Journal of Marine Science and Engineering

33 pages, 3318 KB

Open AccessReview

Sustainable Marine Energy Solutions: Assessing the Renewable Potential of the Adriatic Sea in Croatia

by Nastia Degiuli, Carlo Giorgio Grlj and Ivana Martić

J. Mar. Sci. Eng. 2026, 14(6), 541; https://doi.org/10.3390/jmse14060541 - 13 Mar 2026

Marine energy technologies offer renewable alternatives to conventional energy sources by harnessing ocean-based resources such as wave motion, tides, temperature, and salinity gradients. They are particularly promising for coastal and island regions. This paper presents a literature-based assessment of the technical potential and [...] Read more.

Marine energy technologies offer renewable alternatives to conventional energy sources by harnessing ocean-based resources such as wave motion, tides, temperature, and salinity gradients. They are particularly promising for coastal and island regions. This paper presents a literature-based assessment of the technical potential and limitations of these resources, with a focus on the Adriatic Sea as a model for low-energy, semi-enclosed basins. Resource availability and technological maturity are systematically reviewed. Results indicate that wave energy offers the highest regional potential, with peak annual mean wave power reaching up to 2.784 kW/m near the southern offshore regions of the Adriatic. However, current resource levels limit feasibility to down-scaled, modular installations. Tidal and thermal energy are constrained by the Adriatic’s microtidal regime and limited temperature gradients. Although still in early development, salinity gradient systems may become viable near major river mouths such as those of the Po and Neretva. In addition to technical analysis, broad environmental and socio-economic considerations are reviewed to inform responsible marine energy development. These findings help define strategic development and research priorities for marine renewables in enclosed seas and other resource-constrained marine environments. Full article

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

19 pages, 3740 KB

Open AccessArticle

Spatiotemporal Characteristics and Physical–Ecological Coupling Mechanisms of Spring Phytoplankton Blooms in the Bohai Sea

by Xin Song, Junru Guo, Yu Cai, Jun Song and Yanzhao Fu

J. Mar. Sci. Eng. 2026, 14(6), 540; https://doi.org/10.3390/jmse14060540 - 13 Mar 2026

Abstract

Spring phytoplankton bloom mechanisms in the Bohai Sea show clear spatial differences, but the physical–biological coupling in the ice-covered Liaodong Bay (LDB) remains poorly understood. Utilizing satellite observations and high-resolution reanalysis data from 2009 to 2023, this study explores the drivers of spring [...] Read more.

Spring phytoplankton bloom mechanisms in the Bohai Sea show clear spatial differences, but the physical–biological coupling in the ice-covered Liaodong Bay (LDB) remains poorly understood. Utilizing satellite observations and high-resolution reanalysis data from 2009 to 2023, this study explores the drivers of spring blooms through generalized additive models (GAMs) and the Equation of State of Seawater (EOS). The results reveal pronounced regional heterogeneity. In the southern Bohai Sea, bloom dynamics are co-regulated by a complex combination of nutrient availability and localized physical mixing. In contrast, blooms in LDB are predominantly driven by the shoaling of the mixed layer depth (MLD), a physical state intrinsically linked to winter sea-ice melt. Linear decomposition of water density via EOS quantitatively demonstrates that spring stratification in LDB is salinity-dominated (contributing ~60.7%), rather than thermally driven. The rapid influx of low-salinity meltwater forms a strong halocline that suppresses vertical mixing and physically compresses the MLD into the euphotic zone. Consistent with Sverdrup’s Critical Depth Theory, this inferred physical pathway effectively alleviates light limitation and acts as the primary trigger for the early bloom peak timing. This complete melting–freshening–stratification–light coupling chain provides a novel physical perspective on how mid-latitude marginal sea ecosystems respond to climate change, distinct from canonical polar light-limitation models. Full article

(This article belongs to the Section Marine Ecology)

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26 pages, 8879 KB

Open AccessArticle

A Novel Methodology and Modelling for the Calculation of the Ship’s Pivot Point Making Use of a Full-Mission Bridge Simulator

by Francisco Javier Lama-Carballo, María Natividad López-López, Alsira Salgado-Don and José M. Pérez-Canosa

J. Mar. Sci. Eng. 2026, 14(6), 539; https://doi.org/10.3390/jmse14060539 - 13 Mar 2026

Abstract

In recent years, both the number and the size of ships have increased considerably, whereas port areas have expanded much more slowly. As a result, port manoeuvres are increasingly performed in restricted waters, which increases navigational risk during ship operations. For this reason, [...] Read more.

