Search Results (217)

Despite navigation advancements in enhanced sensor utilization and increased focus on maritime training and education, most marine accidents still involve collisions with high human involvement. Furthermore, navigators’ knowledge and application of the most often misunderstood Rule 10 Traffic Separation Schemes (TSS) according to the Convention on the International Regulations for Preventing Collisions at Sea (COLREG) represents the first focus in this study. To provide insight into the level of understanding and knowledge regarding COLREG Rule 10, a customized, worldwide survey has been created and disseminated among marine industry professionals. The survey results reveal a notable knowledge gap in Rule 10, where we initially assumed that more than half of the respondents know COLREG regulations well. According to the probability calculation and chi-square test results, all three categories (OOW, Master, and others) have significant rule misunderstanding. In response to the COLREG misunderstanding, together with the increasing density of maritime traffic, the implementation of Decision Support Systems (DSS) in navigation has become crucial for ensuring compliance with regulatory frameworks and enhancing navigational safety in general. This study presents a structural approach to vessel prioritization and decision-making within a DSS framework, focusing on the classification and response of the own vessel (OV) to bow-crossing scenarios within the TSS. Through the real-time integration of AIS navigational status data, the proposed DSS Architecture offers a structured, rule-compliant architecture to enhance navigational safety and the decision-making process within the TSS. Furthermore, implementing a Fall-Back Strategy (FBS) represents the key innovation factor, which ensures system resilience by directing operator response if opposing vessels disobey COLREG rules. Based on the vessel’s dynamic context and COLREG hierarchy, the proposed DSS Architecture identifies and informs the navigator regarding stand-on or give-way obligations among vessels. Full article

With the global increase in maritime activities, the frequency of maritime accidents has risen, underscoring the urgent need for faster and more efficient search and rescue (SAR) solutions. This study presents an intelligent unmanned aerial vehicle (UAV)-based maritime rescue system that combines GPS-driven dynamic path planning with vision-based dual-target detection and tracking. Developed within the Gazebo simulation environment and based on modular ROS architecture, the system supports stable takeoff and smooth transitions between multi-rotor and fixed-wing flight modes. An external command module enables real-time waypoint updates. This study proposes three path-planning schemes based on the characteristics of drones. Comparative experiments have demonstrated that the triangular path is the optimal route. Compared with the other schemes, this path reduces the flight distance by 30–40%. Robust target recognition is achieved using a darknet-ROS implementation of the YOLOv4 model, enhanced with data augmentation to improve performance in complex maritime conditions. A monocular vision-based ranging algorithm ensures accurate distance estimation and continuous tracking of rescue vessels. Furthermore, a dual-target-tracking algorithm—integrating motion prediction with color-based landing zone recognition—achieves a 96% success rate in precision landings under dynamic conditions. Experimental results show a 4% increase in the overall mission success rate compared to traditional SAR methods, along with significant gains in responsiveness and reliability. This research delivers a technically innovative and cost-effective UAV solution, offering strong potential for real-world maritime emergency response applications. Full article

Waterway tunnels, a novel type of infrastructure designed for inland waterways in mountainous gorge regions, have seen rapid development in recent years. However, their unique structural characteristics and specific shipping activities pose significant risks in the event of an accident. To enhance the scientific rigor and efficiency of emergency responses to vessel incidents in tunnels, this study focuses on fire accidents in waterway tunnels. Considering the unique challenges of emergency response in such scenarios, we propose an emergency response framework using Business Process Modeling Notation (BPMN). The framework is mapped into a Petri net model encompassing three key stages: detection and early warning, emergency response actions, and recovery. A Colored Hierarchical Timed Petri Net (CHTPN) emergency response model is then developed based on fire incident data and emergency response time functions. Furthermore, a homomorphic Markov chain is employed to assess the network’s validity and performance. Finally, optimization strategies are proposed to improve the emergency response process. The results indicate that the emergency response network demonstrates strong accessibility, effectively mitigating information bottlenecks in critical stages of the response process. The network provides accurate and rapid decision support for different tunnel ship fire scenarios, efficiently and reasonably allocating emergency resources and response teams, and monitoring the operation of key emergency response stages. This enhances the efficiency of emergency operations and provides robust support for decision-making in waterway tunnel fire emergencies. Full article

