Journal of Marine Science and Engineering

29 pages, 6254 KiB

Open AccessArticle

Optimized Deep Reinforcement Learning for Dual-Task Control in Deep-Sea Mining: Path Following and Obstacle Avoidance

by Yulong Xue, Jianmin Yang, Qihang Chen, Jinghang Mao, Wenhao Xu and Changyu Lu

J. Mar. Sci. Eng. 2025, 13(4), 735; https://doi.org/10.3390/jmse13040735 (registering DOI) - 6 Apr 2025

This study investigates the dual-task control challenge of path following and obstacle avoidance for deep-sea mining robots operating in complex, unstructured environments. To address the limitations of traditional training strategies, we propose an optimized training framework that integrates environmental design enhancements and algorithmic [...] Read more.

This study investigates the dual-task control challenge of path following and obstacle avoidance for deep-sea mining robots operating in complex, unstructured environments. To address the limitations of traditional training strategies, we propose an optimized training framework that integrates environmental design enhancements and algorithmic advancements. Specifically, we develop a Dual-Task Training Environment by combining the Random Obstacle Environment with a newly proposed Obstructed Path Environment, ensuring a balanced learning approach. While agents trained solely in the Random Obstacle Environment exhibit unilateral obstacle avoidance strategies and achieve a 0% success rate in randomized obstacle scenarios, those trained in the Dual-Task Environment demonstrate 85.4% success under identical test conditions and acquire more complex bilateral avoidance strategies. Additionally, we introduce a Dynamic Multi-Step Update mechanism, which integrates immediate rewards with long-term returns to enhance deep reinforcement learning (Twin Delayed Deep Deterministic Policy Gradient, TD3) performance without increasing computational complexity. Under the optimal multi-step setting (n = 5), the Dynamic Multi-Step Update mechanism significantly improves path following accuracy, reducing trajectory deviations to 0.128 m on straight paths and 0.195 m on S-shaped paths, while achieving nearly 100% success in multi-directional obstacle avoidance tests. These improvements collectively enhance the adaptability, robustness, and operational performance of deep-sea mining robots, advancing intelligent control strategies for autonomous deep-sea exploration and resource extraction. Full article

(This article belongs to the Section Ocean Engineering)

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24 pages, 8275 KiB

Open AccessArticle

Design of Portable Reefs to Protect Young Mangroves

by Hiroshi Takagi, Farhat Tahsin Prattoyee, Jun Mitsui and Shin-ichi Kubota

J. Mar. Sci. Eng. 2025, 13(4), 734; https://doi.org/10.3390/jmse13040734 (registering DOI) - 6 Apr 2025

Abstract

For a successful mangrove plantation, previous studies have proposed a small rubble mound breakwater, termed a “portable reef”, and explored the effectiveness of such reefs in terms of wave transmission. This study conducted a real-scale wave flume experiment incorporating a portable reef to [...] Read more.

For a successful mangrove plantation, previous studies have proposed a small rubble mound breakwater, termed a “portable reef”, and explored the effectiveness of such reefs in terms of wave transmission. This study conducted a real-scale wave flume experiment incorporating a portable reef to assess the oscillatory behavior of young mangroves. To capture the dynamics of these young mangrove analogs—represented as elastic bodies—we employed a high-speed camera for precise tracking. A comparative analysis of the oscillatory characteristics was performed, evaluating the responses in both the presence and absence of the reef. The findings revealed several important points. First, portable reefs can effectively reduce wave heights, but they reduce plant oscillations to an even greater degree. Second, by calibrating the elastic modulus of the plant models, their oscillation behaviors can be analytically predicted. The results of our analytical model indicate that the acceleration experienced by the plants is amplified under conditions of shorter wave periods and softer stems, highlighting an increased susceptibility to damage from short-period waves, particularly in very young mangroves. Third, we identified that the conventional wave transmission formulas tend to overestimate the reduction in wave energy attributable to portable reefs, which consequently leads to an underestimation of the young mangroves’ oscillations. Based on these findings, we propose an integrated chart that combines wave transmission and plant oscillation coefficients, aimed at enhancing the design and effectiveness of portable reefs in protecting young mangroves. The insights obtained from this study will aid in the informed design of portable reefs. Full article

(This article belongs to the Special Issue Coastal Ecological Restoration: Techniques and Novel Approaches to Living Shorelines and Oyster Reef Construction)

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26 pages, 3619 KiB

Open AccessArticle

Water Surface Spherical Buoy Localization Based on Ellipse Fitting Using Monocular Vision

by Shiwen Wu, Jianhua Wang, Xiang Zheng, Xianqiang Zeng and Gongxing Wu

J. Mar. Sci. Eng. 2025, 13(4), 733; https://doi.org/10.3390/jmse13040733 (registering DOI) - 6 Apr 2025

Abstract

Spherical buoys serve as water surface markers, and their location information can help unmanned surface vessels (USVs) identify navigation channel boundaries, avoid dangerous areas, and improve navigation accuracy. However, due to the presence of disturbances such as reflections, water obstruction, and changes in [...] Read more.