In recent years, both the number and the size of ships have increased considerably, whereas port areas have expanded much more slowly. As a result, port manoeuvres are increasingly performed in restricted waters, which increases navigational risk during ship operations. For this reason, ship-handlers must know the instantaneous position of the pivot point (PP) at any time. The aim of this paper is to propose novel mathematical models to determine the PP’s position and to identify the most relevant variables influencing it. For this purpose, a full-mission bridge simulator was used to generate a dataset based on multiple simulations performed under different combinations of rudder angles and engine telegraph orders. First, a new trigonometric formulation is proposed to determine the instantaneous position of the PP using only directly measurable variables, namely the speed through water and the transverse velocities at the bow and stern. Subsequently, additional predictive models were developed using Design of Experiments (DOE) and response surface techniques. These models achieve high predictive accuracy while remaining simple enough to be applied in practical ship-handling scenarios. The resulting models can assist ship-handlers in anticipating PP behaviour and improving manoeuvring safety, particularly in restricted waters. Original 3D charts showing the combination of several input variables are included to identify the map of the whole process. Full article

(This article belongs to the Section Ocean Engineering)

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17 pages, 857 KB

Open AccessArticle

Toward Realistic Ship Fuel Consumption Prediction Under Chronological Validation

by Aleksandar Vorkapić

J. Mar. Sci. Eng. 2026, 14(6), 538; https://doi.org/10.3390/jmse14060538 - 13 Mar 2026

Abstract

Accurate prediction of ship propulsion fuel consumption from operational data is important for performance assessment and energy efficiency management. This study examines how temporal structure and validation strategy influence the predictive performance of regression-based fuel consumption models using real operational data from a [...] Read more.

Accurate prediction of ship propulsion fuel consumption from operational data is important for performance assessment and energy efficiency management. This study examines how temporal structure and validation strategy influence the predictive performance of regression-based fuel consumption models using real operational data from a seagoing vessel. A controlled experimental framework is used to isolate the effects of chronological validation, temporal feature augmentation based on operational inputs, and autoregressive target information. Under strict chronological validation, a baseline regression model achieves R² = 0.788, while temporal feature augmentation improves performance to R² = 0.845 without using past fuel consumption values. An autoregressive configuration yields R² = 0.982, reflecting strong short-term persistence in the fuel consumption signal. Additional experiments show that random data partitioning can inflate reported R² by up to 0.19 compared with chronological evaluation. The results demonstrate that reported predictive accuracy depends strongly on evaluation design and temporal information structure, highlighting the importance of chronological validation for realistic operational prediction. Full article

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

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15 pages, 1514 KB

Open AccessArticle

Occurrence of Semi-Volatile Organic Compounds in Sediments of the Nerbioi-Ibaizabal Estuary (Bilbao, Spain): Spatial and Temporal Distribution and Ecological Risk Assessment

by Uxue Uribe-Martinez, Leire Mijangos, Juan F. Ayala-Cabrera and Alberto de Diego

J. Mar. Sci. Eng. 2026, 14(6), 537; https://doi.org/10.3390/jmse14060537 - 12 Mar 2026

Abstract

The occurrence and spatial distribution of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), fragrances, UV filters and photoinitiators were investigated in surface sediments of Nerbioi-Ibaizabal estuary between 2005 and 2013, in 2020. Samples were extracted by focused ultrasound solid–liquid extraction [...] Read more.

The occurrence and spatial distribution of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), fragrances, UV filters and photoinitiators were investigated in surface sediments of Nerbioi-Ibaizabal estuary between 2005 and 2013, in 2020. Samples were extracted by focused ultrasound solid–liquid extraction technique and analyzed by gas chromatography coupled with mass spectrometry. Total PAHs, PCBs, OCPs, musks, UV filters and photoinitiators concentrations ranged between not detected (n.d.) and 43000 ng g⁻¹, n.d. and 2500 ng g⁻¹, n.d. and 820 ng g⁻¹, n.d. and 880 ng g⁻¹, n.d. and 91 ng g⁻¹ and from nd to 120 ng g⁻¹, respectively. Hexachlorocyclohexanes (HCHs) were ubiquitous in the estuary, suggesting that these compounds, although banned, leach from landfills. The PCB concentrations showed a decreasing trend. Ecological risk assessments based on sediment quality guidelines (SQGs) and risk quotient (RQ) suggested semi-volatile organic compounds could represent a potential ecological risk in the Nerbioi-Ibaizabal estuary. Full article

(This article belongs to the Section Marine Pollution)

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19 pages, 4533 KB

Open AccessArticle

Depth Conversion of Underwater Static Electric Fields for Submersibles in High-Latitude Low-Temperature Sea Areas

by Yuhong Li, Cong Chen, Hongsen Zhao, Yiqun Liu, Yunfu Hou, Jiaqing Sun and Wentie Yang

J. Mar. Sci. Eng. 2026, 14(6), 536; https://doi.org/10.3390/jmse14060536 - 12 Mar 2026

Abstract

Depth conversion of underwater static electric fields refers to a mathematical approach that indirectly determines the distribution of planar electric fields at larger depths using measured planar electric field data obtained from a shallower region with finite depth and limited area. The complicated [...] Read more.

