Journal of Marine Science and Engineering

18 pages, 1318 KB

Open AccessArticle

A High-Resolution Eigenspace Direction-of-Arrival Estimation Method with an Unknown Number of Sources

by Chen Qian, Xinkai Hao, Yong Wang, Yixin Yang and Xiaoyuan Li

J. Mar. Sci. Eng. 2026, 14(10), 899; https://doi.org/10.3390/jmse14100899 (registering DOI) - 12 May 2026

The Eigenspace method has been widely applied in the ultrasonic field, and this method can improve the resolution and achieve good robustness. However, all existing methods require the number of sources in the space to be known. This paper proposes a high-resolution direction-of-arrival [...] Read more.

The Eigenspace method has been widely applied in the ultrasonic field, and this method can improve the resolution and achieve good robustness. However, all existing methods require the number of sources in the space to be known. This paper proposes a high-resolution direction-of-arrival (DOA) estimation method based on the Eigenspace theory with an unknown number of sources in the PM domain. The proposed method first decomposes the received signals of a circular array into orthogonal PM signals and then extends the Eigenspace method into the phase mode (PM) domain. Since the existing Eigenspace methods project the optimal beam scanning vector onto the signal subspace, the number of sources needs to be known in advance. However, in practical scenarios, the number of sources is unknown. The proposed method employs the combination term of the PM covariance matrix and its eigenvalues to perform power operations, which can approximately achieve the closed-form expressions of the relevant parameters for the signal subspace and the noise subspace. Finally, high-resolution DOA estimation is achieved under the condition of an unknown number of sources. Simulation and experimental results demonstrate the effectiveness of the proposed method in high-resolution DOA with an unknown number of sources. Full article

(This article belongs to the Section Ocean Engineering)

28 pages, 1525 KB

Open AccessArticle

A Hybrid Mamba–ConvLSTM Framework for Multi-Day Sea Surface Temperature Forecasting at 0.05^∘ Resolution

by Bo Peng, Zhonghua Hong and Guansuo Wang

J. Mar. Sci. Eng. 2026, 14(10), 898; https://doi.org/10.3390/jmse14100898 (registering DOI) - 12 May 2026

Abstract

Accurate multi-day sea surface temperature (SST) prediction at sub-mesoscale resolution is challenging due to nonlinear ocean dynamics, heterogeneous multi-source observations, and error accumulation during autoregressive rollout. This paper proposes a hybrid Mamba–ConvLSTM framework that combines recurrent local spatiotemporal encoding with selective state-space long-range [...] Read more.

Accurate multi-day sea surface temperature (SST) prediction at sub-mesoscale resolution is challenging due to nonlinear ocean dynamics, heterogeneous multi-source observations, and error accumulation during autoregressive rollout. This paper proposes a hybrid Mamba–ConvLSTM framework that combines recurrent local spatiotemporal encoding with selective state-space long-range spatial modeling. The ConvLSTM branch captures local spatial patterns and short-range temporal dependencies through convolutional gating, while the Mamba branch captures long-range spatial dependencies across each frame through cross-direction window scanning and maintains temporal coherence via persistent hidden states across successive time steps. A physically informed preprocessing stage aligns 0.083

^{\circ}

reanalysis variables to the 0.05

^{\circ}

OSTIA target grid via a Grow-and-Cut strategy and extracts gradient-based advection and diffusion proxy features under boundary-aware finite differencing. During autoregressive rollout, auxiliary variables are held at their last observed values and physical proxies are recomputed from the predicted SST, following a clearly specified protocol. Experiments on a South China Sea benchmark compare the proposed model against nine baselines—including persistence, daily climatology, ConvLSTM, PredRNN, ConvGRU, TCTN, PANN, Swin-UNet, and ViT-ST—under an identical data-split, normalization, and rollout protocol. Evaluation with RMSE, MAE, SSIM,

R^{2}

, and anomaly correlation coefficient (ACC) shows that the proposed model achieves a 10-day average RMSE of 0.512

^{\circ}

C, outperforming the strongest learning-based baseline ViT-ST by 5.0% and the persistence forecast by 21.0%. Ablation studies, sensitivity analyses, seasonal evaluation, and statistical significance testing verify the contribution of each component and the robustness of the results. Full article

(This article belongs to the Section Physical Oceanography)

18 pages, 1711 KB

Open AccessArticle

Analysis of Risk Factors Influencing the Outcomes of Capsizing, Sinking, and Flooding Accidents in Coastal Waters of the Republic of Korea: A Fuzzy Bayesian Network Approach

by Byung-Hwa Song

J. Mar. Sci. Eng. 2026, 14(10), 897; https://doi.org/10.3390/jmse14100897 (registering DOI) - 12 May 2026

Abstract

Capsizing, sinking, and flooding accidents occurring in the coastal waters of the Republic of Korea constitute a persistent marine safety concern, accounting for approximately 17% of total fatalities associated with marine accidents. Previous statistical analyses of accident causation have identified key contributing factors [...] Read more.