Spherical buoys serve as water surface markers, and their location information can help unmanned surface vessels (USVs) identify navigation channel boundaries, avoid dangerous areas, and improve navigation accuracy. However, due to the presence of disturbances such as reflections, water obstruction, and changes in illumination for spherical buoys on the water surface, using binocular vision for positioning encounters difficulties in matching. To address this, this paper proposes a monocular vision-based localization method for spherical buoys using elliptical fitting. First, the edges of the spherical buoy are extracted through image preprocessing. Then, to address the issue of pseudo-edge points introduced by reflections that reduce the accuracy of elliptical fitting, a multi-step method for eliminating pseudo-edge points is proposed. This effectively filters out pseudo-edge points and obtains accurate elliptical parameters. Finally, based on these elliptical parameters, a monocular vision ranging model is established to solve the relative position between the USV and the buoy. The USV’s position from satellite observation is then fused with the relative position calculated using the method proposed in this paper to estimate the coordinates of the buoy in the geodetic coordinate system. Simulation experiments analyzed the impact of pixel noise, camera height, focal length, and rotation angle on localization accuracy. The results show that within a range of 40 m in width and 80 m in length, the coordinates calculated by this method have an average absolute error of less than 1.2 m; field experiments on actual ships show that the average absolute error remains stable within 2.57 m. This method addresses the positioning issues caused by disturbances such as reflections, water obstruction, and changes in illumination, achieving a positioning accuracy comparable to that of general satellite positioning. Full article

(This article belongs to the Section Ocean Engineering)

30 pages, 7143 KiB

Open AccessArticle

Enabling Future Maritime Traffic Management: A Decentralized Architecture for Sharing Data in the Maritime Domain

by Dennis Höhn, Lorenz Mumm, Benjamin Reitz, Christina Tsiroglou and Axel Hahn

J. Mar. Sci. Eng. 2025, 13(4), 732; https://doi.org/10.3390/jmse13040732 (registering DOI) - 5 Apr 2025

Abstract

Digitalization is transforming the maritime sector, and the amount and variety of data generated is increasing rapidly. Effective data utilization is crucial for data-driven services such as for highly automated maritime systems and efficient traffic coordination. However, these applications depend on heterogeneous, distributed [...] Read more.

Digitalization is transforming the maritime sector, and the amount and variety of data generated is increasing rapidly. Effective data utilization is crucial for data-driven services such as for highly automated maritime systems and efficient traffic coordination. However, these applications depend on heterogeneous, distributed data sources managed by different actors, making secure and sovereign information sharing difficult. This paper investigates how maritime data can be exchanged reliably and securely without jeopardizing data sovereignty. Based on the existing literature, we identify the main challenges and current research gap in sharing maritime information, emphasizing the importance of data availability. From this, we derive requirements for a secure and sovereign infrastructure for data exchange. To address these challenges, we propose a fully decentralized architecture for the maritime sector based on the concept of a data space. Our approach integrates protocols to improve data availability while minimizing data volume, considering maritime constraints such as volatile connectivity, low bandwidth and existing standards. We evaluate our architecture through a maritime traffic management case study and demonstrate its ability to enable secure and sovereign exchange of heterogeneous data. The results confirm that our solution reliably supports distributed data collection and enables data-driven, value-added services, which in turn will improve the safety and efficiency of the maritime domain in the near future. Full article

(This article belongs to the Special Issue Advanced Research in Shipping Informatics and Communications—2nd Edition)

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27 pages, 3666 KiB

Open AccessArticle

Co-Optimization of the Hardware Configuration and Energy Management Parameters of Ship Hybrid Power Systems Based on the Hybrid Ivy-SA Algorithm

by Qian Guo, Zhihang Fu and Xingming Zhang

J. Mar. Sci. Eng. 2025, 13(4), 731; https://doi.org/10.3390/jmse13040731 (registering DOI) - 5 Apr 2025

Abstract

A ship’s diesel–electric hybrid power system is complex, with hardware configuration and energy management parameters being crucial to its economic performance. However, existing optimization methods typically involve designing and optimizing the hardware configuration on the basis of typical operating conditions, followed by the [...] Read more.

