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
Observations of Near-Inertial Internal Waves over the Continental Slope in the Northeastern Black Sea
J. Mar. Sci. Eng. 2024, 12(3), 507; https://doi.org/10.3390/jmse12030507 (registering DOI) - 19 Mar 2024
Abstract
The article presents observations of near-inertial internal waves (NIWs) in the slope waters of the Black Sea in winter and summer. Rotary spectral analysis of a time series of sea current velocity measurements revealed the prevailing anticyclonic component of the motions near the
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The article presents observations of near-inertial internal waves (NIWs) in the slope waters of the Black Sea in winter and summer. Rotary spectral analysis of a time series of sea current velocity measurements revealed the prevailing anticyclonic component of the motions near the local inertial frequency f. The clockwise rotation of the velocity vector with depth implies that the NIWs propagate downwards. The amplitude of NIWs usually was 0.1–0.2 m s−1. NIWs were observed in the layer of the permanent pycnocline and the seasonal pycnocline, which attenuate below depths of 160 m and 80 m in winter and summer, respectively. The amplitude of the near-inertial kinetic energy (NIKE) showed a close relationship with vertical stratification. During winter, NIKE exhibited maximum values in the layer of the permanent pycnocline, whereas, in summer, it was primarily observed in the seasonal pycnocline layer. The near-inertial oscillations were generally more energetic in winter.
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(This article belongs to the Special Issue Latest Advances in Physical Oceanography—2nd Edition)
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Lightweight Underwater Object Detection Algorithm for Embedded Deployment Using Higher-Order Information and Image Enhancement
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Changhong Liu, Jiawen Wen, Jinshan Huang, Weiren Lin, Bochun Wu, Ning Xie and Tao Zou
J. Mar. Sci. Eng. 2024, 12(3), 506; https://doi.org/10.3390/jmse12030506 - 19 Mar 2024
Abstract
Underwater object detection is crucial in marine exploration, presenting a challenging problem in computer vision due to factors like light attenuation, scattering, and background interference. Existing underwater object detection models face challenges such as low robustness, extensive computation of model parameters, and a
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Underwater object detection is crucial in marine exploration, presenting a challenging problem in computer vision due to factors like light attenuation, scattering, and background interference. Existing underwater object detection models face challenges such as low robustness, extensive computation of model parameters, and a high false detection rate. To address these challenges, this paper proposes a lightweight underwater object detection method integrating deep learning and image enhancement. Firstly, FUnIE-GAN is employed to perform data enhancement to restore the authentic colors of underwater images, and subsequently, the restored images are fed into an enhanced object detection network named YOLOv7-GN proposed in this paper. Secondly, a lightweight higher-order attention layer aggregation network (ACC3-ELAN) is designed to improve the fusion perception of higher-order features in the backbone network. Moreover, the head network is enhanced by leveraging the interaction of multi-scale higher-order information, additionally fusing higher-order semantic information from features at different scales. To further streamline the entire network, we also introduce the AC-ELAN-t module, which is derived from pruning based on ACC3-ELAN. Finally, the algorithm undergoes practical testing on a biomimetic sea flatworm underwater robot. The experimental results on the DUO dataset show that our proposed method improves the performance of object detection in underwater environments. It provides a valuable reference for realizing object detection in underwater embedded devices with great practical potential.
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(This article belongs to the Special Issue Underwater Engineering and Image Processing)
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A User Interface Design Framework for Augmented-Reality-Supported Maritime Navigation
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Kjetil Nordby, Jon Erling Fauske, Etienne Gernez and Steven Mallam
J. Mar. Sci. Eng. 2024, 12(3), 505; https://doi.org/10.3390/jmse12030505 - 19 Mar 2024
Abstract
Augmented reality (AR) technology has emerged as a promising solution that can potentially reduce head-down time and increase situational awareness during navigation operations. It is also useful for remote operation centers where video feeds from remote ships can be “augmented” with data and
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Augmented reality (AR) technology has emerged as a promising solution that can potentially reduce head-down time and increase situational awareness during navigation operations. It is also useful for remote operation centers where video feeds from remote ships can be “augmented” with data and information. In this article, we introduce a user interface design concept that supports ship navigation by showing data about points of interest in AR. This approach enables users to view and interact with relevant data in the maritime environment by bridging the gap between digital information and real-world features. The proposed concept can provide operational data from various maritime systems, such as radar, GPS, AIS, or camera systems, empowering users with a wealth of information about their surroundings. Developed through an iterative user-centered design process, it was built as an extension to the OpenBridge design system, an open-source platform facilitating consistent design in maritime workplaces. Furthermore, we use this concept to propose a design framework that paves the way for establishing new standards for AR user interface design in the maritime domain.
