 8.2% erosional, and 21.7% indeterminate. For descriptive comparison, the eight sectors were grouped into three broad alongshore zones: a stable northern zone (Beaches A–B), an accretion-dominated central zone (Beaches C–E), and a heterogeneous southern zone (Beaches F–H). The strongest accretion occurred at Beach D (LRR = 7.63 m/yr), whereas the strongest erosion occurred south of the offshore artificial island at Beach F (LRR = −3.97 m/yr). These contrasts show that coast-wide stability or accretion can mask localized erosion. The observed patterns were spatially associated with differences in headland-bay morphology, nearshore seagrass beds, engineering structures, estuarine processes, and lagoon-inlet settings. The findings support beach-sector monitoring and differentiated coastal management.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161547

Authors: Kai Zheng Huanqiu Xu Hongyu Cui Xianqiang Qu

Real-time monitoring of wave-induced loads supports ship masters’ scientific navigation decisions, where vertical bending moment is a core index representing hull longitudinal bending under waves. This paper combines a temporal convolutional network with the traditional section method to build a vertical bending moment identification model embedded with a section parameter correction mechanism. The main work includes the following: multiple wave condition strain–load datasets are generated via numerical simulations to train the model; the section method calibrates model parameters to boost prediction precision; and wave load tests are conducted to verify the model’s practicability. Results indicate the section method offers physical constraints that embed ship sectional features into the model, lifting identification accuracy, robustness and result rationality. This work applies a temporal convolutional network to the hull vertical bending moment identification with section parameter correction, offering technical references for hull structural safety evaluation and intelligent maritime decision-making.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161546

Authors: Jiazhao Sun Li Zou Nicolin Govender Zhimin Zhao Yingjie Hu Xiangqian Fan

Granular collapse-induced wave generation is a critical process in coastal engineering and natural hazards, yet its rapid and complex fluid–solid coupling mechanism poses significant challenges for numerical modeling. This paper presents a comprehensive validations and performance benchmarking study of non-spherical granular collapse-induced wave generation using a GPU-accelerated resolved SPH-DEM coupling framework. Through three benchmark cases with increasing complexity, the numerical accuracy and robustness of the model are thoroughly verified with respect to free-surface flows, multi-body collisions, and intense fluid–solid interactions. Subsequently, the influence of SPH resolution and particle shape on computational efficiency is quantitatively assessed. It is found that the total runtime is dominated by the number of SPH particles, while the GPU acceleration advantage becomes more pronounced as the number of DEM faces increases. Furthermore, in the granular collapse-induced wave case, the temporal evolution of the leading wave amplitude and the difference in granular runout distance under dry and wet conditions are analyzed, revealing from the particle scale how fluid resistance modulates the coupling between wave generation and granular motion. This study not only validates the capability of the model to capture complex particle–wave interactions, but also provides quantifiable performance benchmarks and physical insights for its engineering applications.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161545

Authors: Dejan Drajić Tomo Popović Srđan Krčo Nikola Vojičić Nives Ogrinc Vladimir D. Urošević

Aquaculture requires continuous environmental monitoring, yet low-cost IoT sensing in marine conditions remains poorly characterised, and the data it produces is rarely accompanied by mechanisms establishing its provenance. This paper presents an IoT sensor system for marine and coastal aquaculture, comprising solar-powered 4G multiparameter nodes, a cloud-native back-end with a RESTful layer, and integration with a blockchain-based change-detection mechanism supplying a GS1-compliant digital product passport. Four nodes in adjacent cages were deployed at a marine site on the Montenegrin Adriatic for eight weeks, measuring temperature, pH, dissolved oxygen, oxidation–reduction potential and conductivity at five-minute resolution. Lacking reference instrumentation, we use agreement between nodes for validation. Temperature showed the closest cross-node agreement, with nodes agreeing to within 0.28 °C, and resolved a coherent cold, low-salinity intrusion detected simultaneously by all four nodes. The electrochemical and optical channels proved precise but not accurate: they tracked relative change coherently while their absolute values diverged, with oxidation–reduction potential moving from 9 mV of agreement to 71 mV over the following weeks. Cross-node coherence in conductivity and dissolved oxygen degraded progressively over the deployment, with no electrochemical or optical channel remaining coherent beyond roughly six weeks. Such sensors suit anomaly detection without calibration but require periodic recalibration for absolute reporting. Tamper-evident provenance is therefore necessary but not sufficient: sensor-level quality assurance is its missing half.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161544

Authors: Xia Yang Kunkun Li Xiong Deng Dingfeng Yu Yiyun Peng Yan Luo Yanyang Wu

With the continuous expansion of deep-sea resource exploration, marine environmental monitoring, and underwater operations, Autonomous Underwater Vehicles (AUVs) have been increasingly widely applied. Aiming at the demand for high-performance main propulsion systems of Autonomous Underwater Vehicles (AUVs), this paper conducts research on the structural design and hydrodynamic performance of a 30 kW rim-driven thruster (RDT) and its coupling mechanism with AUVs. By combining computational fluid dynamics (CFD) simulations and experimental methods, the influence of the advance coefficient on the open-water performance of the thruster is revealed. An integrated coupling simulation model of the AUV and RDT is established to analyze the performance attenuation law of the thruster and the characteristics of the coupled flow field under wake flow conditions, and to clarify the two-way interaction mechanism between the thruster and AUV. Towing tank tests were carried out at sailing speeds ranging from 1 to 4 kn, which verifies the reliability of the numerical simulation model and the matching performance between the thruster and AUV. The results show that the open-water efficiency of the thruster reaches a peak value of 0.536 at the advance coefficient J=0.8, which is close to the optimal efficiency range with good matching performance of the propulsion system Under wake flow conditions, the attenuation range of the thrust coefficient of the thruster is 12.45–16.53% with the increase in advance coefficient. The main reasons are the uneven inflow velocity and unstable flow field pressure distribution caused by the non-uniform wake flow at the AUV stern. At the ship speeds of 2 kn, 3 kn and 4 kn, the self-propulsion rotational speeds obtained from test fitting are in good agreement with the simulation results, with all relative errors less than 8%. This study provides a theoretical basis and technical reference for the engineering design of medium and high-power rim-driven thrusters as well as the matching optimization of AUV-thruster systems.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161543

Authors: Long Yu Xingsheng Zhao Yunrui Han Li Cheng Xiaowei Feng Gang Yang Qing Yang

Model testing is an important method for investigating the interaction between marine structures and soil, and the preparation of high-quality saturated clay samples plays a crucial role in laboratory testing. In this study, a new method for preparing saturated soil samples was developed by combining vacuum extraction and permeation saturation, and its performance was validated through laboratory experiments. A series of laboratory tests, including the gravity and cutting-ring methods, was conducted on columnar soil samples to evaluate the impact of this new technique on soil properties. The results indicate that the soil samples prepared using the new method achieved saturation levels of at least 97% and spatial uniformity. In addition, a large-volume saturated clay sample preparation method was designed and experimentally validated specifically for large-scale model tests. Soil samples were prepared in a model box with dimensions of 300 mm (Lrec) × 300 mm (Wrec) × 200 mm (Drec) in 24–48 h. Both the T-bar penetration and vane shear tests were performed on the prepared soil samples to measure their undrained shear strength. The results show that the middle and lower layers of the large-volume soil samples exhibited spatial uniformity.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161542

Authors: Yafei Sun Kaijie Yang Miaomiao Zhang Mingsheng Zhang Juanjuan Tang

Land subsidence in coastal reclamation areas has emerged as one of the critical hidden hazards for coastal cities. This paper presents an integrated InSAR and coastline-change framework for land subsidence monitoring and driving-factor analysis in coastal reclamation cities. Taking the Fangchenggang City, China, as the study area, we utilized 266 scenes of Sentinel-1A SAR images (2016–2025) from the European Space Agency (ESA) and applied time-series SBAS-InSAR to obtain a 10-year time-series monitoring result of land subsidence, with cross-validation against PS-InSAR showing an RMSE below 4 mm at four checkpoints. Furthermore, influencing factors were analyzed by integrating data on coastline changes, precipitation, and groundwater indicators. The conclusions of this paper are as follows: (1) Seven distinct land subsidence funnels in Fangchenggang City from 2016 to 2025 were identified for the first time. Spatially, land subsidence exhibits significant heterogeneity, primarily concentrated in the coastal reclamation areas of the Qisha Peninsula and the Yuwan Peninsula, the maximum subsidence rate reached as high as −163.53 ± 4.90 mm/yr. Temporally, the subsidence rate in the study area shows a gradual deceleration trend over time. (2) The coastline change results from 1964 to 2025 reveal a three-stage temporal characteristic: the land area increased by 2.23 ± 4.51 km2, 14.28 ± 6.19 km2, and 23.31 ± 4.51 km2 during the periods of 1964–1995, 1995–2008, and 2008–2025, respectively. The time-series InSAR results and coastline change results demonstrate that coastal reclamation is the primary factor contributing to land subsidence in this study area. (3) Apart from land reclamation, driving factors such as precipitation and groundwater indicators also show a slight correlation with land subsidence.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161541

Authors: Sung-Jo Yun Hyogon Kim Ji-Wook Kwon Young-Ho Choi Dong-Hoon Kim Woong-Ki Lee Ji-Wan Kim Jun-Hyuk Choi

This study proposes a safety-enhanced path planning system that integrates a Control Barrier Function (CBF)-based Safety Shield with Deep Reinforcement Learning (DRL). This framework addresses the critical limitations of conventional DRL-based Unmanned Surface Vehicle (USV) navigation models, which can output hazardous control commands in edge cases and violate the International Regulations for Preventing Collisions at Sea (COLREGs). The proposed system continuously operates during navigation via an Encounter Classifier that identifies multi-vessel situations (such as Head-on, Crossing, and Overtaking) in real time. The nominal control inputs generated by the DRL policy are verified and safely filtered through a Control Barrier Function-Quadratic Programming (CBF-QP) optimization layer immediately prior to execution, incorporating ship safety radii and asymmetric COLREGs constraints. Furthermore, we introduce a ‘Shielded Training’ mechanism that penalizes the agent based on the magnitude of the shield’s interventions during the training loop. This effectively diminishes the policy’s over-reliance on the safety filter and guides the network toward discovering robust, inherently safe trajectories. Extensive simulations conducted under diverse single- and multi-vessel encounter scenarios quantitatively demonstrate that the proposed method substantially reduces collision and COLREGs violation rates compared to baseline DRL-only or reward-shaping methods, while maintaining excellent computational scalability and real-time responsiveness. Consequently, by unifying the adaptive environmental exploration of reinforcement learning with model-based runtime safety constraints derived from control theory, this study provides a practical runtime assurance framework for future marine deployment.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161540

Authors: Yong Yang Weijie Wang Yongkai Liu Zhaoyang Yuan Xiaobing Zhang Jun Ouyang Changsong Cai

Rapid three-dimensional electromagnetic field simulation in stratified marine environments is essential for underwater target sensing system design. This paper presents a Physics-Informed Deep Operator Network (PI-DeepONet) that integrates analytical Sommerfeld integral solutions with seafloor experimental measurements to establish a validated, mesh-free forward modeling framework for extremely low-frequency (ELF) electromagnetic propagation. The architecture uses Fourier feature encoding to resolve multiscale dipole fields and incorporates Maxwell’s divergence constraint through automatic differentiation. The model is evaluated using a tiered validation strategy that combines analytical benchmarks, controlled seafloor experiments, and comparison with a purely data-driven DeepONet. The results show close agreement across stratified marine scenarios, improved accuracy and physical consistency from the embedded constraint, and substantially faster pointwise inference than conventional finite element solvers. Analysis of near-field discrepancies further identifies seabed anisotropy and environmental uncertainty as important sources of model–experiment mismatch, thereby clarifying the framework’s applicability and limitations for marine sensing-system design.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161539

Authors: Chuanqi Zhu Jiani Zhang Yitong Li Liang An

Towed hydrophone arrays are widely employed for underwater target detection and direction-of-arrival (DOA) estimation. However, array shape distortion induced by ocean currents, internal waves, and platform maneuvers severely degrades beamforming performance and DOA estimation accuracy. In this paper, a novel Bayesian fusion framework is proposed to achieve robust array shape estimation. Specifically, based on the time-delay estimates derived from the phase differences of line-spectrum components in a pre-processing step, the array geometry is first reconstructed via a piecewise straight-line fitting method. Concurrently, an existing hidden Markov model (HMM)-based method is adopted to estimate the inter-segment deviation angles, in which the smoothness of the array shape is enforced through the state-transition probabilities. The proposed framework then treats these two preliminary estimates as observations from distinct sources and incorporates a smoothness prior within a maximum a posteriori (MAP) formulation that admits a non-iterative closed-form solution to enforce physical continuity constraints on the array geometry. By fusing these complementary estimates, the proposed method simultaneously preserves local sensitivity to fine-scale bends and maintains global consistency of the array shape. Both simulation and lake-trial experiments validate the effectiveness of the proposed method, reducing the array shape estimation error by more than 30% relative to representative existing methods. Moreover, by relying solely on the received acoustic data, the method lowers the dependence on auxiliary sensors and the associated system cost.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161538

Authors: Soonhyun Lee Kwang-Jun Paik Sua Jeong Jae-Hyeon An

The propulsion performance and propeller design of ships have traditionally been evaluated mainly under calm-water conditions. However, under actual sea conditions, waves can increase added resistance, change the stern wake distribution, reduce propulsive efficiency, and affect cavitation behavior. This study evaluates the propulsion performance and designs a propeller for an 1800 TEU container ship under regular wave conditions using computational fluid dynamics. Resistance and self-propulsion simulations are conducted for eleven wavelength ratios in the range of 0.5≤λ/LPP≤2.0, with a fixed wave steepness of H/λ=0.01. The results show that the required power increases significantly in the resonance wavelength range because of the combined effects of added resistance, wake variation, and reduced propulsive efficiency. The Brake Horsepower (BHP) transfer function obtained from the regular wave simulations is combined with representative sea-state spectra using the spectral method to estimate the Daily Fuel Oil Consumption (DFOC) under actual operating sea states. The total long term DFOC is estimated as 37.084 t/day. For the propeller design, the wake distribution at the propeller plane is analyzed at λ/LPP=1.1, as a representative wave condition where the ship motion and propulsion performance variation become significant. The wake analysis shows that the instantaneous inflow changes considerably according to the wave phase, which can affect blade loading and cavitation. Based on this analysis, a new propeller geometry is designed with the cavitation performance as the primary consideration while also improving the propulsion performance. The designed propeller reduces the cavity volume over the selected wave phases and decreases the delivered power by approximately 2.1% in calm water and 3.4% in wave conditions. These results demonstrate the importance of considering wake variation and cavitation characteristics in practical propeller design under actual operating conditions.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161537

