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Determining the Minimum Detection Limit of Methane Hydrate Using Associated Alpha Particle Technique -
Novel Hybrid Aquatic–Aerial Vehicle to Survey in High Sea States: Initial Flow Dynamics on Dive and Breach -
Use of Machine-Learning Techniques to Estimate Long-Term Wave Power at a Target Site Where Short-Term Data Are Available -
Strategizing Artificial Intelligence Transformation in Smart Ports: Lessons from Busan’s Resilient AI Governance Model
Journal Description
Journal of Marine Science and Engineering
Journal of Marine Science and Engineering
is an international, peer-reviewed, open access journal on marine science and engineering, published monthly online by MDPI. The Australia New Zealand Marine Biotechnology Society (ANZMBS) is affiliated with JMSE and their members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed with Scopus, SCIE (Web of Science), Ei Compendex, GeoRef, Inspec, AGRIS, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Marine) / CiteScore - Q2 (Ocean Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 15.6 days after submission; acceptance to publication is undertaken in 1.9 days (median values for papers published in this journal in the first half of 2025).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Journal Clusters of Water Resources: Water, Journal of Marine Science and Engineering, Hydrology, Resources, Oceans, Limnological Review, Coasts.
Impact Factor:
2.8 (2024);
5-Year Impact Factor:
2.8 (2024)
Latest Articles
Stress Analysis in Catenary Flexibles of the Floating Offshore Structures
J. Mar. Sci. Eng. 2025, 13(11), 2081; https://doi.org/10.3390/jmse13112081 (registering DOI) - 1 Nov 2025
Abstract
In this paper, the nonlinear bending of the slender flexible cable connected to floating offshore energy platforms is considered. The aim is to find accurate values for the bending stress in the catenaries that lead to fatigue and short lifetime. A new approach
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In this paper, the nonlinear bending of the slender flexible cable connected to floating offshore energy platforms is considered. The aim is to find accurate values for the bending stress in the catenaries that lead to fatigue and short lifetime. A new approach called Extended Stiffened Catenary Theory (ESCT) is described and outlined, which accurately predicts the bending stresses such that they can be validated by high-fidelity FEM software, e.g., ABAQUS 2024. It is found that some widely used software, such as Orcaflex 11.4, underestimates these bending stresses. Although the Orcaflex uses built-in FEM software to analyse the stresses, there are substantial differences between the results. Since the stresses are underestimated, it can lead to a wrongly estimated higher fatigue lifetime. Therefore, a critical review of stress analysis in Orcaflex is carried out to find the origins of such underestimation. It is shown that the explicit integration of equations of motion in Orcaflex is the reason for such underestimation, even in static analysis. The ABAQUS can predict accurately because of implicit (standard) integration. It is concluded that using this ESCT allows us to estimate a more realistic and reliable stress, thereby leading to a realistic lifetime for catenary umbilicals and cables for floating platforms.
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(This article belongs to the Section Ocean Engineering)
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Modeling Hurricane Wave Forces Acting on Coastal Bridges by Artificial Neural Networks
by
Hong Xiao, Wenrui Huang and Jiahui Wang
J. Mar. Sci. Eng. 2025, 13(11), 2080; https://doi.org/10.3390/jmse13112080 (registering DOI) - 1 Nov 2025
Abstract
Artificial neural networks have been evaluated and compared for modeling extreme wave forces exerted on coastal bridges during hurricanes. Long Short-Term Memory (LSTM) is selected for deep learning neural networks. A feedforward neural network (FFNN) is employed to represent the shallow learning network
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Artificial neural networks have been evaluated and compared for modeling extreme wave forces exerted on coastal bridges during hurricanes. Long Short-Term Memory (LSTM) is selected for deep learning neural networks. A feedforward neural network (FFNN) is employed to represent the shallow learning network for comparison purposes. The two case studies consist of an emerged bridge deck destroyed by Hurricane Ivan and a submerged bridge deck impaired in Hurricane Katrina. Datasets for model training and verifications consist of wave elevation and force time series resulting from previous validated numerical wave load modeling studies. Results indicate that both deep LSTM and shallow FFNNs are able to provide very good predictions of wave forces with correlation coefficients above 0.98 by comparing model simulations and data. Effects of training algorithms on network performance have been investigated. Among several training algorithms, the adaptive moment estimation (Adam) training optimizer leads to the best LSTM performance, while Levenberg–Marquardt (LM) optimized backpropagation is among the most effective training algorithms for FFNNs. In general, a shallow FFNN-LM network results in slightly higher correlation coefficients and lower error than those from an LSTM-Adam network. For sharp variation in nonlinear wave forces in the emerged bridge case study during Hurricane Ivan, FFNN-LM predictions of wave forces show better matching with the quick variations in nonlinear wave forces. FFNN-LM’s speed is approximately 4 times faster in model training but is about twice as slow in model verification and application than the LSTM-Adam network. Neural network simulations have shown substantially faster than CFD wave load modeling in our case studies.
