Search Results (6,995)

The present study utilised a geometric mean model in which sea surface temperature, oxygen, and sea surface salinity were used to predict the effects of climate change on the habitats of mature albacore tuna in the Indian Ocean under multiple representative concentration pathway (RCP) scenarios. Data pertaining to the albacore tuna fishing conducted by Taiwanese longline fisheries during the October–March period in 1998–2016 were analysed. The fishery data comprised fishing location (latitude and longitude), fishing effort (number of hooks used), number of catches, fishing time (month and year), and fish weight. Nominal catch per unit effort data were standardised to mitigate the potential effects of temporal and spatial factors in causing bias and overestimation. The Habitat Suitability Index (HSI) scores of potential habitats for mature albacore in the Indian Ocean are predicted to change considerably in response to varying levels of predicted climate change. Under projected warm climate conditions (RCP 8.5), the stratification of water is predicted to cause low HSI areas to expand and potential habitats for mature albacore to shift southward by 2100. The findings derived from these mature albacore habitat forecasts can contribute to the evaluation of potential hazards and feasible adaptation measures for albacore fishery resources in the context of climate change. The distribution trends pertaining to potential habitats for mature albacore should be used with caution and can provide resource stakeholders with guidance for decision-making. Full article

According to statistics, about 70% of ship fire accidents occur in the engine room, due to the complex internal structure and various combustible materials. Once a fire occurs, it is difficult to extinguish and significantly impacts the crew’s life and property. Therefore, it is urgent to design a method to detect the fire phenomenon in the engine room in real time. To address this problem, a machine vision model (CWC-YOLOv5s) is proposed, which can identify early fires through smoke detection methods. Firstly, a coordinate attention mechanism is added to the backbone of the baseline model (YOLOv5s) to enhance the perception of image feature information. The loss function of the baseline model is optimized by wise intersection over union, which speeds up the convergence and improves the effect of model checking. Then, the coordconv coordinate convolution layer replaces the standard convolution layer of the baseline model, which enhances the boundary information and improves the model regression accuracy. Finally, the proposed machine vision model is verified by using the ship video system and the laboratory smoke simulation bench. The results show that the proposed model has a detection precision of 91.8% and a recall rate of 88.1%, which are 2.2% and 4.6% higher than those of the baseline model. Full article

The aim of this study was to evaluate the impact of oleic acid supplements on the liver metabolome of hybrid grouper fingerlings (Epinephelus fuscoguttatus × Epinephelus lanceolatus) challenged with Vibrio vulnificus. Oleic acid was used as a fish feed supplement because it has been reported to enhance the immune response of fish. After six weeks of feeding trials with the control and experimental diets (oleic acid immunostimulant), 10 fish were randomly selected from each treatment and challenged with V. vulnificus by immersion for 30 min. After seven days of post-bacterial challenge, the liver samples of surviving infected groupers were dissected and used for metabolomics fingerprinting using liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (LC-qTOF-MS). The results were then analyzed using MetaboAnalyst 5.0 and SIMCA+P software. From the analyses conducted, out of 639 primary metabolites detected, a total of 66 metabolites were significantly identified from the liver samples of grouper fed control and oleic acid diets. Further analysis also showed that the control and oleic acid diets have significantly different metabolites by the discriminating clustering of samples based on the PLS-DA analysis. Based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, the known metabolites pathways with high impact values are alanine, aspartate, and glutamate metabolism (0.13) followed by purine metabolism pathways (0.05). Moreover, out of these highly impacted metabolic pathways, L-glutamine (8.71%), L-lysine (4.05%), L-carnitine (11.53%), and inosine (10.49%) were the several metabolites that were highly abundant in the liver sample of surviving infected hybrid groupers fed with dietary oleic acid. The changes of metabolites contributed to improving the immune system of the fish. Thus, our results advance our understanding of the immunological regulation of the hybrid groupers’ immune response toward oleic acid immunostimulants against Vibrio infection. Full article

The Lithuanian coastal area is divided by the jetties of the Port of Klaipėda and represents two geomorphologically distinct parts. Local companies and institutions contribute to shaping the coastal area through infrastructure development. Awareness of the changes in the coastal zone can play an important role in the planning and economic feasibility of activities in the Klaipėda coastal region. Therefore, developing a notification system that provides long– and short–term monitoring data for the Lithuanian coastal zone is necessary. In order to do so, the authors intend to create a system that should provide a link between long– and short–term observation and monitoring data for stakeholders, such as wind speed and direction, wave direction and significant height, water and air temperature, atmospheric pressure, sediment size, and distribution, height above sea level, shoreline position, beach width, change in beach protection measures, beach wreckage, and marine debris management, in order to provide timely notifications to end users. Full article

To address global challenges, research on the safety of polar navigation is indispensable. However, most of studies focus on traditional surface vessels, with few research studies on submarine. The dynamic response of submarine during surface navigation in floating ice channels under special conditions is studied in this work. Firstly, a model of the submarine incorporating an intact internal frame was established. Subsequently, the FEM-ALE coupled method was employed to simulate the structure-ice interaction, and the obtained results was verified by the Colbourne method. Then, the parametric study (navigation speed, ice thickness, and floating ice size) were analyzed from the perspectives of ice resistance, stress and plastic strain. Finally, an empirical equation suitable for the interaction between submarine and floating ice during surface navigation is improved based on the Colbourne method. Full article

