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), GeoRef, Inspec, AGRIS, and other databases.
- Journal Rank: JCR - Q1 (Engineering, Marine) / CiteScore - Q2 (Ocean Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 15.4 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the second half of 2023).
- 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.
Impact Factor:
2.9 (2022);
5-Year Impact Factor:
2.9 (2022)
Latest Articles
EF-UODA: Underwater Object Detection Based on Enhanced Feature
J. Mar. Sci. Eng. 2024, 12(5), 729; https://doi.org/10.3390/jmse12050729 (registering DOI) - 27 Apr 2024
Abstract
The ability to detect underwater objects accurately is important in marine environmental engineering. Although many kinds of underwater object detection algorithms with relatively high accuracy have been proposed, they involve a large number of parameters and floating point operations (FLOPs), and often fail
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The ability to detect underwater objects accurately is important in marine environmental engineering. Although many kinds of underwater object detection algorithms with relatively high accuracy have been proposed, they involve a large number of parameters and floating point operations (FLOPs), and often fail to yield satisfactory results in complex underwater environments. In light of the demand for an algorithm with the capability to extract high-quality features in complex underwater environments, we proposed a one-stage object detection algorithm called the enhanced feature-based underwater object detection algorithm (EF-UODA), which was based on the architecture of Next-ViT, the loss function of YOLOv8, and Ultralytics. First, we developed a highly efficient module for convolutions, called efficient multi-scale pointwise convolution (EMPC). Second, we proposed a feature pyramid architecture called the multipath fast fusion-feature pyramid network (M2F-FPN) based on different modes of feature fusion. Finally, we integrated the Next-ViT and the minimum point distance intersection over union loss functions in our proposed algorithm. Specifically, on the URPC2020 dataset, EF-UODA surpasses the state-of-the-art (SOTA) convolution-based object detection algorithm YOLOv8X by 2.9% mean average precision (mAP), and surpasses the SOTA ViT-based object detection algorithm real-time detection transformer (RT-DETR) by 2.1%. Meanwhile, it achieves the lowest FLOPs and parameters. The results of extensive experiments showed that EF-UODA had excellent feature extraction capability, and was adequately balanced in terms of the number of FLOPs and parameters.
Full article
(This article belongs to the Special Issue Underwater Engineering and Image Processing)
Open AccessArticle
A Time-Domain Wavenumber Integration Model for Underwater Acoustics Based on the High-Order Finite Difference Method
by
Xiang Xu, Wei Liu and Guojun Xu
J. Mar. Sci. Eng. 2024, 12(5), 728; https://doi.org/10.3390/jmse12050728 (registering DOI) - 27 Apr 2024
Abstract
Simulating the acoustic field excited by pulse sound sources holds significant practical value in computational ocean acoustics. Two primary methods exist for modeling underwater acoustic propagation in the time domain: the Fourier synthesis technique based on frequency decomposition and the time-domain underwater acoustic
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Simulating the acoustic field excited by pulse sound sources holds significant practical value in computational ocean acoustics. Two primary methods exist for modeling underwater acoustic propagation in the time domain: the Fourier synthesis technique based on frequency decomposition and the time-domain underwater acoustic propagation model (TD-UAPM). TD-UAPMs solve the wave equation in the time domain without requiring frequency decomposition, providing a more intuitive explanation of the physical process of sound energy propagation over time. However, time-stepping numerical methods can accumulate numerical errors, making it crucial to improve the algorithm’s accuracy for TD-UAPMs. Herein, the time-domain wavenumber integration model SPARC was improved by replacing the second-order finite element method (FEM) with the high-order accuracy finite difference method (FDM). Furthermore, the matched interface and boundary (MIB) method was used to process the seabed more accurately. The improved model was validated using three classic underwater acoustic benchmarks. By comparing the acoustic solutions obtained using the FDM and the FEM, it is evident that the improved model requires fewer grid points while maintaining the same level of accuracy, leading to lower computational costs and faster processing compared to the original model.