Depth conversion of underwater static electric fields refers to a mathematical approach that indirectly determines the distribution of planar electric fields at larger depths using measured planar electric field data obtained from a shallower region with finite depth and limited area. The complicated environment of high-latitude low-temperature sea areas further increases the difficulty of performing practical large-depth measurements of underwater electric fields. Therefore, depth conversion becomes an important technical strategy for overcoming the constraints of field measurements and for comprehensively understanding the distribution of underwater static electric fields of the target. This study begins with the mathematical formulation of the depth conversion problem, solves the related boundary value problem, and develops the corresponding depth conversion method. Subsequently, based on COMSOL simulation data of the underwater static electric field generated by a scaled-down submersible model, numerical analyses are conducted to investigate the effects of factors such as grid discretization, measurement plane dimensions, conversion depth, and data noise on the conversion accuracy. Finally, the reliability of the conversion method is validated in a laboratory environment by simulating a naturally frozen sea area and employing measured underwater static electric field data from the scaled-down submersible model. The results demonstrate that the developed conversion method can effectively achieve extrapolation of the underwater static electric field of the submersible from shallow regions to deeper water. Even when the noise amplitude is nearly twice that of the effective signal and the conversion depth reaches 8 times the outer diameter of the submersible, the relative root mean square error (RRMSE) of the conversion results can still be maintained below 0.10. These findings provide useful references for the advancement of technologies related to underwater electric field characteristic recognition and electric field stealth performance evaluation in high-latitude low-temperature sea areas. Full article

(This article belongs to the Topic Advances in Underwater Signal Processing and Communication: Challenges, Innovations, and Applications)

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22 pages, 292 KB

Open AccessReview

Dual-Gradient Drilling and Riserless Mud Recovery Technology: A Review of Principles, Progress, and Challenges

by Rongrong Qi, Hongfeng Lu, Zhibin Sha, Fangfei Huang, Yan Li, Zhiyuan Luo and Jinsong Lu

J. Mar. Sci. Eng. 2026, 14(6), 535; https://doi.org/10.3390/jmse14060535 - 12 Mar 2026

Abstract

Deepwater drilling operations face critical challenges including narrow pore-fracture pressure windows, wellbore instability, and environmental concerns from drilling discharge. This paper presents a comprehensive systematic review of Riserless Mud Recovery (RMR) technology, tracing its evolution from its conceptual origins to its current applications, [...] Read more.

Deepwater drilling operations face critical challenges including narrow pore-fracture pressure windows, wellbore instability, and environmental concerns from drilling discharge. This paper presents a comprehensive systematic review of Riserless Mud Recovery (RMR) technology, tracing its evolution from its conceptual origins to its current applications, critically analyzing its technical limitations, and identifying future research directions. A systematic literature review was conducted covering peer-reviewed journals, SPE/IADC conference proceedings, industry technical reports, and independent academic studies from 1990 to 2025. Databases searched included Web of Science, Scopus, OnePetro, and Google Scholar, supplemented by Derwent Innovation Index for patents. After screening over 100 publications, approximately 60 references were selected following a two-step process excluding vendor-only promotional materials. Key findings reveal the following: (1) RMR technology has evolved through three distinct hardware generations—flexible hose systems, steel-pipe return lines with tandem pumps enabling deepwater breakthrough to 1419 m, and hybrid riser configurations for conceptual designs beyond 3000 m; (2) documented field benefits include 70% drilling fluid reduction, 9 days’ time savings per well, and successful mitigation of shallow geohazards across more than 1000 global well applications; (3) integration with casing-while-drilling and managed pressure cementing has enabled record-breaking performance of 1710 m in a single run; (4) independent academic validation confirms fatigue mechanisms affecting mud return lines; (5) systematic failure mode analysis identifies critical reliability issues in suction hoses, seals, and control systems; (6) quantitative economic analysis shows RMR cost-effectiveness depends on water depth, geological conditions, and environmental regulations. RMR technology has matured into a reliable drilling solution, yet its continued evolution requires addressing hardware limitations, developing dedicated well-control protocols, expanding to ultra-deepwater and emerging applications, and integrating digitalization for real-time optimization. Full article

