This paper addressed the vessel schedule recovery problem (VSRP) for container liners suffering delays caused by disruptive incidents, and introduced the shipping carbon trading mechanism. A dual-objective optimization model for VSRP was established to minimize voyage schedule recovery costs and maximize customer service level. For scenarios with anticipated operational disruptions, the optimal combined strategy consisting of speed adjustment, port skipping and port swapping was solved. An improved adaptive non-dominated sorting genetic algorithm II (NSGA-II) was designed to solve the proposed model. Multiple scenario-based numerical examples verify the effectiveness of the proposed model and improved algorithm in this paper. Numerical results show that different durations of anticipated disruptions correspond to distinct optimal combined strategies for schedule recovery. Under the dual-objective optimization without preference, utilizing information on anticipated disruptions can reduce voyage recovery costs by 18.31% on average. Sensitivity analysis shows that when the carbon trading price rises, both the schedule recovery cost and vessel carbon emissions decrease simultaneously if the preference weight of the carbon emission reduction objective is large. Besides, an increase in carbon quotas will directly cut down the schedule recovery cost. In contrast, when the preference weight of the carbon reduction objective is small, carbon emissions follow a trend of decreasing first and then increasing. The research conclusions can provide theoretical support and decision-making references for shipping enterprises to formulate schedule recovery schemes under operational disruptions.

Under the background of port intelligence upgrades, the dynamic complexity of business scenarios and the multi-source heterogeneity of data have exposed gaps in the “perception-cognition-decision” chain of current port intelligence systems. Knowledge graphs excel at symbolic reasoning but struggle with handling multi-modal semantics and dynamic knowledge fusion. Large models possess powerful natural language capabilities but face challenges in achieving accurate and reliable decision-making reasoning due to insufficient interpretability and lack of domain knowledge. This situation of “separation of perception and cognition, and disconnection of generation and reasoning” makes it impossible for a single technology to meet the port’s demands for highly reliable, interpretable, and adaptive intelligent decision-making. Therefore, integrating multi-modal knowledge graphs and large models has become a key path for driving the evolution of port intelligence systems. This paper systematically reviewed the related work on artificial intelligence, knowledge graphs, and large models in port intelligence, analyzed the driving mechanism of their integration under the dual perspective of industrial demand and technology integration, and constructed hierarchical technical and functional frameworks. Meanwhile, based on port engineering practice and development status, this paper identified and discussed key technical challenges faced in achieving deep integration, aiming to provide theoretical basis and practical guidance for related research and engineering applications.

Ship pipeline path planning is susceptible to problems such as local optima and path redundancy. To solve these issues, this paper adopted the blocked-path pruning A* algorithm (BPA-star) to study pipeline layout optimization. After establishing the geometric model of the pipeline working space, the algorithm was improved by integrating pruning segmentation and blocked-path iteration techniques. This method not only avoids the local optimum trap of traditional search algorithms and expands the global search range, but also eliminates redundant routes and unnecessary turning points, thereby effectively improving the quality of pipeline planning. The results show that for single-pipeline cases, the BPA-star algorithm achieves optimal values in terms of path length, number of turns and energy cost. For multi-pipeline cases, it produces a more compact layout that fits the hull structure well. Compared with the conventional A* algorithm, the proposed method delivers better pipeline connection performance, along with superior economic efficiency and adaptability. Without the directional guidance of extension segments, the energy value of pipelines planned by the algorithm decreases by 45.68%, and the installation adaptation length increases by 400%. With the directional guidance of extension segments adopted, the number of pipeline turns decreases by 8.64%, and the installation adaptation length increases by 54.64%. The findings can provide guidance for ship pipeline layout design and have practical application value for improving pipeline design and construction efficiency.

To mitigate the deterioration of ship seakeeping performance induced by liquid tank sloshing and reduce the associated navigation safety risks, this paper employed the finite volume method to solve fluid control equations and utilized the VOF method to capture the free liquid surface. A numerical model was developed to investigate the sloshing suppression mechanism and flow field characteristics of vertical symmetric baffles. The study focused on the suppression effect of vertical symmetric baffles with different lengths under sway excitation, as well as their impacts on flow field characteristics such as the free surface of the liquid tank, tank wall pressure, and flow field velocity. The results show that for rectangular liquid tanks with an aspect ratio close to 1, the vertical installation of symmetric baffles at the free liquid surface can significantly suppress sloshing; the sloshing suppression effect varies significantly with different baffle lengths, and the optimal baffle length is set at 0.7 times the width of the liquid tank.

Aiming at the robust control problem of control systems under unknown nonlinear dynamics, time-varying disturbances, input saturation and Gaussian noise, an adaptive sliding mode control method deeply integrating event-triggered mechanism and dynamic coupling strategy was proposed. Firstly, the dynamic surface control (DSC) technique combined with radial basis function neural network (RBFNN) was adopted to approximate the unknown dynamics of the system, and a staged error constraint strategy was designed to achieve dynamic collaborative optimization of convergence speed and steady-state accuracy. Secondly, a time-varying disturbance observer was introduced to estimate disturbances such as wave disturbances online, and an intelligent smoothing processing mechanism driven by Gaussian error function was used to handle the problem of asymmetric input saturation. Furthermore, by combining the event-triggered mechanism, the adaptive dynamic threshold control was used to reduce the control update frequency and decrease the consumption of computing resources. Based on the Lyapunov stability theory, it is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error can converge to a preset neighborhood. Simulation results show that the proposed method significantly improves the system’s anti-interference ability and control efficiency, providing theoretical support for the application of related control theories in engineering practice.