Capsizing, sinking, and flooding accidents occurring in the coastal waters of the Republic of Korea constitute a persistent marine safety concern, accounting for approximately 17% of total fatalities associated with marine accidents. Previous statistical analyses of accident causation have identified key contributing factors such as adverse weather conditions, improper cargo loading, and deficiencies in vessel maintenance; however, the complex interdependencies among these factors have not been sufficiently quantified. To address this limitation, this study proposes a fuzzy Bayesian network (FBN) model to systematically evaluate and quantify the risk factors associated with capsizing, sinking, and flooding accidents. A total of 164 adjudicated marine accident cases that occurred in Korean coastal waters over a 10-year period (2015–2024) were analyzed (data collection cutoff: 31 December 2024) to estimate prior probabilities for six major causal categories. Conditional probability tables (CPTs) were derived through a structured Delphi survey conducted with marine safety experts possessing more than 10 years of professional experience. To mitigate the subjectivity inherent in expert judgment, triangular fuzzy numbers (TFNs) and centroid-based defuzzification were applied. Sensitivity analysis identified sea state (SI = 0.0155) and cargo loading condition (SI = 0.0125) as the two most influential factors affecting the probability of capsizing. Scenario analysis further revealed that when adverse weather conditions and improper cargo loading occur simultaneously, the probability of capsizing increases to 39.3%, representing a 5.3 percentage point increase compared to the baseline. In addition, the model demonstrated a close agreement with observed accident outcome distributions, with a Kullback–Leibler (KL) divergence of 0.038, indicating differences within 1.3 percentage points across all outcome categories. The findings of this study provide practical implications for targeted marine safety interventions and the prioritization of regulatory measures in the coastal waters of the Republic of Korea. Full article

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

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16 pages, 7711 KB

Open AccessArticle

Investigation on the Absorption Characteristics of the Pressure-Resistant Metastructures

by Lejingyi Zhou, Weibo Wang, Xinsheng Fang and Wenwei Wu

J. Mar. Sci. Eng. 2026, 14(10), 896; https://doi.org/10.3390/jmse14100896 (registering DOI) - 12 May 2026

Abstract

The development of pressure-resistant sound-absorbing materials is crucial for enhancing the stealth performance of underwater vehicles operating at great depths. In this paper, a pressure-resistant metastructure is proposed, and an analytical model for its acoustic impedance is derived. Through structural optimization, the low-frequency [...] Read more.

The development of pressure-resistant sound-absorbing materials is crucial for enhancing the stealth performance of underwater vehicles operating at great depths. In this paper, a pressure-resistant metastructure is proposed, and an analytical model for its acoustic impedance is derived. Through structural optimization, the low-frequency sound absorption bandwidth is further extended. The results demonstrate that the proposed metastructure achieves broadband low-frequency sound absorption based on a plate–rubber–cavity coupling resonance mechanism. Experimental validation conducted in a pressurized impedance tube shows that under hydrostatic pressures ranging from 0.5 MPa to 3 MPa, the average sound absorption coefficient between 500 Hz and 10 kHz remains above 0.8. These findings confirm the effectiveness of the proposed configuration in broadening the low-frequency absorption bandwidth while maintaining stable acoustic performance under varying hydrostatic pressures. The study provides a robust platform for the development of underwater artificial functional materials and offers a novel approach for designing noise reduction structures suitable for deep-sea environments. Full article

(This article belongs to the Section Ocean Engineering)

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29 pages, 15781 KB

Open AccessArticle

Energy Harvesting Characteristics and Effects of Structural Parameters of a Near-Surface 2-DOF Oscillating Foil

by Lixian Wang, Longyao Wang, Wei Hua, Taotao Tao and Zhengzhi Deng

J. Mar. Sci. Eng. 2026, 14(10), 895; https://doi.org/10.3390/jmse14100895 (registering DOI) - 12 May 2026

Abstract

In this study, the energy harvesting mechanism of a two-degree-of-freedom (2-DOF) oscillating foil under near-surface conditions and the underlying influence of structural parameters are systematically investigated. Numerical simulations are conducted using the open-source CFD platform OpenFOAM and the waves2Foam toolbox. The free surface [...] Read more.