Authors: Zhaoyan Liao Zhiqiang Du Hongyuan Zeng Kai Liu

Large-scale maritime activity, persistent shipping incidents, and complex marine environments continue to place substantial demands on maritime search and rescue (MSAR). Current MSAR systems do not fully capitalize on the complementary strengths of unmanned aerial vehicles (UAVs) and satellites for collaborative tracking and rescue support. Existing air-space collaboration technologies suffer from two critical limitations: (1) rigid processes, including fixed task allocation, pre-determined path planning without real-time environmental adaptation, and isolated satellite–UAV decision-making, and (2) long task completion cycles, mainly because many methods are adapted to wide-area, long-duration military tracking scenarios. They therefore provide limited support for the dynamic flexibility required in MSAR. This study proposes a Proximal Policy Optimization (PPO)-based air-space collaborative tracking method for maritime moving targets to address these shortcomings and enhance air-space cooperation in MSAR operations. The core implementation of the method includes: (1) integration of target drift forecasting, satellite orbit prediction, UAV task allocation, and path planning into a unified reinforcement learning framework to reduce isolated single-platform decision-making; (2) the adoption of PPO to generate dynamic and flexible air-space collaborative tracking strategies that adjust satellite observation angles and scanning ranges, as well as UAV altitude, speed, and heading according to real-time target, environmental, and platform states; and (3) the design of a multi-dimensional reward function that balances target proximity, energy efficiency, coverage overlap, and inter-platform cooperation to guide strategy optimization. Simulation experiments include system-feasibility verification, baseline-controller comparison, PPO hyperparameter screening, and cross-scenario evaluation. Under idealized communication and payload-matching assumptions, the method enables coordinated tracking of maritime moving targets in simulated MSAR scenarios. In the standardized evaluation, PPO achieved an 11.9% higher mean evaluation episode return, 11.2% lower aggregate UAV energy consumption, and a 9.92-percentage-point greater endurance margin than DDPG. Hyperparameter screening compared candidate learning rates, discount factors, and training budgets, informing the PPO configuration for the subsequent six-scenario evaluation. Across the six controlled scenarios, rewards stabilized after approximately 1400 steps, while action magnitudes varied among regions. These results indicate that the proposed method has potential to enhance air-space collaborative tracking for MSAR decision support.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161536

Authors: Kailing Guo Juncheng Chen Wei Cai Shuo Zhou Mengying Mu

This paper mainly investigates the ice-impact resistance of PVC foam sandwich beams for polar ship protective structures through low-velocity impact experiments and nonlinear finite element simulations. An experimentally validated elastic–plastic coupled model, accounting for ice crushing and large structural deformation, was used to examine the effects of core density and face-sheet thickness distribution on the ice-impact response of sandwich beams. Results show that the upper face sheet undergoes local indentation and global bending, the lower face sheet mainly bends globally, and the foam core exhibits local compression and overall bending, while compressive deformation accompanied by ice crushing and spalling occurs at the front part of the ice impactor. Moreover, the effective structural stiffness decreased during plastic loading as local indentation and core compression developed, whereas the unloading stiffness was higher than the effective stiffness during plastic loading. Energy dissipation primarily comes from ice crushing, face-sheet plasticity, and core compression. Increasing core density reduces deflection and core compression but increases peak force. Among the three face-sheet configurations examined at a constant total thickness, the configuration with a thinner upper face sheet and a thicker lower face sheet produced a smaller final deformation of the lower face sheet. This study provides a useful reference for ice-resistant design of sandwich structures in polar ships.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161535

Authors: Yanfeng Gong Jing Huang Daiyong Zhang Jinlu Sheng

Ship detection over long distances is crucial for the visual perception of intelligent ships. AI techniques, particularly machine learning and deep learning, have achieved a series of breakthroughs in this field. However, due to the limited pixels of ships over long distances, such objects often suffer from weak feature representation and are susceptible to interference in complex environments. To address these challenges, this paper proposes an improved architecture named Ship-DiffDet, based on DiffusionDet. First, we redesign the backbone feature extraction network and propose IDC-Net, which utilizes inception depthwise convolution to enhance feature extraction efficiency while reducing computational complexity. Second, to tackle the difficulty of effectively extracting features from small objects, we design a Hybrid Pooling Attention-enhanced Feature Pyramid Network. By incorporating a hybrid pooling attention mechanism, it strengthens multi-scale feature fusion, thereby improving the performance of the detection heads. Furthermore, we introduce a multi-order gated aggregation mechanism into the dynamic detection head to optimize dynamic convolution and further compress the model’s parameter count. Experimental results demonstrate our method achieves an effective balance between detection accuracy and computational efficiency. On our custom-built small-object ship dataset, the proposed method improves AP50 by 1.7% over the baseline while reducing the parameter and FLOPs counts by 48.8% and 22%, respectively.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161534

Authors: Burak Aydoğan Mehdi Aghajan Dastjerdi Berna Ayat Fulya Islek

Offshore wind energy droughts are quantified at eight strategic sites using a Standardized Renewable Energy Production Index referenced to an 86-year-ERA5 baseline. Events are extracted via multi-threshold run theory and projected to 2100 using bias-corrected CMIP6 models under SSP2-4.5 and SSP5-8.5. Drought climatology shows that mean drought duration and severity exhibit spatial heterogeneity, peaking in the Aegean–Cretan sector. Under future warming, a robust, false-discovery-rate-controlled intensification is predominantly concentrated in the central–western basin, associated with structural shifts toward weaker, heavy-tailed wind distributions. The Sicily Channel and Gulf of Lion emerge as hotspots for drought intensification, exhibiting consistent annual total duration increases of up to 20% and 15%, respectively, under the SSP5-8.5 scenario. Winter droughts across the basin are associated with a complex interplay of the AO, NAO, EA, and EA/WR teleconnections, alongside a pronounced winter MOI influence in the west. Summer droughts in the Aegean–Cretan sector are strongly coupled with the weakening of the MOI, reflecting the collapse of the basin-scale pressure gradient that sustains the Etesian winds. The central–western Mediterranean emerges as a key region for adaptive, long-duration energy storage planning, whereas the climatology of the eastern basin remains a defensible baseline for future capacity design.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161533

Authors: Pieter Maes Elspeth McMahon Doreen Jirak Dirk van Rooy Werner Jacobs Rowan Van Schaeren Edwin Van Hassel Stijn Verwulgen

Research and development of Maritime Autonomous Surface Ships (MASS) has surged in recent years. However, questions remain regarding the safety of interactions between MASS and conventionally crewed ships in mixed-traffic environments, particularly during collision avoidance. Although the critical role of MASS technology is widely recognised, few studies have explored how these interactions may affect the behaviour of the conventional ship’s Officer of the Watch (OOW). The primary aim of this paper is to explore the challenges and complexities of mixed-traffic interaction from the perspective of the conventional OOW as an active participant in collision avoidance. A collision-avoidance framework is presented as an analytical lens linking situational awareness, motion prediction, mental models, conflict detection, conflict resolution, and manoeuvre execution. This framework is used to examine challenges related to communication, COLREG interpretation, uncertainty surrounding MASS capabilities and operations, knowledge and training, and trust. We argue that these factors may influence how OOWs interpret MASS behaviour and determine whether, when, and how to intervene. To address this research gap, key research questions are formulated, and a scenario-driven methodological approach using Full Mission Bridge Simulators (FMBS) is proposed to investigate changes in OOW behaviour and decision-making during mixed-traffic encounters.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161532

Authors: Yingying Wang Jingsi Liu Wenru Zhang Qi Zhang

Underwater marine debris detection is important for marine environmental monitoring, robotic inspection, and debris removal. However, reliable detection remains challenging because underwater images often suffer from low illumination, color distortion, turbidity, cluttered backgrounds, and weak boundaries. These factors reduce feature reliability and hinder accurate localization, especially for small, occluded, or low-visibility debris. To address these challenges, this paper proposes UADet, an adaptive detector for marine debris detection in degraded underwater scenes. UADet integrates two complementary components: Underwater Degradation-aware Feature Modulation (UDFM) and Visibility-aware Boundary Distribution Refinement (VBDR). UDFM extracts lightweight image-level degradation cues and modulates multi-scale features to improve robustness under varying underwater conditions. VBDR incorporates object scale and an appearance-based proxy for local visual difficulty into boundary distribution learning and matching cost, providing adaptive localization supervision for small objects and objects with weak visual evidence. Experiments are conducted on TrashCan and J-Litter, and UADet is compared with representative real-time detectors, including YOLOv8s, YOLOv10s, YOLOv11s, and RT-DETR. The results show that UADet achieves the best performance on both datasets, with 72.74% mAP@0.5, 81.36% precision, and 69.36% recall on TrashCan, and 48.02% mAP@0.5, 70.13% precision, and 55.61% recall on J-Litter. Compared with the strongest baseline, UADet improves mAP@0.5 by 3.12 percentage points on TrashCan and 4.83 percentage points on J-Litter. Ablation and qualitative analyses demonstrate that UDFM and VBDR provide complementary improvements. These results indicate that modeling underwater degradation and boundary uncertainty improves the robustness and reliability of marine debris detection in challenging underwater environments.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161531

Authors: Aziz Kudaikulov Tangnur Amanzholov Abdurashid Aliuly Abzal Seitov Bakytzhan Assilbekov Alibek Kuljabekov Spartak Shabilov Dinmukhambet Baimbetov Samal Syrlybekkyzy Aidarkhan Kaltayev

The Caspian Sea’s unique environment and intense hydrocarbon extraction make it a high-risk, understudied region for oil spill modelling. This review assesses the physical, chemical, and biological processes governing oil spill transport and fate, and evaluates the principal numerical tools available for the Caspian Sea context. The weathering processes are reviewed from foundational formulations to operational implementations. Key research challenges identified include the absence of photo-oxidation from operational models, limited laboratory data for Caspian crude oil types, and simplified biodegradation parameterizations. Hydrodynamic forcing uncertainty, arising from the lack of a dedicated operational ocean model, remains the dominant source of trajectory forecast error. Seven operational oil spill modelling tools and the ROMS hydrodynamic platform are reviewed. Only OSCAR and MIKE 21 have documented applications to the Caspian Sea, representing a significant regional gap. ROMS is identified as the most suitable hydrodynamic platform for future operational forecasting. Finally, the integration of machine learning and deep learning methods, including neural network trajectory prediction and SAR detection, is discussed as a promising frontier for improving forecast accuracy in this data-sparse environment.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161528

Authors: Jun Liu Shaojie Jing Yongsheng Yang Shiteng Yang

To address the challenges of adsorption instability and obstacle-crossing difficulties faced by wall-climbing robots in the harsh operation and maintenance (O&M) environment of offshore wind turbine (OWT) towers, this paper presents the design of a magnetic-adhesive wall-climbing robot with a planetary-gear configuration and investigates its wind resistance stability. First, the magnetic circuit layout is optimized through finite element analysis, revealing that the F-16 continuous planetary configuration (16 poles) effectively suppresses magnetic flux leakage and forms an integrated magnetic pad, maintaining adsorption force at a large air gap of 20 mm, thereby enhancing magnetic robustness during obstacle crossing and making it the optimal choice for high-load offshore conditions. Second, an unsteady flow field model based on the Kaimal turbulence spectrum is constructed to analyze aerodynamic loads. Fluid–structure interaction (FSI) simulations demonstrate that at a height of 30 m, the turbulence integral scale matches the robot dimensions, and combined with the Venturi effect of gap jet flow, this leads to peak turbulence intensity and pitching moment, creating a hazardous, pronounced aerodynamic amplification condition. Finally, an anti-slip stability model is established, revealing that vertical wall climbing represents the critical loading scenario; the magnetic adhesion system must deliver a total adsorption force of no less than 1000 N to resist a 35 m/s wind speed under low-friction conditions, providing a quantitative design basis for anti-wind safety. This study integrates magnetic circuit optimization, turbulence-resolved aerodynamics, and macroscopic anti-slip mechanics, offering theoretical support and engineering guidance for the safe deployment of intelligent O&M equipment for offshore wind power. Bench-scale measurements of magnetic adhesion force, friction coefficient, and translation force fluctuation support the exponential-decay magnetic model and the multi-wheel phase-interleaving concept; however, the current 4 × 16-pole prototype delivers ~627 N at the 2 mm working gap, below the 1000 N design target. The design methodology is therefore validated, while the current physical configuration requires further iteration of the working gap or magnet grade before it can be considered operationally adequate.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161530

Authors: Sixing Guo Yutao Tian Yuting Li Zehan Chen Kexin Xie Yixuan Zeng Dapeng Zhang

Amphibious assault vehicles serve as core equipment for coastal defense and amphibious operations worldwide, with irreplaceable strategic value. Featuring outstanding comprehensive performance, modern amphibious assault vehicles can maintain stable navigation under Sea States 3–4 and adapt to complex nearshore hydrological environments, emerging as the primary platform for mechanized landing operations of the Marine Corps. Cluster navigation is an inevitable tactical form in the operational application of amphibious assault vehicles. When multiple vehicles sail in formation, the wave-making and water pressure effects induced by individual vehicles generate prominent wave interference drag within the formation, which significantly impacts the overall navigation efficiency and stability. Based on the nearshore combat background of amphibious landing, this paper investigates different formation layouts of amphibious assault vehicle clusters to determine the optimal configuration for group navigation. First, a numerical simulation and a physical experiment are combined; a certain type of amphibious assault vehicle is taken as the prototype for 3D geometric modeling via SOLIDWORKS. Then, adopting the CFD numerical simulation method, with navigation speed and optimal inter-vehicle spacing fixed, variables including formation layout and number of vehicles are controlled to simulate the flow field characteristics and total resistance of different cluster formations in calm water. Meanwhile, 3D printing technology is applied to manufacture scaled-down models for towing tank tests. The experimental results are in good agreement with numerical simulations, revealing the fundamental hydrodynamic laws of formation navigation. Under optimal inter-vehicle spacing, the longitudinal tandem formation achieves the best drag-reduction effect, while the double-column staggered formation (diamond/V formation) can effectively suppress wave interference drag and improve the overall hydrodynamic performance and tactical coordination. The research provides a solid theoretical basis and data support for optimizing formation sailing strategies, enhancing cluster navigation stability and safety, and improving maritime maneuver efficiency. It is also of universal reference value for the tactical deployment of amphibious combat equipment globally.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161529

Authors: Golnoosh Toosi Xing Wu Victor A. Zaloom

Maritime transportation, handling over 80% of global trade, is critical to the world economy. Automatic Identification System (AIS) data provides extensive static and dynamic information of vessels, enabling trajectory reconstruction and vessel behavior analysis. Recently, trajectory clustering has become a key method for analyzing maritime traffic, offering valuable insights to improve traffic management and operational efficiency. This research aims to investigate how to effectively cluster ship sub-trajectories derived from AIS data by comparing two machine learning clustering algorithms, Density-based spatial clustering of applications with noise (DBSCAN) and spectral clustering, with a focus on improving data quality, extracting key dynamic features, and evaluating the effect of dimensionality reduction on clustering performance. Clustering sub-trajectories can help reveal localized navigation patterns and movement behaviors. The study implemented the proposed methods for tankers and cargo ships (with AIS data from 2022) in a Y-shaped channel in the Sabine-Neches Waterway (SNWW) in Southeast Texas, where the busiest docks are located. Finally, clustering performance was evaluated with the silhouette coefficient (SC), Davies–Bouldin Index (DBI), and Joint Performance Index (JPI), respectively. Experimental results show that DBSCAN effectively identifies dense, overlapping trajectory clusters and labels noise, while the spectral clustering algorithm detects subtle behavioral differences but struggles with less cohesive clusters, and does not explicitly handle noise.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161527

Authors: Maorong Chen Fan Yang Hongtao Cai Xiongbin Wu Yunfeng Zhang Liang Yu Yilin Luo

The yaw-angle signal output by shipboard attitude sensors (e.g., inertial navigation systems) is a composite of the heading and wave-induced yaw (WIY). The heading reflects large-scale directional changes due to maneuvering or voyage planning, exhibiting slowly varying, trend-like characteristics; WIY is the oscillatory motion caused by random wave–hull interaction, approximately following a zero-mean normal distribution. Accurately and adaptively separating these two components from the composite yaw-angle signal is a key technical challenge in ship motion monitoring or wave parameter inversion. This paper proposes a heading–WIY separation method based on Empirical Mode Decomposition (EMD) and multi-dimensional physical–statistical evaluation. The method adaptively decomposes the composite yaw signal via EMD and automatically determines the optimal mode combination through statistical evaluation. Moreover, a short-time segment processing strategy and overlap-region continuity checks are introduced to overcome heading trend variations over long time scales. The method is validated using a multi-scenario simulation dataset encompassing four conditions and various sea states, as well as at-sea collected data. Results demonstrate high extraction accuracy without requiring a system dynamics model or scenario-specific parameter tuning across all conditions. And the proposed method performs better in comparison to the conventional methods, particularly under conditions of spectral overlapped or high sea states.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161526