A ship’s diesel–electric hybrid power system is complex, with hardware configuration and energy management parameters being crucial to its economic performance. However, existing optimization methods typically involve designing and optimizing the hardware configuration on the basis of typical operating conditions, followed by the design and optimization of the energy management parameters, which makes it difficult to achieve optimal system performance. Moreover, when co-optimizing hardware configurations and energy management parameters, the parameter relationships and complex constraints often lead conventional optimization algorithms to converge slowly and become trapped in local optima. To address this issue, a hybrid Ivy-SA algorithm is developed for the co-optimization of both the hardware configuration and energy management parameters. First, the main engine and hybrid ship models are established on the basis of the hardware configuration, and the accuracy of the models is validated. An energy management strategy based on the equivalent fuel consumption minimization strategy (ECMS) is then formulated, and energy management parameters are designed. A sensitivity analysis is conducted on the basis of both the hardware configuration and energy management parameters to evaluate their impacts under various conditions, enabling the selection of key optimization parameters, such as diesel engine parameters, battery configuration, and charge/discharge factors. The Ivy-SA algorithm, which integrates the advantages of both the Ivy algorithm (IVYA) and the simulated annealing algorithm (SA), is developed for the co-optimization. The algorithm is tested with the CEC2017 benchmark functions and outperforms 11 other algorithms. Furthermore, when the top five performing algorithms are applied for the co-optimization, the results show that the Ivy-SA algorithm outperforms the other four algorithms with a 14.49% increase in economic efficiency and successfully escapes local optima. Full article

(This article belongs to the Special Issue Advanced Ship Technology Development and Design)

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23 pages, 8076 KiB

Open AccessArticle

Structural Assessment of Independent Type-C Liquid Hydrogen Fuel Tank

by Seung-Joo Cha, Hyun-Jin Tak, Byeong-Kwan Hwang, Jong-Pil Lee, Jeong-Hyeon Kim and Jae-Myung Lee

J. Mar. Sci. Eng. 2025, 13(4), 730; https://doi.org/10.3390/jmse13040730 (registering DOI) - 5 Apr 2025

Abstract

As environmental pollution has become a global concern, regulations on carbon emissions from maritime activities are being implemented, and interest in using renewable energy as fuel for ships is growing. Hydrogen, which does not release carbon dioxide and has a high energy density, [...] Read more.

As environmental pollution has become a global concern, regulations on carbon emissions from maritime activities are being implemented, and interest in using renewable energy as fuel for ships is growing. Hydrogen, which does not release carbon dioxide and has a high energy density, can potentially replace fossil fuels as a renewable energy source. Notably, storage of hydrogen in a liquid state is considered the most efficient. In this study, a 0.7 m³ liquid hydrogen fuel tank suitable for small vessels was designed, and a structural analysis was conducted to assess its structural integrity. The extremely low liquefaction temperature of hydrogen at −253 °C and the need for spatial efficiency in liquid hydrogen fuel tanks make vacuum insulation essential to minimize the heat transfer due to convection. A composite insulation system of sprayed-on foam insulation (SOFI) and multilayer insulation (MLI) was applied in the vacuum annular space between the inner and outer shells, and a tube-shaped supporter made of a G-11 cryogenic (CR) material with low thermal conductivity and high strength was employed. The material selected for the inner and outer layers of the tank was STS 316L, which exhibits sufficient ductility and strength at cryogenic temperatures and has low sensitivity to hydrogen embrittlement. The insulation performance was quantitatively assessed by calculating the boil-off rate (BOR) of the designed fuel tank. Structural integrity evaluations were conducted for nine load cases using heat transfer and structural analyses in accordance with the IGF code. Full article

(This article belongs to the Special Issue Green Shipping Corridors and GHG Emissions)

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13 pages, 4944 KiB

Open AccessArticle

Oil Spill Occurrence and Pollution Risk Assessment Based on Sea State, Oil Platform Location, and Shipping Route Density in the Bohai Sea

by Tao Liu, Ruichen Cao, Minxia Zhang, Xing Chen, Fan Bi and Jiangling Xu

J. Mar. Sci. Eng. 2025, 13(4), 729; https://doi.org/10.3390/jmse13040729 (registering DOI) - 5 Apr 2025

Abstract

The Bohai Sea is the only semi-enclosed inland sea in China. With active marine economic activities, it faces a persistently high risk of oil spill accidents. This study assesses the occurrence risk and pollution risk of oil spills by considering factors such as [...] Read more.

The Bohai Sea is the only semi-enclosed inland sea in China. With active marine economic activities, it faces a persistently high risk of oil spill accidents. This study assesses the occurrence risk and pollution risk of oil spills by considering factors such as sea state, the location of oil platform, and shipping route density in the Bohai Sea. The results show that the central part of the Bohai Sea, the southern Liaodong Peninsula, and the Bohai Strait area have a relatively high occurrence risk of oil spills due to busy maritime traffic and harsh sea conditions. In contrast, some areas in the northern, western, and southern parts of the Bohai Sea have a relatively low occurrence risk of oil spills because of weak maritime activity intensity and relatively calm sea state. In terms of the oil pollution risk, its distribution in the Bohai Sea shows significant seasonal characteristics, which are mainly comprehensively affected by multiple dynamic factors such as circulation, monsoon, and seawater exchange. Based on the oil pollution risk distribution, seasonally targeted strategies are proposed, which can provide a scientific basis for oil spill prevention and emergency management in the Bohai Sea, and help relevant departments formulate targeted prevention and control strategies. Full article