In this study, the energy harvesting mechanism of a two-degree-of-freedom (2-DOF) oscillating foil under near-surface conditions and the underlying influence of structural parameters are systematically investigated. Numerical simulations are conducted using the open-source CFD platform OpenFOAM and the waves2Foam toolbox. The free surface is captured using the volume of fluid (VOF) method, while the heave and pitch motions of the foil are simulated via the overWaveDyMFoam solver, coupling 6-DOF dynamic equations with the overset grid technique. The results demonstrate that the periodic evolution and shedding of the leading-edge vortex (LEV) fundamentally drive the self-sustained oscillation of the foil. Moreover, the phase synchronization between the fluid-induced force and the kinematic response serves as the core mechanism for efficient energy extraction. Structural parameters critically regulate these characteristics: stiffness coefficients dictate the natural frequency and phase coordination, thereby modulating the overall motion response. Notably, a local resonance occurs when the system’s natural frequency approaches the fluid’s vortex shedding frequency, inducing the maximum kinematic response. Within the investigated parameter space, the system achieves a peak energy harvesting efficiency of 45.6% and a maximum average power coefficient of 1.15. Finally, the damping coefficients are found to primarily govern the response amplitude and the viscous dissipation of the system. Full article

(This article belongs to the Section Marine Energy)

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19 pages, 173107 KB

Open AccessArticle

Sandstone Reservoir Prediction in the Beikang Basin Using a Fusion Workflow of Tomographic Velocity Inversion and Multiple Seismic Integration

by Shuaibing Luo, Xiaoxue Wang, Kangshou Zhang, Ming Sun, Qiuhua Yu, Guanghui He and Yuan Gao

J. Mar. Sci. Eng. 2026, 14(10), 894; https://doi.org/10.3390/jmse14100894 (registering DOI) - 12 May 2026

Abstract

The Beikang Basin is a large petroliferous sedimentary basin in the southern South China Sea, and is regarded as an important frontier area for deepwater hydrocarbon exploration in the Nansha region. Previous exploration by foreign oil companies has demonstrated its significant hydrocarbon potential. [...] Read more.

The Beikang Basin is a large petroliferous sedimentary basin in the southern South China Sea, and is regarded as an important frontier area for deepwater hydrocarbon exploration in the Nansha region. Previous exploration by foreign oil companies has demonstrated its significant hydrocarbon potential. However, no wells have yet been drilled by China in the Beikang Basin. In this underexplored, well-free setting, sandstone reservoir prediction is hindered by several key challenges, including low velocity-picking accuracy, difficulty in constructing reliable low-frequency models, and limited inversion accuracy. These limitations collectively reduce the reliability of reservoir identification and thus increase exploration risk. To address the challenge of accurately predicting sandstone reservoirs in underexplored areas without well control, this study proposes a reservoir prediction workflow that integrates horizon-controlled gridded tomographic velocity modeling with seismic multiple integration. The workflow includes (1) pre-stack gather optimization, (2) tomographic velocity inversion to construct a precise velocity field, (3) multiple integration to supplement missing medium- to low-frequency information, and (4) pre-stack amplitude-versus-offset (AVO) simultaneous inversion to derive P-wave and S-wave impedances. Combined with petrophysical analysis from adjacent areas to establish a lithology interpretation framework, this integrated approach enables quantitative prediction of sandstone reservoirs in the Beikang Basin. Application to the study area demonstrates that the predicted sandstone thickness distribution is consistent with the regional geological conditions and is supported by drilling results from surrounding areas. The proposed method, therefore, provides a reliable technical approach for reservoir evaluation in the Beikang Basin, and has practical value for sandstone reservoir prediction in other underexplored frontier basins with limited or no well control. Full article

(This article belongs to the Section Geological Oceanography)

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23 pages, 4052 KB

Open AccessArticle

Prediction of Scale Effects on Tidal Turbines with the Reynolds Scaling Method

by Gyeongseo Min, Kangmin Kim, Haechan Yun, Younguk Do, Weichao Shi, Daejeong Kim and Soonseok Song

J. Mar. Sci. Eng. 2026, 14(10), 893; https://doi.org/10.3390/jmse14100893 (registering DOI) - 12 May 2026

Abstract

Accurate power estimation is fundamental to effective tidal turbine design. While turbines are typically designed for specific Tip Speed Ratio (TSR) ranges, the Reynolds number (

R e

) can vary significantly even at a constant TSR depending on flow velocity and turbine [...] Read more.

Accurate power estimation is fundamental to effective tidal turbine design. While turbines are typically designed for specific Tip Speed Ratio (TSR) ranges, the Reynolds number (

R e

) can vary significantly even at a constant TSR depending on flow velocity and turbine scale. Such variations in

R e

can fundamentally alter the flow characteristics around the blades, directly impacting performance. Conventionally,

R e

-dependent lift and drag coefficients are incorporated into Blade Element Momentum Theory (BEMT) to address these variations, often supplemented by hub and tip loss corrections. However, since BEMT relies on two-dimensional airfoil characteristics, it may not fully capture the complex three-dimensional viscous effects that occur during actual operation. Therefore, this study employs three-dimensional CFD simulations to quantitatively evaluate

R e

effects on turbine performance. By quantifying power generation deviations across a broad

R e

spectrum, the results show that discrepancies at identical TSRs range from 0.312% to 7.32%. Notably, these differences stabilise near 1% when