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(This article belongs to the Section Coastal Engineering)
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Integrated LiDAR-Based Localization and Navigable Region Detection for Autonomous Berthing of Unmanned Surface Vessels
by
Haichao Wang, Yong Yin, Liangxiong Dong and Helang Lai
J. Mar. Sci. Eng. 2025, 13(11), 2079; https://doi.org/10.3390/jmse13112079 (registering DOI) - 31 Oct 2025
Abstract
Autonomous berthing of unmanned surface vehicles (USVs) requires high-precision positioning and accurate detection of navigable region in complex port environments. This paper presents an integrated LiDAR-based approach to address these challenges. A high-precision 3D point cloud map of the berth is first constructed
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Autonomous berthing of unmanned surface vehicles (USVs) requires high-precision positioning and accurate detection of navigable region in complex port environments. This paper presents an integrated LiDAR-based approach to address these challenges. A high-precision 3D point cloud map of the berth is first constructed by fusing LiDAR data with real-time kinematic (RTK) measurements. USV pose is then estimated by matching real-time LiDAR scans to the prior map, achieving robust, RTK-independent localization. For safe navigation, a novel navigable region detection algorithm is proposed, which combines point cloud projection, inner-boundary extraction, and target clustering. This method accurately identifies quay walls and obstacles, generating reliable navigable areas and ensuring collision-free berthing. Field experiments conducted in Ling Shui Port, Dalian, China, validate the proposed approach. Results show that the map-based positioning reduces absolute trajectory error (ATE) by 55.29% and relative trajectory error (RTE) by 38.71% compared to scan matching, while the navigable region detection algorithm provides precise and stable navigable regions. These outcomes demonstrate the effectiveness and practical applicability of the proposed method for autonomous USV berthing.
Full article
(This article belongs to the Special Issue New Technologies in Autonomous Ship Navigation)
Open AccessArticle
Evaluating Gas Saturation in Unconventional Gas Reservoirs Using Acoustic Logs: A Case Study of the Baiyun Depression in the Northern South China Sea
by
Jiangbo Shu, Changchun Zou, Cheng Peng, Liang Xiao, Keyu Qiao, Xixi Lan, Wei Shen, Yuanyuan Zhang and Hongjie Zhang
J. Mar. Sci. Eng. 2025, 13(11), 2078; https://doi.org/10.3390/jmse13112078 (registering DOI) - 31 Oct 2025
Abstract
Shallow gas is an unconventional natural gas resource with great potential and has received growing attention recently. Accurate estimation of gas saturation is crucial for reserves assessments and for development program formulations. However, such reservoirs are characterized by weak diagenesis, a high clay
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Shallow gas is an unconventional natural gas resource with great potential and has received growing attention recently. Accurate estimation of gas saturation is crucial for reserves assessments and for development program formulations. However, such reservoirs are characterized by weak diagenesis, a high clay content, and low resistivity. These properties pose significant challenges for saturation evaluations. To address the challenge of insufficient accuracy in evaluating the saturation of gas-bearing reservoirs, we propose an acoustic-based saturation evaluation method. In this study, a shallow unconsolidated rock physics model is first constructed to investigate the effect of variations in the gas saturation on elastic wave velocities. The model especially considers the patchy distribution of fluids within pores. In addition, we propose an iterative algorithm based on the updated relationship between porosity and gas saturation by introducing a correction term for the saturation to the density porosity, and successfully apply it to the logging data collected from the shallow gas reservoirs in the Pearl River Mouth Basin of the South China Sea. It is evident from the results that the saturation derived from the array acoustic logs is comparable to that obtained from the resistivity logs, with a mean absolute error of less than 6%. Additionally, it is also consistent with the drill stem test (DST) data, which further verifies the validity and reliability of this method. This study provides a novel non-electrical method for estimating the saturation of shallow gas reservoirs, which is essential to promote the evaluation of unconsolidated sandstone gas reservoirs.
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(This article belongs to the Special Issue Marine Well Logging and Reservoir Characterization)
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DLC-Organized Tower Base Forces and Moments for the IEA-15 MW on a Jack-up-Type Support (K-Wind): Integrated Analyses and Cross-Code Verification
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Jin-Young Sung, Chan-Il Park, Min-Yong Shin, Hyeok-Jun Koh and Ji-Su Lim
J. Mar. Sci. Eng. 2025, 13(11), 2077; https://doi.org/10.3390/jmse13112077 (registering DOI) - 31 Oct 2025
Abstract
Offshore wind turbines are rapidly scaling in size, which amplifies the need for credible integrated load analyses that consistently resolve the coupled dynamics among rotor–nacelle–tower systems and their support substructures. This study presents a comprehensive ultimate limit state (ULS) load assessment for a
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Offshore wind turbines are rapidly scaling in size, which amplifies the need for credible integrated load analyses that consistently resolve the coupled dynamics among rotor–nacelle–tower systems and their support substructures. This study presents a comprehensive ultimate limit state (ULS) load assessment for a fixed jack-up-type substructure (hereafter referred to as K-wind) coupled with the IEA 15 MW reference wind turbine. Unlike conventional monopile or jacket configurations, the K-wind concept adopts a self-installable triangular jack-up foundation with spudcan anchorage, enabling efficient transport, rapid deployment, and structural reusability. Yet such a configuration has never been systematically analyzed through full aero-hydro-servo-elastic coupling before. Hence, this work represents the first integrated load analysis ever reported for a jack-up-type offshore wind substructure, addressing both its unique load-transfer behavior and its viability for multi-MW-class turbines. To ensure numerical robustness and cross-code reproducibility, steady-state verifications were performed under constant-wind benchmarks, followed by time-domain simulations of standard prescribed Design Load Case (DLC), encompassing power-producing extreme turbulence, coherent gusts with directional change, and parked/idling directional sweeps. The analyses were independently executed using two industry-validated solvers (Deeplines Wind v5.8.5 and OrcaFlex v11.5e), allowing direct solver-to-solver comparison and establishing confidence in the obtained dynamic responses. Loads were extracted at the transition-piece reference point in a global coordinate frame, and six key components (Fx, Fy, Fz, Mx, My, and Mz) were processed into seed-averaged signed envelopes for systematic ULS evaluation. Beyond its methodological completeness, the present study introduces a validated framework for analyzing next-generation jack-up-type foundations for offshore wind turbines, establishing a new reference point for integrated load assessments that can accelerate the industrial adoption of modular and re-deployable support structures such as K-wind.