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(This article belongs to the Special Issue New Trends in Marine Robotics: Virtual Experiments and Remote Access)
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A Corrosion- and Repair-Based Reliability Framework for Offshore Platforms
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Mehdi Hajinezhadian and Behrouz Behnam
J. Mar. Sci. Eng. 2024, 12(3), 504; https://doi.org/10.3390/jmse12030504 - 18 Mar 2024
Abstract
Offshore platforms are important infrastructures that often face severe environmental conditions, such as corrosion, throughout their lifetime. This can continuously decrease their structural robustness. Despite the availability of many anti-corrosion strategies, there is still a need for a sound management scheme that can
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Offshore platforms are important infrastructures that often face severe environmental conditions, such as corrosion, throughout their lifetime. This can continuously decrease their structural robustness. Despite the availability of many anti-corrosion strategies, there is still a need for a sound management scheme that can systematically address the lifetime operation of offshore platforms under corrosion. To address this, the work here proposes a corrosion- and repair-based reliability framework for the lifetime operation of offshore platforms. A fixed offshore platform is designed based on current design codes for severe environmental conditions in a given return period, and the effect of corrosion on the structure’s serviceability is modeled. The results show that the extent of the corrosion depth and damage in different years highly affects the ability of a repair to restore a damaged element to its original design strength. The results also show that the residual reliability of the structural members under the splash zone becomes almost zero after the first 10 years of the operation period, implying that these members require quick repair strategies. This study establishes a management program for fixed offshore platforms subjected to long-term corrosion by performing reliability analyses on the components of the platforms and evaluating the maintenance of the components in the splash zone. In the absence of commonly accepted contemporary industry practice standards, this study proposes a corrosion growth model based on API-RP-2A, DNV, and NORSOK standards that can effectively evaluate code-based structural designs. The framework developed here can help offshore platform owners in their decision-making process for corrosion-based safety analysis.
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(This article belongs to the Section Ocean Engineering)
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Control Optimization Method for Ship Direct Current Microgrid Based on Impedance Reshaping
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Weiqiang Liao, Xin Dong, Rongfeng Yang and Zhongfei Qiao
J. Mar. Sci. Eng. 2024, 12(3), 503; https://doi.org/10.3390/jmse12030503 - 18 Mar 2024
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In response to the constant power negative impedance characteristics on the load side of a ship DC microgrid, leading to voltage oscillation issues in the DC bus, this paper proposes a control optimization method based on impedance reshaping using bus voltage feedback. First,
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In response to the constant power negative impedance characteristics on the load side of a ship DC microgrid, leading to voltage oscillation issues in the DC bus, this paper proposes a control optimization method based on impedance reshaping using bus voltage feedback. First, a simplified small-signal diagram of a lithium battery energy storage system converter is analyzed. Combining active damping control technology, an impedance regulator is introduced, and its parameters are optimized to effectively reduce the output impedance magnitude on the power source side. Subsequently, a ship DC microgrid simulation model is constructed using MATLAB R2022a/Simulink for validation, and comparative analysis is conducted on the anti-interference ability of the DC bus voltage before and after impedance reshaping. Finally, a model is built on a semi-physical simulation platform to experimentally verify the proposed method. The research results indicate that the proposed control optimization method can effectively increase the system’s stability margin, suppress DC bus oscillations, and enhance the anti-interference ability of the ship DC microgrid’s bus voltage when facing significant power load variations.