R e

exceeds

1.0 \times 10^{7}

. Furthermore, the underlying causes of these scale effects were identified by decomposing the torque into shear and pressure components. These quantified indicators provide a practical basis for incorporating Reynolds number effects into the turbine design process, thereby contributing to more accurate full-scale performance prediction. Full article

(This article belongs to the Special Issue New Advances in the Analysis and Design of Marine Structures)

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19 pages, 9183 KB

Open AccessArticle

Assessing the Impact of Soil Hydrocarbon Properties on Plant Functional Types Using Hyperspectral Data in the Niger Delta

by Abdullahi A. Kuta, Stephen Grebby, Doreen S. Boyd and Christopher H. Vane

J. Mar. Sci. Eng. 2026, 14(10), 892; https://doi.org/10.3390/jmse14100892 (registering DOI) - 12 May 2026

Abstract

The presence of soil hydrocarbon parameters (SHPs), including total petroleum hydrocarbons (TPHs), total organic carbon (TOC; %), and soil toxicity (EC50; mg L⁻¹), can affect vegetation in several ways. This study assessed the impact of SHPs on vegetation in the Niger [...] Read more.

The presence of soil hydrocarbon parameters (SHPs), including total petroleum hydrocarbons (TPHs), total organic carbon (TOC; %), and soil toxicity (EC50; mg L⁻¹), can affect vegetation in several ways. This study assessed the impact of SHPs on vegetation in the Niger Delta using field-measured, leaf-scale hyperspectral data acquired across the region. Red-edge position (REP) and four hyperspectral vegetation indices (HVIs)—mND705, photochemical reflectance index (PRI), Normalised Difference Vegetation Vigour Index (NDVVI₈₄₄,₄₄₇; a vegetation vigour index), and modified DATT (MDATT; a chlorophyll-sensitive red-edge index)—were used to quantify chlorophyll content in the vegetation types of Awolowo grass, elephant grass, mango trees, oil palm trees, and mangrove vegetation and to explore their variation with SHPs. The results show that mangrove vegetation was the most impacted by TPHs (R = −0.683), while mango vegetation was the most impacted by TOC (R = −0.725), based on Pearson correlation coefficients derived from the mND705 index. Similarly, mango and mangrove vegetation showed the strongest responses to soil toxicity (EC50; mg L⁻¹), based on Spearman correlation coefficients (r_s = 0.657 and r_s = 0.870, respectively) using the MDATT index. These findings highlight species-specific physiological responses to soil hydrocarbon contamination and demonstrate the applicability of red-edge-based hyperspectral techniques for assessing vegetation stress in complex coastal ecosystems such as the Niger Delta. Full article

(This article belongs to the Special Issue Oil Transport Models and Marine Pollution Impacts)

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14 pages, 2458 KB

Open AccessArticle

A Flow Analysis Modeling Study on the Performance Characteristics of LNG-Fueled Gas Valve Unit

by Jung-Wook Lee, Kyeong-Ju Kong, Do-Yeong Jeong and Seung-Hun Han

J. Mar. Sci. Eng. 2026, 14(10), 891; https://doi.org/10.3390/jmse14100891 (registering DOI) - 12 May 2026

Abstract

As climate change and air pollution problems become more serious around the world, regulations to reduce greenhouse gas emissions are being tightened. The International Maritime Organization (IMO) has adopted measures to limit sulfur oxides and nitrogen oxides generated by ships. Due to the [...] Read more.

As climate change and air pollution problems become more serious around the world, regulations to reduce greenhouse gas emissions are being tightened. The International Maritime Organization (IMO) has adopted measures to limit sulfur oxides and nitrogen oxides generated by ships. Due to the continuous use of fossil fuels, carbon dioxide emissions are increasing rapidly, which is acting as a major cause of global warming and climate change. Currently, the carbon neutrality policy to reduce greenhouse gases emitted by ships is expanding, and the use of alternative energy from marine fuels is increasing worldwide. The shipbuilding industry is actively introducing eco-friendly ships that use liquefied natural gas (LNG) fuels, and the importance of equipment such as the Fuel Gas Supply System (FGSS), which can supply eco-friendly energy, is growing. In this study, we designed a Gas Valve Unit (GVU), one of the FGSS components, and analyzed the internal flow of the GVU by performing computational fluid dynamics (CFD) simulations. Full article

(This article belongs to the Section Ocean Engineering)

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27 pages, 4398 KB

Open AccessArticle

Motion Characteristics and Drag-Reduction Optimization of Moonpool Drillships in Irregular Waves

by Junming Hu, Zhen Zhang, Chengshuai Song, Jiaxia Wang, Xueying Yu and Daiyu Zhang

J. Mar. Sci. Eng. 2026, 14(10), 890; https://doi.org/10.3390/jmse14100890 (registering DOI) - 11 May 2026

Abstract

This study analyzes the effects of different moonpool configurations on drillship hydrodynamics using the Reynolds-averaged Navier–Stokes (RANS) equations. A three-dimensional numerical wave tank is established to realize the prediction and validation of the hydrodynamic performance of irregular waves and the interaction between irregular [...] Read more.