(This article belongs to the Section Ocean Engineering)

15 pages, 11540 KB

Open AccessArticle

A Novel Model for Predicting Permeability Using Porosity Frequency Spectrum in Fractured Deep Metamorphic Rock Reservoirs

by Yunjiang Cui, Peichun Wang, Yi Qi, Ruihong Wang and Liang Xiao

J. Mar. Sci. Eng. 2026, 14(6), 534; https://doi.org/10.3390/jmse14060534 - 12 Mar 2026

Abstract

Permeability prediction of deep metamorphic rock reservoirs in the southwestern Bohai Bay Basin poses an enormous challenge due to the strong heterogeneity. Fractures widely develop in such reservoirs, yet their contributions to permeability were neglected in traditional prediction models. To develop an effective [...] Read more.

Permeability prediction of deep metamorphic rock reservoirs in the southwestern Bohai Bay Basin poses an enormous challenge due to the strong heterogeneity. Fractures widely develop in such reservoirs, yet their contributions to permeability were neglected in traditional prediction models. To develop an effective model to predict permeability, parameters related to fracture needed to be taken into account. In this study, taking the Archaeozoic Formation in BZ 19–6 Region—a typical deep metamorphic rock reservoir in the southwestern Bohai Bay Basin—as an example, the porosity frequency spectra were first extracted from electrical imaging logging, and the correlations between the shape of porosity frequency spectrum and rock pore structure were analyzed. Afterwards, two parameters, which were defined as the logarithmic mean (φ_gm) and standard deviation between two golden section points (φ_gsr), were extracted to reflect the main peak position and wide porosity frequency spectrum, and a novel permeability prediction model was established. After the target formations were classified into two types according to the differences in pore types and pore–fracture configuration relationships, the model coefficients were calibrated. Consecutive permeability curves were derived from the proposed model in the intervals where porosity frequency spectra were obtained. Comparisons of predicted permeabilities from the proposed model, traditional method and core-measured results showed that the proposed model yielded far more reliable results, with an average relative error of only 11.12% between the predicted and core-measured permeabilities. In contrast, the average relative error of the traditional method reached 36.10%. The proposed model contributed significantly to the characterization and effectiveness evaluation of fractured deep metamorphic rock reservoirs. Full article

(This article belongs to the Special Issue Marine Well Logging and Reservoir Characterization)

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25 pages, 32853 KB

Open AccessArticle

Comparison of Machine Learning Models for Predictive Mapping of Surface Sediments in Lianyungang Nearshore Area, China

by Jiaying Yang, Fucheng Liu, Lingling Gu, Xuening Liu and Shujun Jian

J. Mar. Sci. Eng. 2026, 14(6), 533; https://doi.org/10.3390/jmse14060533 - 12 Mar 2026

Abstract

High-precision sediment distribution maps are indispensable for nearshore sediment dynamics and ecology and nearshore resource management. Using grain-size data of surface sediments from the nearshore waters of Lianyungang and auxiliary datasets including bathymetric and hydrodynamic conditions, this study assessed Random Forest (RF), eXtreme [...] Read more.

High-precision sediment distribution maps are indispensable for nearshore sediment dynamics and ecology and nearshore resource management. Using grain-size data of surface sediments from the nearshore waters of Lianyungang and auxiliary datasets including bathymetric and hydrodynamic conditions, this study assessed Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Support Vector Regression (SVR) for predicting sediment grain-size fractions and mapping sediment substrate types. All three models capture the spatial gradient of sediment grain size from fine to coarse from the nearshore to the offshore regions, but differ in preserving local heterogeneity and defining transition boundaries: XGBoost delivers the most balanced performance by preserving grain-size variability, reducing boundary mixing, and improving the identification of classes with limited samples; RF excels in robust delineation of gradual transitions, whereas SVR tends to produce fragmented boundaries and unstable performance for classes with limited samples. Feature importance reveals that hydrodynamic drivers dominate the spatial distribution of sand, whereas terrain indices are more influential for the clay distribution pattern, confirming the role of microtopography in modulating fine-sediment trapping. Overall, this study improves mapping accuracy and supports marine spatial planning and coastal infrastructure design. Full article

(This article belongs to the Section Geological Oceanography)

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22 pages, 6573 KB

Open AccessArticle

Power Prediction for Marine Gas Turbine Plants Using a Condition-Adaptive Physics-Informed LSTM Model

by Jinwei Chen, Zhenchao Hu and Huisheng Zhang

J. Mar. Sci. Eng. 2026, 14(6), 532; https://doi.org/10.3390/jmse14060532 - 12 Mar 2026

Abstract

The accurate prediction of gas turbine output power is critical for flexible scheduling and shipboard microgrid resilience. However, purely data-driven models suffer from poor generalization and physical inconsistency in complex marine environments, especially under unseen operation conditions. This paper proposes a condition-adaptive physics-informed [...] Read more.

