To address the severe scouring challenges faced by offshore wind power infrastructure,

the scouring problem of the four-pile jacket foundation of offshore wind power under the action of ocean currents through numerical simulation. Using FLOW-3D software is studied, adopting the large eddy simulation (LES) turbulence model and the sediment transport model, the validity of the numerical model was verified through comparisons with experimental results, the scouring process of the four-pile jacket foundation under the action of a single steady flow is simulated. The development and changes in the scour pit morphology around the foundation over time are analyzed, and the effects of different flow velocities, incoming flow angles, and pile spacings on the scouring of the four-pile foundation are studied.

The results show that the group pile effect is central to the scouring characteristics of four-pile jacket foundations. The incident flow angle alters the shielding interactions among piles, leading to an asymmetric distribution of scour morphology. Pile spacing modulates the intensity of interference between adjacent piles; as the spacing increases, the group pile effect gradually weakens, and the scour pattern transitions from a unified, interconnected scour hole to relatively independent local scour holes. The maximum scour depth is primarily governed by flow velocity and exhibits only minor variation with changes in pile spacing.

The research findings provide a reference for the scouring of four-pile jacket foundations in offshore wind farms.

In order to formulate a reasonable control strategy for electrothermal de-icing of wind turbine blades,

an experimental approach utilizing electrothermal heating component prototypes has been employed to investigate the influence of factors such as ice thickness (5 mm and 20 mm), heating power (ranging from 400 W to 1 000 W), and ambient temperature on the ice-melting process within an environmental chamber set at temperatures between -20 ℃ and -5 ℃.

The results show that for each 1 ℃ decrease in ambient temperature, an additional approximately 40 W of power is required to sustain the same final temperature, revealing a linear coupling relationship between heating power and ambient temperature with respect to the final temperature of the heated surface. Furthermore, when the ice thickness is 5 mm, the duration of the gradual temperature rise phase during ice melting extends from 2.5 minutes to 10.0 min, and a heating power of 800 W or higher becomes necessary for effective ice melting when the ambient temperature falls below -15℃. As the ice thickness increases to 20 mm, the heat absorption by the ice layer itself increases by 3.2 times, leading to a proportional extension of the ice-melting time by 55%.

Therefore, in practical engineering applications, it is imperative to dynamically adjust the heating power based on real-time data on ambient temperature thresholds and ice thickness, while also optimizing the control logic by taking into account the critical conditions for ice shedding and the temperature abrupt change characteristics during the ice-melting stagnation phase.

Aiming at the problem of the impact of center body position on nozzle cavitation intensity and flow morphology,

based on the CFD-Fluent, the Mixture multiphase model is employed, the k-ε turbulence model, and the Schnerr-Sauer cavitation model, numerical simulations are performed for nozzle flow fields with varying center body positions. The validity and reliability of the methodology are confirmed through comparison with prior research results.

The nonlinear regulatory effect of the center body's axial position on the internal flow field and cavitation intensity within the nozzle is systematically quantified. It clearly identified the junction of the nozzle throat and diffuser section as the optimal position most prone to triggering cavitation effects. Cavitation intensity and mass transfer rate peaked when the center body is located at this position. Cavitation is absent on the center body when positioned inside the nozzle. When center body located outside the nozzle, the downstream extent of the cavitation zone changed minimally, and cavitation intensity gradually diminished as the center body moved further downstream. Furthermore, based on the large eddy simulation (LES) method, an in-depth analyze the complex unsteady flow structures and large-scale radial diffusion characteristics of the vapor phase downstream of the nozzle under the optimal cavitation position condition is further conducted. Significant unsteady features are observed at a location 10 nozzle diameters (10D) downstream, where the vapor phase distribution expanded radially to four times the nozzle diameter (4D).

The research clarifies the regulatory mechanism of center body position on cavitation intensity, providing a theoretical basis for optimizing cavitating nozzle design. The findings contribute to enhancing the efficiency of industrial processes reliant on cavitation, such as cleaning and fragmentation, and offer theoretical support for developing adjustable center body structures to enable real-time control of cavitation intensity.

To address the challenge of coordinated optimization between collision avoidance planning and motion constraints in the scenario where ships navigate close to dynamic surface targets, a hierarchical path planning method integrating the improved A^* algorithm, rapid reverse search iterative planning (RRSIP), and Hybrid A^* fine-grained planning, aiming to achieve efficient and kinematically compliant dynamic target tracking planning is proposed.

An improved A^* algorithm based on dynamic programming and oriented bounding box obstacle detection is used to plan a global reference path, reducing path length and redundant waypoints. For the dynamic target point, the RRSIP method is proposed, which reuses node information from prior searches via reverse search to quickly iterate and predict the approach point, avoiding global replanning and improving efficiency. Hybrid A^* algorithm is introduced near turning points for local refined planning, quickly generating a feasible path that satisfies ship kinematics and approach heading constraints.

Compared with other typical algorithms, the path length of the improved A^* algorithm proposed is reduced by an average of 4.17% and 1.79% respectively. The RRSIP method reduces the iterative planning time by at least 33.9% compared with the FR method. While ensuring path feasibility, the local Hybrid A^* planning reduces the time consumption by at least 72.1% compared with the global application.

The proposed method can effectively solve the problems of real-time performance and kinematic feasibility in dynamic target tracking, and significantly improve the autonomous tracking capability of ships in scenarios such as tugboat escort and maritime police law enforcement.