This study analyzes the effects of different moonpool configurations on drillship hydrodynamics using the Reynolds-averaged Navier–Stokes (RANS) equations. A three-dimensional numerical wave tank is established to realize the prediction and validation of the hydrodynamic performance of irregular waves and the interaction between irregular waves and structures. Combined with the selection of the drillships with relatively favorable resistance performance among different moonpool configurations under calm-water navigation conditions, further studies are carried out on the motion characteristics and drag-reduction optimization of the rectangular- and square-moonpool drillships under irregular wave conditions. Comparative analysis of the numerical results shows that different moonpool shapes result in different drag-increase effects under calm-water conditions, and the moonpool-induced drag increase mainly originates from added residuary resistance. Relative to the non-moonpool baseline drillship, the installation of a moonpool under irregular wave conditions notably elevates the resistance amplitude and amplifies the heave and pitch responses, with a more prominent impact observed on pitch, while also modifying the natural frequency characteristics of the moonpool-equipped drillship. Introducing appropriate rounded corners at the bottom of the moonpool can effectively reduce the resistance of the moonpool drillship and significantly decrease the amplitudes of heave and pitch responses under irregular wave conditions. Based on the present study, a bottom rounded-corner radius of 40 mm effectively improves the hydrodynamic performance of the moonpool drillship in irregular waves. The numerical results provide direct theoretical and design guidance for drag reduction and motion-performance enhancement of moonpool-equipped drillships, highlighting their engineering applicability. Full article

(This article belongs to the Special Issue Advancements in Marine Hydrodynamics and Structural Optimization)

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23 pages, 4646 KB

Open AccessArticle

A Dynamic Bayesian Pre-Warning Framework for Safety-Critical Barriers in Subsea Production Systems

by Wei Zhou, Yaqi Yang, Tao Liu, Ran Tao and Xingwei Zhen

J. Mar. Sci. Eng. 2026, 14(10), 889; https://doi.org/10.3390/jmse14100889 (registering DOI) - 11 May 2026

Abstract

Safety-critical valves in subsea production systems are essential barriers against catastrophic hydrocarbon releases. However, effective risk pre-warning remains challenging under conditions of sparse test data, infrequent failures, and discrete testing intervals, where conventional static thresholds often lead to delayed warnings or excessive false [...] Read more.

Safety-critical valves in subsea production systems are essential barriers against catastrophic hydrocarbon releases. However, effective risk pre-warning remains challenging under conditions of sparse test data, infrequent failures, and discrete testing intervals, where conventional static thresholds often lead to delayed warnings or excessive false alarms. To address this gap, this study proposes a dynamic Bayesian pre-warning method for safety-critical barriers, in which valve-level test data are interpreted as observable manifestations of barrier health states. A Beta–Binomial conjugate model is employed to recursively update failure probabilities, while an adaptive upper credible bound derived from the posterior distribution is introduced as a self-adjusting warning threshold that explicitly accounts for epistemic uncertainty and data scarcity. This approach enables early detection of emerging degradation while maintaining statistical rigor. The method establishes a hierarchical barrier-oriented warning structure covering two levels: individual safety-critical valves and the overall subsea barrier system. This design enables continuous monitoring of probabilistic barrier state evolution and supports consistent escalation of early warning signals from the individual valve level to the system level. The method is validated using fifteen years of test records (2010–2024) from subsea production systems in a specific offshore oil field, involving over 1200 functional tests of safety-critical valves. The method consistently identifies incipient anomalies earlier than industrial benchmarks and has never triggered a system-level red warning, demonstrating its robustness and operational suitability. By bridging Bayesian inference with integrity management practices, this method offers a principled, data-efficient solution for risk pre-warning in subsea production systems. Full article

(This article belongs to the Special Issue Risk Assessment and Mitigation Strategies in Offshore Petroleum)

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15 pages, 3356 KB

Open AccessArticle

Spatiotemporal Variation Characteristics and Drivers of Winter Arctic Sea Ice Thickness Under the New Arctic Regime

by Yaowei Yin and Xiaoyu Wang

J. Mar. Sci. Eng. 2026, 14(10), 888; https://doi.org/10.3390/jmse14100888 (registering DOI) - 11 May 2026

Abstract

The “New Arctic” regime represents a prominent climatic feature of the Arctic Ocean under global warming, characterized by persistently low summer sea ice extent, a marked reduction in sea ice thickness, and an expansion of open water areas at high latitudes. As a [...] Read more.

