Hydraulic turbines can convert tidal current energy into electric energy, and the addition of a deflector cover to the turbine can improve the efficiency of the turbine's energy harvesting. The angle of the inlet section and the angle of the outlet section of the deflector will further affect the final energy-acquisition efficiency.A threedimensional numerical model for turbine flow field analysis is established, and the RNG k-ε turbulence model is selected by CFD method, and the best angles of inlet section and outlet section are analysed by the method of sliding mesh to obtain the best angle of inlet section and outlet section separately, and then three groups of angles are selected near the best angle of inlet section and outlet section to make orthogonal comparisons. The energy acquisition efficiency of the turbine is calculated at different angles of the inlet and outlet sections of the deflector, and the turbine streamline distribution, velocity and pressure maps are analysed with and without the deflector.The study shows that the deflector can play the role of convergence of the downstream flow, which can improve the efficiency of the turbine energy acquisition, and the maximum energy acquisition efficiency is at the inlet angle of 29° and the outlet angle of 40 °, and the maximum energy acquisition efficiency can be improved by about 32 percent.

Forecasting port container throughput is crucial due to its impact on economic development. Socio-economic factors, which introduce uncertainty, are increasingly integrated into throughput forecasting. The complexity of common multivariate forecasting models significantly affects accuracy, yet few studies compare their performance on the same time series for throughput modeling. This study implements, evaluates, and compares the performance of eight multivariate forecasting models for port throughput within a proposed multiple-input single-output (MISO) system, chosen for their frequent use in container throughput research. It investigates two data preprocessing approaches: Random Forest Variable Importance Method (RF-VIM) and a Multi Lagged Value approach. The comparison uses six error metrics: normalized root mean squared error, mean absolute error, mean absolute percentage error, mean error, and root mean percentage error. Performances are discussed, and recommendations for adopting a suitable model are provided.

The issue of marine accidents can be based on the traffic/distribution of vessels in the waterways. These accidents are often associated with human and financial losses and require special attention. Usually, these accidents include collision of two fishing vessels with each other, collision of a fishing vessel with other types of vessels in the course and collision of a fishing vessel with an obstacle in the course (Yancai, et al, 2020). In this article, we first want to deal with analysing the recorded statistical samples in 7 fishing areas in coastal waters of South Korea in 2023, while fuzzy clustering them. Then, according to analysing the sample data and finding the probabilistic structure and the membership of data sets the determined clusters, through Monte Carlo simulation, we will generate similar data in each of the 7 studied regions and model them in unsupervised mode. The generated data by Monte Carlo simulation based on the statistical distribution will able us to study the reality of distribution and possible accident in our target areas and find the model for future demands. We show that how the simulated data reduce the cost of data analysis and deliver us the facts of clusters for fishing vessels collisions. Finally, we reach to the most notified area for preventing the fishing vessels accidents and to make more preparations for reducing the human and costly damages in future activities.

Electric-propulsion systems for ships, also known as electric propulsion devices, represent the current direction of development for maritime power. Issues concerning the environment and fuel economy have compelled the maritime transport sector to seek solutions that reduce emissions and improve fuel efficiency. In this process, power electronics technology plays a significant role in the propulsion systems of ships. Selecting an efficient battery system is of great importance for enhancing the cruising range of yachts and minimizing environmental impact. The battery model is crucial for revealing the working principles of batteries, and it is extremely critical for the application and development of battery technology. The Battery Management System (BMS) serves a crucial regulatory function, optimizing both the safety and performance of battery cells. Central to its operation is the precise estimation of the battery's State of Charge (SOC), a process dependent on an exacting battery model. This system not only enhances longevity and reliability but also ensures that energy storage solutions meet high standards of efficacy. This study focused on testing the impedance characteristics of lithium-sulfur batteries (LSB) at various SOC points and establishing first- and second-order RC equivalent circuit models. The model parameters were identified through experimental data. Subsequently, a simulation platform was constructed using MATLAB/Simulink to simulate the behavior of LSB under a constant current discharge condition. The simulation results showed that the second-order RC model had significantly lower errors than the first-order model, demonstrating higher accuracy. These achievements can provide technical support for the research of energy storage systems in the green aviation and maritime industries.

Shipping universally accounts for 80% of global trade and 70% in price terms. While in Vietnam, not only the maritime transport market share, especially with international goods, has decreased significantly but also the maritime transport volume of national fleet tends to decrease. Therefore, the solutions of increasing the transport volume along with regaining the transport market share are a major concern for Vietnam's shipping development plan. With the purpose of finding these important solutions, this research aims at investigating the factors affecting the national fleet’s transport volume by ARDL model based on Vietnamese fleet’s transport volume quarterly data from 2008 to 2022. The results demonstrate that the deadweight tonnage of the fleet and GDP are the two fundamental factors which have positive influences on transport volume of Vietnamese shipping fleet in both the short run and the long run. Then, the paper proposes solutions how these two variables, especially the tonnage of the fleet increase the maritime transport market share as well. The findings provide clear directions to the policy makers and the shipping company in proposing relevant solutions for shipping development plan.