Full article
Open AccessArticle
Identification of Fish Hunger Degree with Deformable Attention Transformer
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Yuqiang Wu, Huanliang Xu, Xuehui Wu, Haiqing Wang and Zhaoyu Zhai
J. Mar. Sci. Eng. 2024, 12(5), 726; https://doi.org/10.3390/jmse12050726 (registering DOI) - 27 Apr 2024
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Feeding is a critical process in aquaculture, as it has a direct impact on the quantity and quality of fish. With advances in convolutional neural network (CNN) and vision transformer (ViT), intelligent feeding has been widely adopted in aquaculture, as the real-time monitoring
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Feeding is a critical process in aquaculture, as it has a direct impact on the quantity and quality of fish. With advances in convolutional neural network (CNN) and vision transformer (ViT), intelligent feeding has been widely adopted in aquaculture, as the real-time monitoring of fish behavior can lead to better feeding decisions. However, existing models still have the problem of insufficient accuracy in the fish behavior-recognition task. In this study, the largemouth bass (Micropterus salmoides) was selected as the research subject, and three categories (weakly, moderately, and strongly hungry) were defined. We applied the deformable attention to the vision transformer (DeformAtt-ViT) to identify the fish hunger degree. The deformable attention module was extremely powerful in feature extraction because it improved the fixed geometric structure of the receptive fields with data-dependent sparse attention, thereby guiding the model to focus on more important regions. In the experiment, the proposed DeformAtt-ViT was compared with the state-of-the-art transformers. Among them, DeformAtt-ViT achieved optimal performance in terms of accuracy, F1-score, recall, and precision at 95.50%, 94.13%, 95.87%, and 92.45%, respectively. Moreover, a comparative evaluation between DeformAtt-ViT and CNNs was conducted, and DeformAtt-ViT still dominated the others. We further visualized the important pixels that contributed the most to the classification result, enabling the interpretability of the model. As a prerequisite for determining the feed time, the proposed DeformAtt-ViT could identify the aggregation level of the fish and then trigger the feeding machine to be turned on. Also, the feeding machine will stop working when the aggregation disappears. Conclusively, this study was of great significance, as it explored the field of intelligent feeding in aquaculture, enabling precise feeding at a proper time.
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Open AccessArticle
Research on the Influencing Factors of AUV Hovering Control in Null-Speed State
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Jianguo Wang, Chunmeng Jiang, Lei Wan, Yimei Zhou, Gangyi Hu, Xide Cheng and Gongxing Wu
J. Mar. Sci. Eng. 2024, 12(5), 725; https://doi.org/10.3390/jmse12050725 (registering DOI) - 27 Apr 2024
Abstract
Intelligent underwater vehicles hover by way of a hovering control system. To provide design inputs and maneuver guidance, this study focused on the characteristics of intelligent underwater vehicles during hovering control with the propulsion system shut down, established a mathematical model of hovering
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Intelligent underwater vehicles hover by way of a hovering control system. To provide design inputs and maneuver guidance, this study focused on the characteristics of intelligent underwater vehicles during hovering control with the propulsion system shut down, established a mathematical model of hovering control and determined injection and drainage functions based on optimal control theory. From analysis simulation experiments, the influence laws of control parameters, control timing and rate of injection and drainage control upon hovering control were deduced. It is proposed that, at the time of control parameter selection, the continuous injection and drainage rate at each time should be reduced as far as possible to relieve the demand on the volume of the reservoir when the requirement of depth control accuracy has been satisfied. In addition, the injection and drainage control should initiate when depth changes exceed 0.5 m. Suggestions are included on the minimum injection and drainage rate required for different initial disturbances. The proposed suggestions guide the design of hovering control systems and hovering control over intelligent underwater vehicles.
Full article
(This article belongs to the Special Issue Unmanned Marine Vehicles: Navigation, Control and Sensing)
Open AccessArticle
Estimation of Mariculture Carbon Sinks in China and Its Influencing Factors
by
Simiao Guo and Hongtao Nie
J. Mar. Sci. Eng. 2024, 12(5), 724; https://doi.org/10.3390/jmse12050724 (registering DOI) - 27 Apr 2024
Abstract
The scientific assessment of mariculture carbon sinks is crucial to recognize its potential as a significant component of marine blue carbon in global climate change mitigation. Therefore, the objective of the research was to estimate the seaweed and shellfish mariculture carbon sink of
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The scientific assessment of mariculture carbon sinks is crucial to recognize its potential as a significant component of marine blue carbon in global climate change mitigation. Therefore, the objective of the research was to estimate the seaweed and shellfish mariculture carbon sink of different varieties in various sea areas. The paper emphasized the distinction between short-term carbon sequestration in seaweed and shellfish that can be removed and long-term carbon sequestration that is deposited. Methodologically, the evaluation was based on the carbon sequestration mechanism and systematic pathways in shellfish and seaweeds. Additionally, the carbon sequestration of shellfish and seaweed aquaculture over the last decade was evaluated by the carbon sink assessment model, and the reasons for the differences in the carbon sink capacity of mariculture in China’s coastal provinces were discussed by using the LMDI decomposition model. The results indicated the carbon sequestration of offshore seaweeds and shellfish mariculture in China was huge. From 2010 to 2020, offshore seaweed aquaculture in China amounted to 7.959 Mt C/a, while shellfish aquaculture contributed 33.542 Mt C/a to the carbon sinks. Sedimentary carbon sequestration by shellfish accounted for 51% of the total carbon sequestration in mariculture involving shellfish and seaweeds. Especially noteworthy is the sedimentary carbon sequestration by shellfish, which is an indispensable and crucial component of mariculture carbon sequestration estimation. It is concluded that improvements in farming efficiency exerted the greatest influence on the variations of the mariculture carbon sink, while adjustments in farming structure had a relatively minor impact in the case of little change in aquaculture yield. Enhancing farming efficiency emerges as a practical approach to bolstering the carbon sink potential of marine aquaculture fisheries in the future.