The accurate prediction of gas turbine output power is critical for flexible scheduling and shipboard microgrid resilience. However, purely data-driven models suffer from poor generalization and physical inconsistency in complex marine environments, especially under unseen operation conditions. This paper proposes a condition-adaptive physics-informed long short-term memory (CAPI-LSTM) framework to ensure physical consistency across the full operation envelope. In the proposed framework, an MLP-based condition-adaptive regulator is developed to dynamically adjust the compressor air flow rate within the embedded physics-informed loss function. The proposed CAPI-LSTM model is verified using the operation data from an LM2500+ gas turbine. The comparison results demonstrate the superiority of the proposed method over traditional architectures. The CAPI-LSTM model achieves the lowest root mean square error of 0.177 MW, and its error distribution is the most concentrated near zero among all compared models. The robustness of the CAPI-LSTM model is further verified under the unseen operation conditions. The CAPI-LSTM still maintains excellent generalization capability compared to both purely data-driven models and standard physics-informed models, with an average error of only 0.218 MW and a narrow interquartile range of [0.058, 0.363]. The paired t-test results confirm that the improvement of the CAPI-LSTM model is statistically significant. The CAPI-LSTM model achieves competitive computational efficiency despite the integration of the physics-informed loss function with a condition-adaptive regulator. Furthermore, the CAPI-LSTM model achieves superior performance in noise immunity and transferability to other types of gas turbines. In summary, the proposed CAPI-LSTM model provides an effective and practical solution for marine gas turbine output power prediction. Full article

(This article belongs to the Section Ocean Engineering)

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20 pages, 13437 KB

Open AccessArticle

Motion Prediction of Moored Platform Using CNN–LSTM for Eco-Friendly Operation

by Omar Jebari, Chungkuk Jin, Byungho Kang, Seong Hyeon Hong, Changhee Lee and Young Hun Jeon

J. Mar. Sci. Eng. 2026, 14(6), 531; https://doi.org/10.3390/jmse14060531 - 12 Mar 2026

Abstract

Predicting the motion of ships and floating structures is essential for ensuring economical and environmentally friendly operations in the ocean. In this study, we propose a hybrid encoder–decoder Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) architecture to predict motions of a moored Floating Production [...] Read more.

Predicting the motion of ships and floating structures is essential for ensuring economical and environmentally friendly operations in the ocean. In this study, we propose a hybrid encoder–decoder Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) architecture to predict motions of a moored Floating Production Storage and Offloading (FPSO) vessel under varying sea conditions. The model integrates a CNN for spatial wave-field feature extraction and an LSTM encoder–decoder to capture temporal dependencies in vessel motion. Synthetic datasets were generated using mid-fidelity dynamics simulations of a coupled FPSO–mooring–riser system subjected to wave excitations. Five sea states ranging from calm to severe were considered to evaluate the model’s robustness. A key preprocessing step involved determining the optimal spatial domain for wave field input, and a wave field size of 600 m × 600 m was identified as the most cost-effective configuration while maintaining accuracy. The model was validated using the Root Mean Square Error (RMSE) or relative RMSE (RRMSE). Despite low RRMSE values in low sea states, predictions were noisier due to high-frequency, low-amplitude responses. In contrast, higher sea states yielded more stable predictions despite higher RRMSE values. The proposed method offers high-resolution motion forecasting capability, which can enhance operational safety and energy efficiency of offshore platforms, particularly when integrated with stereo camera-based wave monitoring systems. Full article

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

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22 pages, 3578 KB

Open AccessArticle

Numerical Simulation Analysis of Hydrodynamic Coupling Effects and Energy Conversion Efficiency of Dual-Float Wave Energy Converters

by Dongqin Li, Yu Zhang, Jie Hu, Yanqing Yin, Bohan Wang and Wenwen Chen

J. Mar. Sci. Eng. 2026, 14(6), 530; https://doi.org/10.3390/jmse14060530 - 12 Mar 2026

Abstract

This study examines the hydrodynamic performance and energy conversion mechanisms of a dual-float wave energy converter (WEC) to address the limitations of single-float WECs regarding energy capture efficiency and cost-effectiveness. A three-dimensional numerical wave tank is constructed utilizing computational fluid dynamics (CFDs) technology [...] Read more.