Authors: Quanbo Xin Fangzheng Wang Yongchao Wang Chunning Ji

Approach channels are affected by sedimentation and scour, resulting in continuous changes in underwater topography. Such processes tend to generate shallow spots and inadequate navigable dimensions, posing safety hazards that undermine both waterway resilience and navigation capacity. To address these issues, this paper proposes a multi-level grid-based spatiotemporal indexing method for bathymetric data, aiming to support resilience-oriented management by improving the effectiveness of bathymetric data management. First, a channel-segment-section partitioning strategy is designed to construct hierarchical progressive grids for the efficient organization of massive bathymetric data. Second, a multi-dimensional spatiotemporal integrated query method is developed to meet diverse analytical and retrieval requirements. Third, a digital depth model (DDM) construction method is introduced that integrates boundary-constrained terrain reconstruction with efficient mesh optimization, enabling underwater terrain representation that adapts to the elongated and irregular morphology of approach channels. The contribution of this work lies not in proposing new individual algorithms but in the tailored integration of these techniques to address the specific challenges of approach-channel bathymetric data. Experimental results demonstrate that the proposed method achieves high construction efficiency across different storage and query schemes. The method enhances the retrieval and analytical capabilities of bathymetric data in representative application scenarios, such as shallow spot identification, critical section analysis, dredging analysis, and erosion–deposition evolution. Consequently, these improvements provide technical support for resilience-oriented channel management and ensure navigational safety.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161523

Authors: Sirong Qian Yuewen Huang Meng Wang Houlei Jia Xiaoyong Mei Fudan Zheng

Outbreaks of the Crown-of-Thorns Starfish (COTS, Acanthaster spp.) are a leading biological driver of coral cover loss, making timely and accurate population monitoring essential for reef management. Conventional diver-based surveys are labor-intensive and prone to missed detections, motivating automated detection from underwater imagery. However, COTS detection in complex underwater scenes still faces three major challenges. First, COTS individuals are often very small and carry limited discriminative information, making them inherently difficult to detect. Second, low underwater contrast and complex coral textures blur target boundaries and cause targets to be easily confused with the background. Third, ecological monitoring values recall more highly than precision—missing a COTS individual is far more costly than a false alarm—yet the recall of existing detectors remains insufficient. To address these challenges, we propose HiFi-Det (High-resolution Frequency-integration Detector), a collaborative multi-scale frequency-domain feature optimization method built on YOLO11. HiFi-Det integrates three complementary enhancements: a high-resolution detection branch that strengthens feature representation for small targets; wavelet transform convolution (WTConv) modules in the backbone and neck that apply band-separated processing in the wavelet domain to improve discrimination of COTS targets from low-contrast, textured coral backgrounds; and a WIoUv3 bounding box regression loss that dynamically focuses on ordinary-quality samples to improve recall while maintaining precision. On the public Great Barrier Reef dataset, HiFi-Det attains 81.02% F2 and 87.54% mAP@50, surpassing the YOLO11 baseline by 3.00% and 2.57%, respectively, while keeping the parameter count essentially unchanged relative to the YOLO11s baseline (within 3%), so that the accuracy gains are obtained without inflating model size. Ablation studies confirm the synergy of the three components: the high-resolution branch preserves spatial details, WTConv suppresses background textures, and WIoUv3 further curbs false positives while sustaining high recall. Applying the same recipe to a larger YOLO11m backbone yields HiFi-Det-m, which likewise improves over that backbone in both F2 and recall, indicating that the approach is a transferable recipe rather than a single fixed architecture. These results show that task-specific architectural and training designs can effectively adapt generic detectors to the demands of underwater ecological monitoring.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161525

Authors: Haoyu Bu Feng Zha Hongyang He Jingshu Li Chenyang Zhang Qun Zheng

To address the degradation in attitude accuracy caused by mismatched rotation-axis tilt parameters after inertial measurement unit (IMU) reinstallation in rotational inertial navigation systems (RINSs) on large marine platforms, an interleaved rotation-dwell attitude-and-heading calibration method is proposed. First, a relative attitude-and-heading model incorporating the combined effects of the rotation-axis tilt errors of the two systems is established, with the horizontal error mapping induced by the relative heading between their base frames explicitly considered. Second, a four-state interleaved rotation-dwell sequence is designed, and the rotation-axis tilt parameters of the two RINSs are separated in closed form through Hadamard orthogonal projection. Simulations verify the parameter-decoupling capability of the proposed method. Experimental results show that, compared to a filtering-based self-calibration method for a single RINS, the proposed method reduces the roll and pitch root-mean-square errors (RMSE) by 90.29% and 41.80%, respectively. After compensation for the rotation-axis tilt errors, relative heading alignment between the two systems is achieved by estimating the residual heading bias. The proposed method provides a system-level solution for attitude-and-heading calibration after IMU reinstallation under moving-base field conditions.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161524

Authors: Xinjian Wang

Maritime safety and risk assessment have become increasingly important as the shipping industry moves towards larger vessel systems, denser traffic networks, cleaner fuels, autonomous navigation and data-driven decision support [...]

Journal of Marine Science and Engineering doi: 10.3390/jmse14161522

Authors: Jianqiang Shi Sicheng Guo Zhaokun Wang Han Liang Peibo Shi Mingyu Wang Guichen Zhang

This paper studies the automatic berthing control of an unmanned surface vessel under cyber attacks. An adaptive neural-network-based fault-tolerant control method is developed. Unknown vessel dynamics, external disturbances, measurement noise, and cyber attacks are considered at the same time. First, the signal scaling, bias, and power-type distortion caused by cyber attacks are described by a unified nonlinear measurement model. The model has a known structure and unknown parameters. It converts different attack effects into structured uncertainties. Based on the corrupted position and attitude measurements, the tracking errors are defined. The vessel heading is reconstructed by integrating the unaffected yaw-rate signal. A Nussbaum-type function is introduced to handle the unknown gain in the measurement channel. A first-order filter is used to generate a smooth approximation of the virtual control signal. A neural network is then employed to approximate the unknown vessel dynamics. Adaptive laws are designed to estimate the composite uncertainties and external disturbances. Lyapunov analysis shows that all closed-loop signals remain bounded. The berthing tracking errors ultimately converge to a compact set around the origin. Finally, a berthing simulation with time-varying cyber attacks, measurement noise, and marine disturbances is conducted to evaluate the proposed method.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161521

Authors: Hexing Zheng Haitao Gu Tianzhu Gao Kexin Zhang

Wake-induced magnetic fields provide a potential non-acoustic signature for underwater-vehicle sensing, but their weak amplitudes can be masked by ocean-wave magnetic backgrounds. This study evaluates their engineering observability under representative wind–wave conditions. The wake-induced field at fixed observation points was calculated from CFD-derived wake velocities of an engineering-scale fully appended SUBOFF model using discrete Biot–Savart summation. The ocean-wave background was computed using a JONSWAP spectrum and linear wave theory, and a peak-to-background-rms SNR was used as the observability indicator. Results show that speed and diving depth strongly control the target signal. At the baseline point, increasing speed from 10 to 40 kn raised Bwake,max from 0.0406 to 1.65 nT and SNR from −1.01 to 31.2 dB under W2. Increasing diving depth from 2D to 4D reduced Bwake,max from 0.129 to 0.0204 nT and SNR from 9.03 to −6.99 dB. Wind speed dominated the wave background: at U10=10 m/s, Bwave,rms reached 0.542 nT and the Case 2 SNR decreased to −12.5 dB. Sensor placement affected both signal and background; deeper underwater sensors improved observability, whereas aerial observations suffered from weak wake-signal amplitudes. Wake-field observability is therefore jointly governed by wake source strength, ocean-wave magnetic background, and observation geometry.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161520

Authors: Yabei Guo Huigang Wang Wei Qiang Runhe Yao Zhizhen Xie

Autonomous acoustic remote sensing of underwater infrastructure is challenging due to the physical characteristics of 3D sonar and the geometric degeneracy commonly encountered in feature-poor underwater environments. Accurate localization is essential for integrating sequential sonar observations into globally consistent 3D maps; however, existing odometry methods often rely on isotropic noise assumptions despite the highly directional nature of acoustic sensing. This mismatch may cause unreliable measurements to be over-trusted, leading to severe trajectory drift and distortion in sonar-derived 3D reconstructions. To address these challenges, we propose RA-SIDO, a robust and adaptive tightly coupled 3D sonar–inertial–depth odometry framework based on the Error-State Iterated Kalman Filter (ESIKF), which fuses measurements from a 3D sonar, an inertial measurement unit (IMU), and a depth sensor for reliable underwater acoustic mapping. The proposed method introduces two mechanisms to handle sonar-specific uncertainties: (1) a physics-based anisotropic acoustic measurement model that distinguishes high-resolution radial range measurements from highly uncertain cross-range angular measurements; (2) an online degeneracy-awareness module that continuously evaluates the minimum eigenvalue of the translational information matrix and dynamically adjusts sensor fusion weights to avoid over-trusting ill-conditioned constraints. Real-world experiments were conducted with an unmanned surface vehicle in underwater infrastructure inspection scenarios. RA-SIDO achieved an ATE RMSE of 0.8924m, reducing the error by 16.8% compared with SIDO, the strongest baseline. In addition, the proposed method effectively suppresses longitudinal slip and produces globally consistent 3D acoustic maps of submerged structures. These results validate the potential of RA-SIDO as a robust localization and mapping solution for underwater remote sensing, infrastructure inspection, and acoustic 3D reconstruction in challenging aquatic environments.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161519

Authors: Yong Lyu Zhilin Liu Shiquan Ma

To address the need for low-power, real-time underwater acoustic signal processing and autonomous target detection on deep-sea unmanned mobile platforms, such as profiling acoustic buoys and underwater gliders, this study developed an embedded Linux-based signal processing system for buoy platforms. Conventional digital signal processing hardware platforms are often constrained by large size, high power consumption, and limited data communication capability. The proposed system adopts a compact, low-power architecture and a multithreaded processing framework based on the AM6254 heterogeneous multicore processor. It acquires four-channel vector-hydrophone signals together with attitude data from an inertial navigation module and performs band-pass filtering, fast Fourier transform (FFT), direction-of-arrival (DOA) estimation, and constant false alarm rate (CFAR) detection for autonomous target detection. The measured typical power consumption was approximately 2.3 W. Anechoic-tank and sea-trial results showed the lowest tested spectral level at which autonomous detection was achieved was 54 dB at 1 kHz, corresponding to an average in-band level of 46 dB. Under sea state 3, the system maintained continuous bearing tracking after target acquisition for a surface target traveling at 7 kn, up to a range of approximately 7 km, and provided unambiguous bearing estimation. These results demonstrate the target-detection capability and practical applicability of the system under representative operating conditions and indicate its potential for marine environmental monitoring and unmanned-platform observation and detection.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161518

Authors: Hongkun Zhou Yunfei Ding Hanlin Gao Gang Wang Tong Ge Ying Zhang

This study addresses target-to-ROV relative localization in an unmanned surface platform-assisted UAV–ROV search-and-recovery system. Because the submerged ROV is not assumed to be visible from the air, the UAV observes the floating target and a GNSS-equipped ROV-associated surface buoy in the same image. The buoy position and target-to-buoy image displacement are combined to construct a world-frame target-position measurement, whose covariance accounts for buoy GNSS uncertainty and correlated image-projection errors. An upward-looking ROV imaging sonar provides range–bearing measurements. A delay-aware extended Kalman filter fuses the asynchronous observations using sea-state- and confidence-dependent covariance adaptation and normalized-innovation gating. ROV acoustic/inertial navigation uncertainty is propagated into the sonar measurement covariance and the reported relative-state covariance, avoiding duplication of the same navigation error in the aerial channel. The method is evaluated using a JONSWAP-based temporal disturbance model, Monte Carlo simulations, and single-factor and joint sea-state–occlusion–delay sensitivity tests. Under the nominal sea-state-5 condition, the proposed method achieves a mean ROV-frame relative RMSE of 0.992 m, compared with 1.083 m for ROV-only localization and 1.054 m for fixed-covariance fusion, with no run exceeding the 5 m divergence threshold. The results demonstrate improved relative-localization robustness within the simulated environment.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161517

Authors: Yueyuan Ma Shuang Zhao Baojin Li Linhao Li

Ocean sound speed profile (SSP) is a key parameter for underwater acoustic detection, remote sensing, and seafloor geodetic positioning, and its temporal prediction is essential for improving acoustic positioning accuracy. Conventional direct measurements are inefficient and spatially sparse, while statistical and acoustic inversion methods fail to capture the strong nonlinear evolution of the sound speed field. Among existing time series models, LSTM, a recurrent network for time series forecasting, lacks an explicit receptive field. In contrast, the original TCN, a temporal convolutional network with dilated convolutions, poorly captures local fine structures and relies heavily on empirical tuning. To overcome these limitations, we propose an improved TCN-based SSP prediction method and apply it to seafloor geodetic positioning. The approach first constructs a sound speed increment field via first-order time differencing to remove global trends and highlight local variations. It then employs Optuna (version 4.9.0), a Bayesian sampling-based automatic optimization framework, to automatically tune key TCN parameters within a predefined search space, reducing reliance on manual tuning. The predicted high-resolution sound speed time series is finally used for ray tracing positioning to enhance seafloor geodetic accuracy. Experiments on the GLORYS12V1 reanalysis dataset show that LSTM and the original TCN achieve root mean square error (RMSE) and mean absolute error (MAE) values of 0.414 and 0.299 m/s, as well as 0.360 and 0.258 m/s, respectively, whereas our improved TCN reduces these to 0.205 and 0.131 m/s, substantially outperforming both baselines. In simulated Global Navigation Satellite System–Acoustics (GNSS-A) seafloor positioning, the 3D positioning RMSE drops to about 0.075 m, with improved stability. The proposed method offers an effective solution for accurate SSP time series forecasting and high-precision seafloor geodesy.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161516

Authors: Ying Luo Kevin Huang

The high cost of mooring systems, driven by extreme peak tensions during storm conditions, remains a significant barrier to the commercialization of floating offshore wind turbines (FOWTs). This paper proposes an innovative active tension-regulating joint (TRJ) for FOWT mooring lines. The TRJ consists of nested cylinders and an actively controlled accumulator, designed to release additional line length under high tension and to recover it under low tension, thereby reducing extreme dynamic peaks. A finite element scheme is also developed for efficient line dynamics analysis. The TRJ concept is applied to a benchmark IEA 15-MW semi-submersible FOWT in 100 m water depth under 50-year return period environmental conditions. The simulation results demonstrate that the TRJ reduces the maximum mooring line tension by approximately 53% and the maximum suspended line length by over 23%. This active control technique enables the downsizing of mooring components and a significant cost reduction.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161515

Authors: Glib Ivanov Gwo-An Chang Ding Peng Liu Kai-Tung Ma

Fatigue assessment of floating offshore wind turbines (FOWTs) remains challenging because fatigue-sensitive regions may occur outside conventional predefined hotspots. This study applies a previously numerically verified full-field fatigue-screening workflow combining Unit Load Response, submodeling, and Virtual Test Rig concepts to the TaidaFloat semi-submersible FOWT under Taiwan Strait environmental conditions. Reconstructed nodal stress histories are used to map hull fatigue and evaluate occurrence-weighted contributions from 182 environmental bins, including operational and typhoon conditions. The results identify fatigue-sensitive regions not only at conventional column–bracing and column–pontoon connections but also in the upper main column and along the turbine–hull load path. Upper column fatigue is mainly associated with turbine-induced bending, whereas lower column and waterline-adjacent regions are more sensitive to wave-induced global hull bending. Frequently occurring near-rated operational conditions dominate the occurrence-weighted hull fatigue contribution, while selected typhoon conditions produce high short-term damage but limited long-term contributions within the four-year dataset. Approximately 94.6% of hull fatigue damage is captured by 28% of the bins, and a common hull–mooring set captures 97.0% of both contributions using 62% of the bins. These findings support hotspot screening and environmental-bin prioritization rather than detailed or certification-level fatigue life prediction.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161514