Full article
(This article belongs to the Topic Advancements and Challenges in Marine Renewable Energy and Marine Structures)
Open AccessArticle
Investigation on the Aeroelastic Characteristics of Ultra-Long Flexible Blades for an Offshore Wind Turbine in Extreme Environments
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Weiliang Liao, Qian Wang, Feng Xu, Mingming Zhang, Jianjun Yang and Youhua Fan
J. Mar. Sci. Eng. 2025, 13(11), 2076; https://doi.org/10.3390/jmse13112076 (registering DOI) - 31 Oct 2025
Abstract
With the growing demand for wind turbines in deep offshore regions, frequent typhoon disasters at sea have impeded the continued development of the wind power industry. To address the problem of typhoons destroying offshore wind power facilities, this paper investigates the aeroelastic characteristics
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With the growing demand for wind turbines in deep offshore regions, frequent typhoon disasters at sea have impeded the continued development of the wind power industry. To address the problem of typhoons destroying offshore wind power facilities, this paper investigates the aeroelastic characteristics of long flexible blades on ultra-large offshore wind turbines under typhoon loads. The WRF numerical model is employed for high-precision simulations of Typhoon Mangkhut (No. 1822). By optimizing parameterization schemes and incorporating 3DVAR data assimilation techniques, typhoon wind speed profiles in the target sea area are obtained. Based on IEA 15 MW offshore wind turbine data, 3D unsteady CFD models and full-scale finite element models of the blades are established to acquire the aerodynamic loads and structural responses of the blades in typhoon environments. The results indicate that, under extreme typhoon loads and considering wind shear and tower shadow effects, the forces near the blade root are greater; the maximum out-of-plane aerodynamic force occurs at the 14% span position of the blade at 90° azimuth, and the maximum torsional aerodynamic moment is experienced at the 26.5% span position of the blade at 270° azimuth. When the blade pitch angle and rotor yaw angle do not reach ideal states, the deflection of ultra-long flexible blades can increase by up to 3.26 times. These findings overcome the limitations of traditional uniform wind field studies and provide a theoretical basis for subsequent coping strategies for offshore blades under typhoon conditions.
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(This article belongs to the Topic Advancements in Cost-Effective and Reliable Floating Offshore Wind Technologies: From Innovative Design to System Integration)
Open AccessArticle
Numerical Investigation of Hydrodynamic Characteristics of Circular Cylinder with Surface Roughness at Subcritical Reynolds Number
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Erxian Zeng, Songsong Yu, Heng Feng, Zhihui Jiao and Guoqiang Tang
J. Mar. Sci. Eng. 2025, 13(11), 2075; https://doi.org/10.3390/jmse13112075 (registering DOI) - 31 Oct 2025
Abstract
This study investigates the hydrodynamic behavior of rough cylinders, focusing on how surface roughness influences vortex shedding patterns and forces in cross-flow. To achieve this objective, a three-dimensional large-eddy simulation was conducted to study the hydrodynamic coefficients and flow fields of cylinders with
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This study investigates the hydrodynamic behavior of rough cylinders, focusing on how surface roughness influences vortex shedding patterns and forces in cross-flow. To achieve this objective, a three-dimensional large-eddy simulation was conducted to study the hydrodynamic coefficients and flow fields of cylinders with different relative roughness, height, and coverage ratios at a Reynolds number of 3900. The results show that the coverage ratio plays a more significant role in determining hydrodynamic characteristics than relative roughness, with a critical coverage ratio identified at approximately 0.4. Below this threshold, both drag and lift coefficients exhibit a marked increase with higher relative roughness. However, beyond a 0.4 coverage ratio, the impact of roughness diminishes, with the coefficients approaching those of a smooth cylinder. Additionally, the Strouhal number decreases with increasing roughness height and increases with coverage ratio. Flow visualization shows that these changes are closely related to the position and magnitude of the wake vortex shedding in the wake region of a rough cylinder. These findings provide new insights into the fundamental mechanisms of the hydrodynamic characteristics and vortex shedding of rough cylinders and offer valuable guidance for optimizing engineering design and enhancing performance in practical applications.