The “New Arctic” regime represents a prominent climatic feature of the Arctic Ocean under global warming, characterized by persistently low summer sea ice extent, a marked reduction in sea ice thickness, and an expansion of open water areas at high latitudes. As a key indicator of the Arctic sea ice system, the spatiotemporal evolution of sea ice thickness and its underlying driving mechanisms remain incompletely understood. Using reanalysis datasets and remote sensing observations, this study identifies major abrupt shifts in Arctic sea ice thickness under the New Arctic regime, reveals the spatiotemporal distribution characteristics of winter sea ice thickness, and examines the driving factors from both thermodynamic and dynamic perspectives. The results show that the evolution of Arctic sea ice thickness can be divided into three phases: a high-level period during the “Traditional Arctic” (1979–1992), a rapid thinning period during the New Arctic transition (1993–2012), and a low-level stabilization period in the New Arctic regime (2013–2023). The first EOF mode of winter sea ice thickness depicts a spatially consistent thinning pattern across the entire Arctic, with the most significant reduction occurring in the multi-year ice regions north of the Canadian Arctic Archipelago and Greenland. The second EOF mode exhibits an out-of-phase variation between the Atlantic and Pacific sectors of the Arctic, accompanied by a shrinking amplitude and weakened regional oscillations. The coupling between surface air temperature and sea ice thickness displays distinct phase dependence: their negative correlation is strongest during the transition period (r = −0.78, p < 0.001) but becomes statistically insignificant in the New Arctic regime. Sea ice motion speed exhibits an overall accelerating trend, which extends from the marginal seasonal ice zones toward the high-latitude multi-year ice regions, accompanied by a notably enhanced sensitivity of sea ice motion to wind forcing. Sea ice volume flux through the Fram Strait is primarily controlled by ice motion speed, whose contribution to the flux is approximately 2.6 times that of ice thickness. The recovery of ice drift speed offsets the thinning of sea ice cover, leading to a partial rebound in volume flux during the New Arctic steady state. This study identifies the evolutionary patterns and drivers of Arctic sea ice thickness under the New Arctic regime, providing a scientific basis for further understanding the changes in the Arctic climate system and associated air–sea ice interactions. Full article

(This article belongs to the Section Physical Oceanography)

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2 pages, 162 KB

Open AccessCorrection

Correction: Pozo Galván et al. Static Acoustic Monitoring of Harbour (Phoca vitulina) and Grey Seals (Halichoerus grypus) in the Malin Sea: A Revolutionary Approach in Pinniped Conservation. J. Mar. Sci. Eng. 2024, 12, 118

by Yaiza Pilar Pozo Galván, María Pérez Tadeo, Morgane Pommier and Joanne O’Brien

J. Mar. Sci. Eng. 2026, 14(10), 887; https://doi.org/10.3390/jmse14100887 (registering DOI) - 11 May 2026

Abstract

Error in Table 2 [...] Full article

18 pages, 9698 KB

Open AccessArticle

Numerical Investigation of Poisson’s Ratio Effects on Ice–Structure Interaction Using the Peridynamic Method

by Yuan Zhang, Liyu Ye, Chao Wang, Xiuyuan Zhang, Dagang Zhao, Jinlei Mu, Shan Pian and Biliang Lu

J. Mar. Sci. Eng. 2026, 14(10), 886; https://doi.org/10.3390/jmse14100886 (registering DOI) - 11 May 2026

Abstract

The peridynamic (PD) method has been widely utilized in the numerical modelling of ice–structure interactions due to its capability to naturally capture material failure and fracture evolution. PD formulations can be categorized into bond-based and state-based models. While the bond-based model offers computational [...] Read more.

The peridynamic (PD) method has been widely utilized in the numerical modelling of ice–structure interactions due to its capability to naturally capture material failure and fracture evolution. PD formulations can be categorized into bond-based and state-based models. While the bond-based model offers computational simplicity, it inherently restricts Poisson’s ratio to 1/4 in three-dimensional (3D) simulations and 1/3 in two-dimensional (2D) simulations. In contrast, the state-based model allows for arbitrary Poisson’s ratios, which is essential for accurately modelling ice mechanics, as Poisson’s ratio of ice commonly exceeds 0.33 and can reach up to 0.42. This study employs the PD method coupled with the discrete energy release rate criterion to analyze the influence of Poisson’s ratio on ice failure mechanisms and ice-induced loads in two typical scenarios: cylindrical impact on an ice disc and ice–structure interaction with a propeller blade. The benchmark compression test yielded computed Poisson’s ratios of 0.215, 0.258, 0.333, and 0.401 for prescribed values of 0.2, 0.25, 0.33, and 0.40, corresponding to relative errors of 7.5%, 3.2%, 1.02%, and 0.38%, respectively. And the fracture simulations indicate that variations in Poisson’s ratio affects ice fracture patterns and load distributions, underscoring the limitations of the bond-based PD model in accurately representing ice–structure interactions. These findings highlight the necessity of adopting state-based PD formulations for improved numerical predictions of ice-induced mechanical responses. Full article