(This article belongs to the Section Physical Oceanography)

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32 pages, 6362 KiB

Open AccessArticle

Regression-Based Networked Virtual Buoy Model for Offshore Wave Height Prediction

by Eleonora M. Tronci, Matteo Vitale, Therese Patrosio, Thomas Søndergaard, Babak Moaveni and Usman Khan

J. Mar. Sci. Eng. 2025, 13(4), 728; https://doi.org/10.3390/jmse13040728 (registering DOI) - 5 Apr 2025

Abstract

Accurate wave height measurements are critical for offshore wind farm operations, marine navigation, and environmental monitoring. Wave buoys provide essential real-time data; however, their reliability is compromised by harsh marine conditions, resulting in frequent data gaps due to sensor failures, maintenance issues, or [...] Read more.

Accurate wave height measurements are critical for offshore wind farm operations, marine navigation, and environmental monitoring. Wave buoys provide essential real-time data; however, their reliability is compromised by harsh marine conditions, resulting in frequent data gaps due to sensor failures, maintenance issues, or extreme weather events. These disruptions pose significant risks for decision-making in offshore logistics and safety planning. While numerical wave models and machine learning techniques have been explored for wave height prediction, most approaches rely heavily on historical data from the same buoy, limiting their applicability when the target sensor is offline. This study addresses these limitations by developing a virtual wave buoy model using a network-based data-driven approach with Random Forest Regression (RFR). By leveraging wave height measurements from surrounding buoys, the proposed model ensures continuous wave height estimation even in the case of malfunctioning physical sensors. The methodology is tested across four offshore sites, including operational wind farms, evaluating the sensitivity of predictions to buoy placement and feature selection. The model demonstrates high accuracy and incorporates a k-nearest neighbors (kNN) imputation strategy to mitigate data loss. These findings establish RFR as a scalable and computationally efficient alternative for virtual sensing, thereby enhancing offshore wind farm resilience, marine safety, and operational efficiency. Full article

(This article belongs to the Section Ocean Engineering)

36 pages, 8652 KiB

Open AccessArticle

Investigation of Directionality Effect for 10 MW Monopile Offshore Wind Turbine Excited by Wind, Wave, and Earthquakes

by Renqiang Xi, Qingxuan Zhou, Yongqing Lai and Wanli Yu

J. Mar. Sci. Eng. 2025, 13(4), 727; https://doi.org/10.3390/jmse13040727 (registering DOI) - 5 Apr 2025

Abstract

Offshore wind turbines (OWTs) exhibit inherent directional variations in inertia, stiffness, and damping properties. This study examines the directionality effect of a 10 MW monopile-supported OWT using an integrated rotor-nacelle assembly (RNA) and support structure model. Through combined theoretical analysis and numerical simulations, [...] Read more.

Offshore wind turbines (OWTs) exhibit inherent directional variations in inertia, stiffness, and damping properties. This study examines the directionality effect of a 10 MW monopile-supported OWT using an integrated rotor-nacelle assembly (RNA) and support structure model. Through combined theoretical analysis and numerical simulations, this paper systematically investigates the following: (1) the anisotropic characteristics of RNA rotational inertia and blade stiffness, (2) the natural frequency and aerodynamic damping properties of the system, and (3) the directional mechanisms governing seismic responses of MOWTs during parked and running states. The key findings reveal substantial structural anisotropies. The second-order natural frequencies display a 15% disparity between fore–aft (1.43 Hz) and side–side (1.24 Hz) tower modes. The blade frequencies show over 50% differences between flap-wise (0.60 Hz/1.69 Hz) and edge-wise (0.91 Hz/2.71 Hz) modes in first-/second-order vibrations. Moreover, the aerodynamic damping ratios show marked directional contrast, with first-mode fore–aft damping (8%) exceeding side–side values (1.11%) by a factor of 7.2. Consequently, the seismic input directionality induces peak yaw-bearing bending moment variations of 38% (running condition) and 73% (parked condition). The directional effects in parked OWTs are attributed to RNA inertia anisotropy and blade stiffness disparities, while the running condition demonstrates combined influences from inherent system parameters (inertia, stiffness, aerodynamic damping) and wind–wave environmental loading. Full article

(This article belongs to the Section Coastal Engineering)

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27 pages, 106835 KiB

Open AccessArticle

Studying the Impact of the Load Distribution Ratio on the Unsteady Performance of a Dual-Stage Pump-Jet Propulsor

by Jiansheng Zhang, Ning Liang, Jianwei Zhang, Linlin Cao, Dazhuan Wu, Wei Zhao and Hanqiao Han

J. Mar. Sci. Eng. 2025, 13(4), 726; https://doi.org/10.3390/jmse13040726 (registering DOI) - 5 Apr 2025

Abstract

This study investigated the impact of different load distribution ratios between two rotors on the unsteady performance of dual-stage pump-jet propulsors using Computational Fluid Dynamics (CFDs) and experimental methods. The Shear Stress Transport (SST) k-ω model was employed to solve turbulence problems, and [...] Read more.