Full article
(This article belongs to the Special Issue New Era in Offshore Wind Energy)
Open AccessArticle
A Hybrid Empirical–Neural Model for HFSWR False Alarm Reduction Caused by Meteo-Tsunami-Like Phenomena
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Zoran Stankovic, Dejan Nikolic, Nebojsa Doncov, Dejan Drajic and Vladimir Orlic
J. Mar. Sci. Eng. 2025, 13(11), 2074; https://doi.org/10.3390/jmse13112074 (registering DOI) - 31 Oct 2025
Abstract
The meteo-tsunami as an atmospheric phenomenon is still being researched, and its effects beyond physical ones (destruction if they hit the shore) are yet to be fully classified. One such effect is an increase in false alarm occurrence in high frequency surface wave
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The meteo-tsunami as an atmospheric phenomenon is still being researched, and its effects beyond physical ones (destruction if they hit the shore) are yet to be fully classified. One such effect is an increase in false alarm occurrence in high frequency surface wave radar (HFSWR) systems used for vessel traffic surveillance and control. Unfortunately, this effect is characterized by high-dimensional and highly nonlinear functional dependencies that cannot be described by closed-form mathematical equations. Since an artificial neural network is a highly parallelized distributed architecture with a fast flow of signals from input to output designed not to execute a predefined set of commands, but to “learn” dependencies during the training process and to apply that knowledge to solve unknown, but similar problems, it is a natural solution to the presented problem. Hybrid empirical–neural model-based probabilistic neural networks (PNN) used in this research proved to be quite capable of recognizing when an increase in false alarms can be expected based on the monitoring of atmospheric conditions in the HFSWR network coverage area and to eliminate them from the system, thus increasing the safety and security of all the actors in maritime traffic.
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(This article belongs to the Section Ocean Engineering)
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LW-MS-LFTFNet: A Lightweight Multi-Scale Network Integrating Low-Frequency Temporal Features for Ship-Radiated Noise Recognition
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Yu Feng, Zhangxin Chen, Yixuan Chen, Ziqin Xie, Jiale He, Jiachang Li, Houqian Ding, Tao Guo and Kai Chen
J. Mar. Sci. Eng. 2025, 13(11), 2073; https://doi.org/10.3390/jmse13112073 (registering DOI) - 31 Oct 2025
Abstract
Ship-radiated noise (SRN) recognition is vital for underwater acoustics, with applications in both military and civilian fields. Traditional manual recognition by sonar operators is inefficient and error-prone, motivating the development of automated recognition systems. However, most existing deep learning approaches demand high computational
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Ship-radiated noise (SRN) recognition is vital for underwater acoustics, with applications in both military and civilian fields. Traditional manual recognition by sonar operators is inefficient and error-prone, motivating the development of automated recognition systems. However, most existing deep learning approaches demand high computational resources, limiting their deployment on resource-constrained edge devices. To overcome this challenge, we propose LW-MS-LFTFNet, a lightweight model informed by time-frequency analysis of SRN that highlights the critical role of low-frequency components. The network integrates a multi-scale depthwise separable convolutional backbone with CBAM attention for efficient spectral representation, along with two LSTM-based modules to capture temporal dependencies in low-frequency bands. Experiments on the DeepShip dataset show that LW-MS-LFTFNet achieves 75.04% accuracy with only 0.85 M parameters, 0.38 GMACs, and 3.27 MB of storage, outperforming representative lightweight architectures. Ablation studies further confirm that low-frequency temporal modules contribute complementary gains, improving accuracy by 2.64% with minimal overhead. Guided by domain-specific priors derived from time-frequency pattern analysis, LW-MS-LFTFNet achieves efficient and accurate SRN recognition with strong potential for edge deployment.
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(This article belongs to the Section Ocean Engineering)
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Multi-AUV Cooperative Search for Moving Targets Based on Multi-Agent Reinforcement Learning
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Le Li, Ruiqi An, Zhaozhi Guo and Jian Gao
J. Mar. Sci. Eng. 2025, 13(11), 2072; https://doi.org/10.3390/jmse13112072 (registering DOI) - 31 Oct 2025
Abstract
This paper proposes a convolutional multi-agent deep deterministic policy gradient method with prioritized experience replay (PER-CMADDPG) for the problem of multi-AUV cooperative search for moving targets. A comprehensive mathematical model of the multi-AUV cooperative search for moving targets is first established, which includes
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This paper proposes a convolutional multi-agent deep deterministic policy gradient method with prioritized experience replay (PER-CMADDPG) for the problem of multi-AUV cooperative search for moving targets. A comprehensive mathematical model of the multi-AUV cooperative search for moving targets is first established, which includes the environment model, the AUV model, and the information update and fusion model. Building upon the MADDPG framework, the proposed PER-CMADDPG method introduces two major enhancements. Convolutional neural networks (CNNs) are integrated into both the actor and critic networks to extract spatial features from local observation maps and global states, enabling agents to better perceive the spatial structure of the environment. In addition, a prioritized experience replay (PER) mechanism is incorporated to improve learning efficiency by emphasizing informative experiences during training, thereby accelerating policy convergence. Simulation experiments demonstrate that the proposed method achieves faster convergence and higher rewards compared with MADDPG. Furthermore, the influences of the multi-AUV cluster system’s scale, AUV speed, and sonar detection radius on performance are analyzed. The results verify the effectiveness of the proposed PER-CMADDPG method for the multi-AUV cooperative search for moving targets.