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Short-Term Marine Wind Speed Forecasting Based on Dynamic Graph Embedding and Spatiotemporal Information
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Dibo Dong, Shangwei Wang, Qiaoying Guo, Yiting Ding, Xing Li and Zicheng You
J. Mar. Sci. Eng. 2024, 12(3), 502; https://doi.org/10.3390/jmse12030502 - 18 Mar 2024
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Predicting wind speed over the ocean is difficult due to the unequal distribution of buoy stations and the occasional fluctuations in the wind field. This study proposes a dynamic graph embedding-based graph neural network—long short-term memory joint framework (DGE-GAT-LSTM) to estimate wind speed
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Predicting wind speed over the ocean is difficult due to the unequal distribution of buoy stations and the occasional fluctuations in the wind field. This study proposes a dynamic graph embedding-based graph neural network—long short-term memory joint framework (DGE-GAT-LSTM) to estimate wind speed at numerous stations by considering their spatio-temporal information properties. To begin, the buoys that are pertinent to the target station are chosen based on their geographic position. Then, the local graph structures connecting the stations are represented using cosine similarity at each time interval. Subsequently, the graph neural network captures intricate spatial characteristics, while the LSTM module acquires knowledge of temporal interdependence. The graph neural network and LSTM module are sequentially interconnected to collectively capture spatio-temporal correlations. Ultimately, the multi-step prediction outcomes are produced in a sequential way, where each step relies on the previous predictions. The empirical data are derived from direct measurements made by NDBC buoys. The results indicate that the suggested method achieves a mean absolute error reduction ranging from 1% to 36% when compared to other benchmark methods. This improvement in accuracy is statistically significant. This approach effectively addresses the challenges of inadequate information integration and the complexity of modeling temporal correlations in the forecast of ocean wind speed. It offers valuable insights for optimizing the selection of offshore wind farm locations and enhancing operational and management capabilities.
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Laboratory Investigations of Iceberg Melting under Wave Conditions in Sea Water
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Aleksey Marchenko and Nataliya Marchenko
J. Mar. Sci. Eng. 2024, 12(3), 501; https://doi.org/10.3390/jmse12030501 - 18 Mar 2024
Abstract
Changes in the masses of icebergs due to deterioration processes affect the drift of icebergs and should be taken into account when assessing iceberg risks in the areas of offshore development. In 2022 and 2023, eight laboratory experiments were carried out in the
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Changes in the masses of icebergs due to deterioration processes affect the drift of icebergs and should be taken into account when assessing iceberg risks in the areas of offshore development. In 2022 and 2023, eight laboratory experiments were carried out in the wave tank of the University Centre in Svalbard to study the melting of icebergs in sea water under calm and rough conditions. In the experiments, the water temperatures varied from to . Cylindrical iceberg models were made from columnar ice cores with a diameter of 24 cm. In one experiment, the iceberg model was protected on the sides with plastic fencing to investigate the iceberg’s protection from melting when towed to deliver fresh water. The iceberg masses, water temperatures, and ice temperatures were measured in the experiments. The water velocity near the iceberg models was measured with an acoustic Doppler velocimeter. During the experiments, time-lapse cameras were used to describe the shapes and measure the vertical dimensions of the icebergs. Using experimental data, we calculated the horizontal dimensions of icebergs, latent heat fluxes, conductive heat fluxes inside the iceberg models, and turbulent heat fluxes in water as a function of time. We discovered the influence of surface waves and water mixing on the melt rates and found a significant reduction in the melt rates due to the lateral protection of the iceberg model using a plastic barrier. Based on the experimental data obtained, the ratio of the rates of lateral and bottom melting of the icebergs and lateral melting of the icebergs under wave conditions was parametrized depending on the wave frequency.
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(This article belongs to the Special Issue Recent Research on the Measurement and Modeling of Sea Ice)
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A Fault-Tolerant Control Method Based on Reconfiguration SPWM Signal for Cascaded Multilevel IGBT-Based Propulsion in Electric Ships
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Fan Zhang, Zhiwei Zhang, Zhonglin Zhang, Tianzhen Wang, Jingang Han and Yassine Amirat
J. Mar. Sci. Eng. 2024, 12(3), 500; https://doi.org/10.3390/jmse12030500 - 18 Mar 2024
Abstract
Electric ships have been developed in recent years to reduce greenhouse gas emissions. In this system, inverters are the key equipment for the permanent-magnet synchronous motor (PMSM) drive system. The cascaded insulated-gated bipolar transistor (IGBT)-based H-bridge inverter is one of the most attractive
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Electric ships have been developed in recent years to reduce greenhouse gas emissions. In this system, inverters are the key equipment for the permanent-magnet synchronous motor (PMSM) drive system. The cascaded insulated-gated bipolar transistor (IGBT)-based H-bridge inverter is one of the most attractive multilevel topologies for modern electric ship applications. Usually, the fault-tolerant control strategy is designed to keep the ship in operation for a certain period. However, the fault-tolerant control strategy with hardware redundancy is expensive and slow in response. In addition, after fault-tolerant control, the ship’s PMSM may experience shock and overheating, and IGBT life is reduced due to uneven switching frequency distribution. Therefore, a stratified reconfiguration carrier disposition Sinusoidal Pulse Width Modulation (SPWM) fault-tolerant control strategy is proposed. The proposed strategy can achieve fault tolerance without any extra hardware. A reconfiguration carrier is applied to improve the fundamental amplitude of inverter output voltage to maintain the operation of the ship’s PMSM. In addition, the available states of faulty H-bridge are fully used to contribute to the output. These can improve the life of IGBTs by reducing and balancing the power loss of each H-bridge. The principles of the proposed strategy are described in detail in this study. Taking a cascaded H-bridge seven-level inverter as an example, simulation and experimental results verify that the proposed strategy, in general, has a potential future application on electric ships.