Full article
(This article belongs to the Section Marine Aquaculture)
Open AccessArticle
Temperature Structure Inversion of Mesoscale Eddies in the South China Sea Based on Deep Learning
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Jidong Huo, Jungang Yang, Liting Geng, Guangliang Liu, Jie Zhang, Jichao Wang and Wei Cui
J. Mar. Sci. Eng. 2024, 12(5), 723; https://doi.org/10.3390/jmse12050723 (registering DOI) - 27 Apr 2024
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Mesoscale eddies are common in global oceans, playing crucial roles in ocean dynamics, ocean circulation, and heat transport, and their vertical structures can affect the water layers from tens to thousands of meters. In this study, we integrated sea surface height and sea
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Mesoscale eddies are common in global oceans, playing crucial roles in ocean dynamics, ocean circulation, and heat transport, and their vertical structures can affect the water layers from tens to thousands of meters. In this study, we integrated sea surface height and sea surface temperature data into deep learning methods to study the mesoscale eddy subsurface temperature structure and to explore the relationship between sea surface data and eddy subsurface layers. In this study, we introduce Dual_EddyNet, a deep learning algorithm designed to invert the subsurface temperature structure of mesoscale eddies. Using this algorithm, we explore the impact of the sea surface height and sea surface temperature on the subsurface temperature structure inversion of mesoscale eddies. Furthermore, we compare different data fusion strategies, namely single-stream neural networks and dual-stream neural networks, to validate the effectiveness of the dual-stream model. To capture the interrelations among surface data and integrate feature information across various dimensions, we introduce the Triplet Attention Mechanism. The experimental results demonstrate that the proposed Dual_EddyNet performs well in reconstructing the three-dimensional structure of mesoscale eddies in the South China Sea (within a depth of 1000 m), with an inversion accuracy of 91.44% for cyclonic eddies and 95.25% for anticyclonic eddies. This algorithm provides a new method for inverting the subsurface temperatures of mesoscale eddies, and can not only be directly deployed in systems, embedded in ship moving platforms, etc., but can also provide a data reference for assimilations and numerical simulations, demonstrating its rich application potential.
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Open AccessArticle
Latent Heat Flux Trend and Its Seasonal Dependence over the East China Sea Kuroshio Region
by
Chengji Chen and Qiang Wang
J. Mar. Sci. Eng. 2024, 12(5), 722; https://doi.org/10.3390/jmse12050722 - 26 Apr 2024
Abstract
Investigating latent heat flux (LHF) variations in the western boundary current region is crucial for understanding air–sea interactions. In this study, we examine the LHF trend in the East China Sea Kuroshio Region (ECSKR) from 1959 to 2021 using atmospheric and oceanic reanalysis
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Investigating latent heat flux (LHF) variations in the western boundary current region is crucial for understanding air–sea interactions. In this study, we examine the LHF trend in the East China Sea Kuroshio Region (ECSKR) from 1959 to 2021 using atmospheric and oceanic reanalysis datasets and find that the LHF has a significant strengthening trend. This strengthening can be attributed to sea surface warming resulting from the advection of sea surface temperatures. More importantly, the LHF trend has an apparent seasonal dependence: the most substantial increasing trend in LHF is observed in spring, while the trends are weak in other seasons. Further analysis illustrates that the anomaly of air–sea humidity difference plays a pivotal role in controlling the seasonal variations in LHF trends. Specifically, as a result of the different responses of the East Asian Trough to global warming across different seasons, during spring, the East Asian Trough significantly deepens, resulting in northerly winds that facilitate the intrusion of dry and cold air into the ECSKR region. This intensifies the humidity difference between the sea and air, promoting the release of oceanic latent heat. These findings can contribute to a better understanding of the surface heat budget balance within western boundary currents.
