Submerged breakwater, as an important marine engineering structure, can effectively absorb wave energy and is widely used in marine engineering protection. As a new type of breakwater, porous medium breakwater has a certain influence on wave propagation. However, the influence of multiple porous medium submerged breakwaters on extreme waves remains to be studied. In the study, considering effects of extreme waves generated by hurricanes or tsunamis, the influence of the solitary wave on the multiple semi-circle porous medium breakwater is systematically investigated. According to the computational fluid dynamics theory, a numerical tank is established, in which the porous medium module is coupled. The computational capability of this model is verified first. Then, depending on the model, a series of cases are carried out to study the effects of different porous medium breakwaters on the propagation of the solitary wave. The results show that when the porosity is 0.8, the force on the submerged breakwaters is the smallest, and the water level and the velocity decrease seriously. With the increase in the diameter of the submerged breakwater, the wave profile gradually becomes flat. The higher the wave height, the more serious the wave deformation after passing through the submerged breakwater.

Lifeboat is one of the most important life-saving equipment for escaping at sea when a ship is abandoned in an extreme emergency. An accurate drift model can help rescuers find the drift position of lifeboat in the shortest time, thus improving the efficiency of marine search and rescue (SAR) at sea and ensuring the safety of wrecked people. The purpose of this paper is to investigate the drift characteristics and to develop an accurate drift prediction model for the open lifeboat. First, large-scale drift experiments were conducted to analyze the drift characteristics with three 6.5-meter-long real-size open lifeboats in the South China Sea. Next, three drift prediction models of the lifeboats were developed using the least squares method based on the drift experimental data. Finally, the drift prediction models of the lifeboats were compared and evaluated using the Lagrangian method and Monte Carlo technique, respectively. Results indicate that the probability of positive crosswind leeway (CWL) of the open lifeboat is 47.5%. The jibing frequency is 6% per hour, and the maximum leeway divergence angle is 45°. These drift characteristics are very important for the prediction of the open lifeboat drift trajectory. The comparison results of three drift models show that the improved drift model is more accurate than the other two drift models for predicting drift trajectories of the open lifeboat, which can be directly applied to maritime search and rescue operations in the South China Sea.

The coastline of Shantou is tortuous, while the hydrodynamic environment is complicated. In this paper, the hydrodynamic model is established by the FVCOM (Finite Volume Coastal Ocean Model); the open boundary conditions such as water level, river, and wind field are the input; and the model is verified by tidal harmonic function. According to the previous research, the typhoon wind field with a 10-year return period is selected for storm surge simulation. When there is a bank, the accumulated water on the land cannot enter the ocean due to the block of the bank but accumulates on the inner side of the bank, resulting in higher accumulated water, but less than 0.5 m. In the aspect of sediment deposition, a sediment transport model is established to analyze the sediment deposition in Shantou Port and its surrounding waters. Some reasonable suggestions are put forward for the sediment deposition in Shantou. According to the simulation results, the following conclusions can be drawn: (1) In the case of typhoon storm surge in the return period of 10 years, the bank can effectively protect the inland. Still, accumulated water will collect near the bank. (2) The offshore water level will rise by 0.4 m after adding a bank. (3) The sediment in Shantou Bay mainly comes from the ocean sediment caused by tides, and the largest sedimentation occurs in the main channel.

Low-frequency alternating-current (LFAC) transmission has attracted significant attention for medium- and long-distance offshore wind integration due to its ability to mitigate the substantial charging currents and reactive power burdens associated with long submarine cables. This paper investigates the frequency-dependent electrothermal behaviors of a 500 kV three-core XLPE submarine cable using a coupled electromagnetic–thermal finite-element model. The simulation framework evaluates the current distribution, power losses in metallic components, temperature rise, and ampacity across various frequency regimes. To validate the numerical model, a thermal-circuit approach based on the IEC 60287 standard is developed, with comparisons confirming that deviations remain within acceptable engineering margins. The study reveals that operating at lower frequencies effectively mitigates skin and proximity effects, leading to reduced conductor and sheath losses. Quantitative results demonstrate that reducing the operating frequency from 50 Hz to 5 Hz results in a 30.6% reduction in total power losses and a 14.2% increase in current-carrying capability. These findings confirm that LFAC transmission offers a viable pathway to enhance the efficiency and capacity of submarine power transmission systems.

The distribution of the underwater electric field around a target in stratified media provides a crucial foundation for research on target detection and localization in marine environments. This paper proposed a four-layer analytical model (air–sea ice–seawater–seabed) to address the issue of electric field propagation in ocean environments involving sea ice. Starting from the Laplace equation for a steady electric field, the repeated image method was employed to introduce image current sources. Combined with the boundary conditions, an analytical solution for the electric field intensity within the seawater layer of the four-layer medium model was derived. Subsequently, a numerical model employing the finite volume method (FVM) was constructed according to the conditions of the experiment and compared with the analytical solutions under the same idealized four-layer conditions. Finally, a scaled-down experiment was designed to compare the measured electric field intensity values with the analytical solutions. The results indicated that the relative error between the measured electric field intensity values and the analytical solutions ranged from 1.17% to a maximum of 11.28%, thus validating the effectiveness of the analytical model and demonstrating its applicability in realistic environments. This work provides the theoretical and technical foundations for detecting underwater targets in the sea-ice-covered marine electromagnetic environment.

The issue of target drift prediction based on ocean current from high-frequency (HF) ground-wave radar was studied in this paper. A large number of unpowered drift observation experiments for a class of South China Sea characteristic offshore fishing vessel was carried out in the range of radar radiation. The calculation of sub-grid velocity in the test area was based on the comparison between the HF radar data and the meteorological observation data of the buoy at sea. The two observation data also have good consistency in the matching of time and space. To analyze the temporal characteristics of diffusion velocity, the sample autocorrelation and the partial autocorrelation function of a sub-grid velocity were calculated separately, and a sub-grid model based on the ARMA model was proposed. Firstly, trajectory simulation based on the Runge-Kutta method was used to preliminarily verify the improvement of target drift prediction accuracy by ARMA model. In addition, the Monte-Carlo method was used to calculate and compare the prediction range of different sub-grid velocity models, and the ARMA model with different continuous prediction time steps was studied. Compared with the traditional sub-grid velocity model, the ARMA model with short-term continuous prediction can significantly improve the performance of target drift prediction model in terms of mean prediction error and separation. However, ARMA model is also limited by its continuous prediction step size to a large extent. On the one hand, this study verifies that the ARMA model with short-term continuous prediction improves the performance of target drift prediction model. On the other hand, the results further demonstrated that measured data provided by the HF radar, combined with other continuous ocean observation data, are of value for trajectory analysis of drift targets.