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(This article belongs to the Special Issue Advanced Research on the Sustainable Maritime Transportation)
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Experimental Study on the Effect of Wind on Armor Stone Stability
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Young-Min Kim, Jae-Ho Lim and Hyun-Doug Yoon
J. Mar. Sci. Eng. 2024, 12(3), 499; https://doi.org/10.3390/jmse12030499 - 18 Mar 2024
Abstract
Wind is a significant factor influencing the stability of breakwater armor stones. However, few existing studies have considered the effects of wind on these structures. In this study, two-dimensional laboratory experiments were conducted to examine the effect of wind on the stability of
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Wind is a significant factor influencing the stability of breakwater armor stones. However, few existing studies have considered the effects of wind on these structures. In this study, two-dimensional laboratory experiments were conducted to examine the effect of wind on the stability of breakwater armor stones. The stability factor ( ) of the armor stone, fluid velocity, runup, and rundown were observed under the action of waves and winds. A wind turbine was installed in front of the physical model of the breakwater to generate extreme wind conditions of 5.5 and 12 m/s. The results showed that decreased by 42.18% at 5.5 m/s and 57.82% at 12 m/s compared with that without wind. The maximum runup and rundown heights increased with wind velocity, following a Rayleigh distribution. The fluid velocity distribution conformed to a normal distribution, with the mean velocity directed offshore. Many studies have suggested that runup, rundown, and fluid velocity are the main factors affecting the stability of breakwater armor stones. The analysis revealed that wind affects these factors and lowers the stability coefficient. These wind-induced hydrodynamic changes suggest the need for a detailed hydrodynamic review of wind-wave conditions.
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(This article belongs to the Special Issue Design of Harbour and Coastal Structures)
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IRNLGD: An Edge Detection Algorithm with Comprehensive Gradient Directions for Tidal Stream Turbine
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Dingnan Song, Ran Liu, Zhiwei Zhang, Dingding Yang and Tianzhen Wang
J. Mar. Sci. Eng. 2024, 12(3), 498; https://doi.org/10.3390/jmse12030498 - 17 Mar 2024
Abstract
Tidal stream turbines (TSTs) harness the kinetic energy of tides to generate electricity by rotating the rotor. Biofouling will lead to an imbalance between the blades, resulting in imbalanced torque and voltage across the windings, ultimately polluting the grid. Therefore, rotor condition monitoring
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Tidal stream turbines (TSTs) harness the kinetic energy of tides to generate electricity by rotating the rotor. Biofouling will lead to an imbalance between the blades, resulting in imbalanced torque and voltage across the windings, ultimately polluting the grid. Therefore, rotor condition monitoring is of great significance for the stable operation of the system. Image-based attachment detection algorithms provide the advantage of visually displaying the location and area of faults. However, due to the limited availability of data from multiple machine types and environments, it is difficult to ensure the generalization of the network. Additionally, TST images degrade, resulting in reduced image gradients and making it challenging to extract edge and other features. In order to address the issue of limited data, a novel non-data-driven edge detection algorithm, indexed resemble-normal-line guidance detector (IRNLGD), is proposed for TST rotor attachment fault detection. Aiming to solve the problem of edge features being suppressed, IRNLGD introduces the concept of “indexed resemble-normal-line direction” and integrates multi-directional gradient information for edge determination. Real-image experiments demonstrate IRNLGD’s effectiveness in detecting TST rotor edges and faults. Evaluation on public datasets shows the superior performance of our method in detecting fine edges in low-light images.