Full article
(This article belongs to the Special Issue Air-Sea Interaction and Marine Dynamics)
Open AccessArticle
Spacing Ratio Effects on the Evolution of the Flow Structure of Two Tandem Circular Cylinders in Proximity to a Wall
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Xiang Qiu, Xuezhi Ji, Jiankang Zhou, Jiahua Li, Yizhou Tao and Yulu Liu
J. Mar. Sci. Eng. 2024, 12(5), 721; https://doi.org/10.3390/jmse12050721 - 26 Apr 2024
Abstract
The flow around two tandem circular cylinders in proximity to a wall is investigated using particle image velocimetry (PIV) for Re = 2 × 103. The spacing ratios L/D are 1, 2, and 5, and the gap ratios G
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The flow around two tandem circular cylinders in proximity to a wall is investigated using particle image velocimetry (PIV) for Re = 2 × 103. The spacing ratios L/D are 1, 2, and 5, and the gap ratios G/D are 0.3, 0.6, and 1. The proper orthogonal decomposition (POD) method and λci vortex identification method are used to investigate the evolution of flow structure, and the influences of L/D and G/D on flow physics are shown. At L/D = 2 and G/D = 0.3, a “pairing” process occurs between the wall shear layer and the upstream cylinder’s lower shear layer, resulting in a small separation bubble behind the upstream cylinder. At L/D = 1, the Strouhal number (St) increases with decreasing G/D. At three gap ratios, the St gradually decreases as L/D increases. At G/D = 0.3, there is nearly a 49.98% decrease from St = 0.3295 at L/D = 1 to St = 0.1648 at L/D = 5, which is larger than the reductions in cases of G/D = 0.6 and G/D = 1. The effects of L/D on the evolution of flow structure at G/D = 0.6 are revealed in detail. At L/D = 1, the vortex shedding resembles that of the single cylinder. As L/D increases to 2, a squarish flow structure is formed between two cylinders, and a small secondary vortex is formed due to induction of the lower shear layer of the upstream cylinder. At L/D = 5, there is a vortex merging process between the upper wake vortices of the upstream and downstream cylinders, and the lower wake vortex of the upstream cylinder directly impinges the downstream cylinder. In addition, the shear layers and wake vortices of the upstream cylinder interact with the wake of the downstream cylinder as L/D increases, resulting in reductions in velocity fluctuations, and the production and turbulent diffusion of turbulent kinetic energy are decreased behind the downstream cylinder.
Full article
(This article belongs to the Section Ocean Engineering)
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Open AccessArticle
Local Path Planning Method for Unmanned Ship Based on Encounter Situation Inference and COLREGS Constraints
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Gang Wang, Jingheng Wang, Xiaoyuan Wang, Quanzheng Wang, Longfei Chen, Junyan Han, Bin Wang and Kai Feng
J. Mar. Sci. Eng. 2024, 12(5), 720; https://doi.org/10.3390/jmse12050720 - 26 Apr 2024
Abstract
Local path planning, as an essential technology to ensure intelligent ships’ safe navigation, has attracted the attention of many scholars worldwide. In most existing studies, the impact of COLREGS has received limited consideration, and there is insufficient exploration of the method in complex
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Local path planning, as an essential technology to ensure intelligent ships’ safe navigation, has attracted the attention of many scholars worldwide. In most existing studies, the impact of COLREGS has received limited consideration, and there is insufficient exploration of the method in complex waters with multiple interfering ships and static obstacles. Therefore, in this paper, a generation method for a time–space overlapping equivalent static obstacle line for ships in multi-ship encounter scenarios where both dynamic and static obstacles coexist is proposed. By dynamically inferring ships’ encounter situations and considering the requirements of COLREGS, the influence of interfering ships and static obstacles on the navigation of the target ship at different times in the near future is represented as static obstacle lines. These lines are then incorporated into the scene that the target ship encountered at the path planning moment. Subsequently, the existing path planning methods were extensively utilized to obtain the local path. Compared with many common path planning methods in random scenarios, the effectiveness and reliability of the method proposed are verified. It has been demonstrated by experimental results that the proposed method can offer a theoretical basis and technical support for the autonomous navigation of unmanned ships.
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(This article belongs to the Section Ocean Engineering)
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Open AccessArticle
Study on the Flame Transition Characteristics of a Gas Turbine Combustor
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Mingmin Chen, Li Wang, Xinbo Huang, Minwei Zhao, Lingwei Zeng, Hongtao Zheng and Fuquan Deng
J. Mar. Sci. Eng. 2024, 12(5), 719; https://doi.org/10.3390/jmse12050719 - 26 Apr 2024
Abstract
Gas turbines are widely used as important equipment for electricity generation on islands and offshore platforms. During the operation of a gas turbine, the flame shape in the combustion chamber undergoes variations in response to changes in parameters such as gas turbine load,
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Gas turbines are widely used as important equipment for electricity generation on islands and offshore platforms. During the operation of a gas turbine, the flame shape in the combustion chamber undergoes variations in response to changes in parameters such as gas turbine load, fuel distribution, and burner structure. These alterations in flame shape exert influence on combustion instability, emissions, and load characteristics. This study explores the variations in flame transition, emissions, and operating parameters among three distinct center stage structures: namely, the non-premix center stage (NPCS), premix center stage (PCS), and enhanced premix center stage (PCSE). The investigation is conducted using a heavy-duty gas turbine hybrid burner on a full temperature, full pressure, and full-size single burner experimental bench. Simultaneously, a multi-parameter numerical simulation regarding the influence of the central fuel split on flame shape analysis was conducted using the PCS burner under the design point for a more in-depth understanding of the mechanisms and for influencing factors associated with flame transition. The findings indicate that variations in flame transition loads among different central stage structures: for the NPCS burner, the transition occurs between 45% and 50% load; for the PCS burners, it takes place between 60% and 65% load; for the PCSE burners, it shifts between 55% and 60% load. Additionally, a reduction in NOx emissions is observed during the flame transition process. Furthermore, it was found that decreasing the central stage fuel results in a decline in flame angle for the same burner structure. As the central stage fuel diminishes to a specific value, the flame shape undergoes a sudden change. Further reduction in central stage fuel does not significantly affect the flame shape and temperature distribution.
