With the increasing demand for energy conservation and emissions reduction in the shipping industry, suctionbased turbine sails have emerged as a novel wind energy utilization technology and have become a research hotspot. This study focuses on the aerodynamic performance of suction-based turbine sails with the aim of investigating the effects of suction intensity and suction port position on their aerodynamic characteristics. By employing Computational Fluid Dynamics (CFD) numerical simulations using the Re-Normalization Group (RNG) k–ε turbulence model and the SIMPLE algorithm, this study provides a detailed analysis of lift and drag coefficients, pressure distribution, and vorticity distribution under various combinations of suction intensity (γ) and suction port position (α). The results show that variations in suction intensity significantly affect the lift and drag characteristics of the turbine sail, while changes in the suction port position directly influence the attachment and separation behavior of airflow on the sail surface. Furthermore, a synergistic effect is observed between γ and α—their interaction not only alters the flow distribution but also plays a critical role in determining the overall performance of the turbine sail.By comprehensively considering the influence of these two factors, the study draws key conclusions for optimizing the design of suction-based turbine sail, providing valuable theoretical insights and technical guidance for their practical application in wind-assisted marine propulsion.

The development of Jinhae New Port is expected to have positive effects on the local economy and foster the regional port logistics industry. However, since most of the port-related industry companies are located in the old downtown areas of Busan, such as Yeongdo and Jungang-dong, the main focus of the port will still remain in the old downtown of Busan even after the opening of Jinhae New Port. This study conducted basic research to maximize the benefits of the Jinhae New Port opening by exploring ways to establish Gyeongnam and Changwon as port logistics hubs. The specific research objectives included identifying target port-related industries and companies for attraction, as well as presenting the justification and rationale for establishing Gyeongnam and Changwon as port logistics hubs. The results indicated that the supply industry, ship management industry, ship repair industry, and shipbuilding equipment industry are sectors that Gyeongnam and Changwon should focus on attracting. The necessity of establishing Gyeongnam and Changwon as port logistics hubs is presented based on: 1) local tax revenue from the operation of Busan New Port, and 2) regional balanced development and the construction of a megacity. Specific implementation measures suggested include: 1) renaming the port, 2) attracting port-related industries, 3) seizing key agendas for port advancement, 4) establishing a smart port task force for the coexistence of ports, universities, and cities, and 5) enhancing the attractiveness of port cities to prevent population outflow.

The Magnus airfoil can convert wind energy into kinetic energy, driving the boat forward. The rotating cylinder at the airfoil's leading edge enhances lift and reduces drag, positioning it as a promising technology for boundary layer flow control. This study, based on the NACA0015 airfoil, employs Computational Fluid Dynamics (CFD) to investigate the effect of cylinder diameter on the aerodynamic performance of the Magnus airfoil. The Reynolds number is set to 4×10⁵, with an angle of attack of 18°, a rotational speed ratio of 1.4, and cylinder diameters ranging from 6% to 13% of the airfoil's chord length. Numerical simulations are conducted to analyze and compare the lift and drag characteristics, vorticity distribution, pressure distribution, and flow field structure for varying cylinder diameters. The results show that a high-speed rotating cylinder, when placed at the airfoil’s leading edge, effectively suppresses flow separation on the suction surface, delays boundary layer development, and enhances the overall aerodynamic performance of the airfoil. For the Magnus airfoil studied, the optimal diameter of the rotating cylinder at the leading edge is found to be 12% of the chord length.

The primary objective of the study is to analyze and evaluate the situation and trends of inland waterway traffic accidents in Vietnam from 2017 to 2024. The study employs reliable secondary data sources, which are analyzed using statistical methods and heatmap applications to examine and assess trends in inland waterway traffic accidents in Vietnam. The results indicate a steady increase in both the number and scale of inland waterway accidents nationwide over the years. Additionally, the accident-prone areas in key inland waterways will be identified. Based on these findings, the research team has proposed recommendations and solutions aimed at improving traffic safety on Vietnam's inland waterways.

With the rapid development of economic globalization and the shipping industry, seafarers have been working at sea for a long time, facing psychological problems such as loneliness, depression, and frustration, which pose serious threats to their physical and mental health. The occurrence of psychological symptoms among crew members during their service on board and during their vacations was analyzed through psychological surveys. Research has found that crew members are prone to psychological problems such as obsessive-compulsive symptoms, interpersonal sensitivity, depression, anxiety, hostility, and paranoia during their time on board. The two stages with a relatively high probability of developing psychological problems are: one month and 3-6 months after starting working on board. In response to these issues, some onboard management measures and shore-based support measures have been proposed.