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(This article belongs to the Special Issue Offshore Renewable Energy)
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Research on the Deployment of Professional Rescue Ships for Maritime Traffic Safety under Limited Conditions
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Minghui Shao, Biao Wu, Yan Li and Xiaoli Jiang
J. Mar. Sci. Eng. 2024, 12(3), 497; https://doi.org/10.3390/jmse12030497 - 17 Mar 2024
Abstract
This paper focuses on optimizing the deployment plan for standby points of professional rescue vessels based on the data of maritime incidents in the Beihai area of China. The primary objective is to achieve multi-level and multiple coverage of the jurisdictional waters of
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This paper focuses on optimizing the deployment plan for standby points of professional rescue vessels based on the data of maritime incidents in the Beihai area of China. The primary objective is to achieve multi-level and multiple coverage of the jurisdictional waters of the Beihai Rescue Bureau. Models including the coverage quality of the jurisdictional waters, the coverage quality in high-risk areas, the maximum coverage of jurisdictional areas, and the maximum coverage of high-risk areas are constructed and solved using 0–1 integer programming. The optimal plan for eight standby points and their corresponding deployment plans for rescue vessels are obtained. A comparison with the current site selection plan of the Beihai Rescue Bureau validates the superiority of the proposed deployment plan for rescue vessel standby points in this paper.
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(This article belongs to the Special Issue Smart and Low Carbon Emission-Oriented Maritime Traffic Management and Controlling)
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Analysis of the Swordfish Xiphias gladius Linnaeus, 1758 Catches by the Pelagic Longline Fleets in the Eastern Pacific Ocean
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Luis Adán Félix-Salazar, Emigdio Marín-Enríquez, Eugenio Alberto Aragón-Noriega and Jorge Saul Ramirez-Perez
J. Mar. Sci. Eng. 2024, 12(3), 496; https://doi.org/10.3390/jmse12030496 - 16 Mar 2024
Abstract
During the last 50 years, the increase in the efforts of the longline fleet in the Eastern Pacific Ocean (EPO) resulted in an increase in the capture of the swordfish Xiphias gladius. We analyzed a historical database of swordfish catches (1980–2020) reported
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During the last 50 years, the increase in the efforts of the longline fleet in the Eastern Pacific Ocean (EPO) resulted in an increase in the capture of the swordfish Xiphias gladius. We analyzed a historical database of swordfish catches (1980–2020) reported by the industrial longline fleet to the Inter-American Tuna Tropical Commission (IATTC), which contains catch and effort data aggregated in monthly quadrants of 5° × 5° in the EPO. The swordfish catch reported by the international longline fleets was analyzed to evaluate the spatiotemporal variation of the catch and the different phases through which this important fishery has gone through. Different statistical models such as the Generalized Additive Mixed Model (GAMM) and the breaks for additive season and trend BFAST algorithm were used for the decomposition of the time series. Results indicated that the effort directed towards the swordfish increased in recent years and that the highest catches occurred by Peru. The adjusted GAMM explained 80% of the total temporal variation of the swordfish catch per unit effort CPUE and had a 90% prediction efficiency. The BFAST algorithm found three break points in the time series of the standardized CPUE, points associated with abrupt changes, thus defining four distinct periods, all of them statistically significant. According to the BFAST model, the current trend of swordfish CPUE is upward. It is recommended to take this finding with caution to obtain the sustainable exploitation of the swordfish fishery resource.
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(This article belongs to the Section Marine Biology)
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Oil Spill Classification Using an Autoencoder and Hyperspectral Technology
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María Gema Carrasco-García, María Inmaculada Rodríguez-García, Juan Jesús Ruíz-Aguilar, Lipika Deka, David Elizondo and Ignacio José Turias Domínguez
J. Mar. Sci. Eng. 2024, 12(3), 495; https://doi.org/10.3390/jmse12030495 - 15 Mar 2024
Abstract
Hyperspectral technology has been playing a leading role in monitoring oil spills in marine environments, which is an issue of international concern. In the case of monitoring oil spills in local areas, hyperspectral technology of small dimensions is the ideal solution. This research
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Hyperspectral technology has been playing a leading role in monitoring oil spills in marine environments, which is an issue of international concern. In the case of monitoring oil spills in local areas, hyperspectral technology of small dimensions is the ideal solution. This research explores the use of encoded hyperspectral signatures to develop automated classifiers capable of discriminating between polluted and clean water and distinguishing between various types of oil. The overall objective is to leverage these classifiers to be able to improve the performance of conventional systems that rely solely on hyperspectral imagery. The acquisition of the hyperspectral signatures of water and hydrocarbons was carried out with a spectroradiometer. The range of the spectroradiometer used in this study covers the ranges between [350–1000] (visible near-infrared) and [1000–2500] (short-wavelength infrared). This gives detailed information regarding the targets of interest. Different neural autoencoders (AEs) have been developed to reduce inputs into different dimensions, from 1 to 15. Each of these encoded sets was used to train decision tree (DT) classifiers. The results are very promising, as they show that the AE models encoded data with correlation coefficients above 0.95. The classifiers trained with the different sets provide accuracies close to 1.