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(This article belongs to the Topic Marine Renewable Energy, 2nd Volume)
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Open AccessArticle
The High-Resolution Interannual Evolution of the Dune Toe at a Mesotidal Barrier (Camposoto Beach, SW Spain)
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Cristina Montes, Javier Benavente, María Puig, Juan Montes, Lara Talavera and Theocharis A. Plomaritis
J. Mar. Sci. Eng. 2024, 12(5), 718; https://doi.org/10.3390/jmse12050718 - 26 Apr 2024
Abstract
Over recent years, processes related to marine storms, sediment shortages and human intervention have caused the global retreat of many coastal systems and the degradation of their dunes. In this context, changes in the dune toe are commonly used as a proxy to
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Over recent years, processes related to marine storms, sediment shortages and human intervention have caused the global retreat of many coastal systems and the degradation of their dunes. In this context, changes in the dune toe are commonly used as a proxy to study the interannual shoreline evolution, and it is usually analyzed using orthophotography, while high temporal- and spatial-scale resolution studies of dune toe evolution are not frequent. In this work, a quasi-monthly study of dune toe data was carried out between 2008 and 2018. These data, taken from the RTK-DGPS and UAS systems, were subjected to shoreline analysis, and they showed an average regression rate of −2.30 m/year, a higher value than the one registered until 2008 (1 m/year). This suggests an acceleration in the erosion suffered within the system, which was revealed to be more intense in the northern sector of the study area. Dune toe variability increased over the years, probably due to the presence of washover fans breaking the foredune that were reactivated and expanded during storm events. The ephemeral progradation of the dune toe was also noted, which could be explained with reference to wind events and/or beach nourishment that had been carried out over the studied period. From the analysis of the dune toe elevation, a decrease in this variable was obtained, especially in the areas affected due to washover fans. This finding is supported by the significant correlation of the dune toe elevation and erosion trend, suggesting that the areas where the dune toe was lower are prone to suffering a greater retreat. This correlation provides insight into the future evolution of the barrier, suggesting a state of degradation and a transition to a lower-resilience state.
Full article
(This article belongs to the Special Issue Learning from Geomorphological Adaptation of Coasts at Different Time Scales)
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Open AccessArticle
Fuzzy Logic-Based Decision-Making Method for Ultra-Large Ship Berthing Using Pilotage Data
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Yibo Li, Guobin Song, Tsz-Leung Yip and Gi-Tae Yeo
J. Mar. Sci. Eng. 2024, 12(5), 717; https://doi.org/10.3390/jmse12050717 - 26 Apr 2024
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As seafarers are involved in Maritime Autonomous Surface Ships (MASS), except for those in the fourth level of autonomy, the decision making of autonomous berthing should be carried out and be understood by human beings. This paper proposes a fuzzy logic-based human-like decision-making
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As seafarers are involved in Maritime Autonomous Surface Ships (MASS), except for those in the fourth level of autonomy, the decision making of autonomous berthing should be carried out and be understood by human beings. This paper proposes a fuzzy logic-based human-like decision-making method for ultra-large ship berthing, which considers locations, ship particulars and the natural environment, and these factors are treated as the input variables. The IF–THEN rules are then established after the fuzzification of the input variables and are used for fuzzy inference to derive the decision of ship handling. It can be implemented in the decision-making system for safe navigation or be included in the process of autonomous berthing. The pilotage data are collected with nautical instruments and a distance measurement system during the berthing process, which are used to validate the proposed model and calculate the speed and turn errors. The overall and individual error of the decision-making model is in a reasonable and small range, which indicates that the model has good accuracy. The results of this research offer theoretical and practical insights into the development of a human-like decision-making method for autonomous navigation in port waters and maritime safety management in the shipping industry. The model can be further applied to develop a more widely applicable decision-making system for autonomous navigation in confined waters.