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(This article belongs to the Section Marine Energy)
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Coordinated Control Strategy for Island Power Generation System with Photovoltaic, Hydrogen-Fueled Gas Turbine and Hybrid Energy Storage
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Zhicheng Ye, Zemin Ding, Yongbao Liu and Youhong Yu
J. Mar. Sci. Eng. 2025, 13(11), 2071; https://doi.org/10.3390/jmse13112071 (registering DOI) - 31 Oct 2025
Abstract
Marine and island power systems usually incorporate various forms of energy supply, which poses challenges to the coordinated control of the system under diverse, irregular, and complex load operation modes. To improve the stability and self-sufficiency of island-isolated microgrids with high penetration of
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Marine and island power systems usually incorporate various forms of energy supply, which poses challenges to the coordinated control of the system under diverse, irregular, and complex load operation modes. To improve the stability and self-sufficiency of island-isolated microgrids with high penetration of renewable energy, this study proposes a coordinated control strategy for an island microgrid with PV, HGT, and HESS, combining primary power allocation via low-pass filtering with a fuzzy logic-based secondary correction. The fuzzy controller dynamically adjusts power distribution based on the states of charge of the battery and supercapacitor, following a set of predefined rules. A comprehensive system model is developed in Matlab R2023b, integrating PV generation, an electrolyzer, HGT and a battery–supercapacitor HESS. Simulation results across four operational cases demonstrate that the proposed strategy reduces DC bus voltage fluctuations to a maximum of 4.71% (compared to 5.63% without correction), with stability improvements between 0.96% and 1.55%. The HESS avoids overcharging and over-discharging by initiating priority charging at low SOC levels, thereby extending service life. This work provides a scalable control framework for enhancing the resilience of marine and island microgrids with high renewable energy penetration.
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(This article belongs to the Section Marine Energy)
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Reliability Assessment of Marine Propulsion Systems for MASS: A Bibliometric Analysis and Literature Review
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Rabiul Islam, Yueting Guo, Sidum Adumene and Nagi Abdussamie
J. Mar. Sci. Eng. 2025, 13(11), 2070; https://doi.org/10.3390/jmse13112070 - 30 Oct 2025
Abstract
The maritime industry is rapidly advancing towards Industry 4.0 and the integration of autonomous shipping technologies. As the main propulsion system for autonomous vessels, marine engines play a critical role in ensuring the safety and reliability of operations at sea. Therefore, assessing the
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The maritime industry is rapidly advancing towards Industry 4.0 and the integration of autonomous shipping technologies. As the main propulsion system for autonomous vessels, marine engines play a critical role in ensuring the safety and reliability of operations at sea. Therefore, assessing the reliability and associated risks of marine engine systems is essential to prevent failures that could compromise autonomous navigation. This study conducts a comprehensive bibliometric analysis to provide up-to-date insights into the reliability assessment of marine engine machinery in the context of autonomous shipping. A total of 139 publications were retrieved from Web of Science and 133 from the Scopus database. The analysis addresses the key questions like (i) Which countries are leading research in this field? (ii) Which sources are most active in publishing this research? (iii) Which articles have had the greatest impact? (iv) Who are the most influential authors? (v) What keywords appear most frequently? (vi) What methodologies are commonly used? The findings indicate that this research area has attracted global attention, with Norway, the United States, Finland, Poland, and China being the most active contributors. However, Norway is leading in total output. Among the methodologies employed, the Bayesian network has been identified as the most widely used approach for reliability assessment of marine propulsion systems in MASS.
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(This article belongs to the Section Ocean Engineering)
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Shape Optimization and Fatigue Analysis of the Bracket in the Jacking Frame of a Wind Turbine Installation Vessel
by
Guanyi Gao, Shumei Chen, Guoqing Feng and Kaiyan Li
J. Mar. Sci. Eng. 2025, 13(11), 2069; https://doi.org/10.3390/jmse13112069 - 30 Oct 2025
Abstract
As offshore wind power continues to extend into deeper waters, the operational environment has expanded from shallow to deep seas. Self-elevating and self-propelled installation vessels have been widely adopted due to their jack-up systems and self-propulsion capabilities. The structural integrity of wind turbine
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As offshore wind power continues to extend into deeper waters, the operational environment has expanded from shallow to deep seas. Self-elevating and self-propelled installation vessels have been widely adopted due to their jack-up systems and self-propulsion capabilities. The structural integrity of wind turbine installation vessels is crucial to ensure successful operations, among which the strength of the jacking frame is particularly critical. This study focuses on the bracket made of E550 steel at the root of the jacking frame. Shape optimization of the bracket was performed using parametric modeling technology, resulting in a 26% reduction in peak stress and a 12% decrease in bracket mass. Following the optimization, a full-scale fatigue test targeting local fatigue hot spots of the bracket was carried out. Based on the experimental data, the fatigue S-N curve of the bracket was obtained. Finally, a fatigue assessment was conducted on the high-stress region at the toe of the bracket. The results indicate that the bracket with unequal arm lengths exhibits lower stress concentration. Fatigue cracks of the bracket initiate at the weld toe, and the fatigue strength of the E550 steel toe joint obtained from the test is superior to that of the D-curve specified in the standards. Based on the derived S–N curve, a spectral fatigue analysis was further carried out to verify the fatigue performance of the optimized bracket. The total fatigue damage of the optimized structure over a 20-year design life was calculated as 0.6, which is below the allowable limit of 1.0, demonstrating that the optimized design satisfies the fatigue safety requirements.
