With the rapid advancement of autonomous vessel technology, future port channels will witness mixed navigation involving both autonomous and conventional ships. A key challenge lies in ensuring navigational safety while enabling effective coordination between autonomous and traditional vessels during port entry and exit, thereby maximizing channel throughput. This paper proposes a formation strategy for autonomous vessels tailored to mixed traffic scenarios in ports and develops a robust macroscopic modeling framework to assess the impact of such strategies on channel capacity. Two formation strategies are introduced: cooperative formation and random formation. A comparative analysis is conducted under varying traffic demands and autonomous ship penetration rates. Experimental results show that at medium penetration rates, the impact of autonomous formations on channel capacity is minimal; however, at high penetration rates, the impact becomes significant. The cooperative formation strategy outperforms the random one in terms of capacity enhancement. The proposed formation strategies for autonomous ships can effectively enhance channel capacity in mixed navigation scenarios, providing theoretical support and technical guidance for future optimization of port and channel traffic management.

Ship trajectory prediction is a core technology for intelligent shipping, yet existing models suffer from high computational costs, inadequate modeling of global spatio-temporal dependencies, and lack of privacy protection when processing long-sequence data. To address these challenges, this paper proposes a ship trajectory prediction and privacy-preserving scheme based on Mamba-Transformer fusion. The scheme innovatively designs a dual-path parallel architecture in the trajectory prediction module, efficiently capturing long-range temporal dependencies through the linear scaling capability of the Mamba branch while leveraging the powerful global modeling capability of the Transformer branch to extract macroscopic trajectory patterns. Deep fusion is achieved through a hierarchical multi-head attention module designed in this work, thereby effectively capturing both local navigation details and global trajectory patterns simultaneously. Furthermore, recognizing that real-time trajectory prediction poses higher privacy leakage risks compared to delayed publication, the proposed scheme introduces a differential privacy mechanism at the model output layer, with a time-decay-based privacy budget allocation strategy that significantly enhances the utility of published trajectories under privacy protection. Experimental results on the Danish maritime dataset demonstrate that the proposed scheme achieves substantial improvements in ship trajectory prediction accuracy over existing methods while providing rigorous privacy guarantees for high-precision predictions through a flexible differential privacy mechanism.

To address the limitations of the RRT* algorithm in effectively optimizing non-convex and asymmetric path costs for unmanned sailboats in fixed wind fields, this study proposes an improved RRT*-based path planning algorithm with the objective of minimizing sailing time. Firstly, an adaptive sampling strategy based on the Beta distribution is designed to establish a directional-biased non-uniform sampling mechanism, enabling targeted sampling in goal-oriented regions. Subsequently, a dynamic step-size adjustment strategy incorporating real-time vessel speed feedback is introduced to enhance search efficiency. Next, a polynomial interpolation model is constructed to simulate sailboat speed under varying wind angles, establishing a quantitative relationship between sailing speed and wind angle to achieve precise sailing time calculation. Finally, the bisection method is employed to further optimize the sailing path for reduced voyage duration, with Bézier curves utilized for path smoothing. Simulations conducted in the Matlab R2024a environment demonstrate that, across diverse fixed-wind scenarios, the proposed improved RRT* algorithm significantly reduces sailing time compared to both standard RRT* and Q-RRT* algorithms. The enhanced algorithm provides reliable path planning support for autonomous navigation of unmanned sailboats in wind field environments.

This paper proposes a novel rudder device based on the Magnus effect. By using the Computational Fluid Dynamics (CFD) simulation method, the lift/drag characteristics of the Magnus rudder were analyzed. Firstly, the geometric model of the Magnus rudder was created through SolidWorks software. Secondly, steady-state fluid analysis of the Magnus rudder was conducted using ANSYS-Fluent, focusing on the changes in lift/drag under different rotational speeds and the influence of the rotational speed ratio on performance. Thirdly, a comparative study on the lift/drag characteristics between the traditional ship rudder and the Magnus rudder was carried out. The simulation results show that the Magnus rudder generates significantly greater lift during operation compared to the traditional rudder, and its drag is relatively smaller, demonstrating superior lift-to-drag ratio characteristics. Finally, a PID rotational speed control system for the Magnus rudder driven by a hydraulic motor was established on the Matlab-Simulink platform, providing an effective control solution for the practical application of the Magnus rudder.

To address the problem of unbalanced power allocation and unstable bus voltage in shipboard distributed power battery system under weak grid support conditions, a hierarchical cooperative stabilization control method is proposed. This method is based on the layered control idea, which divides the controller of the power battery converter into the main control layer, observation layer and cooperative control layer. In the main control layer, the droop control link is removed, and a droop-free control framework based on a distributed communication mechanism is constructed to solve the inherent contradiction between power equalization and voltage regulation in traditional droop control. In the observation layer, a dynamic diffusion algorithm is utilized to iteratively calculate the average state variables at local power battery converters, which drives the distributed averaging calculation process to converge smoothly and solves the communication data congestion problem between neighboring power battery converters. In the cooperative control layer, a multi-objective cooperative stabilization controller is designed to achieve composite dynamic equalization of State-of-Charge and State-of-Health, load power allocation by capacitance, and stable regulation of average bus voltage. The experimental results show that the proposed method can extend the service life of distributed power battery system by 20%, and the average bus voltage transient deviation is controlled within 0.6%. This method can provide a reference to the application of the operation control for the power battery system in new energy ships.