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(This article belongs to the Special Issue Recent Experiences and Monitoring in Coastal, Fluvial and Marine Hydrography)
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Behavior Analysis of a Bucket Foundation with an Offshore Wind Turbine during the In-Water Sinking Process
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Fangdi Ye, Jijian Lian, Tianrun Xiao, Dongzhi Xiong, Haijun Wang, Yaohua Guo and Nan Shao
J. Mar. Sci. Eng. 2024, 12(3), 494; https://doi.org/10.3390/jmse12030494 - 15 Mar 2024
Abstract
To enhance the safety of the in-water sinking operation for an integrated system, including a bucket foundation (BF), tower, and rotor nacelle assembly (RNA), in complex marine environmental conditions, a model test of in-water sinking for an offshore wind turbine and bucket foundation
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To enhance the safety of the in-water sinking operation for an integrated system, including a bucket foundation (BF), tower, and rotor nacelle assembly (RNA), in complex marine environmental conditions, a model test of in-water sinking for an offshore wind turbine and bucket foundation (OWT–BF) is conducted. The motion behavior of the OWT–BF and the sling tensions during the in-water sinking process are investigated, and the numerical method is validated through test results. The results demonstrate a positive correlation between the wave height and motion response of the OWT–BF. The most critical stage of the in-water sinking operation occurs when the top cover of the bucket is fully submerged, resulting from the substantial cross-sectional difference between the bucket base and the transition section. Furthermore, the closer the OWT–BF is to the seabed, the less it is affected by waves in terms of motion response. It is advisable to conduct the in-water sinking operation of the OWT–BF in sea states with wave heights below 1.5 m. Simultaneously, slings can efficiently control the motion response of the OWT–BF, thereby enhancing the safety of the sinking operation.
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(This article belongs to the Special Issue Offshore Renewable Energy)
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A Prescriptive Model for Failure Analysis in Ship Machinery Monitoring Using Generative Adversarial Networks
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Baris Yigin and Metin Celik
J. Mar. Sci. Eng. 2024, 12(3), 493; https://doi.org/10.3390/jmse12030493 - 15 Mar 2024
Abstract
In recent years, advanced methods and smart solutions have been investigated for the safe, secure, and environmentally friendly operation of ships. Since data acquisition capabilities have improved, data processing has become of great importance for ship operators. In this study, we introduce a
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In recent years, advanced methods and smart solutions have been investigated for the safe, secure, and environmentally friendly operation of ships. Since data acquisition capabilities have improved, data processing has become of great importance for ship operators. In this study, we introduce a novel approach to ship machinery monitoring, employing generative adversarial networks (GANs) augmented with failure mode and effect analysis (FMEA), to address a spectrum of failure modes in diesel generators. GANs are emerging unsupervised deep learning models known for their ability to generate realistic samples that are used to amplify a number of failures within training datasets. Our model specifically targets critical failure modes, such as mechanical wear and tear on turbochargers and fuel injection system failures, which can have environmental effects, providing a comprehensive framework for anomaly detection. By integrating FMEA into our GAN model, we do not stop at detecting these failures; we also enable timely interventions and improvements in operational efficiency in the maritime industry. This methodology not only boosts the reliability of diesel generators, but also sets a precedent for prescriptive maintenance approaches in the maritime industry. The model was demonstrated with real-time data, including 33 features, gathered from a diesel generator installed on a 310,000 DWT oil tanker. The developed algorithm provides high-accuracy results, achieving 83.13% accuracy. The final model demonstrates a precision score of 36.91%, a recall score of 83.47%, and an F1 score of 51.18%. The model strikes a balance between precision and recall in order to eliminate operational drift and enables potential early action in identified positive cases. This study contributes to managing operational excellence in tanker ship fleets. Furthermore, this study could be expanded to enhance the current functionalities of engine health management software products.