This study investigated the impact of different load distribution ratios between two rotors on the unsteady performance of dual-stage pump-jet propulsors using Computational Fluid Dynamics (CFDs) and experimental methods. The Shear Stress Transport (SST) k-ω model was employed to solve turbulence problems, and the numerical simulation method used was validated. The following conclusions were drawn: Different load distribution ratios of the dual-stage rotors have no significant impact on the overall propulsion performance of the propulsor. As the load distribution ratio is aft-shifted, the axial unsteady force of the entire propulsor continuously decreases, with a reduction of up to 53.6%. This is due to the gradual reduction in the energy of the first-stage rotor, leading to a more uniform Blade-Passing Frequency Velocity Harmonic Coefficient (BPFVHC) in front of the second-stage rotor, thereby gradually reducing the unsteady force of the second-stage rotor. The experimental results also indicate that the aft-shifted load model can reduce the sound pressure level of the propulsor. Compared to the prototype propulsor, the sound pressure level at the Blade-Passing Frequency decreases by 6.67 dB, or about 78.5%, in sound energy. This study has important implications for the low-excitation design of dual-stage pump-jet propulsors. Full article

(This article belongs to the Section Ocean Engineering)

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18 pages, 11293 KiB

Open AccessArticle

An Improved Real-Time LOS-Based Model Predictive Control for the Semi-Submersible Offshore Platform Under Ocean Disturbances

by Shunli Wang, Xiufen Ye, Ronghao Zhang and Meng Luo

J. Mar. Sci. Eng. 2025, 13(4), 725; https://doi.org/10.3390/jmse13040725 (registering DOI) - 4 Apr 2025

Abstract

To enhance the autonomy of semi-submersibles, a Model Predictive Control (MPC) strategy was proposed based on real-time Line-of-Sight (LOS) to address the issue of thruster saturation. By identifying parameters using experimental data from sea trials, the dynamic model of the semi-submersible was derived [...] Read more.

To enhance the autonomy of semi-submersibles, a Model Predictive Control (MPC) strategy was proposed based on real-time Line-of-Sight (LOS) to address the issue of thruster saturation. By identifying parameters using experimental data from sea trials, the dynamic model of the semi-submersible was derived and established. The kinematic and dynamic models were combined to construct a complete MPC prediction model, and the LOS method was integrated into the MPC strategy to achieve trajectory-tracking functionality. Unlike prior research that was validated exclusively through simulations, this paper further validated the efficacy of the improved LOS-MPC in real path tracking through a series of sea trials. The experimental findings indicate that the improved LOS-MPC approach is capable of rapidly guiding the semi-submersible to precisely follow the reference trajectory. In comparison to conventional PID controllers, the LOS-MPC-based path-tracking controller demonstrates enhanced effectiveness in terms of response speed, tracking accuracy, and robustness. Full article

(This article belongs to the Special Issue Underwater Robots)

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23 pages, 8962 KiB

Open AccessArticle

Parallel Net: Frequency-Decoupled Neural Network for DOA Estimation in Underwater Acoustic Detection

by Zhikai Yang, Xinyu Zhang, Zailei Luo, Tongsheng Shen, Mengda Cui and Xionghui Li

J. Mar. Sci. Eng. 2025, 13(4), 724; https://doi.org/10.3390/jmse13040724 - 4 Apr 2025

Abstract

Under wideband interference conditions, traditional neural networks often suffer from low accuracy in single-frequency direction-of-arrival (DOA) estimation and face challenges in detecting single-frequency sound sources. To address this limitation, we propose a novel model called Parallel Net. The architecture adopts a frequency-parallel [...] Read more.