Authors: Yi Wu Wenguang Zhang Kehan Yi Xiaogang Xing Pengbin Wang Qian Liu Mengmeng Tong

The obligate mixotroph Mesodinium rubrum significantly impacts coastal ecosystems, yet its population control in oligotrophic waters remains unclear. Integrating field observations from Coast of Sanya (South China Sea) with laboratory nutrient manipulation, we investigated how dissolved inorganic nutrients and prey availability regulate cell cycle progression, using biovolume as a proxy for cycle transitions. Nutrient starvation arrested cells at the small (newly divided) stage. Inorganic replenishment triggered rapid somatic growth and consistent diel biovolume oscillations, expanding in light and shrinking in darkness. However, without cryptophyte prey, cells failed to progress beyond the medium (actively growing) stage and could not accumulate into the large (pre-division) size class, revealing a decoupled regulatory mechanism. Dissolved inorganic nutrients drive cell size expansion (somatic growth), whereas prey-derived organelles serve as a critical prerequisite for division. Field data confirmed that the virtual absence of cryptophytes in Sanya waters restricts M. rubrum to consistently low levels. Our findings demonstrate that population dynamics of this specialist mixotroph transcend traditional nutrient-driven paradigms, underscoring the irreplaceable role of prey in sustaining photosynthetic metabolism and triggering population expansion in oligotrophic systems.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161513

Authors: Sergey S. Kubrin Sergey I. Kondratyev Evgeniy V. Khekert Viktor V. Kondratiev Natalia Nikolaevna Bryukhanova Vitaliy A. Gladkikh Boris V. Malozyomov Nikita V. Martyushev Roman V. Klyuev Antonina I. Karlina

Liquefaction and dynamic separation of moisture-sensitive solid bulk cargoes may remain latent for much of a voyage and then manifest as a sustained heel, leaving a comparatively short interval for emergency action. This study develops an exploratory reliability-based analysis of accident chronology using a source-traceable registry of 35 casualties and incidents. Eighteen cases provided post-heel information suitable for the principal emergency time reserve analysis; the observations comprised exact, approximate, reconstructed, interval-censored, and right-censored times. Descriptive statistics calculated from the selected central values and censoring bounds yielded a mean emergency time reserve TR of 200.99 min, a median of 192.20 min, and a range of 67.50–335.10 min. In likelihood-based fitting that retained censoring, the Weibull model achieved the lowest AIC (212.51) and BIC (215.18), with Kolmogorov–Smirnov D = 0.097 (p = 0.989). The fitted lower-tail quantiles were Q10 = 105.40 min and Q25 = 147.99 min, substantially shorter than the descriptive mean. Robustness was examined using nonparametric estimators, Akaike-weighted model averaging, source-confidence weighting, leave-one-out analysis, and alternative interval assumptions. The contribution is a reproducible framework for converting heterogeneous casualty narratives into uncertainty-qualified lower-tail time-reserve evidence and non-prescriptive bridge–team decision support. The framework is not a physical stability model and cannot replace ship-specific GM/GZ calculations, approved loading and stability information, or the master’s judgement.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161511

Authors: Zhongdi Liu Chenmu Li Bin Zhou Qiming Ma Liang Xie

Line-spectrum features in ship-radiated noise are essential for the analysis and recognition of passive sonar targets. Robust automatic extraction from low-frequency analysis and recording (LOFAR) spectrograms remains challenging in underwater acoustic environments owing to strong background fluctuations and interference. Supervised learning-based methods are further constrained by the limited availability of manually annotated data. This study proposes an automatic LOFAR line-spectrum extraction method that combines hybrid dataset construction with a continuity-aware U-Net (CAU-Net). Simulated and measured samples are integrated into a hybrid training dataset. A pseudo-label generation strategy combining two-pass split-window (TPSW) responses with inter-frame continuity constraints incorporates unlabeled measured samples into training. In addition, a temporal continuity modeling module combines multi-range inter-frame context with local frequency information, improving the extraction of weak components with pronounced energy variations. On an independent test set with known line-spectrum references, CAU-Net achieved an F1 score of 0.9635±0.0012 and a line-location accuracy (LLA) of 0.9756±0.0023 over five random seeds. It also maintained the highest F1 and LLA across the tested signal-to-noise ratio (SNR) range. Qualitative results on complete ShipsEar recordings illustrate that CAU-Net provides visually clearer weak narrowband responses while suppressing scattered background and transient-interference responses.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161512

Authors: Junjun Zhang Xishuang Li Xiaoqing Xu Lejun Liu Qingjie Zhou

Bottom currents and their associated sedimentary structures are key agents in shaping deep-sea morphodynamics, among which the genesis of seafloor undulations is still debated, restricting engineering risk assessment and resource development safety. Based on high-resolution multibeam bathymetry, sub-bottom profiles, and near-bottom current observations, this study analyzes morphological characteristics, internal reflection structures, and near-bottom current dynamic processes of seafloor undulations in the Shenhu canyon area. The results indicate that undulations occur at canyon heads, canyon interfluve, and east side of canyon. The undulations are generally characterized by vertical aggradation, with some sediment waves exhibiting directional crestline migration accompanied by wave merging, indicating the existence of persistent sediment transport processes. Within the canyon, the flow is concentrated and exhibits significant vertical deflection, reflecting the pronounced flow-guiding effect of the confined topography on near-bottom currents, which consequently controls the lateral migration of crestlines on both sides of the canyon and the shaping of seafloor undulations at canyon heads by internal tides. In contrast, in the relatively open canyon interfluve, flow directions are more dispersed, predominantly characterized by weaker currents. These findings contribute to the understanding of deep-water sedimentary dynamic processes and provide a reference for interpreting the genesis of similar deep-water seafloor undulations.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161510

Authors: Rongxia Ma Bufan Zhou Mingming Xu Yunfei Wu Hang Shi Yusheng Yang Xiaohan Guo Yangmin Xie

Achieving high-accuracy path following remains challenging for an unmanned surface vehicle (USV) in narrow waterways with time-varying curvature and straight–curve transitions; fixed-parameter line-of-sight (LOS) guidance can cause delayed response, overshoot, and steady-state cross-track error. This paper proposes a curvature-coupled adaptive vector-field integral LOS (AVFILOS) guidance law. It incorporates curvature-adaptive guidance: a lookahead distance regulated by curvature and cross-track error and a field-source radius that contracts with curvature to strengthen centripetal correction in high-curvature regions. A fuzzy adaptive proportional–integral–derivative (PID) controller tracks surge speed and heading. A stability analysis establishes local exponential stability for straight and constant-curvature paths and local ISS with local uniform ultimate boundedness for time-varying curvature under a bounded-rate condition. Across six elliptical and sinusoidal cases, AVFILOS achieved an average root mean square error (RMSE(ye)) of 0.1325 m, reducing RMSE(ye) by 90.6%, 63.6%, and 37.2% compared with LOS, time-varying LOS (TLOS), and vector-field integral LOS (VFILOS), respectively. Its average maximum absolute cross-track error (Max(|ye|)) was 0.3478 m, with reductions of 88.2%, 48.2%, and 30.7%. The ablation and sensitivity results indicate that coupled adaptive mechanisms improve curved-path tracking and reduce overshoot. The simulations indicate that AVFILOS is promising for cross-track-error-sensitive USV navigation.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161509

Authors: Kunpeng Liu Haoda Huang Wanyong Zhang Wanfu Zhang Chun Li

Owing to transportation, installation, grid-connection, and maintenance requirements, nearshore offshore wind farms are often located close to busy shipping routes, substantially increasing the risk of ship–offshore wind turbine (OWT) collisions. To enhance the impact resilience of OWT support structures against ship collisions, a novel honeycomb sandwich fender is proposed for tower protection. Nonlinear transient analyses were performed using ANSYS/LS-DYNA to simulate a 5000 t ship traveling at 2 m/s and colliding with a 4 MW OWT supported by a single-column tripod foundation. The effects of rubber and aluminum foam cores on the crashworthiness and protective performance of the fender were compared. The results show that the rubber core stores collision energy through recoverable large deformation and releases most of the stored energy during unloading, resulting in pronounced energy restitution and prolonged structural excitation. By contrast, the aluminum foam core dissipates 7.5 MJ through cell-wall buckling, progressive crushing, and plastic collapse, corresponding to 75% of the initial kinetic energy of the ship. Compared with the rubber-core fender, the higher initial stiffness of the aluminum foam increases the peak contact force by 23.1%, from 13.0 to 16.0 MN. However, its irreversible energy-dissipation mechanism reduces the maximum tower-top displacement by 40.0%, from 1.25 to 0.75 m, and decreases the residual tower stress after three successive collisions by 25.0%, from 200 to 150 MPa. These results demonstrate that, despite transmitting a higher peak contact force, the aluminum foam fender provides more effective overall protection under the collision conditions considered because of its greater irreversible energy-dissipation capacity.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161508

Authors: Taofeng Wang Sanming Song Liming Li Jinxing Yu Kaizhou Liu Adam Rushworth Xisheng Feng

Propulsors are essential power units for underwater vehicles and major sources of self-noise, with unsteady pressure pulsations linked to flow-induced noise. To study the impact of guide vane case on the hydrodynamic performance and pressure pulsation of a shaftless pump-jet thruster, six guide vane configurations were first compared under a reference operating condition of 600 rpm: a vaneless baseline, fixed vertical guide vanes, fixed forward-inclined guide vanes, fixed reverse-inclined guide vanes, co-rotating guide vanes, and counter-rotating guide vanes. Based on this comparison, the vertical-vane and counter-rotating-vane configurations were selected for extended operating-condition analysis under three rotational speeds and three inflow conditions. Transient numerical simulations were conducted using the SST k−ω turbulence model. The rotating regions were defined in a rotating reference frame, and the unsteady rotor–stator interaction was resolved using a transient sliding-mesh interface. Results show that the counter-rotating guide vane configuration achieves the highest head and efficiency among the tested cases, with a head of 1.8955 m and efficiency of 0.7306, representing increases of 19.64% and 22.87% over the fixed vertical guide vane case. The fixed forward-inclined guide vane exhibits the strongest thrust fluctuation and pressure pulsation. Pressure-pulsation intensity generally decreases from the impeller rim toward the central axis. Frequency-domain results indicate that most cases are dominated by the blade-passing frequency, whereas the counter-rotating guide vanes show a response nearly twice this frequency.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161507

Authors: Huaxiao Wu Sunwei Li Sheng Zhang Bin Peng Weijie Feng

The upscaling of floating wind turbines and the lightweight design of floating support structures make floater flexibility increasingly important for the dynamic response and load transfer of two-body floating platforms. This study investigates the influence of upper-floater flexibility on Tsemi, a previously proposed suspended-ballast two-body floating platform supporting the IEA 22 MW reference wind turbine, using a fully coupled multi-body flexible-joint model. The floater is discretized into multiple rigid bodies connected by damped six-degree-of-freedom joints, which represent equivalent flexibility and local energy dissipation. The model is evaluated through member-level response comparisons, global modal analysis, and nearly rigid limiting-case simulations. Results show that equivalent floater stiffness strongly affects wave-frequency responses. Reducing the stiffness shifts the platform pitch period from 25.6 s to 30.6 s and significantly amplifies structural and tendon loads under extreme environmental conditions. The standard deviations of tower-top acceleration and tower-base bending moment increase by 75.8% and 72.1%, respectively, and the maximum effective tension in the upwave tendon increases from 19.93 MN to 32.50 MN, exceeding the tendon minimum breaking load. For the considered low-stiffness case, equivalent damping reduces this tension to 21.77 MN. These results suggest that neglecting floater flexibility may underestimate tower responses and extreme tendon loads, while equivalent damping can mitigate wave-frequency amplification under low-stiffness conditions.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161506

Authors: Hyeon-gyo Chae Jong-su Kim Chan Roh

This study proposes a stability-aware load-shaping energy management system (EMS) for a hybrid electric shipboard power system. The proposed EMS uses the energy storage system (ESS) as a dynamic load-shaping buffer to reduce active diesel-generator (DG) low-load exposure and electrical power fluctuations. A supervisory reference-generation procedure integrating low-pass filtering, ESS state-of-charge (SOC) compensation, DG ramp-rate limiting, residual-power calculation, and explicit power and SOC constraints was implemented on a real-time controller. Comparative experiments were conducted on an MW-class platform comprising one active 600 kW DG, a 400 kW/400 kWh ESS, two 450 kW propulsion-load channels, and a 100 kW service-load channel connected to a 750 V DC bus. The second installed DG remained offline during all comparative experiments. Under a common one-hour ship-load profile, the proposed EMS reduced the low-load exposure ratio from 0.1320 to 0.00139, the DG power variance from 3.06 × 104 to 1.37 × 104 kW2, and the mean DG ramp rate from 13.8 to 0.776 kW/s relative to the rule-based EMS. These values correspond to reductions of approximately 98.9%, 55.2%, and 94.4%, respectively. After terminal-SOC correction, the BSFC-map-estimated equivalent fuel consumption decreased from 90.4 to 88.2 kg. Experimental parameter-sensitivity tests demonstrated the trade-offs among DG power smoothing, low-load exposure, SOC regulation, and ESS participation. A supplementary offline Monte Carlo analysis further indicated that the principal comparative benefits were maintained under bounded variations in load magnitude and fluctuation amplitude. The results demonstrate that the proposed EMS improves supervisory DG loading quality while maintaining the ESS within its prescribed power and SOC limits.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161505

Authors: Yuning Liu Yunkai Ji Qiang Fu Zhenyu Zhu Zihao Wang Gaowei Hu Qiang Chen Yongchao Zhang Qingtao Bu Yizhao Wan

Dynamic damage to the seepage characteristics of the near-well zone during natural gas hydrate exploitation is a key factor limiting production stability. There is still a lack of systematic understanding of the microscopic mechanisms underlying fine-particle migration and blockage in the near-well zone. In this study, a long sand-packed column was segmentally packed with clayey-silt sediments from the South China Sea and quartz sand to simulate the near-well reservoir and the packed layer, respectively. Long-term seepage processes in the near-well zone were simulated using water flow experiments at constant flow velocities. By combining pressure distribution monitoring with particle-size analysis, the spatiotemporal evolution of seepage characteristics in the near-well zone is revealed from both macroscopic and microscopic perspectives. Results indicate that under long-term displacement, the reservoir permeability near the injection end increased from 0.0149 mD to 0.0159 mD; the reservoir permeability near the packed layer exhibits the greatest decline, dropping from 0.0089 mD to 0.0065 mD. Combined with the particle-size analysis of the packer layer, the boundary between the reservoir and the packed layer is identified as the critical site for permeability damage in the near-well zone. Radial flow inversion shows that a reduction in wellbore radius leads to an increase in reservoir pressure, with the increase being greater the farther from wellbore. A decrease in the permeability of packed layer causes an increase in reservoir pressure, but the magnitude of the increase is consistent across different locations. It provides a theoretical basis for the optimized design of production wells.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161504