To support the International Maritime Organization’s (IMO) 2050 greenhouse gas reduction targets, hybrid propulsion energy management systems (EMS)—which integrate multi-energy coordination and dynamic scheduling—have become a critical pathway for enabling low-carbon transitions and improving energy efficiency in the maritime sector. This paper conducts a comprehensive and structured analysis of EMS technologies applied to ship hybrid propulsion systems. It evaluates the functional roles of EMS under varying system architectures, synthesizes mainstream energy management strategies, and identifies current technological bottlenecks, thereby contributing theoretical foundations for the green transformation of the shipping industry. The study first examines representative hybrid propulsion architectures, detailing their technical characteristics to clarify the functional positioning and optimization priorities of EMS in each configuration. It then reviews prevailing energy management and control strategies, with a focus on their integration with artificial intelligence (AI) and the emergence of adaptive and data-driven approaches. Finally, the paper identifies key challenges in hybrid propulsion EMS, proposes future research directions, and offers practical recommendations to support the advancement and implementation of intelligent energy management technologies in maritime applications.

Due to cognitive differences, traditional perceptual engineering (KE) frequently relies too heavily on designers' experience in analyzing customers' emotional demands, which can result in product designs that deviate from users' expectations. This work suggests a thorough evaluation approach that combines the particle swarm optimization-support vector regression (PSO-SVR) model and perceptual engineering to increase the scientificity and precision of design choices. The approach first determines the subjective weights of users' emotional needs using spherical fuzzy hierarchical analysis (SFAHP). Next, it uses the entropy weighting method to determine the objective weights. Finally, it combines the subjective and objective data using game theory to produce a more rational evaluation system. Finally, the emotional prediction model based on PSO-SVR is constructed to realize the accurate mapping between emotional needs and design features. The empirical study shows that“speed”, “dynamic”and“luxury” are the core emotional demands of users, and the algorithm's prediction results are highly consistent with users' actual evaluations, which strongly verifies the accuracy of the model. Compared with the traditional KE method, the model better integrates subjective experience and objective data and provides more practical support for the design of flybridge yachts.

To address the issues of slow magnetization current tracking speed, prolonged magnetization time, and low accuracy during magnetic particle testing of ship castings, forgings, and welded components, this study designed a high-precision rapid current tracking control system. By integrating the predictive characteristics of the Newton interpolation algorithm with the robustness of PID control, a compound control algorithm with a pre-judgment mechanism was developed. An innovative three-phase zero-crossing detection circuit architecture was also implemented, combining high-speed A/D converters and CS5460 chips to optimize current tracking methods, resolving the conflict between initial tracking phase deviation and dynamic process overshoot in conventional approaches. Experimental results demonstrated that this method significantly improves magnetization speed, achieving target current tracking within 0.5 seconds with errors below 2%, meeting the design requirements for non-destructive testing in ship welding applications.

This study aims to identify and prioritize the key factors essential for transforming a traditional port into a smart port using the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) based on Chang’s extent analysis method. Based on the insights of 30 experts from Vietnam and South Korea, the research framework comprises three main dimensions, namely Policy, Operation, and Environment, which are further divided into ten sub-factors. The analysis revealed that Policy and Operation were perceived as the most critical dimensions, while Environment received relatively less emphasis. At the factor level, Automation & Intelligent Infrastructure ranked highest, followed by Investment & Financial Support, Productivity, and Regulatory Frameworks. In contrast, environmental factors such as Water & Waste Management and Emission Control were ranked lowest. Notably, Vietnamese and Korean experts all value the importance of advanced technology and investment capacity but still have some differences in prioritizing the other factors, reflecting differing national contexts and developmental stages. These findings offer strategic guidance for policymakers and port authorities in tailoring smart port development strategies to local conditions and priorities.

Efficient yet realistic ship routing is critical for reducing fuel consumption and greenhouse-gas emissions. However, conventional weather-routing algorithms often produce mathematically optimal routes that conflict with the paths mariners use. This study presents a hybrid approach that constrains physics-based weather routing within an AISderived maritime traffic network (MTN) built from one year of global Automatic Identification System data. The MTN represents common sea lanes as a graph of approximately 10,956 waypoints (nodes) and 17,561 directed edges. Using this network, an optimal low-emission route is computed via graph search and then compared against both a traditional unconstrained route and an advanced weather-routing model (VISIR-2). In a May transitionseason case (Busan–Singapore voyage), the AIS-constrained route reduced fuel consumption and CO₂ emissions by about 1.9% relative to the fastest feasible route, while closely following real traffic corridors (over 90% overlap with actual 2024 AIS tracks). While this 1.9% saving does not reach the high-end potential of an unconstrained, state-of-the-art model like VISIR-2 (which can demonstrate double-digit savings in certain conditions), it is achieved with an increase in transit time of ~6.5 h (≈3.2%). This represents a crucial trade-off, prioritizing operational realism and adherence to real-world traffic corridors over maximum theoretical efficiency.