Under wideband interference conditions, traditional neural networks often suffer from low accuracy in single-frequency direction-of-arrival (DOA) estimation and face challenges in detecting single-frequency sound sources. To address this limitation, we propose a novel model called Parallel Net. The architecture adopts a frequency-parallel design: it first employs a recurrent neural network, the generalized feedback gated recurrent unit (GFGRU), to independently extract features from each frequency component, and then it fuses these features through an attention mechanism. This design significantly enhances the network’s capability in estimating the DOA of single-frequency signals. The simulation results demonstrate that when the signal-to-noise ratio (SNR) exceeds −10 dB, Parallel Net achieves a mean absolute error (MAE) below 2°, outperforming traditional frequency-coherent neural networks and the MUSIC algorithm, and reduces the error to half that of classical beamforming (CBF). Further validation on the SWellEx-96 experiment confirms the model’s effectiveness in detecting single-frequency sources under wideband interference. Parallel Net exhibits superior sidelobe suppression and fewer spurious peaks compared to CBF, achieves higher accuracy than MUSIC, and produces smoother and more continuous DOA trajectories than conventional neural network models. Full article

(This article belongs to the Topic Advances in Underwater Acoustics and Aeroacoustics)

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25 pages, 14510 KiB

Open AccessArticle

Dynamic Analysis of Subsea Sediment Engineering Properties Based on Long-Term In Situ Observations in the Offshore Area of Qingdao

by Zhiwen Sun, Yanlong Li, Nengyou Wu, Zhihan Fan, Kai Li, Zhongqiang Sun, Xiaoshuai Song, Liang Xue and Yonggang Jia

J. Mar. Sci. Eng. 2025, 13(4), 723; https://doi.org/10.3390/jmse13040723 - 4 Apr 2025

Abstract

The drastic changes in the marine environment can induce the instability of seabed sediments, threatening the safety of marine engineering facilities such as offshore oil platforms, oil pipelines, and submarine optical cables. Due to the lack of long-term in situ observation equipment for [...] Read more.

The drastic changes in the marine environment can induce the instability of seabed sediments, threatening the safety of marine engineering facilities such as offshore oil platforms, oil pipelines, and submarine optical cables. Due to the lack of long-term in situ observation equipment for the engineering properties of seabed sediments, most existing studies have focused on phenomena such as the erosion suspension of the seabed boundary layer and wave-induced liquefaction, leading to insufficient understanding of the dynamic processes affecting the seabed environment. In this study, a long-term in situ observation system for subsea engineering geological environments was developed and deployed for 36 days of continuous monitoring in the offshore area of Qingdao. It was found that wave action significantly altered sediment mechanical properties, with a 5% sound velocity increase correlating to 39% lower compression, 7% higher cohesion, 11% greater internal friction angle, and 50% reduced excess pore water pressure at 1.0–1.8 m depth. suggesting sustained 2.2 m wave loads of expelled pore water, driving dynamic mechanical property variations in seabed sediments. This long-term in situ observation lays the foundation for the monitoring and early warning of marine engineering geological disasters. Full article

(This article belongs to the Special Issue Advances in Marine Gas Hydrate Exploration and Discovery—2nd Edition)

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25 pages, 9308 KiB

Open AccessArticle

A Multi-Spatial-Scale Ocean Sound Speed Profile Prediction Model Based on a Spatio-Temporal Attention Mechanism

by Shuwen Wang, Ziyin Wu, Shuaidong Jia, Dineng Zhao, Jihong Shang, Mingwei Wang, Jieqiong Zhou and Xiaoming Qin

J. Mar. Sci. Eng. 2025, 13(4), 722; https://doi.org/10.3390/jmse13040722 (registering DOI) - 3 Apr 2025

Abstract

Marine researchers rely heavily on ocean sound velocity, a crucial hydroacoustic environmental metric that exhibits large geographical and temporal changes. Nowadays, spatio-temporal series prediction algorithms are emerging, but their prediction accuracy requires improvement. Moreover, in terms of ocean sound speed, most of these [...] Read more.

Marine researchers rely heavily on ocean sound velocity, a crucial hydroacoustic environmental metric that exhibits large geographical and temporal changes. Nowadays, spatio-temporal series prediction algorithms are emerging, but their prediction accuracy requires improvement. Moreover, in terms of ocean sound speed, most of these models predict an ocean sound speed profile (SSP) at a single coordinate position, and only a few predict multi-spatial-scale SSPs. Hence, this paper proposes a new data-driven method called STA-Conv-LSTM that combines convolutional long short-term memory (Conv-LSTM) and spatio-temporal attention (STA) to predict SSPs. We used a 234-month dataset of monthly mean sound speeds in the eastern Pacific Ocean from January 2004 to June 2023 to train the prediction model. We found that using 24 months of SSPs as the inputs to predict the SSPs of the following month yielded the highest accuracy. The results demonstrate that STA-Conv-LSTM can achieve predictions with an accuracy of more than 95% for both single-point and three-dimensional scenarios. We compared it against recurrent neural network, LSTM, and Conv-LSTM models with optimal parameter settings to demonstrate the model’s superiority. With a fitting accuracy of 95.12% and the lowest root-mean-squared error of 0.8978, STA-Conv-LSTM clearly outperformed the competition with respect to prediction accuracy and stability. This model not only predicts SSPs well but also will improve the spatial and temporal forecasts of other marine environmental factors. Full article