Full article
(This article belongs to the Special Issue Advanced Analysis and Optimization of Tubular Joints in Marine Structures for Offshore Renewable Energy Applications)
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Open AccessArticle
Assessing the Performance of Shipboard Instruments Used to Monitor Total Residual Oxidants
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Matthew R. First, Gregory Ziegler, Stephanie H. Robbins-Wamsley, Janet M. Barnes and Mario N. Tamburri
J. Mar. Sci. Eng. 2025, 13(11), 2068; https://doi.org/10.3390/jmse13112068 - 29 Oct 2025
Abstract
Shipboard ballast water management systems (BWMS) commonly employ chlorine or other oxidants to treat ballast. Oxidant-based BWMS inject these biocides to meet a concentration threshold or target value that is lethal to most aquatic organisms. Resulting concentrations of total residual oxidant (TRO) may
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Shipboard ballast water management systems (BWMS) commonly employ chlorine or other oxidants to treat ballast. Oxidant-based BWMS inject these biocides to meet a concentration threshold or target value that is lethal to most aquatic organisms. Resulting concentrations of total residual oxidant (TRO) may span two orders of magnitude between initial doses (e.g., ~10 mg L−1) and discharged ballast, which must meet discharge limits (e.g., <0.1 mg L−1). Here, we evaluated three TRO instruments (two colorimetric-based and one based on amperometry) that have been integrated into BWMS for use in shipboard applications. Our study quantified accuracy and precision using test waters along a range of temperatures and salinities, using a pipe loop to mimic in-line shipboard operations, where the instruments continuously sample and analyze circulating water. Linear regression analysis compared the instruments to a standard reference method along a range of concentrations relevant to oxidant-based BWMS. In general, measurements from the TRO sensors showed strong linear relationships to the reference method, but slopes of these relationships were significantly <1 in all but one instance. Precision—measured as the coefficient of variation—ranged from 2 to 4%. These initial tests occurred on units shipped directly from the manufacturer, immediately following calibration and quality checks, and in a controlled laboratory environment. Thus, in this context, our evaluations represent a “best-case” outcome. We recommend that laboratory studies (as described here) be paired with endurance trials and in-service monitoring to include tests in a shipboard environment. These trials should evaluate TRO instruments that are integrated with BWMS and functioning under normal ship operations, measuring both high (treated ballast) and low (neutralized discharge) concentrations of TRO. Shipboard trials in concert with frequent calibration checks will reduce the risks of under- or overestimating TRO concentrations, as both outcomes may harm the environment.
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(This article belongs to the Section Marine Pollution)
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Open AccessArticle
Numerical Investigation on the Hydrodynamic Characteristics of Submarine Power Cables for Offshore Wind Turbines Under Combined Wave–Current Loading
by
Deping Zhao, Xiaowei Huang, Zhenjin Cen, Jianfeng Ren, Bolin Zhan and Guoqiang Tang
J. Mar. Sci. Eng. 2025, 13(11), 2067; https://doi.org/10.3390/jmse13112067 - 29 Oct 2025
Abstract
A 2D numerical model for viscous flow is established in OpenFOAM version 10 to analyze the hydrodynamic response of submarine power cables for offshore wind turbines under combined wave–current conditions. It focuses on analyzing the effect of the cable suspension ratio e/
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A 2D numerical model for viscous flow is established in OpenFOAM version 10 to analyze the hydrodynamic response of submarine power cables for offshore wind turbines under combined wave–current conditions. It focuses on analyzing the effect of the cable suspension ratio e/D and the current-to-wave velocity ratio Uc/Um on the Morison coefficient of the suspended cable. The results indicate that for the cable suspension ratio e/D of less than 0.5, the strength of the dependence of both the drag coefficient Cd and inertia coefficient CM on the cable suspension ratio e/D is significantly influenced by the current-wave-ratio Uc/Um, while this dependence becomes less pronounced for e/D greater than 0.5. And the inertia force coefficient CM decreases monotonically with the current-to-wave velocity ratio Uc/Um, while the drag force coefficient Cd demonstrates a more complex, non-monotonic relationship with it. Based on the simulation results in this paper, a quantitative relationship between Cd, CM, and the key governing parameters is established using a two-layer feedforward neural network model, providing a method for predicting wave–current forces on subsea suspended cables.