(This article belongs to the Section Ocean Engineering)

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31 pages, 48945 KB

Open AccessArticle

RF-LSTM-Based Motion State Prediction for Unmanned Surface Vehicles Under Variable Operating Conditions

by Pengpeng Wan, Liming Wang, Yexin Song, Bi He, Hua Ouyang and Xing Xu

J. Mar. Sci. Eng. 2026, 14(10), 885; https://doi.org/10.3390/jmse14100885 (registering DOI) - 10 May 2026

Abstract

As a core piece of equipment for marine monitoring, search and rescue missions, and other applications, the motion state prediction accuracy of Unmanned Surface Vehicles (USVs) directly determines mission reliability and safety. However, existing methods fail to fully consider the motion characteristic differences [...] Read more.

As a core piece of equipment for marine monitoring, search and rescue missions, and other applications, the motion state prediction accuracy of Unmanned Surface Vehicles (USVs) directly determines mission reliability and safety. However, existing methods fail to fully consider the motion characteristic differences in various vessel sizes and variable-speed navigation under complex sea conditions, and struggle to capture the spatiotemporal dynamic features of state variations. This paper proposes a hybrid prediction algorithm based on Random Forest-Long Short-Term Memory (RF-LSTM), which utilizes Random Forest for key feature selection while employing LSTM to excavate temporal correlations. An intelligent routing mechanism based on the dominant frequency energy ratio (P_d) is introduced to achieve adaptive prediction mode switching, enabling comprehensive characterization of state variations. Under the 20 kn high-speed condition of a 7.5 m USV, the proposed algorithm achieves a Circular RMSE for heading prediction that is 1.9 times lower than the Extended Kalman Filter (EKF) and 1.2 times lower than a standalone LSTM, with pitch and roll prediction RMSE reduced to 0.36° and 0.85°, respectively. On a 14.5 m-long USV at 23 kn, it maintains a heading prediction accuracy of 0.10°, verifying favorable scale generalization capability. Furthermore, the algorithm demonstrates strong robustness against Gaussian white noise and synthetic ocean noise. Experimental results indicate that RF-LSTM significantly outperforms traditional methods, effectively breaking through the application limitations of fixed-architecture models, substantially enhancing USV autonomy and adaptability in complex marine environments, and providing robust guarantees for mission reliability and safety. Full article

(This article belongs to the Special Issue Unmanned Surface Vessels (USVs): Technology, Applications and Regulatory Landscapes)

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28 pages, 11675 KB

Open AccessArticle

A Prediction Model for Collision Damage Considering the Coupling Effect of Wedge-Shaped Bow and Side Structures

by Yanjie Zhao, Zisheng Lin, Yichi Zhang, Yuchao Yuan and Tongtong Guo

J. Mar. Sci. Eng. 2026, 14(10), 884; https://doi.org/10.3390/jmse14100884 (registering DOI) - 10 May 2026

Abstract

The prediction model for collision damage to a ship’s side structure plays a crucial role in the design phase. In traditional analytical methods, the bow of the striking ship is often simplified as a rigid body, with the majority of studies focusing on [...] Read more.

The prediction model for collision damage to a ship’s side structure plays a crucial role in the design phase. In traditional analytical methods, the bow of the striking ship is often simplified as a rigid body, with the majority of studies focusing on spherical or ellipsoidal bows. This paper focuses on wedge-shaped bows. First, numerical simulation analysis reveals that when the stiffness of the striking ship’s bow is relatively close to that of the struck ship’s side structure, accounting for the elastic–plastic deformation of the bow significantly affects the prediction results of collision damage to the struck ship. Building upon the rigid-body analytical prediction model (RAPM), further consideration of the elastic–plastic deformation of the striking ship’s bow leads to the development of a prediction model that accounts for the coupled collision damage process between the bow and the side structure (CDPM). Comparisons with simulation results and predictions from RAPM demonstrate that CDPM captures the physical process of collision damage more accurately, thereby proving the superiority of this approach over RAPM. Full article

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

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27 pages, 1588 KB

Open AccessArticle

Sensitivity Analysis of Injection Duration on Combustion Characteristics and Exhaust Emissions in a Marine Diesel Engine

by Mina Tadros and Evangelos Boulougouris

J. Mar. Sci. Eng. 2026, 14(10), 883; https://doi.org/10.3390/jmse14100883 (registering DOI) - 10 May 2026

Abstract

This study investigates the role of injection duration in marine diesel engine combustion within an optimised operating framework. While injection parameters are typically analysed in isolation, their interaction within a coupled engine system remains insufficiently understood, particularly under realistic operating conditions. To address [...] Read more.