The traditional fault diagnosis methods for ship machinery usually only focus on single fault scenarios and lack the ability to diagnose simultaneous faults across domains. To address this issue, this paper proposes an intelligent fault diagnosis framework based on the Fully Connected Multi-label Domain Adaptive Neural Network (FMANN). Firstly, this framework achieves the transfer of fault features under different working conditions by introducing the joint domain adaptation method, thereby solving the problem of small sample fault diagnosis in the target working condition. Secondly, it introduces the multi-label classification method to capture the complex relationships among different faults, and thus realizes the transfer diagnosis of simultaneous faults. Finally, the performance of several common domain adaptation methods under this framework is compared and analyzed, and the effectiveness and robustness of the framework are verified by using the degradation dataset of a certain ship gas turbine propulsion system.

Focusing on the impact of lubricating oil vapor on low-speed two-stroke diesel engine performance, this study employed a combined approach of numerical simulation and bench testing. By developing an engine model and a lubricating oil vapor model, and coupling the combustion mechanism with physical parameters of diesel fuel and lubricating oil components, we revealed how the introduction of lubricating oil vapor triggers reorganization of the radical network, thereby influencing combustion characteristics and emission behaviors. The results showed that the introduction of lubricant vapor led to an increase in H/HOOH (hydrogen and hydroperoxyl radicals) and a decrease in O/OH (oxygen and hydroxyl radicals), which prolonged the stagnant combustion period of diesel fuel (CA0-10 increased by 1.1°CA) and accelerated the process of main combustion period (CA10-90 decreased by 4.84°CA). The increase of H radicals promoted the hydrogenation of soot precursors and inhibited soot nucleation and surface growth, resulting in an 18% decrease in peak soot emissions. In contrast, the reduction of OH radicals weakened the process of CO oxidation to CO₂ deep conversion, resulting in a 6.8% decrease in peak CO emissions. The H/O radicals triggered the recombination of hydrocarbons through hydrocarbon cleavage, resulting in a 5.8% increase in peak unburned hydrocarbons (HC). The H/O/HO₂ radical cycle accelerated thermal nitrogen oxide (NO_x) generation kinetics, resulting in an 8% increase in NO_X emissions. 

A three-dimensional numerical simulation was carried out on a diffuser cascade with a cavity structure, and improvements were made to the cavity by adding a rotor inside and varying its position and size. Comparative analysis was conducted on the flow field structures and performance parameters of different improved schemes. The results show that the modified cavity structures can reduce the overall total pressure loss coefficient and entropy generation loss coefficient of the cascade. When the rotor is placed near the leakage outlet cavity, the total pressure loss coefficient decreases by 16.4% compared to the original configuration, although the reduction in entropy generation loss coefficient is not significant. When the rotor is located near the leakage inlet cavity, the total pressure loss coefficient decreases by 12.0%, and the overall entropy generation loss is reduced, with the entropy generation loss coefficient decreasing by 13.0% compared to the prototype. After the leakage flow gains energy from the rotor within the cavity, its circumferential velocity increases. Upon mixing with the mainstream, the strengthened resistance to crosswise secondary flows improves the flow in the cascade passage. The migration of low-energy fluid along the spanwise direction near the endwall is reduced, the spanwise extent of corner separation is diminished, and the aerodynamic performance of the stator blades is enhanced.

Oscillating flow can exert forces on structures immersed in it, resulting in flow-induced vibration and other problems. The vortex-induced vibration (VIV) of a circular cylinder in a non-zero mean oscillatory flow at different frequencies is simulated, and the characteristics of the vortex-excitation vibration response are investigated. Numerical simulations were conducted on the superposition of uniform flow and high- and low-frequency oscillating flows. The displacement response, lift-drag coefficient, and vortex field morphology of the cylinder were then compared under different flow conditions. The results show that under high-frequency oscillating flow conditions, the vibration response of the cylinder is similar to that under uniform flow conditions, with a constant displacement amplitude that is in phase with the lift coefficient, and a vortex shedding frequency close to the structural frequency. In contrast, low-frequency flow induces periodic "growth-decay" behavior in the displacement time history, significantly reducing the root-mean-square and peak displacement values compared to uniform flow. It is found that the lift coefficient exhibits an anti-phase relationship with displacement during certain intervals, effectively suppressing structural vibration. Additionally, the vortex shedding structure in the wake is affected by the oscillating incoming flow, resulting in a different flow pattern than that of uniform flow.