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Open AccessArticle
An Underwater Localization Method Based on Visual SLAM for the Near-Bottom Environment
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Zonglin Liu, Meng Wang, Hanwen Hu, Tong Ge and Rui Miao
J. Mar. Sci. Eng. 2024, 12(5), 716; https://doi.org/10.3390/jmse12050716 - 26 Apr 2024
Abstract
The feature matching of the near-bottom visual SLAM is influenced by underwater raised sediments, resulting in tracking loss. In this paper, the novel visual SLAM system is proposed in the underwater raised sediments environment. The underwater images are firstly classified based on the
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The feature matching of the near-bottom visual SLAM is influenced by underwater raised sediments, resulting in tracking loss. In this paper, the novel visual SLAM system is proposed in the underwater raised sediments environment. The underwater images are firstly classified based on the color recognition method by adding the weights of pixel location to reduce the interference of similar colors on the seabed. The improved adaptive median filter method is proposed to filter the classified images by using the mean value of the filter window border as the discriminant condition to retain the original features of the image. The filtered images are finally processed by the tracking module to obtain the trajectory of underwater vehicles and the seafloor maps. The datasets of seamount areas captured in the western Pacific Ocean are processed by the improved visual SLAM system. The keyframes, mapping points, and feature point matching pairs extracted from the improved visual SLAM system are improved by 5.2%, 11.2%, and 4.5% compared with that of the ORB-SLAM3 system, respectively. The improved visual SLAM system has the advantage of robustness to dynamic disturbances, which is of practical application in underwater vehicles operated in near-bottom areas such as seamounts and nodules.
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(This article belongs to the Topic Applications and Development of Underwater Robotics and Underwater Vision Technology)
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Open AccessReview
How to Achieve Comprehensive Carbon Emission Reduction in Ports? A Systematic Review
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Liping Zhang, Qingcheng Zeng and Liang Wang
J. Mar. Sci. Eng. 2024, 12(5), 715; https://doi.org/10.3390/jmse12050715 - 26 Apr 2024
Abstract
Under the mounting pressure to make changes to become more environmentally friendly and sustainable, port authorities have been exploring effective solutions to reduce CO2 emissions. In this regard, alternative fuels, innovative technology, and optimization strategies are key pathways for ports to transition
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Under the mounting pressure to make changes to become more environmentally friendly and sustainable, port authorities have been exploring effective solutions to reduce CO2 emissions. In this regard, alternative fuels, innovative technology, and optimization strategies are key pathways for ports to transition toward a low-carbon pattern. In this review work, the current development status and characteristics of renewable and clean energy in ports were meticulously analyzed. The CO2 emission reduction effects and limitations of port microgrids, carbon capture, and other technological operations were thoroughly examined. Lastly, the emission reduction optimization strategies ports could adopt under different scenarios were evaluated. The research findings showed that (1) combining the characteristics of the port and quantifying the properties of different renewable energy sources and low-carbon fuels is extremely necessary to select suitable alternative energy sources for port development; (2) technological advancements, multi-party interests, and policy impacts were the primary factors influencing the development of emission reduction technology methods; and (3) the coordinated optimization of multiple objectives in cross-scenarios was the main direction for ports to achieve sustainable development. This study provides theoretical guidance to ports that are transitioning to a greener pattern, as well as pointing out future research directions and development spaces for researchers.
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(This article belongs to the Section Marine Environmental Science)
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Open AccessArticle
Long-Term Evolution of Significant Wave Height in the Eastern Tropical Atlantic between 1940 and 2022 Using the ERA5 Dataset
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Olorunfemi Omonigbehin, Emmanuel OlaOluwa Eresanya, Aifeng Tao, Victor Edem Setordjie, Samuel Daramola and Abiola Adebiyi
J. Mar. Sci. Eng. 2024, 12(5), 714; https://doi.org/10.3390/jmse12050714 - 26 Apr 2024
Abstract
Studies on the variability in ocean wave climate provide engineers and policy makers with information to plan, develop, and control coastal and offshore activities. Ocean waves bear climatic imprints through which the global climate system can be better understood. Using the recently updated
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Studies on the variability in ocean wave climate provide engineers and policy makers with information to plan, develop, and control coastal and offshore activities. Ocean waves bear climatic imprints through which the global climate system can be better understood. Using the recently updated ERA5 dataset, this study evaluated the spatiotemporal distribution and variability in significant wave height (SWH) in the Eastern Tropical Atlantic (ETA). The short-term trends and rates of change were obtained using the Mann–Kendall trend test and the Theil–Sen slope estimator, respectively, and decadal trends were assessed using wavelet transformation. Significant, positive monthly and yearly trends and a prevailing decadal trend were observed across the domain. Observed trends suggest that stronger waves are getting closer to the coast and are modulated by the Southern and Northern Atlantic mid-latitude storm fields. These observations have implications for the increasing coastal erosion rates on the eastern coast of the Tropical Atlantic.