Authors: Ahra Kim Yeonju Jeong Namkyun Im

With the growing interest in Maritime Autonomous Surface Ships (MASS), numerous risk-assessment models have been proposed for route planning and hazard avoidance during navigation. Existing models, however, generally share two limitations. First, many assess risk from information such as vessel traffic and therefore do not adequately reflect the marine weather and sea state itself. Second, they often consider only one or two factors, such as wave height or wind, and even when several factors are merged into a single value, it is difficult to trace back why the result is dangerous. To overcome these limitations, this study proposes a Meteo-Hydrological Fusion Index (MHFI) that combines five environmental factors—wave height, swell period, current, wind, and visibility—into a single risk value. Each factor is first mapped to a 0–4 risk score, and the three highest scores at a given location are then combined by a weighted sum. This summarizes composite risk in a single value while preserving the ranking of the factors that produced it, so the result remains traceable. Applying the index to the coastal waters of Mokpo, we confirmed that the dominant factor behind a given risk grade varies with time and location, and that a rapid, area-wide rise in risk over a short period can be captured by a single indicator. We further show how risk varies along the main fairway and how the index can be overlaid on a display panel. These results indicate that the MHFI could serve as a decision-support layer in an S-100-based digital navigation environment.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161503

Authors: Wenxin Xiao Xiaowei Zhou Junyu Dong

Underwater object detection remains challenging in adverse aquatic environments, where severe image degradation caused by turbidity, light scattering, color attenuation, and low illumination substantially reduces detection reliability. Although real-world underwater datasets are essential, their limited scale and environmental diversity make it difficult to cover the wide range of degraded conditions encountered in practice. To improve detection robustness without collecting additional annotations, we propose physics-aware diffusion synthesis (PADS), a framework that uses a small set of labeled real images to synthesize diverse physically plausible degraded underwater samples. PADS couples a ControlNet-conditioned latent diffusion generator with a physics-based underwater image-formation model inspired by Jaffe–McGlamery and Akkaynak optics. Semantic masks are first employed to preserve object layout during generation. Meanwhile, water-optics parameters are incorporated through cross-attention to guide the degradation process. In addition, the physical model enforces a color and attenuation consistency loss during training and serves as an SDEdit-style latent prior during synthesis. To further improve localization under degradation, especially for small objects, we introduce a training-only scale-aware focaler–NWD (SA-FNWD) bounding-box loss, which emphasizes normalized Wasserstein distance for small boxes while retaining IoU-based regression for larger objects. Experiments on the MOUD dataset demonstrate that detectors trained with PADS-synthesized data achieve substantially stronger robustness under severe degradation. At the harshest turbidity level, PADS retains 59.3% of clean accuracy compared with 14.9% for the copy–paste-based synthesis method and 14.1% for the pix2pix-based synthesis method. SA-FNWD further improves mAP@0.5:0.95 across degradation severities. These results show that physics-grounded diffusion synthesis provides the main robustness gain, while SA-FNWD offers a complementary small-object localization improvement with no inference overhead.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161502

Authors: Yingchao Gou Jingbo Yin Xiangyu Wang Chengwei Zhang

Tropical cyclones reduce port capacity and leave heterogeneous congestion. Yet empirical measurements of port resilience are rarely connected to operational strategy evaluation on the same observed event baseline. This study develops a dual-layer framework that measures event-level operational resilience under prevailing practice and estimates modelled marginal improvements from three operational levers. Aggregate baseline measures calibrate multi-server queues for 28 ports without event-period tuning, and discrete-event simulation replays 178 port-event trajectories. The calibrated representation places heterogeneous ports on a common queueing scale. Measured states are benchmarked against a dynamic four-hour business-as-usual (BAU) baseline that retains normal temporal variation. During exposure, median service-capacity loss reaches 0.627, and sustained operational-capacity restoration is confirmed after a median 44 h. Service-focused recovery (SES), coordinated recovery (CRS), and two-stage proactive–reactive response (TPRS) are compared after matching costs within each event. CRS gives the largest mean reduction in cumulative queue burden under the base-case cost coefficients and ranks first in 113 of 128 cost-sensitivity scenarios. SES leads when capacity coordination becomes sufficiently expensive, while TPRS becomes more competitive under prolonged, high-loss exposure. The framework supports strategy assessment according to event state, operational feasibility, and implementation cost.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161501

Authors: Linghan Meng Zebin Huang Qingfeng Yao Yunxiu Zhang Qifeng Zhang

ROVs are essential for marine exploration and underwater operations, yet conventional teleoperation relies heavily on skilled human operators, and many autonomous methods stop at high-level planning rather than low-level actuation, limiting robustness in disturbed and cluttered environments. This paper proposes ODARRL, an obstacle- and disturbance-aware sensor-to-thruster (ST) end-to-end residual reinforcement learning framework for safe trajectory execution of underwater robots. Using a three-stage curriculum, ODARRL first acquires a basic policy from MPC demonstrations in a static obstacle-free environment, then improves disturbance-robust tracking under random currents, and finally extends to scenarios involving both currents and obstacles. A Dual-Horizon Attention Disturbance Encoder is further designed to capture current-related features from long- and short-term histories, which are fused with robot states and reference information as the input to the ST end-to-end policy. Experiments in Marine Gym with BlueROV2 Heavy demonstrate that ODARRL achieves more stable and robust trajectory tracking under random currents, reducing the mean total tracking error by 69.3%, 31.9%, 45.8%, 73.0% and 25.8% relative to the MPC-imitation policy, PPO, SAC, A2C and VNRS-SAC, respectively. With obstacles introduced, curriculum-initialized policies also exhibit higher path progress and more stable task completion during obstacle-avoidance training.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161500

Authors: Chenyang Ma Yibin Wang Ning Zhao

A CFD-based constrained three-component aerodynamic-trim procedure is implemented to investigate the load balance and coupled flowfield response of a simplified shipborne helicopter hovering over a flight deck. During the unsteady CFD calculation, the collective and cyclic pitch controls are updated according to the period-averaged vertical force and the rolling and pitching moments of the helicopter center of gravity. A pre-trim initialization is introduced before the formal-trim process to avoid large pitch corrections from the initial fixed-pitch state. Under a 20 m/s headwind, the initial fixed-pitch case shows a vertical-force deficit and extra rolling and pitching moments. After dynamic trim, the pitch controls converge to θ0=8.46°, A1=−2.48°, and B1=1.20°. Over the final one-revolution interval of approximately t = 31.74–32.00 s, the period-averaged loads are Fz=112.82 kN, Mx=−0.06 kN·m, and My=−0.07 kN·m. Additional +30° and −30° oblique-wind calculations confirm convergence toward the prescribed three-component load targets under asymmetric inflow conditions. The instantaneous flowfield comparisons suggest local responses in the rotor-inflow and fuselage-pressure regions after trim. Frequency-domain analysis identifies a dominant blade-passing-frequency component together with additional low-frequency content characteristic of the coupled rotor–ship aerodynamic response.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161499

Authors: Chan-sub Lee Joo-sung Kim

Safe navigation in coastal waters remains a persistent challenge for conventional grid-based path planning methods, which prioritize shortest-distance optimization while neglecting spatial risk distribution and kinematic trackability. This study proposes a local path planning framework that integrates an integral image-based risk field with kinematic constraints for small vessel navigation in high-resolution coastal environments. The proposed method evaluates local obstacle density through an area-based spatial risk model and employs an integral image structure to reduce risk computation complexity from O(W2) to O(1). A 16-direction node expansion strategy incorporating kinematic filtering and cubic B-spline smoothing was applied to improve maneuvering feasibility and trajectory continuity. Simulation results across two topologically distinct coastal environments, Mokpo–Sinan and Myeongnyang Strait, demonstrated that the proposed framework increased the minimum clearance distance from 20 m to 238.32 m and the average clearance distance from 884.2 m to 1038.3 m relative to the conventional A* algorithm, and consistently outperformed a static buffer-based baseline. The 16-direction search reduced the maximum course change angle by up to 39% and the average course change angle by up to 55% relative to the 8-direction configuration across both environments while maintaining practical computational efficiency. Kinematic feasibility was further verified through curvature-based analysis of the final smoothed trajectories, confirming that the minimum turning radius consistently exceeded the vessel’s theoretical minimum turning radius across all tested configurations. The results demonstrate that the proposed framework can generate risk-aware and kinematically feasible navigation routes using coastline-based occupancy information alone, suggesting potential applicability to coastal autonomous navigation in environments with limited bathymetric data.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161498

Authors: Zhipeng Chen Penghui Xie Lei Chen Sheng Fu Gaocheng Wang Liwei Jiang Chen Zou

The Mao-1 Member of the Middle Permian Maokou Formation in the Yongchuan area contains distinctive eyelid–eyeball limestones developed in an outer-ramp to intraplatform-basin transitional setting. The two components alternate as mud-rich laminae and carbonate-rich nodules or layers. Eyelid limestone contains 10–45% micritic carbonate mud and a mean total-grain content of 69.11%, whereas eyeball limestone contains <10% carbonate mud and 30.89% total grains. In the exploratory geochemical subset (five samples per facies), eyelid limestone has higher mean V, Mn, Fe, and Ba contents, but only Ba differs significantly between facies (Welch p = 0.036; exact Mann–Whitney p = 0.032). Bulk-rock rare-earth-element data are PAAS-normalized and used descriptively because concentrations are low and neither weak-acid leaching nor detrital correction was performed. The observations support a preferred interpretation involving primary depositional differentiation followed by localized early diagenesis, differential compaction, and pressure solution. Relative sea-level change may have modulated the alternation, but the available data do not resolve a unique cyclic driver. Core-scale pore data demonstrate facies-dependent heterogeneity rather than field-scale deliverability.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161497

Authors: Cillian Frawley Syed Ahmad Hasan Danny Golden Tom Doyle

Floating Offshore Wind (FOW) enables offshore wind deployment in deeper waters not suitable for bottom-fixed turbines, unlocking new areas for renewable energy generation. Most major cost contributors to FOW have clear pathways for cost reduction however mooring systems are the exception due to the pre-existing market maturity. Solutions to lower mooring costs include Mechanical Compliance Devices (MCDs) aimed at reducing the high peak and snatch loads in mooring lines and thus driving down the capital, operations and maintenance costs. In this paper, a comparison of a physical tank testing campaign and corresponding numerical analysis, for an MCD is described and analysed. The objective of the testing campaign was to validate the component-only tank results with the modelling of an MCD, namely Dublin Offshore’s Load Reduction Device (LRD) using a multi-body dynamics (MBD) approach. The paper presents analysis of the experimental testing and numerical modelling and compares the results with the validated Load–Extension Curve (LEC). Experimental testing was carried out at 1:38.5 scale using bespoke mooring test apparatus at Lír, Ireland’s National Ocean Test Facility. The results of testing are presented for all of the MCD model scales tested and compared with the modelled LEC. The correlation between the experimental and numerical data and with the LEC, characterised by Pearson Correlation Coefficient (R) in the range of 0.952 to 0.999, demonstrates the ability to model the LRD using the MBD approach.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161496

Authors: Zhounan Xu Rufu Qin

Deep learning-based vessel trajectory prediction using Automatic Identification System (AIS) has become a hot topic in the fields of maritime traffic monitoring, situational awareness, and navigational decision support. However, most previous studies have focused primarily on end-to-end model training using trajectory data from a single water area, which limits the resulting models’ ability to generalize to regions with different traffic patterns. To address this issue, this study proposes a method that constructs traffic context from historical AIS records at multiple geographic resolutions using H3, a hexagonal hierarchical spatial indexing system, and integrates this context with a Transformer-based trajectory predictor. A reliability-aware selector determines the contribution of the context to the final prediction, conditioning this decision on the vessel’s motion state and the retrieved historical patterns. Experiments on AIS data from three distinct water areas demonstrated that H3-indexed context improved cross-water prediction accuracy without requiring model retraining on the target area. These findings demonstrate that H3-indexed context, structured at multiple geographic resolutions and integrated through a selective mechanism, serves as transferable spatial context for vessel trajectory prediction.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161495

Authors: Yitao Wang Weidong Zhao Zichen Xiao Yifan Wang

To address the challenge of fatigue life prediction caused by multiple-crack interactions in ship and offshore structures, this study proposes a dynamic Bayesian network (DBN)-based method for predicting the fatigue life of structures with multiple cracks, which is systematically validated through physical experiments. First, a numerical model of a representative structure containing a central hole and multiple initial cracks was established based on the coupled simulation platform of ABAQUS and Franc3D. The nonlinear interaction behavior among multiple cracks under different geometric configurations was systematically investigated. Subsequently, a neural network surrogate model was developed, in which geometric features and crack lengths were employed as inputs and key fracture mechanics parameters were taken as outputs, enabling efficient prediction of complex stress intensity factor (SIF) fields. On this basis, fatigue crack growth experiments were conducted on DH36 high-strength steel specimens containing multiple cracks, and crack evolution data under realistic cyclic loading conditions were obtained. Finally, by coupling the surrogate model with the Paris law as the state transition equation and incorporating sparse experimental observations as dynamic updating information, a dynamic Bayesian network framework based on the particle filtering algorithm was established. This framework enables posterior probability tracking of multiple-crack fatigue states and rolling prediction of the remaining fatigue life. The results demonstrate that the proposed method can effectively mitigate the error accumulation associated with deterministic simulation models during long-term open-loop prediction while relying only on a limited number of discrete observation anchors. Consequently, the prediction accuracy of the fatigue life of multiple-crack systems is significantly improved. Furthermore, under crack co-propagation conditions, the proposed framework exhibits a strong capability to capture the propagation retardation of secondary cracks induced by shielding effects. The proposed method provides a theoretical foundation and technical support for the dynamic assessment of fatigue damage and the development of digital twins for complex structures containing multiple cracks.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161494

Authors: Qian Ma Pengyu Zhou Hongcheng Xue Jingjie Feng Jun Wu Yuanyuan Li Chaozhe Zhang Xiaoshuang Cheng

Landslide-induced waves are primarily controlled by granular dynamics during landslide–water impact. While particle size, velocity, and volume are recognized influences, the role of internal grain arrangement and segregation remains less clear. This study employs a coupled CFD-DEM model to investigate how vertical permutation of three fixed grain fractions and layered configurations affect surge generation and propagation. Simulations using three particle sizes (1, 3, and 5 mm) in six initial arrangements reveal that fine particles dominate leading wave formation through efficient momentum transfer, yielding an overall wave height growth of 5.22% and a maximum local growth rate of 2.42%. Grain size segregation governs deposit morphology, with larger particles migrating preferentially along the flow direction. Increasing still-water depth systematically shifts surge characteristics from strongly nonlinear, high-amplitude shallow-water waves to more linear, longer-wavelength, smaller-amplitude deep-water features. Energy dissipation, which is linked to reduced equivalent water depth, decreases wave celerity with propagation distance. The model reproduces granular collapse experiments with a relative error below 5%, confirming that granular segregation critically controls surge dynamics and providing a refined framework for simulating natural landslide-generated waves.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161493

Authors: Gary B. Griggs

Two breakwaters were constructed between 1959 and 1961 by the U.S. Army Corps of Engineers to form a harbor within Half Moon Bay on the central California coast. Prior to construction, the bay had a smooth hook-shaped or spiral form with a shoreline in equilibrium with waves refracted around a resistant point. Following breakwater completion, wave energy that had previously been dissipated along the equilibrium shoreline of the bay was concentrated at the downcoast end of the breakwater against the low weak bluffs. The original very low (~8 cm/year) bluff recession rates increased rapidly to as much as 2 m/year which led to the destruction of a county road and wastewater transmission line and began to threaten a state highway and a group of homes. Bluff erosion has progressed as far as 1.4 km downcoast which has led to rock revetment placement to protect the highway and homes. Breakwater planning also underestimated the potential for waves to enter the gap between the two breakwaters, so a dogleg extension had to be constructed. This also failed to reduce wave action, which led to the construction of an additional set of breakwaters within the harbor to protect moored boats.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161492