Ocean-going vessels rely on marine diesel engines, referred to as the main engine, to carry the vessel’s load and ensure safe travel. These engines play a critical role, as their operation impacts on all aspects of the vessel’s functionality. To meet increasing demands for extended run times while maintaining reliability, it is essential to address the risks of main engine failure. Previous studies have highlighted numerous accidents resulting from such failures. Consequently, the reliability of the main propulsion engine is a crucial component of safe vessel operation. This study addresses the lack of methodologies for predicting engine reliability using failure running hours (FRHs). A data-driven model was developed using FRH data collected from marine engineers during on-board maintenance operations. Additionally, fault tree analysis (FTA) was employed to calculate the reliability of individual subsystems and the overall main propulsion engine. The findings indicate that the lube oil system, freshwater cooling system, scavenge system, and fuel system reach 0% reliability at approximately 2000 h, 14,000 h, 2500 h, and 1400 h of operation, respectively. Additionally, the reliability of the main propulsion engine drops to 0% after around 900 h of operation. By incorporating this prediction model, ship operators can better schedule maintenance, significantly enhancing engine reliability and reducing maritime accidents. This approach contributes to safer and more efficient operations for commercial marine systems. This study represents a vital step toward improving the reliability of ocean-going vessels. Full article

The Beluga Reefer accident underscores the hidden risks associated with complex wave–current interactions along South Africa’s coastline, particularly in the Agulhas Current retroflection zone. This study utilized ERA5 reanalysis and CMEMS surface current data to analyze the sea state conditions at the time of the accident. While the wind speeds were moderate (5.42 m/s) and windsea heights were relatively low (0.99 m), the significant wave height (Hs) peaked at 3.24 m, with a strong opposing NE Agulhas Current (1.27 m/s) inducing wave steepening and group compression, creating transient hazardous conditions despite a low overall wave steepness (0.0209). Just before the accident, the directional disparity (Δθ) between the swell and windsea systems collapsed sharply from 167.45° to 8.98°, providing a false sense of stability. The synergy of these conditions at the accident site triggered the event, demonstrating that visually aligned wave conditions can mask dangerous underlying interactions. These findings highlight the critical need for integrated wave–current diagnostics in maritime forecasting to better predict complex hazards and enhance vessel safety. Full article

High-completeness ship trajectory data are critical for analyzing navigation behavior characteristics and enhancing effective maritime management. To address the common issues of prolonged AIS data loss for small coastal vessels in nearshore waters, an intelligent trajectory repairing model based on the artificial potential field-enhanced A* algorithm (APF-A*) has been proposed. Kernel density estimation was utilized to quantify the distribution characteristics of vessels, thereby constructing an attractive potential field based on historical trajectories and a repulsive potential field based on coastal terrain. Speed distribution characteristics were extracted from historical trajectory points in different regions; on the basis of this, the A* algorithm, integrated with attractive and repulsive fields, was proposed to repair missing trajectory segments. Based on the speed distribution characteristics, time intervals, and distance information, the temporal information of the vessel trajectories was effectively reconstructed. The present study fills the research gap in AIS data reconstruction for small coastal vessels in complex coastal waters. A case study has been conducted in Luoyuan Bay, Fujian Province, China, to further validate the proposed model. The results demonstrate that the trajectory repairing model based on the artificial potential field-enhanced A* algorithm outperformed other models. More specifically, the Hausdorff Distance and Dynamic Time Warping (DTW) metrics decreased by 81.67% and 91.56%, respectively. The present study shares useful insights into intelligent maritime management and further supports accident prevention in coastal waters. Full article

The frequent occurrence of collision accidents between merchant and fishing vessels in China’s offshore waters not only threatens human lives and property, but also disrupts shipping and fishing activities and may cause marine environmental pollution. To effectively reduce such accidents and increase maritime safety in Chinese coastal waters, this study integrates association rules with complex networks to develop a directed weighted network of causal factors. Grounded theory and the Human Factors Analysis and Classification System (HFACS) are applied to identify and categorize causal factors from 152 collision accident investigation reports. Potential causal relationships are mined using the association rule, which is then applied to construct the causal network. Finally, the topological characteristics of the network are analyzed. The results reveal that serious negligence in lookout, failure to assess collision risks properly, and failure to adopt a safe speed significantly impact collision accidents. These findings highlight the necessity of implementing targeted preventive measures to address critical factors. This study provides valuable insights for maritime stakeholders to develop effective strategies. Full article

Fishing vessels are essential for the activities of catching, moving, and storing fish. However, fishing vessel accidents claim thousands of deaths every year. This study presents a novel integrated safety monitoring and early warning system designed for fishing vessels, offering significant advancements in maritime safety through real-time alerts based on vessel attitude motion and environmental conditions. The innovation of the system lies in its dual-subsystem architecture: a sensing terminal equipped with a nine-axis sensor, temperature and humidity sensors, a GPS module, and a surveillance camera collects critical data, while a decision support subsystem processes this information via a fuzzy logic-based algorithm to generate a “danger score”. This score quantifies the vessel’s safety status, enabling the system to trigger alerts through SMS and web notifications when predefined thresholds are exceeded. Field trials in the Zhoushan Sea area confirmed the system’s effectiveness in accurately predicting safety hazards and providing timely alerts. The results highlight its potential to enhance operational safety and contribute to the digitization of fisheries management by offering reliable real-time data on vessel conditions. The system’s modular and cost-efficient design ensures it is scalable and adaptable for widespread use across the fishing industry. Our study addresses the limitations of existing technologies by providing a balanced solution that combines comprehensive sensing capabilities with real-time responsiveness and cost-effectiveness, offering a practical and innovative approach to improve fishing vessel safety. Full article