(This article belongs to the Special Issue Underwater Acoustic Field Modulation Technology)

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59 pages, 7782 KiB

Open AccessReview

Research Progress of Fuel Cell Technology in Marine Applications: A Review

by Zheng Zhang, Xiangxiang Zheng, Daan Cui, Min Yang, Mojie Cheng and Yulong Ji

J. Mar. Sci. Eng. 2025, 13(4), 721; https://doi.org/10.3390/jmse13040721 - 3 Apr 2025

Abstract

With the increasing severity of global environmental issues and the pressure from the strict pollutant emission regulations proposed by the International Maritime Organization (IMO), the shipping industry is seeking new types of marine power systems that can replace traditional propulsion systems. Marine fuel [...] Read more.

With the increasing severity of global environmental issues and the pressure from the strict pollutant emission regulations proposed by the International Maritime Organization (IMO), the shipping industry is seeking new types of marine power systems that can replace traditional propulsion systems. Marine fuel cells, as an emerging energy technology, only emit water vapor or a small amount of carbon dioxide during operation, and have received widespread attention in recent years. However, research on their application in the shipping industry is relatively limited. Therefore, this paper collects relevant reports and literature on the use of fuel cells on ships over the past few decades, and conducts a thorough study of typical fuel cell-powered vessels. It summarizes and proposes current design schemes and optimization measures for marine fuel cell power systems, providing directions for further improving battery performance, reducing carbon emissions, and minimizing environmental pollution. Additionally, this paper compares and analyzes marine fuel cells with those used in automotive, aviation, and locomotive applications, offering insights and guidance for the development of marine fuel cells. Although hydrogen fuel cell technology has made significant progress in recent years, issues still exist regarding hydrogen production, storage, and related safety and standardization concerns. In terms of comprehensive performance and economics, it still cannot effectively compete with traditional internal combustion engines. However, with the continued rapid development of fuel cell technology, marine fuel cells are expected to become a key driver for promoting green shipping and achieving carbon neutrality goals. Full article

(This article belongs to the Special Issue Marine Fuel Cell Technology: Latest Advances and Prospects)

25 pages, 10092 KiB

Open AccessArticle

A New Energy Management Strategy Supported by Reinforcement Learning: A Case Study of a Multi-Energy Cruise Ship

by Xiaodong Guo, Daogui Tang, Yupeng Yuan, Chengqing Yuan, Boyang Shen and Josep M. Guerrero

J. Mar. Sci. Eng. 2025, 13(4), 720; https://doi.org/10.3390/jmse13040720 (registering DOI) - 3 Apr 2025

Abstract

Hybrid ships offer significant advantages in energy efficiency and environmental sustainability. However, their complex structures present challenges in developing effective energy management strategies to ensure optimal power distribution and stable, efficient operation of the power system. This study establishes a mathematical model of [...] Read more.

Hybrid ships offer significant advantages in energy efficiency and environmental sustainability. However, their complex structures present challenges in developing effective energy management strategies to ensure optimal power distribution and stable, efficient operation of the power system. This study establishes a mathematical model of a hybrid system for a specific ship and proposes an energy management strategy based on the deep deterministic policy gradient (DDPG) algorithm, a reinforcement learning technique. The proposed strategy’s feasibility and effectiveness are validated through comparisons with alternative energy management strategies and real-world ship data. Simulation results demonstrate that the DDPG-based strategy optimizes the diesel engine’s operating conditions and reduces total fuel consumption by 3.6% compared to a strategy based on the deep Q-network (DQN) algorithm. Full article

(This article belongs to the Section Ocean Engineering)

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28 pages, 6479 KiB

Open AccessReview

Current Status of Bibliometrics-Based Research on Measurement and Communication Technology for Space Tracking Ships

by Haoyu Jiang, Yunsheng Ma, Shengqing Zeng, Yutao Tian and Dapeng Zhang

J. Mar. Sci. Eng. 2025, 13(4), 719; https://doi.org/10.3390/jmse13040719 - 3 Apr 2025

Abstract

Space tracking ships are critical assets in modern space exploration, overcoming the limitations of land-based tracking systems by providing real-time telemetry, trajectory monitoring, and communication support for satellites and spacecraft. However, the existing literature offers limited insights into the historical development, technological evolution, [...] Read more.