This paper investigates the performance of a fully passive flapping foil device for energy harvesting in a free surface flow. The study uses numerical simulations to examine the effects of varying submergence depths and the impact of monochromatic waves on the foil’s performance. For the numerical simulations, a in-house artificial compressibility two-phase solver is employed and coupled with a rigid body dynamic solver. The results show that the fully passive flapping foil device can achieve high efficiency for submergence depths between 4 and 9 chords, with an “optimum” submergence depth where the flapping foil performance is maximised. The effects of regular waves on the foil’s performance were also investigated, showing that waves with a frequency close to that of the natural frequency of the flapping foil-aided energy harvesting. Overall, this study provides insights that could be useful for future design improvements for fully passive flapping foil devices for energy harvesting operating near the free surface. Full article

International Association of Classification Societies (IACS) is responsible for many of the ship strengthrules including both generally applicable Unified Strength Requirements (UR-S) and other rules specific for various ship types. For historical reasons, there have been different structural strength requirements regarding hatch covers, hatch coamings, and related structures in IACS UR S21, S21A, and CSR (Common Structural Rules for bulk carriers and oil tankers). This paper presents the work carried out to improve the related rules and thereby the development of the unified strength requirements for hatch covers. Firstly, related IACS rules are reviewed and compared, and some major improvements to the buckling formulations are proposed for improved accuracy. Secondly, with UR S35 being developed as a unified buckling toolbox, the unified strength requirements for hatch covers—UR S21 (Rev.6, complete revision)—are developed with a standardized interface of reference to UR S35 for buckling assessment. Finally, the numerical calculations of typical stiffened panels and full hatch covers are carried out for rule verification and consequence assessment, which demonstrates that more rational hatch cover designs can be achieved based on UR S21 (rev 6). Full article

Container ports play a crucial role in global maritime trade by serving as key transportation hubs for the movement of goods. Their performance differs due to unique local characteristics, creating a need for benchmarking to improve. Trends in trade patterns, supply chains and maritime transport operations can substantially impact on the cargo handling requirement at ports and therefore port performance. The aim of this research is two-fold; first, to examine the current situation, main trends and disruptions affecting maritime container transport and ports, and second, to investigate the key criteria for assessing and benchmarking port performance. Regarding the first objective, for the investigation of the global trends in the liner shipping and container port sector, desk research is performed. Regarding the second, a framework is developed by identifying five areas of interest based on the strategic value of data and selecting the best available data. This allows creating a two-layer data framework that enables the collection of data at the country and port level. The developed framework is applied to gather relevant data points for various container ports, and allows drawing conclusions on the performance of the framework. The results of this research contribute to the understanding of container port performance and may serve as a valuable resource for port operators and researchers in the field. By examining the specific factors that influence port performance, this study provides a foundation for enhancing the comparability of container port operational performance. Full article

With the continued development of artificial intelligence technology, unmanned surface vehicles (USVs) have attracted the attention of countless domestic and international specialists and academics. In particular, path planning is a core technique for the autonomy and intelligence process of USVs. The current literature reviews on USV path planning focus on the latest global and local path optimization algorithms. Almost all algorithms are optimized by concerning metrics such as path length, smoothness, and convergence speed. However, they also simulate environmental conditions at sea and do not consider the effects of sea factors, such as wind, waves, and currents. Therefore, this paper reviews the current algorithms and latest research results of USV path planning in terms of global path planning, local path planning, hazard avoidance with an approximate response, and path planning under clustering. Then, by classifying USV path planning, the advantages and disadvantages of different research methods and the entry points for improving various algorithms are summarized. Among them, the papers which use kinematic and dynamical equations to consider the ship’s trajectory motion planning for actual sea environments are reviewed. Faced with multiple moving obstacles, the literature related to multi-objective task assignment methods for path planning of USV swarms is reviewed. Therefore, the main contribution of this work is that it broadens the horizon of USV path planning and proposes future directions and research priorities for USV path planning based on existing technologies and trends. Full article

The interim guidelines of second-generation intact stability criteria and their explanatory note were issued by the IMO in 2022. However, due to their complexity, the direct stability assessments of broaching and loss of stability still need to be made easier for users. Therefore, the mathematical models for broaching and loss of stability in astern seas are studied in this paper. Firstly, a time-domain 6 DOF numerical model is adopted, combining seakeeping and maneuvering mathematical models. Secondly, the hydrodynamic forces, heave, and pitch motions are obtained by an enhanced strip method with the upright hull at different speeds in the frequency domain. Then, their time-domain values are transferred from their frequency-domain values with the speed variation considered. Thirdly, the time-domain varied wet hull in waves is captured by the 6 DOF ship motion. Then, the Froude–Krylov and the hydrostatic forces in the surging, swaying, rolling, and yawing directions are simulated considering the wave pressure around the wet hull. Fourthly, the exposure of the twin rudders and the wave-particle velocity are considered for predicting broaching. Finally, the calculated results are compared with the published results. The results show that the time-domain 6 DOF coupled numerical model can be unified for predicting broaching and loss of stability in the astern seas. Full article