Authors: Xinhao Zuo Congcong Wang Jin Wang

HY–4A is China’s first ocean salinity remote-sensing satellite, launched into orbit in November 2024 and currently in operational service. The LASMR (L-Band Aperture Synthesis Microwave Radiometer) is the L-band synthetic aperture radiometer onboard the HY–4A satellite. This study validates the LASMR Level-2 SSS (sea surface salinity) product using in situ salinity observations from Argo floats, covering the period from November 2024 to December 2025. Global analysis indicates that the LASMR SSS retrieval uncertainties show a distinct zonal distribution, which primarily reflects the impact of sea surface temperature (SST) and sea surface wind speed on SSS retrieval accuracy. A lower SST reduces the sensitivity of brightness temperature (TB) to SSS variations, and a high wind speed degrades the sea surface roughness correction. Both factors lead to increasing uncertainties in SSS retrieval. Furthermore, atmospheric parameters including water vapor content and precipitation also affect the SSS retrieval uncertainty. The influence of water vapor may originate from its coupling with SST/wind speed and inherent uncertainties in the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data. The effect of precipitation is more complex: it increases ocean TB through rain-induced surface freshening and additional rain-induced roughening, which aliases into the satellite signal. Moreover, precipitation-enhanced vertical salinity gradients amplify the vertical representativeness error arising from the depth difference between satellite sensing and Argo measurements. Meanwhile, impacted by land brightness temperature contamination and radio-frequency interference (RFI), the SSS retrieval accuracy of HY–4A decreases significantly in coastal waters compared with the open ocean. Since the traditional buoy–satellite dual-matching method tends to overestimate uncertainties in satellite data, an Argo/HY–4A/SMAP (Soil Moisture Active Passive) triple-collocation dataset is used to estimate the LASMR SSS retrieval uncertainties. The triple-collocation method yields robust uncertainty estimates for both satellites (HY–4A and SMAP) over the global ocean and high-salinity-variability regions. In conclusion, the global uncertainty of the HY–4A LASMR SSS product is 0.35 psu. These results provide a reference for future product refinement and improvements in HY–4A SSS retrieval algorithms.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161491

Authors: Ting Ji Yang Yang Wensen Zhang Peng Yu Jiuchao Chen Lie Yu Junhao Li

During the floating transportation and installation of immersed tube tunnels, the mechanical stability of the mooring system is a key factor governing construction safety. Current conditions and mooring-line arrangements are two major factors controlling the magnitude and distribution of mooring-line tensions. However, their coupled effects and the applicability of different calculation methods remain insufficiently understood. Based on a large-cross-section immersed tube tunnel project, this study employed a semi-empirical method specified in the Chinese Code for Loads on Port Engineering and a three-dimensional floating-body-mooring numerical model established in ANSYS AQWA. Multiple combinations of current velocity and direction were considered to compare the mooring-line responses under five typical arrangements corresponding to different construction stages. The effects of current conditions and mooring configurations on the magnitude, distribution, and transfer of mooring-line loads were systematically examined. The results show that current velocity is the dominant factor controlling the magnitude of mooring-line tensions, which generally increase with the square of the current velocity. Changes in current direction directly alter the principal load-bearing mooring-line group, and a current velocity of 1.5 m/s during the falling tide represents the most unfavorable current condition throughout the construction process. The mooring-line arrangement governs the spatial distribution and concentration of the line loads. During the floating transportation and mooring stages with multi-line constraints, the maximum mooring-line tensions calculated using China’s code-based method are 18.5–25.2% higher than those obtained from the numerical simulations, indicating relatively conservative predictions. In contrast, during stages with weakened constraints, such as line release and positioning in the foundation trench, the numerical model captures more pronounced local load concentration, yielding maximum tensions 19.4–28.8% higher than those predicted by the code-based method. Across all operating conditions, the maximum mooring-line tensions calculated by the code-based method and numerical model are 924 and 750 kN, respectively. This study clarifies the coupled effects of current conditions and mooring-line arrangements on mooring-load transfer and identifies the applicable scenarios of the two calculation methods. The findings provide a quantitative basis for calculation-method selection, mooring-force assessment, and construction-safety management during immersed tube tunnel installation.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161490

Authors: Ling Tan Jianqiang Zhang Yiping Liu Pengfei Zhang Xingda Li

Unmanned surface vehicle (USV) formations operating under GNSS denial require accurate relative localization using proprioceptive sensors and inter-vehicle ranging. This paper presents an anomaly-aware adaptive extended Kalman filter for four-USV formations using inertial measurements, compass, and ultra-wideband ranging, and systematically characterizes its operating envelope. Observability analysis establishes that S-curve maneuvering achieves structural rank 24, with only global translation unobservable, while straight-line motion leads to a rank deficiency of exactly seven dimensions All four gyroscope biases remain observable under both trajectories. The proposed filter integrates chi-square testing, cumulative sum (CUSUM) detection, and bias drift rate monitoring to trigger coordinated R adaptation and Q-boost mechanisms. Controlled experiments spanning outlier magnitudes and drift rates reveal three performance regimes, clean conditions with equivalent performance across all variants, moderate outliers [3σd,10σd] where the proposed method achieves 4.8–13.4% improvement, and extreme outliers where all robust methods converge. Critically, pure bias drift experiments expose a structural limitation of single-hypothesis, residual domain robustification within the tested drift range—all variants exhibit equivalent performance across the tested drift rates, analytically attributable to Kalman gain partitioning that distributes innovations between position and bias subspaces. The characterized operating envelope establishes that robust mechanisms provide measurable benefits for transient anomalies but encounter hard boundaries under persistent drift conditions, with all variants converging to equivalent performance across the tested range, necessitating multi-hypothesis or constraint-based approaches.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161489

Authors: Chaozhi Qiu Shigeo Yoshida Zhiqiang Hu Chang Cai Yingyi Liu

This paper presents WSMAQ (WEC-Sim-MoorDyn-AeroelasticQ), a coupled aero-hydro-elastic-mooring simulation framework for floating offshore multi-rotor wind turbines. The framework integrates WEC-Sim for platform hydrodynamics; MoorDyn-C for mooring-line dynamics; and in-house aeroelastic code, AeroelasticQ, for rotor-level aerodynamic and blade structural calculations. These modules are coupled within MATLAB/Simulink/Simscape 2023a. The novelty of WSMAQ lies in three coupling-oriented methodological extensions. First, for deep-draft spar platforms, the WEC-Sim body is configured using the physical mass and inertia at the true center of gravity, the full unadjusted added-mass matrix is retained in the radiation-load calculation, and a three-block integrator filter is used to break the added-mass–acceleration algebraic loop. Second, the WEC-Sim mooring class is extended to pass the non-zero initial platform orientation to MoorDyn-C. Third, AeroelasticQ is integrated with the multibody wind turbine model through a rotor-count-parameterized Level-2 C++ MEX S-function. The framework was benchmarked against OpenFAST through aeroelastic, platform-mooring, and full-wind-turbine tests on the OC3 spar with the 5 MW reference turbine developed by the National Renewable Energy Laboratory. Across the primary response channels, the mean relative error remained below 2% in most cases. Multi-rotor capacity was demonstrated using three NREL WindPACT 1.5 MW turbines mounted on the OC3 spar. In this case study, an asymmetric rotor-parked condition generated a mean yaw offset of approximately 4°, which did not appear in the symmetric-load cases.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161488

Authors: Theodosis D. Tsaousis Constantine Michailides Ioannis K. Chatjigeorgiou

The purpose of this paper is to derive and propose site-specific joint environmental contours for two eligible Offshore Wind Farm Organized Development Areas (OWFODAs) in the Aegean Sea, Greece. The contours are tailored primarily for the design, structural reliability assessment and definition of site-specific environmental load combinations of offshore wind turbines (OWTs); they are quantified based on publicly available 28-year data sets related to offshore wind and wave conditions, namely, wave height, Hs, wave peak period, Tp and mean wind speed at the hub height of the wind turbine, u¯hub. A new methodology, using the modified Inverse First Order Reliability Method (IFORM), is proposed to accurately reflect the regional climate peculiarities, combined with fifth-order polynomials and a sigmoid function to fit the data of the Weibull parameters and correctly capture the low- and mid-range values of Hs, which are statistically far more frequent. Several results, in terms of 2D and 3D contour surfaces for two locations in each OWFODA, for 50-year and 100-year return periods are presented. Finally, two tables are cited: one gathering Hs and Tp values corresponding to the maximum u¯hub conditions, and another gathering u¯hub and Tp values corresponding to the maximum Hs conditions. The presented joint probability distributions and the environmental contour surfaces bridge metocean statistical modelling with renewable energy systems design. By providing site-specific joint metocean conditions, the proposed methodology supports offshore wind farm design and structural assessment, thereby contributing to sustainable wind energy development in the Aegean Sea.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161487

Authors: Kai Yan Xunhua Zhang Xingwei Guo Fanghui Hou Xiaoqing Zhu

Most studies on the Early Triassic paleomagnetism of the Yangtze Block (YB) have concentrated on the Western to Middle parts, but the South Yellow Sea (SYS) in the Eastern YB (EYB) is relatively lacking. To ascertain the paleogeographic position of the SYS, we isolated the characteristic remanent magnetization (ChRM) direction from 46 standard core samples and characterized the magnetic mineral compositions of 70 fragmentary samples. These samples were all derived from continuous full-core drilling in the Lower Triassic Qinglong Formation within the CSDP-2 Well. We also reconstruct the paleomagnetic directions by utilizing published Early Triassic paleomagnetic pole data individually from the YB and North China Block (NCB). The experimental results show that the CSDP-2 Well was at 15.9° N (+2.9°/−3.2°) in the Early Triassic after paleomagnetic inclination correction. Taking the CSDP–2 Well as the reference point, published data indicated that the YB was at 19.4° N ± 1.2° and the NCB was at 13.7° N ± 2.7° in the Early Triassic. On the basis of previous knowledge and the paleomagnetic data, we think that the YB and NCB collided before the Triassic and further confirm the reliability of the scissor-like collisional model which was initially in the East and later in the West. In addition, we consider that the crust of the EYB may have moved northward 389.2 ± 166.8 km since the Early Triassic. These results have implications for reconstructing paleogeographic position of the SYS and some details of collisional process between two blocks.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161486

Authors: Tianrui Zhang Jiaxiang Zheng Changjin Dong Baoju Wu Nanmu Hui

To address the motion control challenges of remotely operated vehicles (ROVs) under model uncertainties, external disturbances, and uncertain hydrodynamic parameters, this study proposes a fractional-order super-twisting sliding mode control (FOST-SMC) strategy based on improved active disturbance rejection control (IADRC). The proposed method reduces dependence on accurate dynamic models and enhances disturbance rejection capability by integrating IADRC with FOST-SMC. A sine-function-based nonlinear extended state observer (ESO) was developed to improve lumped disturbance estimation and noise robustness. The proposed ESO reduces the root mean square (RMS) estimation error from 2.226 × 10−5 to 5.224 × 10−6, corresponding to a 76.5% reduction compared with the conventional ESO. Lyapunov analysis verified the stability of the closed-loop system. MATLAB/Simulink version R2024a (MathWorks, Natick, MA, USA) simulations based on the Falcon ROV model demonstrated improved tracking performance under step response, sinusoidal tracking, and three-dimensional trajectory tracking with time-varying disturbances and Gaussian white noise. Compared with conventional active disturbance rejection control (ADRC), the proposed controller achieved average RMSE reductions of 87.0%, 57.2%, and 49.4 to 65.4% in different tracking scenarios, respectively. The proposed strategy provides an effective approach for robust ROV motion control in uncertain underwater environments.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161485

Authors: Yizhou Lai Hailong Guo Feimeng Huang Gang Zhang

A high-resolution unstructured-grid ocean model was used to investigate the generation, propagation, and dissipation of M2 internal tides in the Luzon Strait and northeastern South China Sea, with the aim of clarifying how energy evolves across contrasting topographic regimes. Wave decomposition, harmonic and modal analyses, energy-budget diagnostics, and along-path tracking were applied to quantify the spatial distribution and modal evolution of internal-tide energy. The results show that the Luzon Strait double-ridge system is the primary source region, contributing approximately 4.826 GW of barotropic-to-baroclinic energy conversion, with the Lanyu Ridge (3.080 GW) exhibiting stronger conversion than the Hengchun Ridge (1.643 GW). The generated low-mode internal tides radiate mainly westward into the northeastern South China Sea, with energy progressively attenuated over the deep basin and continental slope. Energy-budget analyses indicate that the ridge region dominates generation, the Luzon Trough mainly supports transmission, and the deep basin and slope are associated with enhanced dissipation and scattering. Along-path energetic diagnostics quantitatively reveal a sequential depletion of mode 1 internal-tide energy in the vicinities of steep topography and internal-tide steepening zones, concomitant with a marked augmentation of mode 2 energy and intensified cross-frequency energy transfer. Specifically, within the deep basin of the South China Sea, the fractional contribution of mode 1 energy declines from 78.3% to 73.8% as the internal tide propagates from the abyssal to the shallower shelf-slope region, whereas that of mode 2 increases correspondingly from 18.2% to 24.3%. Moreover, pronounced internal-tide steepening is observed in the deep basin, and the spectrally integrated cross-frequency transfer coefficient reaches 0.32 in this area, substantially exceeding that in other regions. These findings suggest that topographic scattering, modal redistribution, and nonlinear interactions contribute substantially to regional internal-tide dissipation.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161484

Authors: Xinyuan An Huibing Gan Yanlin Liu

The exhaust gas temperature (EGT) of marine diesel engines is an important parameter reflecting the engine’s operating conditions. Its variation is influenced by complex thermodynamic processes, including combustion fluctuations and thermal inertia effects, and exhibits significant non-stationarity and multiscale fluctuation characteristics, posing considerable challenges for multi-step forecasting. To address this issue, this paper proposes a multi-step EGT forecasting method for marine diesel engines based on frequency-aware trend-residual learning. This method first extracts long-term variation information from the EGT sequence, then employs frequency-domain analysis to enhance and characterize short-term fluctuation components, and applies temporal feature learning with an adaptive fusion strategy to effectively integrate information across different time scales, thereby improving the accuracy of multi-step EGT forecasting. Based on actual ship operation data, multi-step EGT forecasting tasks with different horizons are established, and the proposed method is compared with several typical deep learning models. Experimental results show that the proposed method achieves competitive and consistent performance across all forecasting horizons. For one-step to four-step forecasting tasks, the mean absolute errors are 0.3078, 0.5037, 0.6835 and 0.8312, respectively, all of which are lower than those of the comparison models. Moreover, the proposed method demonstrates stable performance in evaluation metrics such as mean squared error. These results verify the effectiveness of the proposed method.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161483

Authors: Yoonseo Lee Chanjin Jeong SeungOh Lee

Coastal defenses under tsunami-like long waves are judged not only by wave attenuation but by their own stability and the hazard left landward, so a porous structure is assessed through several responses at once. OpenFOAM (porousWaveFoam) and FLOW-3D HYDRO are the two models most widely used for such problems, representing the open-source and the commercial approach, and each has an extensive record for solitary waves and for porous structures separately. Which to adopt for a given response is not established, since the two have not been compared where both occur together. Five hydraulic benchmarks were, therefore, reproduced with both, taken as configured in practice, since the differing elements cannot be exchanged by the user. Agreement was decomposed into error components and into the scalars that enter a design check, and each difference was weighed against a combined uncertainty. Neither model is superior across the responses. Across 57 signals, the more accurate one changes with the metric in 81% of cases, and six of thirteen governing comparisons exceed the uncertainty. Some of the largest errors are shared, so changing the model does not remove them, and the cost ordering reverses with the problem size. Model selection should, therefore, follow the target design response, together with a statement of whether the difference exceeds the uncertainty. These findings hold within the configurations tested; extension to random waves remains for future work.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161482

Authors: Bjorna Qesaraku Jan Steckel

Predicting vessel motion and environmental dynamics is essential for safe operation of autonomous maritime navigation systems. Transformer-based models have achieved strong results in AIS-trajectory forecasting and in anticipating future sonar observations, however, their use in maritime radar frame prediction has received little attention, despite radar being a key sensing modality in challenging weather and visibility conditions. In an effort to address this gap, this paper introduces a transformer architecture for predicting future maritime radar frames from sequences of past X-band observations and vessel ego-motion derived from GNSS, adapting the EchoPT paradigm originally developed for simulated in-air sonar imagery to the real-world MOANA dataset. We detail the model architecture and evaluate its prediction performance under both single-frame and autoregressive settings on held-out test data, and benchmark the model against persistence and rigid geometric warp references. A complementary failure mode analysis links the observed prediction errors to specific architectural and dataset choices, providing concrete directions for further research.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161481

Authors: Lipeng Huo Jifeng Zhu Jian Wang Heng Wen Zheng Peng Xiaoxin Guo Yusha Liu Jun-Hong Cui

To address task-driven selection bias in historical deployment records, this study proposes a structural-causal-model-based framework for quantifying bias in the utility assessment and deployment-effect estimation of integrated underwater communication and positioning networks. Four datasets were constructed under unbiased, communication-dominant, positioning-dominant, and joint-biased sampling mechanisms, and double machine learning (DML) was adopted to analyze overall utility and its communication/localization components under decision factors. The simulation results demonstrate that communication-dominated data overestimates overall utility by 23.5%, while location-dominated data underestimates by 21.4%. CATE analysis further identifies noise spectral level as the strongest effect modifier (feature importance 0.76). The sea trial results show close agreement between simulated CRLB and measured RMSE, which supports the physical plausibility of the positioning utility model and the WOA23-based simulation pipeline underlying the causal analysis.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161480

Authors: Christian Velasco-Gallego Leszek Chybowski

The maritime sector is undergoing an unprecedented digital transformation driven by rapid advances in artificial intelligence (AI), data analytics, cyber–physical systems, and edge computing [...]