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(This article belongs to the Special Issue Risk, Safety and Reliability Assessment in the Maritime and Offshore Industries)
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Application of Regularized Meshless Method with Error Estimation Technique for Water–Wave Scattering by Multiple Cylinders
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Kue-Hong Chen, Jeng-Hong Kao and Yi-Hui Hsu
J. Mar. Sci. Eng. 2024, 12(3), 492; https://doi.org/10.3390/jmse12030492 - 15 Mar 2024
Abstract
In this manuscript, we will apply the regularized meshless method, coupled with an error estimation technique, to tackle the challenge of modeling oblique incident waves interacting with multiple cylinders. Given the impracticality of obtaining an exact solution in many real engineering problems, we
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In this manuscript, we will apply the regularized meshless method, coupled with an error estimation technique, to tackle the challenge of modeling oblique incident waves interacting with multiple cylinders. Given the impracticality of obtaining an exact solution in many real engineering problems, we introduce an error estimation technique designed to achieve reliable solutions. This technique excels in providing dependable solutions that closely approximate analytical solutions. An additional advantage is its capacity to identify the optimal number of points for both source and collocating points, thereby enhancing computational efficiency. The validity of the proposed method will be demonstrated through three numerical cases, presenting results that exhibit substantial agreement.
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(This article belongs to the Special Issue Advances in Marine Computational Fluid Dynamics and Wave Studies)
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Variable Natural Frequency Damper for Minimizing Response of Offshore Wind Turbine: Effect on Dynamic Response According to Inner Water Level
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Dong-Ju Kim, Young-Suk You and Min-Young Sun
J. Mar. Sci. Eng. 2024, 12(3), 491; https://doi.org/10.3390/jmse12030491 - 15 Mar 2024
Abstract
Offshore wind turbines (OWTs) are exposed to cyclic loads resulting from wind, waves, and rotor rotation. These loads can induce resonance, thereby significantly increasing the amplitude of the structure and accelerating the accumulation of fatigue damage. Particularly, wave loads can induce the first
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Offshore wind turbines (OWTs) are exposed to cyclic loads resulting from wind, waves, and rotor rotation. These loads can induce resonance, thereby significantly increasing the amplitude of the structure and accelerating the accumulation of fatigue damage. Particularly, wave loads can induce the first mode of large turbines. While many studies have been conducted to suppress OWT vibrations due to external loads, research on variable natural frequency damper (VNFD), which control vibrations through changes in the natural frequency by adjusting the inner water level of the structure, is still in its infancy. Herein, the performance of a VNFD in controlling the vibration of monopile-type OWTs is analyzed by focusing on cyclic environmental loads. To analyze the amplitude minimization achieved using a VNFD, wave loads with the same period as that of the structure’s natural frequency were generated, and the structural response resulting from changes in the inner water level were analyzed. As a result, the peak displacement at the top of the tower decreased by 5.8% and 34% at the water depths of 20 m and 50 m, respectively. In terms of the peak intensity determined through Fast Fourier Transform of the displacement response, reductions of 33% and 65% were confirmed at the depths of 20 m and 50 m, respectively.
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(This article belongs to the Special Issue Offshore Structures and Hydrodynamic Modeling)
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Open AccessReview
Review on the Hydro- and Thermo-Dynamic Wakes of Underwater Vehicles in Linearly Stratified Fluid
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Liushuai Cao, Yanyan Pan, Gang Gao, Linjie Li and Decheng Wan
J. Mar. Sci. Eng. 2024, 12(3), 490; https://doi.org/10.3390/jmse12030490 - 15 Mar 2024
Abstract
Wakes produced by underwater vehicles, particularly submarines, in density-stratified fluids play a pivotal role across military, academic, and engineering domains. In comparison to homogeneous fluid environments, wakes in stratified flows exhibit distinctive phenomena, including upstream blocking, pancake eddies, internal waves, and variations in
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Wakes produced by underwater vehicles, particularly submarines, in density-stratified fluids play a pivotal role across military, academic, and engineering domains. In comparison to homogeneous fluid environments, wakes in stratified flows exhibit distinctive phenomena, including upstream blocking, pancake eddies, internal waves, and variations in hydrodynamic performance. These phenomena are crucial for optimizing the operation of underwater vehicles. This review critically assesses the hydrodynamic and thermodynamic aspects of these wakes through an integration of theoretical, experimental, and numerical approaches. The hydrodynamic wake evolution, comprising near-wake, non-equilibrium, and quasi-two-dimensional regimes, is scrutinized. The underlying physics, encompassing energy transformation, vertical motion suppression, and momentum dissipation, are analyzed in detail. Special emphasis is placed on numerical methods, encompassing diverse approaches and turbulence models and highlighting their differences in fidelity and computational cost. Numerical simulations not only provide insights into the intricate interplay among various factors but also emerge as a crucial focal point for future research directions. In the realm of thermodynamic wakes, we delve into the thermal wake induced by the discharge of high-temperature cooling water and the cold wake resulting from the stirring of seawater. The generation, evolution, and ascent to the free surface of these wakes are explored. Additionally, this review identifies and analyzes current research shortcomings in each aspect. By systematically addressing existing knowledge gaps, our study contributes novel insights that propel academic progress and bear significant implications for submarine engineering. This work not only enhances our understanding of the intricate dynamics involved but also provides a foundation for future research endeavors in this critical field.