This study examines the hydrodynamic performance and energy conversion mechanisms of a dual-float wave energy converter (WEC) to address the limitations of single-float WECs regarding energy capture efficiency and cost-effectiveness. A three-dimensional numerical wave tank is constructed utilizing computational fluid dynamics (CFDs) technology and STAR-CCM+ to simulate the dynamic response of the dual-float system under specific wave conditions characterized by a height of 0.1 m and a period of 1.5 s. The effects of a front-rear configuration with a quarter-wavelength spacing on the converter’s power output, turbofan rotational characteristics, and heave motion are systematically analyzed. The results indicate that the wave-facing float attains a consistent rotational speed of 4 rad/s, exhibiting significant fluctuations in heave displacement and velocity. Conversely, the downstream float exhibits diminished motion amplitude, a constant rotational velocity of 2.5 rad/s, and curtailed power generation attributable to wave diffraction and energy shielding from the wave-facing float. The mutual hydrodynamic interference between the floats influences the total energy conversion efficiency, as evidenced by the dual-float system’s array impact factor of 0.989. A parametric study covering multiple wave conditions and float spacing is supplemented to reveal the influence law of key parameters on system performance. This paper elucidates the fundamental mechanism of hydrodynamic coupling in dual-float arrays and offers a theoretical foundation and technical guidance for the optimal design and engineering application of arrayed WECs. Full article

(This article belongs to the Special Issue CFD Applications in Ship and Offshore Hydrodynamics (2nd Edition))

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19 pages, 9004 KB

Open AccessArticle

Influence of Station-to-Station Line Orientation on Sea Current Speed Observation Using Coastal Acoustic Tomography

by Wan-Gu Kim, Byoung-Nam Kim and Yohan Chweh

J. Mar. Sci. Eng. 2026, 14(6), 529; https://doi.org/10.3390/jmse14060529 - 11 Mar 2026

Abstract

The influence of station-to-station line orientation on sea current speed observations using Coastal Acoustic Tomography (CAT) was quantitatively investigated. For this purpose, we conducted CAT experiments at five stations in Yeosu Bay, South Korea. Through these experiments, the sea current speeds were estimated [...] Read more.

The influence of station-to-station line orientation on sea current speed observations using Coastal Acoustic Tomography (CAT) was quantitatively investigated. For this purpose, we conducted CAT experiments at five stations in Yeosu Bay, South Korea. Through these experiments, the sea current speeds were estimated along a total of six tomographic observation lines with different orientations, and the results were compared with current speeds measured simultaneously by an Acoustic Doppler Current Profiler (ADCP). The comparison showed that the concordance between tomography-estimated sea current speed and ADCP-measured sea current speed tended to decrease as the acute angle between the predominant tidal current direction in Yeosu Bay and a tomographic observation line increased. This tendency is interpreted as arising because the smaller the difference between the two one-way travel times obtained during tomographic observations, the greater the effect of the travel time measurement error whose magnitude is relatively direction-independent. This interpretation was supported by a simple numerical simulation. Furthermore, quantitative analysis of these simulation results indicated that a smaller acute angle between the predominant sea current direction in the survey area and a tomographic observation line enhances the robustness of sea current speed estimation against travel time measurement errors. The results show that the station-to-station line in CAT should be arranged considering the predominant sea current direction in the survey area, which can provide an important guideline for selecting station locations. Full article

(This article belongs to the Special Issue Underwater Acoustics: Advances in Modelling, Measurement, and Technological Applications)

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18 pages, 3097 KB

Open AccessArticle

Nitrogen Dominates Sedimentary Organic Carbon Distribution in a Tropical Marine Ranch

by Xiaoran Shi, Liting Chen, Aiyao Yang, Yu Han, Xiaoju Pan, Zhaoyun Wang, Weijie Gong and Xiangen Wu

J. Mar. Sci. Eng. 2026, 14(6), 528; https://doi.org/10.3390/jmse14060528 - 11 Mar 2026

Abstract

Marine ranching, as a pivotal strategy for enhancing the ocean’s carbon sequestration potential, offers significant potential to mitigate nearshore fishery depletion and restore marine ecosystems amid the global carbon neutrality agenda. However, the mechanistic pathways linking sediment total organic carbon (TOC) to various [...] Read more.