Journal of Marine Science and Engineering doi: 10.3390/jmse14161479

Authors: Yingna Li Jingcai Zhang Hao Yang Shuhang Wang Siyu Liu Lingxi Gu

To elucidate the influence of operational conditions on the seismic responses of offshore wind turbines (OWTs) and the vibration mitigation efficacy of tuned mass dampers (TMDs) under multi-hazard scenarios, time-domain dynamic analyses are performed for OWT systems subjected to combined wind, wave and seismic excitations. Five typical operational conditions are considered, including cut-in operation, rated-power operation, cut-out shutdown, 1-year return-period extreme shutdown, and 50-year return-period extreme shutdown. The nacelle acceleration and tower-top displacement responses of the uncontrolled structure are comparatively characterized, the peak and root-mean-square (RMS) vibration reduction ratios of the TMD for fore-aft vibrations are quantitatively assessed, and the intrinsic mechanism governing the response discrepancies across operational conditions is elucidated. Numerical results demonstrate that seismic excitation dominates the extreme structural responses of the OWT system. Under the rated-power condition, the peak acceleration and displacement under coupled seismic loading reach 6.90 and 2.19 times the corresponding values under wind–wave loads alone, respectively. Substantial discrepancies in structural responses are observed across operational conditions, with aerodynamic damping magnitude and the spectral properties of hub rotational loads identified as the key influencing factors. The TMD exhibits reliable vibration control performance overall: the optimal control efficacy is achieved under the 1-year return-period shutdown condition, with a peak acceleration reduction ratio of 34.8%—by contrast, its mitigation performance degrades significantly under the 50-year return-period extreme-turbulence condition, with the peak acceleration reduction ratio dropping to merely 15.8%.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161478

Authors: Bin Wang Jiawei Yu Chao Luo Yujia Tang Yongqing Lai Yefeng Cai

This study employs a multi-region coupled method to investigate the motion responses and aerodynamic load variations of the IEA 15 MW semi-submersible floating wind turbine (FOWT) under extreme focused wave conditions. The methodology employs the self-developed MRFoam solver within OpenFOAM to integrate aerodynamic and hydrodynamic analyses. The computational framework combines an incompressible viscous flow model with kOmegaSST turbulence closure and an actuator line representation of turbine blades. Extreme wave conditions are generated using NewWave theory, with systematic variations in wave height and wind speed to evaluate coupled effects. Results demonstrate that platform heave responds predominantly to wave excitation, showing minimal wind sensitivity. Turbine thrust maintains consistent mean values across wave conditions but exhibits wind-speed-dependent fluctuations. Mooring dynamics correlate strongly with surge motions, showing amplified tension variations from wave-induced platform displacements, though mean tensions remain stable under uniform wind regardless of wave magnitude.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161477

Authors: Weijun Wang Mingjie Li Bushuo Wang Jiajie Hu Tao Zhang

Ship path planning is a central challenge in autonomous navigation for unmanned surface vehicles and maritime autonomous surface ships. It is not simply a shortest-path problem, but a constrained sequential decision process that must reconcile collision risk, route efficiency, COLREGs compliance, vessel dynamics, and environmental uncertainty. Here we review the field through a unified framework based on planning scope, decision basis, and deployment requirements. We examine search- and sampling-based, geometric and rule-based, optimization-based, learning-driven, and hybrid methods, with particular emphasis on deep reinforcement learning for discrete decisions, continuous maneuvering, multi-vessel interaction, and safety-oriented control. Representative studies are compared across objective and reward design, state representation, exploration and policy optimization, rule integration, disturbance modeling, simulation platforms, and operational validation. The synthesis identifies persistent barriers, including ambiguous rule formalization, partial observability, strategic coupling among vessels, inconsistent benchmarks, limited cross-scenario generalization, and insufficient full-scale validation. We further discuss priority directions in explicit safety constraints, digital twins, transfer and meta-learning, world models, scalable multi-agent coordination, and large-model-assisted mission reasoning. We argue that progress will depend less on further algorithmic proliferation than on integrated, verifiable architectures that combine data-driven adaptation with model-based structure, standardized evaluation, and staged real-world assurance.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161476

Authors: Shafqat Ali Aamir Mehmood Faiza Iftikhar Jamal Alotaibi Faisal Alhwikem Saddam Hussain Khan Arshad Ali

This study addresses the trajectory tracking control problem for an underactuated hovercraft subject to additive bias and multiplicative loss-of-effectiveness thruster faults under environmental disturbances. In these systems, actuator degradation structurally breaks the differential flatness mapping, driving nominal controllers to generate control actions that induce severe actuator saturation and cause instability. To resolve this challenge, a hierarchical physics-informed neural adaptive control (PINAC) framework is proposed. First, a gated-recurrent-unit physics-informed neural observer (PINO) is designed to isolate thruster faults from exogenous hydrodynamic disturbances. Second, a constrained Safe-TD3 reinforcement learning agent functions as a supervisor, computing an online dilation factor to slow down the mission timeline, thereby reconfiguring the reference trajectory to accommodate degraded actuator boundaries. Third, a low-level non-singular terminal sliding mode (NTSM) controller is implemented as a tracking-guarantee layer. Unlike classical asymptotic schemes where convergence is only achieved as time approaches infinity, or finite-time controllers where the settling time depends on the initial state, the proposed PINAC framework guarantees practical fixed-time stability, ensuring that the settling-time bound is independent of initial conditions. Simulation results demonstrate that the designed controller prevents actuator saturation, provides smooth trajectory adjustment, and reduces tracking errors under severe composite faults.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161475

Authors: Wei Li Chenjie Xu Hanyun Zhou Yiting Hong

To address the path following of underactuated unmanned surface vehicles (USVs) under external disturbances with computational efficiency, this paper proposes an efficient algebraic model predictive control (e-AMPC) framework with disturbance compensation. A nonlinear disturbance observer (NDOB) is embedded into the prediction model, and a variable coincidence-point strategy is adopted to reduce the computational load. The cascade system, composed of the e-AMPC controller and the NDOB, is analyzed as a whole, and a Lyapunov-based proof is provided to establish input-to-state practical stability under bounded disturbances. Extensive simulations verify the superior path-following performance and accurate disturbance estimation, achieving an approximately 74% reduction in computation time compared with conventional MPC. The simulations also quantitatively reveal the influence of prediction-point distribution, weighting matrices, and observer gain on disturbance rejection and tracking accuracy. These guidelines significantly enhance the engineering practicality and reliability of the proposed controller.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161474

Authors: George Konstantopoulos Dimitrios N. Konispoliatis

This study investigates the hydrodynamic behavior of the OC4-DeepCwind floating offshore wind turbine, with a specific focus on the influence of wave reflection and hydrodynamic interaction effects between the platform components. The OC4-DeepCwind semi-submersible platform, supporting the NREL 5 MW reference wind turbine, is analyzed using the commercial software ANSYS AQWA 2024 R1 and the in-house codes HAMVAB and SEMISUB. While ANSYS AQWA and HAMVAB account for multiple wave scattering effects within the multi-column configuration, SEMISUB neglects hydrodynamic interactions, enabling a systematic assessment of their influence on the predicted response. Interaction effects are most pronounced in the surge degree of freedom, where neglecting wave reflection distorts the exciting wave force above 0.65 rad/s, and in the surge, heave, and pitch added mass and radiation damping coefficients, with substantial deviations above approximately 0.6 rad/s. The influence of column separation distance on these diffraction loads is also examined. Stochastic-wave simulations of the moored wind turbine under realistic JONSWAP sea states show normalized errors across all examined sea states of 16.6% (heave), 14.6% (surge), and 9.9% (pitch) in platform motions when interactions are neglected, whereas tower-base loads and mooring line tensions are less sensitive, with errors of 11.5% (vertical shear force), 9.4% (horizontal shear force), 9.2% (bending moment), 8.7% (downstream mooring tension), and 5.6% (upstream mooring tension). These results indicate that hydrodynamic interaction effects are critical for predicting platform motions and hydrodynamic coefficients but have a comparatively limited effect on design-governing structural and mooring loads, offering quantitative guidance on when simplified interaction-free models remain adequate for semi-submersible FOWT design.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161473

Authors: María Pérez Tadeo Joanne O’Brien

Static Acoustic Monitoring (SAM) using C-PODs, deep C-PODs, and F-PODs was conducted as part of the STRAITS project (Strategic Infrastructure for improved animal Tracking in European Seas), funded under the EU’s Horizon research and innovation programme, to investigate odontocete acoustic occurrence across four European straits: the North Channel, the Sound, the Strait of Gibraltar, and the Dardanelles Strait. The acoustic presence of dolphin species and harbour porpoises was modelled in relation to tidal cycle, moon phase, sea surface temperature (SST), diel period, season, and Sound Pressure Levels (SPLs), representing ambient underwater sound using a Generalised Additive Modelling (GAM) approach. Harbour porpoises were primarily detected in the Sound and the North Channel, while dolphin detections were higher in the Strait of Gibraltar and the Dardanelles Strait. There was a significant association with SPLs on both species across all locations where it was assessed. There was a significant effect of tidal cycle and SST on both species across all locations except the Dardanelles Strait. Temporal patterns were significant across species and study sites. This study presents the first multi-strait assessment of odontocete occurrence in key marine corridors, highlighting the relationship of environmental and temporal drivers, underwater noise, and odontocete occurrence, and providing insights for marine spatial planning and conservation management in highly trafficked regions.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161471

Authors: Ali Fituri Abdelouahed Gherbi Hmeda Musbah

In hybrid energy systems, maintaining an optimal scheduling strategy for real-time distribution systems, particularly in triple hybrid power generation units, remains a critical challenge. The lack of an efficient real-time observability platform for off-grid hybrid units directly impacts scheduling priorities. In this work, a novel operational condition monitor that has a data-driven predictive mechanism for determining the instant states of each tidal stream turbine is proposed. Environmental variables are first preprocessed using a multivariate fuzzy logic system to generate informative features, which in turn are used by a machine learning classifier to identify the turbine availability states. The classifier is evaluated using K-fold cross-validation and robustness under increasing environmental noise levels. The main contributions of this work are the reduction in uncertainty and the association with real-time operating conditions, which enable optimal scheduling decisions. The baseline XGBoost classifier achieved an F1-score that increased after adding fuzzy-derived features. Comparative evaluation under noise-free and increasing noise levels demonstrates that the proposed framework consistently outperformed the baseline model while maintaining robust classification performance.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161472

Authors: Wei Wang Xiaoyan Liu Song Peng Yijing Gong Yongqiang Tu

The application of a staged booster system can significantly extend the operational range of a supercavitating vehicle. Booster separation from the main body within the supercavity, followed by its downstream movement and exit from the cavity, constitutes a key process in the realization of this technology. To investigate the hydrodynamic characteristics of the vehicle’s main body during in-cavity booster separation, an unsteady numerical study was conducted using the finite volume method, the Volume of Fluid (VOF) multiphase flow model, and a dynamic mesh technique. The evolution of cavity morphology and the corresponding hydrodynamic characteristics of the main body during the booster separation process were obtained. Furthermore, the effects of the relative separation velocity and separation distance on the hydrodynamic characteristics of the vehicle were analyzed, and the primary mechanisms responsible for the complex variations in hydrodynamic forces were clarified. When the booster separation velocity is not greater than the free-stream velocity, the hydrodynamic forces of the vehicle remain stable. When the separation velocity exceeds the free-stream velocity, the hydrodynamic forces undergo significant changes as the booster moves to a position approximately 0.75~1.0L downstream of the vehicle. A novel numerical approach based on the conventional dynamic mesh technique was employed to simulate two-body separation inside a supercavity, providing a new perspective for future investigations of multistage booster systems for range extension of supercavitating vehicles.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161470

Authors: Guanghua Zhang Gaoyue Ma Wudi Wen Guangyuan Zhou Yifan Tu

Passive recognition of medium access control (MAC) protocols allows an underwater acoustic monitoring node to infer channel-access behavior without decoded control headers or cooperation from the observed network. This study evaluates a parameter-efficient time–frequency temporal convolutional network (RTF-TCN) using exclusively simulated clean waveforms corrupted by independently generated Gaussian or symmetric alpha-stable noise. The processing chain is fully specified from the clean sig arrays through MATLAB’s power-spectral-density output of spectrogram, temporal resampling, cropping, log-percentile normalization, and model evaluation. To reduce leakage from shared simulation geometry, the new experiments use topology group-wise train/validation/test splits rather than the sample-wise split used by the inherited benchmark. Across five seeds, in-domain performance remained stable over the Gaussian −5 to +5 dB range. At 0 dB for the study-defined scale-based signal-to-noise measure (scale-GSNR), performance remained high at alpha = 1.8 and 1.7, became unstable at alpha = 1.6 (70.75% ± 18.66%), and approached the balanced five-class performance floor at alpha = 1.5 and 1.2. Checkpoints trained at alpha = 1.8 also degraded when directly transferred to heavier-tailed conditions. An inherited sample-wise ablation found higher Macro-F1 for a standard 3 × 3 frontend, but that variant used 3.5× as many parameters as the asymmetric frontend. RTF-TCN contains 158,149 parameters and has profiled costs of 289.08 million multiply-accumulate operations and 578.16 million floating-point operations for one 1 × 1 × 100 × 580 input. The results support parameter efficiency within the tested conditions, but they do not establish generalization to measured sea data.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161469

Authors: Gustavo Pires da Ponte Erik Eduardo Rego

Offshore wind energy is rapidly emerging as a pivotal technology for global decarbonization and energy security, particularly in emerging markets with vast maritime resources like Brazil. This article presents a comprehensive and integrative literature review that evaluates the socio-environmental impacts of offshore wind while simultaneously analyzing its strategic role in providing “Capacity Value” and systemic security to the Brazilian Power System. Unlike onshore wind, offshore resources in Brazil exhibit superior technical characteristics, with capacity factors reaching up to 67% and a strong countercyclical complementarity with hydrological regimes. These features allow offshore wind to reliably contribute to meeting peak demand and reducing power deficits, quantified through metrics such as Conditional Value at Risk (CVaR) and Firm Energy Certificates. However, the expansion of the sector brings complex socio-environmental challenges, including impacts on marine biodiversity, disruptions to artisanal fisheries, and a high reliance on critical minerals. The analysis reveals that current licensing frameworks in Brazil, although evolving with the enactment of Law No. 15,097/2025, still face gaps in cumulative impact assessment and participatory governance. The article concludes by proposing a “dual-track” governance approach that integrates Marine Spatial Planning (MSP) with supply-adequacy requirements. By aligning technical optimization with biodiversity safeguards and social equity, Brazil can foster a sustainable offshore wind sector that acts as a reliable pillar for its long-term energy transition.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161468