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(This article belongs to the Special Issue Computational Marine Hydrodynamics (CMH))
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Open AccessArticle
Bio-Inspired Cooperative Control Scheme of Obstacle Avoidance for UUV Swarm
by
Zhao Wang, Hongjian Wang, Jianya Yuan, Dan Yu, Kai Zhang and Jingfei Ren
J. Mar. Sci. Eng. 2024, 12(3), 489; https://doi.org/10.3390/jmse12030489 - 14 Mar 2024
Abstract
The complex underwater environment poses significant challenges for unmanned underwater vehicles (UUVs), particularly in terms of communication constraints and the need for precise cooperative obstacle avoidance and trajectory tracking. Addressing these challenges solely through position information is crucial in this field. This study
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The complex underwater environment poses significant challenges for unmanned underwater vehicles (UUVs), particularly in terms of communication constraints and the need for precise cooperative obstacle avoidance and trajectory tracking. Addressing these challenges solely through position information is crucial in this field. This study explores the intricate task of managing a group of UUVs as they navigate obstacles and follow a given trajectory, all based on position information. A new dynamic interactive topology framework utilizing sonar technology has been developed for the UUVs. This framework not only provides position information for the UUV swarm but also for the surrounding obstacles, enhancing situational awareness. Additionally, a bio-inspired cooperative control strategy designed for UUV swarms utilizing sonar interaction topology is introduced. This innovative method eliminates the need for velocity data from neighboring UUVs, instead relying solely on position information to achieve swarm cooperative control, obstacle avoidance, and trajectory adherence. The effectiveness of this method is validated through extensive simulations. The results show that the proposed method demonstrates improved sensitivity in obstacle detection, enabling faster trajectory tracking while maintaining a safer distance compared to traditional methods. Ultimately, this innovative strategy not only enhances operational efficiency but also enhances safety measures in UUV swarm operations.
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(This article belongs to the Special Issue Navigation and Detection Fusion for Autonomous Underwater Vehicles)
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Open AccessArticle
Robust Fish Recognition Using Foundation Models toward Automatic Fish Resource Management
by
Tatsuhito Hasegawa and Daichi Nakano
J. Mar. Sci. Eng. 2024, 12(3), 488; https://doi.org/10.3390/jmse12030488 - 14 Mar 2024
Abstract
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Resource management for fisheries plays a pivotal role in fostering a sustainable fisheries industry. In Japan, resource surveys rely on manual measurements by staff, incurring high costs and limitations on the number of feasible measurements. This study endeavors to revolutionize resource surveys by
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Resource management for fisheries plays a pivotal role in fostering a sustainable fisheries industry. In Japan, resource surveys rely on manual measurements by staff, incurring high costs and limitations on the number of feasible measurements. This study endeavors to revolutionize resource surveys by implementing image-recognition technology. Our methodology involves developing a system that detects individual fish regions in images and automatically identifies crucial keypoints for accurate fish length measurements. We use grounded-segment-anything (Grounded-SAM), a foundation model for fish instance segmentation. Additionally, we employ a Mask Keypoint R-CNN trained on the fish image bank (FIB), which is an original dataset of fish images, to accurately detect significant fish keypoints. Diverse fish images were gathered for evaluation experiments, demonstrating the robust capabilities of the proposed method in accurately detecting both fish regions and keypoints.
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