The creep properties of 15Kh2NMFAA nuclear WWER (water–water energetic reactor) vessel steel in the range of 500–1200 °C temperatures, which may appear during severe nuclear reactor accidents, were investigated. The present paper attempts to analyze the creep curves obtained from tensile testing at high temperatures using the Larson–Miller parametric technique. The power law rate and material coefficient of Norton’s equation with the Monkman–Grant relationship coefficient were found for each test temperature. It is shown that in accordance with the Monkman–Grant relationship coefficient values, changing the creep type from dislocation glide to high temperature dislocation climb occurs in the temperature range of 600–700 °C, which leads to a slope change in the Larson–Miller parameter plot and the conversion of steel creep behavior. It is also shown that in the range of $A_1$–$A_3$ temperatures, a stepwise change in creep characteristics occurs, which is associated with phase transformations. In addition, the constancy of the product of the time to rupture ${\tau }_r$ and the minimum creep rate ${\dot{ϵ}}_{min}$ in the ranges of 600–700 °C and $A_3$—1200 °C was noted. The proposed approach improves the accuracy of time to rupture estimation of 15Kh2NMFAA steel by at least one order of magnitude. Based on the research results, the calculated dependence of the steel’s long-term strength limit on temperature was obtained for several time bases, allowing us to increase the accuracy of material survivability prediction in the case of a severe accident at a nuclear reactor. Full article

The water environment is a dynamic domain critical to global transportation and commerce, where seaplanes operate during take-offs, landings, and ground operations, often near maritime traffic. Canada’s vast remote regions and unique geography increase reliance on seaplanes, especially for private and recreational purposes. This article examines the intersection of aviation and maritime operations through a mixed-methods approach, analyzing seaplane safety on waterways using quantitative and qualitative methods. First, data from 1005 General Aviation (GA) seaplane accidents in Canada (1990–2022) are analyzed, revealing 179 fatalities, 401 injuries, and 118 destroyed aircraft—significant given that seaplanes comprise under 5% of GA aircraft. Of these, 50.35% occurred while the seaplane was not airborne. Second, insights from interviews, focus groups, and questionnaires involving 136 participants are explored through thematic and content analysis. These capture pilot concerns that are not evident in accident data, such as hazards from jet ski interactions and disruptive boat wakes. The findings highlight risks like limited visibility and maneuverability during waterborne take-offs, worsened by seaplanes’ lack of priority over maritime vessels in shared spaces. This article concludes with recommendations for both the seaplane and maritime communities, including increasing awareness among boaters about the presence and operations of seaplanes, as well as regulatory adjustments, particularly considering the right of way. Full article

Maritime safety is a critical concern for the transport sector and remains a key challenge for the international shipping industry. Recognizing that maritime accidents pose significant risks to both safety and operational efficiency, this study explores the application of big data analysis techniques to understand the factors influencing maritime transport accidents (MTA). Specifically, using extensive datasets derived from vessel performance measurements, environmental conditions, and accident reports, it seeks to identify the key intrinsic and extrinsic factors contributing to maritime accidents. The research examines more than 90 thousand incidents for the period 2014–2022. Leveraging big data analytics and advanced statistical techniques, the findings reveal significant correlations between vessel size, speed, and specific environmental factors. Furthermore, the study highlights the potential of big data analytics in enhancing predictive modeling, real-time risk assessment, and decision-making processes for maritime traffic management. The integration of big data with intelligent transportation systems (ITSs) can optimize safety strategies, improve accident prevention mechanisms, and enhance the resilience of ocean-going transportation systems. By bridging the gap between big data applications and maritime safety research, this work contributes to the literature by emphasizing the importance of examining both intrinsic and extrinsic factors in predicting maritime accident risks. Additionally, it underscores the transformative role of big data in shaping safer and more efficient waterway transportation systems. Full article