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(This article belongs to the Topic Wind, Wave and Tidal Energy Technologies in China)
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Open AccessArticle
Self-Organizing of Waves and Sandy Bottom Relief—Laboratory Experiments
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Yana Saprykina and Sergey Kuznetsov
J. Mar. Sci. Eng. 2025, 13(11), 2066; https://doi.org/10.3390/jmse13112066 - 29 Oct 2025
Abstract
Many studies suggest that, as waves propagate toward the shore, mutual adaptation (self-organization) occurs between the wave transformation and the bottom relief. However, the details of this process are unknown. Is nonlinear transformation or wave breaking the primary factor influencing bottom relief deformation?
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Many studies suggest that, as waves propagate toward the shore, mutual adaptation (self-organization) occurs between the wave transformation and the bottom relief. However, the details of this process are unknown. Is nonlinear transformation or wave breaking the primary factor influencing bottom relief deformation? The main goal of this study is to assess the impact of nonlinear wave transformation on bottom relief changes and to identify the key patterns of mutual adaptation between bottom topography and waves. A specialized laboratory experiment was conducted for this purpose. Based on an analysis of the evolution of wave spectra, changes in wave asymmetry, phase shift between harmonics and bottom relief deformations, it was revealed that self-organization occurs primarily due to the nonlinear properties of wave transformation. The nonlinear wave transformation scenario (the spatial evolution of the amplitudes of nonlinear wave harmonics toward the shore) determines the positions of the main minima and maxima of the first and second harmonic amplitudes, corresponding to sediment flow divergence points, which are maintained throughout the period of constant wave action. Wave breaking does not change this scenario, but it does affect the absolute values of the amplitudes and biphases, accelerating bottom change.
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(This article belongs to the Section Coastal Engineering)
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Open AccessArticle
A Comparison of Methods to Quantify Nano- and/or Microplastic (NMPs) Deposition in Wild-Caught Eastern Oysters (Crassostrea virginica) Growing in a Heavily Urbanized, Subtropical Estuary (Galveston Bay, USA)
by
Melissa Ciesielski, Marc Hanke, Laura J. Jurgens, Manoj Kamalanathan, Asif Mortuza, Michael B. Gahn, David Hala, Karl Kaiser and Antonietta Quigg
J. Mar. Sci. Eng. 2025, 13(11), 2065; https://doi.org/10.3390/jmse13112065 - 29 Oct 2025
Abstract
Nano- and microplastics (NMPs) in waterways reflect the impact of anthropogenic activities. This study examined spatial variations in the presence and types of NMPs in Galveston Bay (Texas, USA) surface waters and eastern oysters (Crassostrea virginica). The results reveal most MPs
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Nano- and microplastics (NMPs) in waterways reflect the impact of anthropogenic activities. This study examined spatial variations in the presence and types of NMPs in Galveston Bay (Texas, USA) surface waters and eastern oysters (Crassostrea virginica). The results reveal most MPs carried by surface waters are fibers > films > fragments. Up to 200 MPs were present in individual oysters [=1.88 (± 0.22 SE) per g wet weight]. Oyster health, based on condition index, varied spatially, but was not correlated with MP load. Based on attenuated total reflectance—Fourier-transform infrared spectroscopy, polyamide and polypropylene were frequently found in waters in the upper bay while ethylene propylene and polyethylene terephthalate were more common in the lower parts of the bay. Pyrolysis–gas chromatography–mass spectrometry revealed a very large range in concentrations of NMPs, from 28 to 10,925 µg ∑NMP/g wet weight (or 172 to 67,783 µg ∑NMP/g dry weight) in oysters. This chemical analysis revealed four main types of plastics present in oysters regardless of location: polypropylene, nylon 66, polyethylene and styrene butadiene rubber. Based on this finding, the average daily intake of NMPs estimated for adult humans is 0.85 ± 0.45 mg NMPs/Kg of body weight/day or a yearly intake of 310 ± 164 mg NMPs/Kg of body weight/year. These findings reveal higher body burdens of plastics in oysters are revealed by the chemical analysis relative to the traditional approach; this is not unexpected given the higher sensitivity and selectivity of mass spectrometry and inclusion of the nanoplastic particle range (i.e., <1 mm) in the sample preparation and analysis.
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(This article belongs to the Special Issue Ecological Risk Assessments in Marine Pollutants)
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Open AccessArticle
An Evaluation of Port Environmental Efficiency Considering Heterogeneous Abatement Capacities: Integrating Weak Disposability into the Epsilon-Based Measure Model
by
Jiewei Zhang and Gaofeng Gu
J. Mar. Sci. Eng. 2025, 13(11), 2064; https://doi.org/10.3390/jmse13112064 - 29 Oct 2025
Abstract
As pivotal hubs in maritime logistics networks, ports bear a growing responsibility to harmonize economic activities with environmental stewardship. Evaluating and enhancing port environmental efficiency (PEE) is therefore imperative for maritime decarbonization and sustainability. However, conventional approaches often assume homogeneous abatement capacities across
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As pivotal hubs in maritime logistics networks, ports bear a growing responsibility to harmonize economic activities with environmental stewardship. Evaluating and enhancing port environmental efficiency (PEE) is therefore imperative for maritime decarbonization and sustainability. However, conventional approaches often assume homogeneous abatement capacities across heterogeneous ports, which may distort evaluation results. To address this flaw, we develop a modified EBM-Undesirable model embedding weak disposability and non-uniform abatement factors, explicitly accounting for heterogeneity the in port’s abatement capabilities. Drawing on panel data from China’s major coastal ports during 2013–2022, this study further employs the Global Malmquist Index and Dagum Gini coefficient to investigate dynamic characteristics and regional disparities in PEE. Key findings reveal: (1) PEE exhibits a modest yet volatile upward trend, accompanied by pronounced inter-port divergence; (2) Total factor productivity (TFP) demonstrates sustained improvement attributable to technical efficiency advancements, yet reveals untapped potential in technological level; (3) Substantial spatial heterogeneity persists, dominated by interregional differences, though overall inequality is gradually converging. Given the observed regional disparities and technological potential, policy suggestions are proposed to advance port decarbonization, regional coordination, and maritime sustainability.