This study investigates the role of injection duration in marine diesel engine combustion within an optimised operating framework. While injection parameters are typically analysed in isolation, their interaction within a coupled engine system remains insufficiently understood, particularly under realistic operating conditions. To address this gap, a structured methodology integrating one-dimensional (1D) engine simulation and optimisation is applied to evaluate the sensitivity of injection duration around optimised operating points across multiple engine loads. The approach is based on a calibrated engine model developed in WAVE, coupled with an optimisation framework to determine load-dependent optimal control parameters. Injection duration is then systematically varied around its optimised values to assess its influence on engine performance, emissions, and heat release rate (HRR). This enables the evaluation of the robustness of the optimised solution under realistic deviations. The results demonstrate that injection duration governs the transition between premixed and diffusion-controlled combustion, directly influencing heat release structure, combustion stability, and emissions formation. Longer injection durations promote mixing-limited combustion, leading to reduced peak temperatures and lower nitrogen oxide (NO_x) emissions, but increased incomplete combustion products, including carbon monoxide (CO) and unburned hydrocarbons (HCs), due to reduced oxidation efficiency. These effects are strongly load-dependent, with part-load operation showing higher sensitivity. The study provides a system-level interpretation of injection duration as a control variable rather than an isolated parameter, offering new insight into its role in combustion regime transitions and engine response. The proposed framework enables a more physically consistent understanding of injection control in modern electronically controlled marine diesel engines and supports the development of robust optimisation and calibration strategies. Full article

(This article belongs to the Special Issue Towards Net-Zero Shipping Innovation and Integration in Maritime Decarbonization)

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16 pages, 4641 KB

Open AccessArticle

Study on the Influence of Different Slope Perforations on the Hydrodynamic Performance of Ship Stabilizing Fins

by Wei Wang, Jibing Zhang, Jingyi Hu, Cheng Zhao, Zhenhuang Du and Yonghe Xie

J. Mar. Sci. Eng. 2026, 14(10), 882; https://doi.org/10.3390/jmse14100882 (registering DOI) - 10 May 2026

Abstract

The hydrodynamic characteristics of fin stabilizers are investigated in this paper. Numerical simulations are conducted via a computational fluid dynamics (CFD) method for a fin stabilizer based on the NACA0018 airfoil, and the influence mechanisms of parameters including perforation size, structural configuration, and [...] Read more.

The hydrodynamic characteristics of fin stabilizers are investigated in this paper. Numerical simulations are conducted via a computational fluid dynamics (CFD) method for a fin stabilizer based on the NACA0018 airfoil, and the influence mechanisms of parameters including perforation size, structural configuration, and perforated chamfer angle on the hydrodynamic performance of the fin stabilizer are systematically analyzed. In combination with model experiments on roll stabilizing fins carried out in a towing tank, the feasibility of the numerical simulation method is verified through comparative testing. A solid theoretical basis for the optimal design of high-performance fin stabilizers is provided by this study, and important engineering application value is obtained for improving the navigational safety and adaptability of ships. Full article

(This article belongs to the Section Ocean Engineering)

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25 pages, 3484 KB

Open AccessArticle

Hovering Control of ROV Based on Event-Triggered Image Moments Nonlinear Model Predictive Control

by Ziyang Shen, Yunxiu Zhang, Shengguo Cui, Peng Zhang and Siyue Wang

J. Mar. Sci. Eng. 2026, 14(10), 881; https://doi.org/10.3390/jmse14100881 (registering DOI) - 9 May 2026

Abstract

Hovering control of remotely operated vehicles (ROVs) is a key fundamental capability for underwater operation tasks, and vision-based ROV hovering control has become a current research focus because of its significant advantages. To address the limited constraint-handling capability and high online optimization frequency [...] Read more.

Hovering control of remotely operated vehicles (ROVs) is a key fundamental capability for underwater operation tasks, and vision-based ROV hovering control has become a current research focus because of its significant advantages. To address the limited constraint-handling capability and high online optimization frequency in vision-based hovering control, this paper proposes an event-triggered image-moment nonlinear model predictive control method. The proposed method uses image moments as visual feedback features, constructs a prediction model in a reduced control-relevant subspace, and updates the optimal control sequence only when the event-triggering condition is satisfied. Joint simulation experiments were conducted under Ideal, Disturbed, Dynamic-target, and Complex scenarios. The results show that the proposed ETIM-NMPC method achieved effective hovering performance in the joint simulation environment, with translational RMSEs remaining below the simulation-level hovering accuracy reference of 0.15 m in all evaluated directions. Compared with IM-NMPC, ETIM-NMPC maintained comparable control performance while reducing the number of online optimization updates and the cumulative computation time. The trigger rates of ETIM-NMPC ranged from 45.42% to 78.33% across the four scenarios, indicating its on-demand update characteristic under different task conditions. Full article

(This article belongs to the Section Ocean Engineering)

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Journal of Marine Science and Engineering

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