As terrestrial resources become increasingly scarce, the exploration and utilization of marine resources have become crucial for ensuring a stable resource supply. A maritime A-Frame is a specialized lifting mechanism mounted on the stern of a vessel, designed for deploying and retrieving heavy loads during subsea exploration. Real-time monitoring of the stress of A-Frames is essential for identifying potential failures and preventing accidents. This paper presents a stress-monitoring campaign conducted on a maritime A-Frame during a deep-sea mining project in the South China Sea. Fiber Bragg Grating (FBG) strain sensors were installed on the A-Frame to measure its stress responses throughout the deep-sea mining operation. The stress variations observed during the deployment and retrieval of a deep-sea mining vehicle were analyzed. The results indicate that the stress caused by the swinging motion of the A-Frame was significantly higher than that generated by the lifting and deployment of the mining equipment. Additionally, a finite element model (FEM) of the A-Frame was developed to estimate the stress of the hot spots by integrating the measured strain data. The analysis confirmed that the maximum stress experienced by the A-Frame was well below the allowable threshold, indicating that the structure had sufficient strength to withstand operational loads. In addition, the swing angle of the A-Frame significantly affects the stress value of the A-Frame, while lifting the mining vehicle has a very slight effect. Thus, it is advisable to accelerate the deployment and retrieval speeds of the mining vehicle and minimize the outward swing angle of the A-Frame. These findings provide valuable insights for optimizing the design and ensuring the safe operation of maritime A-Frames in deep-sea mining exploration. Full article

Lead-bismuth eutectic (LBE) is a eutectic alloy of lead (44.5 at%) and bismuth (55.5 at%) that can be used as the coolant for the fast nuclear reactors. In the event of specific conditions or even accidents of the reactors, the temperature of liquid LBE decreases, and it may undergo solidification and volume expansion during the aging process after solidification, which can easily cause damage to the reactor’s internal structure as well as the reactor vessels. In this study, the microstructure and mechanical properties of solidified LBE obtained at different cooling rates are systematically investigated after different aging times. It was found that the internal structure of LBE after aging remained a eutectic microstructure, consisting of the γ-phase (Bi-rich phase) and β-phase (Pb₇Bi₃). After a long period of static aging, the white γ-phase precipitated into the black β-phase, which further confirms the phase transition mechanism. Meanwhile, the acceleration of the cooling rate can aggravate volume expansion. As the aging time increases, there is no significant difference in the compressive yield strength σ of the LBE samples with the same cooling rate and only a certain degree of fluctuation. The elastic modulus E also shows similar results, indicating that aging time has a minor effect on the compressive yield strength σ and elastic modulus E of the LBE. With the increase in cooling rate, the compressive yield strength σ shows an upward trend, while the elastic modulus E is not significantly affected, with a small amplitude of fluctuation. Meanwhile, the hardness of LBE samples after long-term aging treatment is enhanced. After long-term aging, the overall density of the LBE samples shows a decreasing trend, the density fluctuation range of the fast cooling rates (5 K/min and 10 K/min) are significantly larger than that of the slow cooling rates. The decrease in density leads to volume expansion of the LBE during the aging process after solidification. Full article

Human reliability is a key factor in long-term sustainability, especially for tasks that are critical to safety. It is also evident that human behavior is often the main or significant cause of system failures. Identifying human error is challenging, particularly when it comes to determining the exact moment when an error occurred that led to an accident, as errors develop over time. It is essential to understand the causes and mechanisms of human errors. This finding is not new; for over 30 years, it has been recognized that human operations in safety-critical systems are so important that they should be modeled as part of risk assessment in operation. This article discusses various HRA methodologies and argues that further research and development are necessary. An example of selected HRA techniques will be demonstrated through a case study on acetylene filling activities. When filling acetylene into pressure vessels or cylinders, it is critically important to analyze the reliability of the human factor, as this process involves handling a highly explosive gas. Irresponsibility, lack of training, or incorrect decision-making can lead to severe accidents. Any deficiencies in this process can result in not only equipment damage but also endanger the health and lives of people nearby. This case may also suggest potential improvements to existing guidelines, international standards, and regulations, which often require the consideration of a wider range of ergonomic factors in the risk assessment process. Full article

The global demand for liquefied natural gas (LNG) has led to a significant increase in the number of LNG carriers (LNGCs), consequently elevating the risk of operational accidents. Unlike conventional vessels, LNGCs present a high risk of fire and explosion and involve extensive repair times and costs due to the complex structure of the cargo containment system (CCS). This study investigates the effects of seawater exposure on the uni-axial compressive properties of plywood used in LNGC CCS structures, with the goal of establishing material strength criteria that could reduce repair requirements. The analysis focuses on the NO96 CCS, which incorporates the highest volume of plywood among existing designs. In this configuration, compressive strength is a critical design parameter. Therefore, the mechanical response of plywood was evaluated under both room temperature and cryogenic conditions (−163 °C), simulating the LNG operating environment. The results demonstrate that plywood exhibited increased compressive strength after three hours of seawater and saltwater immersion, although the rate of improvement diminished with extended exposure. In contrast, specimens immersed in distilled water showed a consistent reduction in compressive strength. Furthermore, cryogenic temperatures significantly enhanced the compressive strength compared to ambient conditions. This study establishes a methodology for assessing the mechanical performance of plywood under marine and cryogenic conditions, contributing to its reliable application in LNG carrier structures. Full article