Marine ranching, as a pivotal strategy for enhancing the ocean’s carbon sequestration potential, offers significant potential to mitigate nearshore fishery depletion and restore marine ecosystems amid the global carbon neutrality agenda. However, the mechanistic pathways linking sediment total organic carbon (TOC) to various environmental factors in tropical marine ranches remain insufficiently quantified. This study selected the Wuzhizhou Island Marine Ranch in Hainan Province—a representative tropical marine ranch—as the research site. Field investigations and sampling were conducted during the dry (March 2024) and wet (September 2024) seasons to quantify TOC in surface sediments and associated environmental variables. A two-step analytical framework, integrating Principal Component Analysis (PCA) and Generalized Additive Models (GAM), was employed to elucidate the environmental drivers governing the spatiotemporal dynamics of TOC. The results show that the surface sediment TOC at Wuzhizhou Island Marine Ranch exhibits a distinct spatial gradient—Core Reef > Atoll > Control > Estuarine, and a pronounced seasonal pattern with elevated concentrations in the dry season relative to the wet season. The spatiotemporal differentiation of TOC is mainly driven by a gradient (explaining 52.1% of variation) that encompasses processes related to carbon accumulation from terrestrial inputs and primary production, as well as organic matter degradation promoted by nutrients and higher water temperatures. Sediment total nitrogen (TN) emerges as the primary environmental driver of TOC distribution, contributing up to 46.9% of the variance at an extremely significant level (p < 0.001). Furthermore, total phosphorus (TP), pH, and water temperature (WT) have relatively minor influences on the distribution of sedimentary TOC. Our study offers a crucial reference for elucidating the key processes governing the carbon cycle in tropical marine ranches and provides essential theoretical support for optimizing ocean carbon sink strategies in the context of global climate change. Full article

(This article belongs to the Section Marine Environmental Science)

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2 pages, 681 KB

Open AccessCorrection

Correction: Xie et al. Prediction Analysis of Sea Level Change in the China Adjacent Seas Based on Singular Spectrum Analysis and Long Short-Term Memory Network. J. Mar. Sci. Eng. 2024, 12, 1397

by Yidong Xie, Shijian Zhou and Fengwei Wang

J. Mar. Sci. Eng. 2026, 14(6), 527; https://doi.org/10.3390/jmse14060527 - 11 Mar 2026

Abstract

In the original publication [...] Full article

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27 pages, 5110 KB

Open AccessArticle

HAIS-SegFormer: A Lightweight Underwater Crack Segmentation Network Based on Hybrid Attention and Feature Inhibition

by Gang Li, Junchi Zhang and Kun Hu

J. Mar. Sci. Eng. 2026, 14(6), 526; https://doi.org/10.3390/jmse14060526 - 10 Mar 2026

Abstract

Underwater crack detection is critical for the structural health monitoring of concrete dams; however, complex turbid environments and limited computational resources on underwater robots pose significant challenges. This study proposes HAIS-SegFormer, a lightweight segmentation network utilizing a Mix Transformer backbone. We introduce a [...] Read more.

Underwater crack detection is critical for the structural health monitoring of concrete dams; however, complex turbid environments and limited computational resources on underwater robots pose significant challenges. This study proposes HAIS-SegFormer, a lightweight segmentation network utilizing a Mix Transformer backbone. We introduce a tandem Hybrid Attention mechanism—cascading Coordinate Attention (CoordAtt) and Convolutional Block Attention Modules (CBAM)—to preserve long-range topological connectivity and refine local edge details. Furthermore, a Feature Inhibition Module (FIM), modeled after biological lateral inhibition, is designed to actively suppress high-frequency background noise such as water plants. Experimental results on an underwater crack dataset demonstrate that HAIS-SegFormer achieves a favorable trade-off between segmentation accuracy (71.66% mIoU) and computational efficiency (73 FPS, 3.80 M parameters). The proposed framework provides a robust and resource-efficient solution for automated underwater inspections. Full article

(This article belongs to the Section Ocean Engineering)

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21 pages, 5256 KB

Open AccessArticle

Numerical Simulation and Optimization Study of Liquid Sloshing in a LNG Storage Tank

by Zhimei Lu, Zhanxue Cao, Zhaodan Xia, Xiong Zhang and Xiaoli Yuan

J. Mar. Sci. Eng. 2026, 14(6), 525; https://doi.org/10.3390/jmse14060525 - 10 Mar 2026

Abstract

Liquefied natural gas (LNG) sloshing occurs during marine transportation and storage due to vessel motion or external disturbances, leading to complex fluid–structure interactions within the containment system. This study employs OpenFOAM to develop a numerical model of LNG sloshing. The model solves the [...] Read more.