In this study, an intelligent hybrid algorithm based on deep-reinforcement learning (DRL) is proposed to achieve autonomous navigation and intelligent collision avoidance for a smart autonomous marine surface vessel (SMASV). First, the kinematic model of the SMASV is used, and clauses 13 to 17 of the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) are introduced. Then, the electronic chart is rasterized and used for path planning. Next, states, actions, and reward functions are designed, and collision avoidance strategies are formulated. In addition, a temperature factor and a constrained loss function are used to improve the soft actor–critic (SAC) algorithm. This improvement reduces the challenges of hyperparameter adjustment and improves sampling efficiency. By comparing the improved SAC algorithm with other deep-reinforcement learning (DRL) algorithms based on strategy learning, it is proved that the improved SAC algorithm converges faster than the other algorithms. During the experiment, some unknown obstacles are added to the simulation environment to verify the collision-avoidance ability of the trained SMASV. Moreover, eight sea areas are randomly selected to verify the generalization ability of the intelligent-navigation system. The results show that the proposed method can plan a path for the SMASV accurately and effectively, and the SMASV decision-making behavior in the collision-avoidance process conforms to the COLREGs in both unknown and dynamic environments. Full article

With the increasing volume of ship traffic, maritime traffic safety is facing a great challenge because the traffic in port becomes more and more crowded and complicated, which will make ship collisions more likely to happen. As a special water area of the port, the anchorage is also threatened by collision risk all the time. For accurately assessing the collision risk in anchorage and its adjacent waters in real time, this paper proposed an analytic model based on Automatic Identification System (AIS) data. The proposed anchorage collision risk model was established in microscopic, macroscopic, and complexity aspects, which considered ship relative motion, anchorage characteristics, and ship traffic complexity, respectively. For validation, the AIS data of the anchorages near the Shandong Peninsular were used to carry out a series of experiments. The results show that the proposed model can identify the anchorage collision risk effectively and has an advantage in dealing with complicated scenarios. The proposed anchorage collision risk model can help maritime surveillance better monitor and organize the ship traffic near the port and provide mariners with a reference about the collision risk situation of the anchorage on their route, which are important to improving maritime traffic safety. Full article

Oil spills pose a significant threat to the marine ecological environment. The intelligent interpretation of synthetic aperture radar (SAR) remote sensing images serves as a crucial approach to marine oil spill detection, offering the potential for real-time, continuous, and accurate monitoring. This study makes valuable contributions to the field of marine oil spill detection based on low-quality SAR images, focusing on the following key aspects: (1) We thoroughly analyze the Deep SAR Oil Spill dataset, known as the SOS dataset, a prominent resource in the domain of marine oil spill detection from low-quality SAR images, and rectify identified issues to ensure its reliability. (2) By identifying and rectifying errors in the original literature that presented the SOS dataset, and reproducing the experiments to provide accurate results, benchmark performance metrics for marine oil spill detection with low-quality SAR remote sensing images are established. (3) We propose three progressive deep learning-based marine oil spill detection methods (a direct detection method based on Transformer and UNet, a detection method based on FFDNet and TransUNet with denoising before detection, and a detection method based on integrated multi-model learning) and the performance advantages of the proposed methods are verified by comparing them with semantic segmentation models such as UNet, SegNet, and DeepLabV3+. (4) We introduce a feasible, highly robust and easily scalable system architecture approach that effectively addresses practical engineering applications. This paper is an important addition to the research on marine oil spill detection from low-quality SAR images, and the proposed experimental method and performance details can provide a reference for related research. Full article

T-foils with active control systems can adjust their attack angle according to the movement of the ship in real time, providing higher lift force and improving the seakeeping performance of a ship. The optimization of the control signal and that of the control method have an important influence on the effect of active T-foils. In this paper, the control method of the T-foil’s swinging angle is established and optimized on the basis of model testing in order to increase the effect of the T-foil. First, the governing equation is introduced by establishing the proportional relationship between the angular motion of the hull and the lift moment of the T-foil. On the basis of the model of the T-foil’s lift force, the governing equation of the T-foil’s swinging angle is deduced and simplified using the test results of the ship model with a passive T-foil and without a T-foil. Then, the active T-foil control system is established by comparing the effects of T-foils with different control signals. Finally, the efficacies of the passive and active T-foil are reported and discussed. It is found that the pitch angular velocity is a more appropriate signal than the pitch angle and pitch angular acceleration. T-foils with pitch angular velocity control can decrease the vertical motion response in the resonance region of a ship’s encounter frequency by more than about 20% compared to the case of the bare ship model, while also increasing the anti-bow acceleration effect by more than 15% compared to the case of passive control. The results obtained by model testing have a certain guiding significance for specific engineering practices. Full article