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(This article belongs to the Section Physical Oceanography)
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Open AccessArticle
Rare Earth Elements in Shells of Black Sea Molluscs: Anomalies and Biogeochemical Implications
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Sergey V. Kapranov, Vitaliy I. Ryabushko, Juliya D. Dikareva, Larisa L. Kapranova, Nikolay I. Bobko and Sophia Barinova
J. Mar. Sci. Eng. 2024, 12(5), 713; https://doi.org/10.3390/jmse12050713 - 25 Apr 2024
Abstract
Rare earth elements (REE) are a class of increasingly used high-tech product components and new emerging environmental pollutants, which are accumulated, in particular, in marine biota. In this study, REE contents were estimated in shells of several molluscs common in the Black Sea.
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Rare earth elements (REE) are a class of increasingly used high-tech product components and new emerging environmental pollutants, which are accumulated, in particular, in marine biota. In this study, REE contents were estimated in shells of several molluscs common in the Black Sea. The summed REE contents in mollusc shells decreased in the following order of species: Magallana gigas = Anadara kagoshimensis > Flexopecten glaber ponticus ≥ Rapana venosa > Mytilus galloprovincialis, ranging from 0.46 to 1.9 mg·kg−1. Canonical analysis of principal coordinates allowed for the correct identification of species based on the REE composition in no fewer than 67% of the samples. The mollusc shells were anomalously enriched in Sc, Y, La, Eu and Tb, most likely due to anthropogenic contamination. The Y/Ho ratios in all samples were represented by two fit values: 23.2 (chondritic) and 67.6 (superchondritic, mainly associated with A. kagoshimensis). A new universal relationship linking the contents of three light and heavy REE in Black Sea mollusc shells was proposed: Ce0.3 Er0.7⁄Yb = 2.00 ± 0.46 (mean ± standard deviation).
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Open AccessArticle
Slamming Characteristics Due to the Special Shape of New Sandglass-Type Model in Waves by Comparing with Cylindrical Model
by
Wenhua Wang, Taiwei Piao, Chong Geng, Kedong Zhang, Zhongyu Wang and Yi Huang
J. Mar. Sci. Eng. 2024, 12(5), 712; https://doi.org/10.3390/jmse12050712 - 25 Apr 2024
Abstract
For the new sandglass-type FPSO, the unique shape of its floating body with oblique side and external expansion can significantly improve the motion performance, but meanwhile may result in specific slamming characteristics in waves. On this basis, this paper establishes a CFD method
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For the new sandglass-type FPSO, the unique shape of its floating body with oblique side and external expansion can significantly improve the motion performance, but meanwhile may result in specific slamming characteristics in waves. On this basis, this paper establishes a CFD method including numerical wave-tank technique based on the Open FOAM platform. Therein, the velocity-inlet boundary method and the active absorption method are applied for numerical wave-making and wave-absorption. Compared with experimental results, the numerical method can be validated to be accurate enough to simulate wave slamming on floating ocean platforms. Then, the specific slamming phenomena on the sandglass-type floating body under a classic long wave can be investigated by comparing with the cylindrical model, including nonlinear wave rollover and breaking, water cushion, rooster-tail wave, side wave, water tongue, and so on. The mechanism of these phenomena and their effects on slamming pressure are studied. The essences of typical peaks in the time-history curve of the slamming pressure are mainly discussed. More interestingly, the main peak can be found to be related to the small peak due the amount of the broken water and the thickness of the water cushion. Finally, the slamming characteristics of the sandglass-type model in a classic short-wave condition are comparatively discussed.
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Multivariate USV Motion Prediction Method Based on a Temporal Attention Weighted TCN-Bi-LSTM Model
by
Yuchao Wang, Zixiang Tian and Huixuan Fu
J. Mar. Sci. Eng. 2024, 12(5), 711; https://doi.org/10.3390/jmse12050711 - 25 Apr 2024
Abstract
Unmanned surface vehicle (USV)’s motion is represented by time-series data that exhibit highly nonlinear and non-stationary features, significantly influenced by environmental factors, such as wind speed and waves, when sailing on the sea. The accurate prediction of USV motion, particularly crucial parameters, such
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Unmanned surface vehicle (USV)’s motion is represented by time-series data that exhibit highly nonlinear and non-stationary features, significantly influenced by environmental factors, such as wind speed and waves, when sailing on the sea. The accurate prediction of USV motion, particularly crucial parameters, such as the roll angle and pitch angle, is imperative for ensuring safe navigation. However, traditional and single prediction models often struggle with low accuracy and fail to capture the intricate spatial–temporal dependencies among multiple input variables. To address these limitations, this paper proposes a prediction approach integrating temporal convolutional network (TCN) and bi-directional long short-term memory network (Bi-LSTM) models, augmented with a temporal pattern attention (TPA) mechanism, termed the TCN-Bi-LSTM-TPA (TBT) USV motion predictor. This hybrid model effectively combines the strengths of TCN and Bi-LSTM architectures to extract long-term temporal features and bi-directional dependencies. The introduction of the TPA mechanism enhances the model’s capability to extract spatial information, crucial for understanding the intricate interplay of various motion data. By integrating the features extracted by TCN with the output of the attention mechanism, the model incorporates additional contextual information, thereby improving prediction accuracy. To evaluate the performance of the proposed model, we conducted experiments using real USV motion data and calculated four evaluation metrics: mean square error (MSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and R-squared (R2). The results demonstrate the superior accuracy of the TCN-Bi-LSTM-TPA hybrid model in predicting USV roll angle and pitch angle, validating its effectiveness in addressing the challenges of multivariate USV motion prediction.