To enhance the real-time computational capability of diesel generator set simulation models under dynamic conditions such as sudden load changes, and to address the issues of computational complexity and insufficient dynamic response timeliness in traditional mechanistic models during ship deployment,

a physics-mechanism-inspired multilayer perceptron (MLP) data-driven modeling method is proposed. By constructing a dual-hidden-layer network topology mapped to the electromagnetic-electromechanical transient process of generators, the approach achieves coordinated rapid calculation of the DC bus voltage and current of diesel generator sets.

The model effectively captures the nonlinear dynamic characteristics of diesel generator sets, improving computational efficiency while maintaining the accuracy of mechanistic models.

The research providing rapid-deployable technical support for real-time situational awareness and intelligent management of ship power systems.

Aiming at the problem of unstable bus voltage output caused by Marine condition disturbance switching during the operation of ship direct current (DC) microgrid photovoltaic power generation units,

a photovoltaic power generation control strategy based on double integral sliding mode controller is proposed, including establishing an engineering model of photovoltaic cells and adopting a new exponential approach law and hyperbolic tangent switching function.

Simulation verification shows that the controller shortens the startup time to 0.002 s, reduces the overshoot to 2%, and effectively eliminates the steady-state error. Compared with traditional proportional-integral (PI) control, the startup time is reduced by 67% and the ability to resist load disturbances is enhanced by 41.2%.

The strategy significantly enhances the dynamic response speed and robustness, and is applicable to the dynamic working conditions of ships, addressing the shortcomings of traditional control methods under sudden light changes and load disturbances.

To objectively and systematically understand the current status of reliability testing of maritime autonomous surface ships (MASS),

the current research status from three aspects: testing methods, testing technologies, and evaluation systems, and discusses the future development trends are analyzed. Specifically, it includes: conducting a visual analysis of 134 related papers using CiteSpace and VOSviewer to systematically sort out the research directions and development trends in the field of ship collision avoidance capability testing; sorting out the uses, advantages and disadvantages, and research status of the three major testing platforms: real ship testing, model testing, and virtual simulation testing; in-depth discussion on the development trends, feature comparisons, and challenges faced by the three mainstream testing scenario generation technologies based on expert knowledge, random sampling, and artificial intelligence; summarizing the evaluation indicators from four dimensions: data authenticity, scene complexity, risk, and generation efficiency; and on this basis, looking forward to future research directions.

The results show that virtual simulation testing has the advantages of low cost and high coverage and has become the main testing method. The ship collision avoidance capability testing method based on artificial intelligence has development potential in high-risk edge scenarios and ship interaction games, but the current research still faces challenges such as idealized motion models, lack of multi-ship dynamic game mechanisms, single evaluation indicators, and difficulties in virtual-to-real migration.

The research on testing scenario generation and deduction based on artificial intelligence has important research value and significance for promoting the testing of MASS.

Aims to establish a cloud-edge-device collaborative intelligent management and control system to enhance production process controllability, shorten construction cycles, and strengthen decision support capabilities.

Driven by production plans and guided by process flows, a three-level cloud-edge-device collaborative architecture is designed. By constructing a physical-information fusion environment in the ship block workshop, a "plan-resource-execution" linkage mechanism is established. An improved genetic algorithm (IGA) combined with simulated annealing is proposed for the dynamic scheduling model, alongside the development of a multi-source heterogeneous data fusion engine to achieve full-factor visual management and control.

After system implementation, the ship block construction cycle is reduced by 19.7% compared to traditional models, production anomaly response time is shortened by 75%, and the equipment load balancing index is optimized by 28%.

The proposed cloud-edge-device collaborative management and control model effectively resolves the dynamic matching dilemma between planning and execution in ship block workshops. The established "perception-analysis-decision-execution" closed-loop system provides a reusable implementation framework for intelligent ship manufacturing, promoting the digital transformation of the shipbuilding industry.

Offshore wind speed observations often suffer from data gaps, limiting the accuracy of wind resource assessment and wind farm operation.

A ratio-based interpolation method for reconstructing missing wind speed data using ERA5 reanalysis and floating LiDAR observations is proposed. Taking 100 m wind speed data from a coastal buoy as a case study, the method is evaluated across annual scale, seasonal variability, wind speed levels, and typical extreme weather events.

Results show that the method effectively captures temporal wind speed trends, with an annual average correlation coefficient of 0.839. However, it tends to underestimate wind speed magnitudes, with errors increasing notably under high wind conditions, especially during convective summer periods and typhoon events. Compared to traditional linear regression methods, the ratio method performs better in maintaining trends and controlling errors, and it demonstrates greater stability and robustness under conditions of severe wind speed fluctuations or extreme weather.

Overall, the ratio method demonstrates good applicability in stable wind environments and is suitable for long-term wind resource evaluation and data reconstruction. Nevertheless, its accuracy under extreme weather remains limited, suggesting the need for integration with high-resolution simulations or multi-source data fusion approaches.

To quantitatively analyse the impact of digital transformation on enhancing the performance of shipbuilding enterprises and to understand its underlying mechanisms,

the research employs principal component analysis and regression models to assess the influence of digital transformation on corporate performance, based on its digital transformation level data from 2011 to 2023.

It reveals that for every one standardised unit increase in an enterprise's digital transformation level, its total output value grows by 30.4%. The combined contribution from the four application systems-design, manufacturing, management, and supply chain-remains relatively balanced. The research indicates that digital transformation is an indispensable pathway for the development of the shipbuilding industry. The key to successfully achieving digital transformation lies in enabling data sharing across design, procurement, manufacturing, and management systems. Crucially, realising data sharing hinges on establishing an enterprise data standards system and developing an enterprise data model that describes organisational behaviour, characteristics, status, and performance.

The proposed comprehensive measurement method for digital transformation levels, based on the depth of core system application, provides a reference for manufacturing enterprises to evaluate transformation effectiveness and optimise resource allocation.