The effect of nano-metakaolin on the tensile properties of fly ash cement mortar at early age was investigated. 4 nano-metakaolin contents (1%, 3%, 5%, 7%) and 3 fly ash contents (10%, 20%, 30%) were taken into consideration. 40 cement mortar specimens were prepared in the laboratory. The direct tensile experiments were executed on the prepared mortars at early age (3h, 4h, 5h, 6h, 8h, 10h). The digital image correlation technique was applied to monitor the strain on the surface of specimens during the tensile process. Tensile behavior of the mortar specimens were obtained. The results show that the addition of fly ash leads to a reduction in the tensile strength, the tensile strength of mortar with 30% fly ash at 6h decreased by 52.4% compared to ordinary mortar. The addition of nano-metakaolin significantly improves the tensile properties of both ordinary mortar and fly ash cement mortar at early age. Specifically, the tensile strength of mortar with 5% nano-metakaolin reached 4 times that of ordinary cement mortar at 6h. Moreover, incorporating 5% nano-metakaolin increased the 6h ultimate tensile strength of mortar containing 10% fly ash by 23%.  

In order to meet the development needs of lightweight, high power density and high reliability of marine power system, ZL109 aluminum alloy has been widely used in piston manufacturing due to its low density, high strength ratio, light weight and excellent mechanical properties under the special working conditions of cylinder liner-piston friction pair in marine low speed diesel engine. The working environment of the cylinder liner-piston friction pair is often under the condition of poor oil lubrication, resulting in partial semi-dry friction or even dry friction. To enhance the wear resistance of the ZL109 aluminum alloy surface, many scholars have studied the surface strengthening treatment technology of ZL109 aluminum alloy. However, traditional surface treatment technologies still have some deficiencies in terms of cost and coating performance. Micro-arc oxidation, also known as liquid phase plasma electrolytic oxidation, is an advanced metal surface treatment technology. It generates micro-arc discharge at the interface between the metal and the electrolyte through precisely controlled pulsed current, thereby promoting the formation of a dense and highly adherent oxide film on the metal surface. Micro-arc oxidation technology has the advantages of low cost, environmental friendliness, no need for strict surface pretreatment, and the ability to control the surface morphology of the ceramic layer through process parameters. Therefore, it is easy to combine with other technologies to prepare functional coatings. The novel mechanism is established through surface-modified micro-arc oxidation (MAO) coatings and a kind of lubricant additive (MoS₂). The surface-modified micro-arc oxidation is accomplished by aminating the surface of MAO coatings with 3-aminopropyl triethoxysilane. To analyze the influence of micromorphology of MAO coatings on the novel anti-friction and anti-wear mechanism, the coatings prepared by different forward duty cycles were systematically studied in terms of reaction process, micromorphology, thickness, surface roughness and chemical composition. Friction and wear tests were carried out to characterize the tribological property of the MAO coatings. The microstructure, thickness, porosity and average pore size of the ceramic layer were analyzed by scanning electron microscopy, Image J software, optical profilometer and X-ray diffractometer. Then, amino functional groups were introduced on the surface of the ceramic layer by amination treatment. The surface modified ceramic layer was detected by infrared spectrometer, and the amino functional group was successfully grafted on the surface of the ceramic layer. Combined with the lubricating oil containing MoS₂, a stable chemical adsorption film of MoS₂ at the friction interface was formed at the friction and wear scratches. The results show that a chemical adsorption film of MoS₂ was successfully established on the surface of worn surface by surface amination, the action of frictional physical and chemical reactions, and the micro-contact formed by the porous promontories fabricated by MAO. Furthermore, the coefficient of friction was reduced by around 50 percent compared with the level of the MAO coating without amination and ZL109 substrate, and the wear amount of the coating prepared by duty cycle 70% is near 0.3 mg.

Deep-sea heavy oil heating and viscosity reduction is key to improving recovery efficiency. Taking the heated oil flow in pipelines as the research object, a temperature field model of high-viscosity heavy oil in heating pipelines was established to analyze the influence of transmission distance, pipe diameter, heating temperature, and flow rate on the temperature rise of oil in the liquid/solid interface region (y/D < 0.1).Results demonstrate that an 80 °C pipe heating temperature yields the maximum interfacial temperature rise. Pipe diameter enlargement elevates interfacial oil temperature through increased heated surface area. A thermal inflection point emerges when the Reynolds number exceeds 2300 at pipe diameters of 151.66 mm, indicating aminar-to-turbulent flow transition that intensifies interfacial convective heat transfer. Under prescribed conditions, elevation of pipe heating temperature to 140 °C augments the effective heat transfer coefficient from 63.14 W/(m²·°C) to 134.24 W/(m²·°C), constituting a 52.96% increase that thereby enhances interfacial convective heat transfer effects.