Authors: Jae-Yong Lee Joo-Sung Kim

Navigational obstacles pose compound collision and pollution risks, yet conventional quantitative assessment models relying on data-driven “best-estimate” approaches suffer from “alarm masking”, whereby critical risk signals are diluted through averaging. This study develops a conservative hybrid risk assessment framework that preserves critical risk signals while systematically incorporating qualitative factors beyond the reach of quantitative data. The fuzzy inference rules of an existing integrated model were redesigned into a priority-stratified hybrid hierarchical–parallel fuzzy inference system (HHP-FIS); a qualitative evaluation matrix of four categories and 32 items was constructed through a two-stage expert procedure (a Delphi panel of eight officials and an analytic hierarchy process (AHP) survey of 59 experts with 34 valid responses); and a Red Flag Protocol was introduced as a fail-safe veto mechanism. The framework was verified through eighteen paired random-input simulations across two grid systems and a case study of a 68.9-ton drifting fishing vessel near Seongsan Port, Jeju Island. The model upwardly reclassified underestimated low-frequency, high-consequence scenarios, raised the case-study risk from Low (44.6 and 47.7) to Moderate (59.1 and 74.8), with an action level consistent with expert judgment, and was robust to rule-weight perturbations, providing a decision-support tool for obstacle-removal prioritization and marine pollution prevention.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161467

Authors: Wenting Diao Chuang Xu Yongqi Yang Yuzhi Yao Jianan Xu

The oscillating hydrofoil represents a promising tidal energy harvesting device, but its hydrodynamic behavior and energy harvesting performance can be significantly affected by the wing-in-ground (WIG) effect under near-wall conditions. The present work establishes a two-dimensional numerical model that accounts for bilateral WIG effect to investigate the effect of three key parameters, namely the dimensionless wall distance (H∗), the Reynolds number (Re), and the reduced oscillation frequency (f∗) on energy harvesting performance. The formation, shedding, and reattachment of the leading-edge vortex (LEV) are analyzed to clarify the underlying hydrodynamic mechanisms. The results demonstrate that the WIG effect notably enhances the energy harvesting efficiency of the oscillating hydrofoil. At Re=5×105 and f∗=0.14, the maximum energy harvesting efficiency reaches 69.6% at H∗=2, representing an improvement of 84.1% over the reference efficiency of 37.8% at the negligible WIG reference condition of H∗=40. As H∗ increases, the hydrodynamic performance gradually approaches that of the unconfined hydrofoil. Based on the predefined 5% efficiency-deviation criterion, the WIG effect becomes negligible at approximately H∗=9. The sensitivity to the WIG effect increases at higher oscillation frequencies, whereas its dependence on Re is non-monotonic, decreasing up to Re=4.5×105 and increasing thereafter. Finally, the four-component Gaussian mixture model (GMM) is employed to construct a prediction model for the wall distance at which the WIG effect becomes negligible under different combinations of the Reynolds number and the oscillation frequency. The model achieves an RMSE of 1.991 and an R2 of 0.667. These results quantify the effective range of the bilateral WIG effect and provide a practical criterion for reducing wall interference in relevant experiments.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161466

Authors: Jiawen Lu Bin Xi Wang Xi Xuekun Hua Hongjun Liu Xuemei Xu

Special orthogonal lateral-intake pumping stations on coastal plains face severe lateral deflection and recirculation in the approach channel and forebay. Their underlying evolutionary mechanisms remain unclear, and conventional rectification methods cause substantial hydraulic losses. Using numerical simulations and hydraulic model experiments, this study investigates these unfavorable flow patterns and proposes an original Combined Arc-Frame Flow Straightening Structure (CAFS). This newly proposed CAFS differs from existing structures, achieving effective flow pattern improvement with reduced hydraulic loss. Results reveal three typical flow regimes—S-shaped mainstream, branching flow, and recirculation—and the flow field is partitioned into four hydrodynamic zones: the Mainstream Incident Zone, Mainstream Impact Zone, Mainstream Reflection Zone, and Low-Velocity Recirculation Zone. Axial velocity uniformity and flow angle are strongly influenced by lateral velocity, while turbulent kinetic energy exhibits intrinsic correlations with vertical vorticity. Lateral velocity, recirculation intensity, and hydraulic losses all increase positively with the Froude number. The CAFS effectively suppresses the low-velocity recirculation zone. Quantitative data show an improvement of 46.40 percentage points in uniformity of axial velocity distribution, a reduction of 0.157 rad (9°) in velocity-weighted average angle, 60.98% less turbulent dissipation, and 38.85% less total hydraulic loss. This study clarifies lateral-intake defect mechanisms and provides a valuable engineering reference.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161465

Authors: Jinjun Jia Kang An Yuchen Liao Xun Yan Tiedong Zhang Dapeng Jiang

This paper develops a contraction-certified trajectory-tracking and gain-selection framework for fully actuated autonomous underwater vehicles on SE(3). The vehicle dynamics are represented in port-Hamiltonian form with a Rayleigh-type dissipation potential, and a dual potential shaping controller provides an energy-structured rotational–translational cascade. Regional contraction certificates are derived separately for the rotational and translational subsystems. The rotational analysis uses fixed left-trivialised momentum coordinates and retains anisotropic-inertia effects and the complete off-diagonal differential coupling. The translational analysis applies to a general known symmetric positive-definite inertia matrix through an attitude-cover semidefinite programme, with an exact endpoint reduction for isotropic inertia. A scaled composite metric combines the subsystem certificates and guarantees every strict complete-cascade rate below the slower subsystem rate. Large initial attitude errors are handled by an energy-entry phase followed by contraction within a prescribed tube, without controller switching. The four-dimensional gain-selection problem is decomposed into two independent two-dimensional offline searches using bisection and SDP/LMI feasibility tests. Numerical studies on the ODIN AUV quantify the region–gain–rate trade-off and examine small-angle, large-angle, and near-antipodal manoeuvres. The framework certifies complete-cascade rates of 0.042096s−1 and 0.008524s−1 for the 60∘/60∘ and 150∘/80∘ regions, respectively.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161464

Authors: Jin-Man Kim Heon-Hui Kim Taek-Kun Nam

Vibration-based diagnosis of propulsion-shaft misalignment supports condition monitoring in electric ships, but reported accuracies are often inflated by overlapping-window leakage and by untested cross-recording, cross-session, and cross-speed generalization. We evaluated leakage-free, deployment-oriented protocols (chronological, leave-one-recording-out (LORO), leave-one-session-out, and leave-one-speed-out) on a 50 kW electric-propulsion land-based test system with six accelerometer channels under 0, 2, and 4 mm offset misalignments, comparing feature-engineered gradient-boosting models, raw-signal deep models, and nominal-speed order-normalized features. Under LORO evaluation, a raw-signal one-dimensional convolutional neural network (1D-CNN) achieved 0.93–1.00 accuracy and outperformed LightGBM in all 15 folds. Under leave-one-speed-out testing, MiniRocket retained 0.775 accuracy, whereas InceptionTime dropped to 0.468. Fixed-Hz features outperformed nominal-speed order-normalized features by 0.079 (p = 0.022), and single-window 1D-CNN inference required 0.50 ms on a CPU. Recording-level and cross-session evaluation are therefore essential for reliable misalignment diagnosis, and raw-signal models provide the strongest deployable performance on the present test rig.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161463

Authors: Xinyuan Li Yujie Zhang Yang Shen

In automated dry bulk terminal operations, accurate perception of the spatial pose of portal crane wire ropes is important for grab positioning and can provide geometric information for subsequent anti-sway control research. Vision-based measurements may be affected by metallic reflections, illumination variation, and dust occlusion, whereas inertial or mechanically coupled measurements may be affected by vibration and dynamic coupling. This study proposes a LiDAR-based method for wire rope point cloud segmentation and pose estimation using an improved PointNet++. Dual-LiDAR point clouds are aligned and filtered using a kinematic constraint-based Region of Interest (ROI) to reduce background redundancy. A Spatial Self-Attention (SSA) module is introduced to combine long-range semantic dependencies with local spatial weighting, improving the representation of sparse and fragmented wire rope points. The segmented wire rope points are separated by t–k-means clustering and fitted with spatial lines for pose estimation. The complete acquisition comprises 11,348 annotated frames: a 9458-frame model development dataset from 1000 complete operating cycles, and a separately retained 1890-frame independent engineering test set from 200 condition-specific operating sequences. The development dataset was divided into mutually exclusive training and validation partitions at the level of complete operating cycles, and checkpoint selection was performed only on the validation set. Three independent training runs with fixed random seeds were conducted. On the independent test set, PointNet++ achieved an F1-score of 87.5 ± 0.2% and an mIoU of 79.0 ± 0.2%, whereas the complete proposed method achieved an F1-score of 92.8 ± 0.2% and an mIoU of 86.6 ± 0.2%. These results characterize performance on independent operating sequences collected from the crane and sensor configurations represented in the dataset. The standalone segmentation stage achieved 111.9 FPS, whereas the complete processing pipeline required slightly more than 2 s per frame because of frame-by-frame KD-ICP fine registration.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161462

Authors: Huitae Joo Byoung-Jun Lim Hae Kun Jung

Coastal upwelling and typhoon-driven mixing can cool a buoy record by several degrees within hours. Sensor faults do the same. Quality-control schemes that flag anomalies by residual magnitude alone therefore risk discarding real events. We analysed 30 min temperature records from six buoys and three depths off the east coast of Korea, spanning 2008–2024, and built a machine-learning-assisted, physics-guided, event-preserving quality-control framework that adds new labels without altering any observation or existing flag. Cooling events were catalogued from changes in the observed surface temperature and in the surface-to-bottom temperature difference and classified using three physically interpretable axes: spatial coherence with neighbouring buoys, vertical consistency between layers, and atmospheric forcing from ERA5 and typhoon best-track data. A station-wise ridge prediction model, fitted to the surface layer at five of the six stations, supplied prediction residuals that served only to flag candidates. Residual magnitude separated sensor-like anomalies from regional-event candidates poorly (direction-free AUC 0.52–0.56); upwelling-candidate and typhoon-related events produced residuals as large as those of the sensor-like reference group, or larger. The physical axes showed much stronger internal operational separability, reaching pairwise AUC values up to 1.000 and a multivariate cross-validated mean AUC of 0.987. These values do not represent external validation because the groups were partly defined using the same axes. The framework preserved regional-event candidates while affecting derived monthly means by at most about 0.0005 °C, yet retained event-scale cooling of up to about 8 °C. Prediction residuals are therefore useful for broad anomaly-candidate detection but insufficient for final event classification, which should rely on physically interpretable, multi-station criteria.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161461

Authors: Jianjun Zhang Wentao Zhou Shuhu Yang Yun Zhang

Snow density influences Arctic climate, ecosystems, and surface energy exchange, yet spatially continuous observations remain limited. This study constructed an ERA5-supervised snow-density dataset for 60–90° N by collocating Advanced Microwave Scanning Radiometer 2 (AMSR-2) Level-1R brightness temperatures with ECMWF Reanalysis v5 (ERA5) snow density, Soil Moisture Active Passive (SMAP) surface roughness, and auxiliary variables. Ten models were evaluated using 29 observation days spanning September 2022–February 2023 under a chronological training–validation–test split. Extra Trees achieved the best overall performance, with a root mean square error of 18.54 kg m−3 and an R2 of 0.87, while the bidirectional gated recurrent unit (BiGRU) was the strongest deep-learning model. Feature-attribution and ablation analyses showed that microwave brightness temperatures contained predictive information, although geographic and auxiliary variables also contributed substantially. The evaluated models could reproduce ERA5-referenced Arctic snow-density patterns, but their performance partly reflected regional information. Moreover, ERA5 showed limited consistency with station-based Northern Hemisphere Snow Water Equivalent estimates. Consequently, the reported metrics quantify agreement with ERA5 rather than accuracy against independently observed snow density. Temporally coincident and spatially independent field validation remains necessary in the future.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161460

Authors: Daniele Spatola Luca Basilone Fabiano Gamberi Francesco Latino Chiocci Gualtiero Basilone Attilio Sulli

Ferdinandea Island, part of a shallow-water submarine volcanic field, emerged in the Sicily Channel between Italy and Tunisia in July 1831 and was eroded below sea level within months; its submerged remnant forms the shallowest water depth region of Graham Bank. Here, we review nearly two centuries of historical accounts, geological interpretations and geomorphological data analysis and reassess them against high-resolution multibeam bathymetry, sub-bottom profiles (CHIRP) and published multichannel seismic data. The field comprises six volcanic edifices (V1–V6), 100–170 m high, located along structural trends characteristic of the Sicily Channel Rift. V3, the shallowest edifice, is the remnant of Ferdinandea Island formed during the 1831 Surtseyan eruption. Its flat summit, wave-reworked terrace and steep flanks record rapid post-eruptive modification. Historical observations and hydrographic surveys document the destruction of the emergent island and a further ~6 m lowering of its shallowest point between 1883 and 2012–2015; the separate contributions of wave erosion, subsidence and gravitational adjustment cannot be resolved from the available data. The same regional structural framework appears to have governed the distribution of the other volcanic centres, pockmarks, erosional escarpments and mass-transport deposits of the study area. Seventeen pockmarks, up to ~540 m wide and 22 m deep, occur as isolated, clustered and locally aligned depressions; they are associated with subsurface concave-upward reflectors and local water-column acoustic anomalies, consistent with focused fluid escape. Failures of volcanic and sedimentary slopes are widespread, with the largest debris-avalanche deposit covering ~2.2 km2. Taken together, these observations indicate that tectonics, volcanism, fluid migration, wave- and bottom-current reworking, and gravitational instability have operated over different timescales to shape Graham Bank. Ferdinandea thus offers a rare historical and geological reference for investigating the rapid construction, degradation and long-term evolution of shallow-water volcanic edifices and highlights the still-open questions regarding the evolution and fate of ephemeral volcanic islands.

Journal of Marine Science and Engineering doi: 10.3390/jmse14161458

Authors: Xiaopeng Lv Yuqi Qiao Qifeng Zhang Yunfei Bai Qingfeng Yao

Using cable transmission in underwater manipulators helps to reduce the mass and rotational inertia of distal moving components, but the control performance of cable-driven joints is affected by flexible cable transmission, equivalent joint-side friction, hydrodynamic effects, and external disturbances. This paper proposes a control method combining time-delay estimation (TDE) with gain-scheduled sliding mode control (GSMC) for a cable-driven joint of an underwater manipulator. TDE uses delayed control-input and joint-acceleration data to estimate and compensate for the lumped dynamic term in the equivalent joint model online. GSMC employs a composite sliding surface and an error-dependent gain-scheduling mechanism to suppress trajectory-tracking errors in the presence of the TDE estimation residual. In joint-level MATLAB/Simulink R2024b simulations, smooth-step, sinusoidal-trajectory-tracking, and ablation results under predefined combined-uncertainty conditions, together with the results of 50 paired Monte Carlo runs, show that TDE-GSMC achieves the lowest major tracking-error indices among the four methods for the smooth-step and 0.35Hz sinusoidal trajectories and also yields the lowest mean tracking error and 95th percentile of the disturbance peak in the Monte Carlo simulations; the ablation results further characterize the performance differences among the tested controller configurations.