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(This article belongs to the Section Ocean Engineering)
Open AccessArticle
An Adaptive Large Neighborhood Search Algorithm for Equipment Scheduling in the Railway Yard of an Automated Container Terminal
by
Hongbin Chen and Wei Liu
J. Mar. Sci. Eng. 2024, 12(5), 710; https://doi.org/10.3390/jmse12050710 - 25 Apr 2024
Abstract
In container sea–rail combined transport, the railway yard in an automated container terminal (RYACT) is the link in the whole logistics transportation process, and its operation and scheduling efficiency directly affect the efficiency of logistics. To improve the equipment scheduling efficiency of an
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In container sea–rail combined transport, the railway yard in an automated container terminal (RYACT) is the link in the whole logistics transportation process, and its operation and scheduling efficiency directly affect the efficiency of logistics. To improve the equipment scheduling efficiency of an RYACT, this study examines the “RYACT–train” cooperative optimization problem in the mode of “unloading before loading” for train containers. A mixed-integer programming model with the objective of minimizing the maximum completion time of automated rail-mounted gantry crane (ARMG) tasks is established. An adaptive large neighborhood search (ALNS) algorithm and random search algorithm (RSA) are designed to solve the abovementioned problem, and the feasibility of the model and algorithm is verified by experiments. At the same time, the target value and calculation time of the model and algorithms are compared. The experimental results show that the model and the proposed algorithms are feasible and can effectively solve the “RYACT–train” cooperative optimization problem. The model only obtains the optimal solution of the “RYACT–train” cooperative scheduling problem with no more than 50 tasks within a limited time, and the ALNS algorithm can solve examples of various scales within a reasonable amount of time. The target value of the ALNS solution is smaller than that of the RSA solution.
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(This article belongs to the Section Ocean Engineering)
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Open AccessArticle
Artificial Neural Networks for Mapping Coastal Lagoon of Chilika Lake, India, Using Earth Observation Data
by
Polina Lemenkova
J. Mar. Sci. Eng. 2024, 12(5), 709; https://doi.org/10.3390/jmse12050709 - 25 Apr 2024
Abstract
This study presents the environmental mapping of the Chilika Lake coastal lagoon, India, using satellite images Landsat 8-9 OLI/TIRS processed using machine learning (ML) methods. The largest brackish water coastal lagoon in Asia, Chilika Lake, is a wetland of international importance included in
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This study presents the environmental mapping of the Chilika Lake coastal lagoon, India, using satellite images Landsat 8-9 OLI/TIRS processed using machine learning (ML) methods. The largest brackish water coastal lagoon in Asia, Chilika Lake, is a wetland of international importance included in the Ramsar site due to its rich biodiversity, productivity, and precious habitat for migrating birds and rare species. The vulnerable ecosystems of the Chilika Lagoon are subject to climate effects (monsoon effects) and anthropogenic activities (overexploitation through fishing and pollution by microplastics). Such environmental pressure results in the eutrophication of the lake, coastal erosion, fluctuations in size, and changes in land cover types in the surrounding landscapes. The habitat monitoring of the coastal lagoons is complex and difficult to implement with conventional Geographic Information System (GIS) methods. In particular, landscape variability, patch fragmentation, and landscape dynamics play a crucial role in environmental dynamics along the eastern coasts of the Bay of Bengal, which is strongly affected by the Indian monsoon system, which controls the precipitation pattern and ecosystem structure. To improve methods of environmental monitoring of coastal areas, this study employs the methods of ML and Artificial Neural Networks (ANNs), which present a powerful tool for computer vision, image classification, and analysis of Earth Observation (EO) data. Multispectral satellite data were processed by several ML image classification methods, including Random Forest (RF), Support Vector Machine (SVM), and the ANN-based MultiLayer Perceptron (MLP) Classifier. The results are compared and discussed. The ANN-based approach outperformed the other methods in terms of accuracy and precision of mapping. Ten land cover classes around the Chilika coastal lagoon were identified via spatio-temporal variations in land cover types from 2019 until 2024. This study provides ML-based maps implemented using Geographic Resources Analysis Support System (GRASS) GIS image analysis software and aims to support ML-based mapping approach of environmental processes over the Chilika Lake coastal lagoon, India.
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(This article belongs to the Special Issue Remote Sensing Applications in Marine Environmental Monitoring)
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