Space tracking ships are critical assets in modern space exploration, overcoming the limitations of land-based tracking systems by providing real-time telemetry, trajectory monitoring, and communication support for satellites and spacecraft. However, the existing literature offers limited insights into the historical development, technological evolution, and collaborative research trends of these specialized vessels. This study employs a bibliometric analysis using CiteSpace (6.3.R1) to identify research trends, highlight key technological advancements, and assess international collaboration. By analyzing publications from major contributors, including the United States, the former Soviet Union, France, and China, the paper reveals technological innovations such as advancements in measurement systems, communication technologies, and the integration of artificial intelligence (AI) for enhanced tracking precision. Structural and operational analyses emphasize the importance of design factors, including ship dimensions and internal systems, for ensuring optimal performance in challenging maritime environments. The findings highlight evolving technological priorities and persistent gaps in international collaboration, suggesting opportunities for global partnerships to advance the field. This study bridges historical and technical gaps, providing valuable insights for enhancing the efficiency and strategic relevance of space tracking ships in future space exploration missions. Full article

(This article belongs to the Special Issue Advanced Research in Shipping Informatics and Communications—2nd Edition)

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19 pages, 4737 KiB

Open AccessArticle

A Novel Reactive Power Sharing Control Strategy for Shipboard Microgrids Based on Deep Reinforcement Learning

by Wangyang Li, Hong Zhao, Jingwei Zhu and Tiankai Yang

J. Mar. Sci. Eng. 2025, 13(4), 718; https://doi.org/10.3390/jmse13040718 - 3 Apr 2025

Abstract

Reactive power sharing in distributed generators (DGs) is one of the key issues in the control technologies of greenship microgrids. Reactive power imbalance in ship microgrids can cause instability and potential equipment damage. In order to improve the poor performance of the traditional [...] Read more.

Reactive power sharing in distributed generators (DGs) is one of the key issues in the control technologies of greenship microgrids. Reactive power imbalance in ship microgrids can cause instability and potential equipment damage. In order to improve the poor performance of the traditional adaptive droop control methods used in microgrids under high-load conditions and influenced by virtual impedance parameters, this paper proposes a novel strategy based on the deep reinforcement learning DQN-VI, in which a deep Q network (DQN) is combined with the virtual impedance (VI) method. Unlike traditional methods which may use static or heuristically adjusted VI parameters, the DQN-VI strategy employs deep reinforcement learning to dynamically optimize these parameters, enhancing the microgrid’s performance under varying conditions. The proposed DQN-VI strategy considers the current situation in greenships, wherein microgrids are generally equipped with cables of different lengths and measuring the impedance of each cable is challenging due to the lack of space. By modeling the control process as a Markov decision process, the observation space, action space, and reward function are designed. In addition, a deep neural network is used to estimate the Q function that describes the relationship between the state and the action. During the training of the DQN agent, the process is optimized step-by-step by observing the state and rewards of the system, thereby effectively improving the performance of the microgrids. The comparative simulation experiments verify the effectiveness and superiority of the proposed strategy. Full article

(This article belongs to the Special Issue Optimization and Control of Marine Renewable Energy Systems)

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24 pages, 10936 KiB

Open AccessArticle

Surface Current Observations in the Southeastern Tropical Indian Ocean Using Drifters

by Prescilla Siji and Charitha Pattiaratchi

J. Mar. Sci. Eng. 2025, 13(4), 717; https://doi.org/10.3390/jmse13040717 - 3 Apr 2025

Abstract

The Southeastern Tropical Indian Ocean (SETIO) forms part of the global ocean conveyor belt and thermohaline circulation that has a significant influence in controlling the global climate. This region of the ocean has very few observations using surface drifters, and this study presents, [...] Read more.

The Southeastern Tropical Indian Ocean (SETIO) forms part of the global ocean conveyor belt and thermohaline circulation that has a significant influence in controlling the global climate. This region of the ocean has very few observations using surface drifters, and this study presents, for the first time, paths of satellite tracked drifters released in the Timor Sea (123.3° E, 13.8° S). The drifter data were used to identify the ocean dynamics, forcing mechanisms and connectivity in the SETIO region. The data set has high temporal (~5 min) and spatial (~120 m) resolution and were collected over an 8-month period between 17 September 2020 and 25 May 2021. At the end of 250 days, drifters covered a region separated by ~8000 km (83–137° E, 4–21° S) and transited through several forcing mechanisms including semidiurnal and diurnal tides, submesoscale and mesoscale eddies, channel and headland flows, and inertial currents generated by tropical storms. Initially, all the drifters moved as a single cluster, and at 120° E longitude they entered a region of high eddy kinetic energy defined here as the ‘SETIO Mixing Zone’ (SMZ), and their movement was highly variable. All the drifters remained within the SMZ for periods between 3 and 5 months. Exiting the SMZ, drifters followed the major ocean currents in the system (either South Java or South Equatorial Current). Two of the drifters moved north through Lombok and Sape Straits and travelled to the east as far as Aru Islands. The results of this study have many implications for connectivity and transport of buoyant materials (e.g., plastics), as numerical models do not have the ability to resolve many of the fine-scale physical processes that contribute to surface transport and mixing in the ocean. Full article

(This article belongs to the Special Issue Monitoring of Ocean Surface Currents and Circulation)

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