Liquefied natural gas (LNG) sloshing occurs during marine transportation and storage due to vessel motion or external disturbances, leading to complex fluid–structure interactions within the containment system. This study employs OpenFOAM to develop a numerical model of LNG sloshing. The model solves the incompressible multiphase Navier–Stokes equations and utilizes the Volume of Fluid (VOF) method to capture the dynamic behavior of gas–liquid interface. The numerical model was validated against experimental data. Based on this model, the key hydrodynamic characteristics are investigated for LNG sloshing, including nonlinear free surface, transient pressure distribution on the tank walls due to liquid impact, and energy dissipation mechanisms. By varying excitation frequencies, amplitudes, and the configuration of internal components such as baffles or anti-sloshing devices, the study explores the sloshing response and effective control strategies. The results indicate that appropriately designed baffles can significantly mitigate sloshing-induced impact pressures on tank walls and enhance system stability. In the future, this study could extend to multi-layer fluids, multi-degree-of-freedom motions, and simulations under more complex real-world conditions. Full article

(This article belongs to the Topic Marine Energy)

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32 pages, 7748 KB

Open AccessArticle

Research on Energy-Efficient Path Planning for Tugboat Based on Ant Colony Optimization Integrated with Potential Field Maps

by Yao Fang and Diju Gao

J. Mar. Sci. Eng. 2026, 14(6), 524; https://doi.org/10.3390/jmse14060524 - 10 Mar 2026

Abstract

To address the problems of high energy consumption and excessive navigation time in autonomous tugboat operations during cross-regional missions, an Ant Colony Optimization algorithm integrated with Potential Field Maps (PFM-ACO) is proposed. The proposed method is capable of planning routes that satisfy navigation [...] Read more.

To address the problems of high energy consumption and excessive navigation time in autonomous tugboat operations during cross-regional missions, an Ant Colony Optimization algorithm integrated with Potential Field Maps (PFM-ACO) is proposed. The proposed method is capable of planning routes that satisfy navigation time constraints, thereby improving navigation efficiency while minimizing voyage energy consumption. Specifically, time-based and energy-consumption-based potential field maps are constructed using ocean current data. The initial pheromone matrix and heuristic function are further redesigned to enhance target-oriented guidance. In addition, an adaptive heuristic factor based on a goal-biased strategy is introduced to strengthen the global search capability of the algorithm. Finally, the proposed PFM-ACO algorithm is compared with the A*, A*-DCE and NDACA algorithms. Experimental results demonstrate that, under navigation time constraints, the paths generated by PFM-ACO achieve both the lowest energy consumption and the highest path smoothness. Overall, the proposed algorithm outperforms the comparative methods, indicating its effectiveness and superiority in energy-efficient path planning for tugboat navigation. Full article

(This article belongs to the Section Ocean Engineering)

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22 pages, 35886 KB

Open AccessArticle

Characteristics and Migration Patterns of Deltaic Channels in Tide-Controlled Coal-Accumulating Environments: A Case Study of the Pinghu Formation in the K Area, Xihu Depression

by Yaning Wang, Bin Shen, Yan Zhao and Shan Jiang

J. Mar. Sci. Eng. 2026, 14(6), 523; https://doi.org/10.3390/jmse14060523 - 10 Mar 2026

Abstract

This paper focuses on the Pinghu Formation in the K region of the Xihu Depression, conducting a systematic study on the channel types, migration patterns, and the coupling mechanisms of tectonics, paleogeomorphology, and tidal dynamics in the tidal-controlled and river-controlled composite delta system [...] Read more.

This paper focuses on the Pinghu Formation in the K region of the Xihu Depression, conducting a systematic study on the channel types, migration patterns, and the coupling mechanisms of tectonics, paleogeomorphology, and tidal dynamics in the tidal-controlled and river-controlled composite delta system of the region. By integrating core, well logging, and 3D seismic data, and addressing the challenges of channel identification under the influence of coal seams, methods such as PCA, K-means clustering, and fuzzy c-means clustering were employed for multi-attribute fusion analysis. An indicator system for channel identification and type classification was established, revealing the sedimentary characteristics of tidal-modified delta channels and their planar distribution and migration evolution process. The results of the study indicate that: (1) The early stage of the Pinghu Formation developed a tidal-controlled delta, with channels in network, linear, and dendritic shapes, where individual channels were small and fragmented; in the later stage, it transformed into a river-controlled delta, with sandbodies more concentrated; (2) In areas with weak tectonic constraints, the control of geomorphic boundaries became more prominent, and the barrier islands’ shielding effect on tides led to river-controlled migration of the channels, with limited tidal channels and tidal-modified sandbodies developed only in local areas; (3) The planar distribution and evolution of channels in the study area showed significant differences at different times due to the influences of geomorphology and tectonics. The findings of this paper provide new insights into the sedimentary evolution of tidal-modified delta channels. Full article

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