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(This article belongs to the Special Issue Sustainable and Efficient Maritime Operations)
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Open AccessArticle
Study on Motion Performance and Mooring Tension Response of 16 MW Tension Leg Platform Floating Wind Turbine Under Extreme Environmental Conditions
by
Xiaolong Yang, Yu Zhang, Shengwei Yan, Weihong Yu, Shunhang Lu, Haoshuang Wang and Wei Shi
J. Mar. Sci. Eng. 2025, 13(11), 2063; https://doi.org/10.3390/jmse13112063 - 29 Oct 2025
Abstract
This paper presents a 16 MW typhoon-resistant Tension Leg Platform floating offshore wind turbine (TLP FOWT) designed for the South China Sea. The survivability of the TLP FOWT under extreme environmental conditions is investigated through an integrated time-domain coupled analysis numerical model. The
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This paper presents a 16 MW typhoon-resistant Tension Leg Platform floating offshore wind turbine (TLP FOWT) designed for the South China Sea. The survivability of the TLP FOWT under extreme environmental conditions is investigated through an integrated time-domain coupled analysis numerical model. The accuracy of the numerical model is calibrated by comparing its results with experimental data. In comparisons of mooring system static stiffness tests and white noise tests, the results from the calibrated numerical model show good agreement with the experimental data. Regarding the free decay tests and the statistical time-domain response results, the most significant discrepancies are only 1.17% and 6.91%, respectively. Subsequently, the time-domain response of the numerical model was investigated under extreme South China Sea conditions, configured according to the IEC 61400-3-2 design load conditions. The safety of the design was then evaluated against ABS specifications. The analysis yielded maximum platform motion amplitudes and inclinations of 34.99 m (less than 30% of water depth) and below 1°, respectively. Under both 50-year and 500-year return period conditions, the platform maintained stable TLP motion characteristics with no tendon slackness, evidenced by a minimum tendon tension of 107.23 kN. All motion responses and tendon tensions complied with the ABS safety factors, confirming the design’s capability to ensure safe operation throughout its service life. The present work provides valuable insights for the design and risk assessment of future large-scale TLP FOWTs.
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(This article belongs to the Section Ocean Engineering)
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Open AccessReview
Next-Gen Nondestructive Testing for Marine Concrete: AI-Enabled Inspection, Prognostics, and Digital Twins
by
Taehwi Lee and Min Ook Kim
J. Mar. Sci. Eng. 2025, 13(11), 2062; https://doi.org/10.3390/jmse13112062 - 29 Oct 2025
Abstract
Marine concrete structures are continuously exposed to harsh marine environments—salt, waves, and biological fouling—that accelerate corrosion and cracking, increasing maintenance costs. Traditional Non-Destructive Testing (NDT) techniques often fail to detect early damage due to signal attenuation and noise in underwater conditions. This study
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Marine concrete structures are continuously exposed to harsh marine environments—salt, waves, and biological fouling—that accelerate corrosion and cracking, increasing maintenance costs. Traditional Non-Destructive Testing (NDT) techniques often fail to detect early damage due to signal attenuation and noise in underwater conditions. This study critically reviews recent advances in Artificial Intelligence-integrated NDT (AI-NDT) technologies for marine concrete, focusing on their quantitative performance improvements and practical applicability. To be specific, a systematic comparison of vision-based and signal-based AI-NDT techniques was carried out across reported field cases. It was confirmed that the integration of AI improved detection accuracy by 17–25%, on average, compared with traditional methods. Vision-based AI models such as YOLOX-DG, Cycle GAN, and MSDA increased mean mAP 0.5 by 4%, while signal-based methods using CNN, LSTM, and Random Forest enhanced prediction accuracy by 15–20% in GPR, AE, and ultrasonic data. These results confirm that AI effectively compensates for environmental distortions, corrects noise, and standardizes data interpretation across variable marine conditions. Lastly, the study highlights that AI-enabled NDT not only automates data interpretation but also establishes the foundation for predictive and preventive maintenance frameworks. By linking data acquisition, digital twin-based prediction, and lifecycle monitoring, AI-NDT can transform current reactive maintenance strategies into sustainable, intelligence-driven management for marine infrastructure.
Full article
(This article belongs to the Special Issue Monitoring and Evaluation of Marine Engineering Equipment and Structures)
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