To reveal the influence mechanism of jet oscillation on the removal of residual palm oil during the dynamic cleaning of shipboard cargo tanks, dynamic cleaning experiments were carried out on a self-built test platform. A numerical simulation model for jet oscillation tank cleaning was established by using FLUENT, combined with dynamic mesh and user-defined functions. The effects of jet oscillation velocity on the cleaning performance of palm oil were systematically analyzed. The results show that the cleaning mechanism of palm oil is the coupling effect of wall pressure and shear stress. During the cleaning process, wall pressure acts first as the dominant factor, breaking through the palm oil layer attached to the tank wall and forming an initial oil-free zone. Afterwards, the shear stress generated by the radial expansion of the jet thoroughly strips the residual oil from the wall surface. The horizontal oscillation velocity of the jet is a key parameter affecting cleaning performance, and it has a significant negative correlation with tank wall pressure and maximum shear stress. Excessively high horizontal oscillation velocity leads to jet motion lag, which reduces the effective coverage area of the jet “water pad” and lowers the utilization efficiency of shear stress, thus degrading the cleaning performance. Under the test conditions, the optimal matching between wall pressure and shear stress is achieved at a horizontal oscillation velocity of 1.11 r/min, the effective coverage area of the “water pad” is relatively large, the utilization efficiency of shear stress reaches the maximum, and the oil removal performance is the best. The vertical oscillation velocity is also a key factor affecting the cleaning effect, and it needs to be reasonably matched with the horizontal oscillation velocity. With the vertical oscillation velocity keeps constant, an excessively high horizontal oscillation velocity results in insufficient deep cleaning of the tank wall, while an excessively low value enlarges the blind area. Increasing the vertical oscillation velocity will further widen the spacing between jet cleaning paths, expand the blind area and degrade the cleaning quality. Comparative analysis shows that the combination of 1.11 r/min (horizontal) and 20 mm/s (vertical) oscillation velocity achieves the best performance. Under this combination, the synergistic effect of wall pressure and shear stress is the strongest, and the effective coverage area of the “water pad” is relatively large, which can fully cover and peel off the residual palm oil on the wall. While achieving a 100% cleaning effect, the time consumed is only 18.75 s. Compared with the worst parameter combination that also achieves a 100% cleaning effect, the cleaning efficiency of this optimal working condition is improved by 50%, which can be used as a reference for efficient tank washing operations of actual ships.

Visual observation technology and nonlinear fitting method were adopted to analyze the fluid behavior characteristics in the cavity of the rotating disk reactor. Water, glycerol and sodium dodecyl benzene sulfonate solution were selected as working fluids. A high-speed camera and Image J image processing software were used to investigate the flow patterns and breakup modes of fluid in the cavity. The critical condition equation for flow pattern transition was fitted, and the influence laws of operating parameters on the characteristic droplet diameter and droplet distribution uniformity index were explored. Results show that the typical flow patterns include ligament flow, ligament-droplet flow, and droplet flow. Meanwhile, the breakup mechanisms consist of film-to-droplet and film-to-ligament-to-droplet transitions. The cumulative droplet volume follow the Rosin-Rammler (R-R) distribution, with characteristic droplet diameters ranging from 1 to 4 mm, and the droplet distribution uniformity index between 2 and 8. Rotor speed and fluid viscosity significantly influence on the fluid behavior characteristics in the cavity zone. The findings contribute to a deeper understanding of the internal fluid behavior characteristics of supergravity devices and can provide basic data and theoretical references for constructing mass transfer models.

To systematically investigate the effects of different interphase force models on numerical simulation results, transient numerical simulations of gas-liquid two-phase flow were carried out by using the Euler-Euler two-fluid model based on the open-source platform OpenFOAM. The prediction performances of various interphase force closures were analyzed, and the accuracy of each model was validated by comparison with experimental data and reference results. The study covered low, medium, and high Reynolds number conditions, corresponding to various gas-liquid flow regimes. It focused on revealing the mechanisms of drag, lift, wall lubrication, and turbulent dispersion forces governing bubble dynamics and radial void fraction distribution. The results show that there exists no universal model valid for the entire range of flow conditions, and the choice of interphase force models depends on the specific bubbly flow regime and Reynolds number range. At low Reynolds numbers, the drag force model dominates the bubble migration process. At high Reynolds numbers, the lift force model plays a dominant role in phase distribution patterns, shifting the void fraction peak from the wall region to the core flow region. The turbulent dispersion force tends to homogenize the radial void fraction distribution. Furthermore, the coupling effect among lift force, wall lubrication force and turbulent dispersion force significantly improves the prediction accuracy of radial phase distribution. The simulation results determine the optimal combinations of interphase force models within different Reynolds number ranges. Based on a systematic analysis of the mechanisms of each interphase force under various Reynolds numbers, this paper proposes a strategic framework for selecting interphase force models, which provides a theoretical basis and optimization guidance for the multiphase flow model configuration in numerical simulations of complex bubble flows. The study further confirms that, under low gas fraction conditions, the phase distribution of vertical adiabatic bubbly flow can be accurately predicted even if bubble coalescence and breakup effects are neglected, which provides a feasible reference for the simplification of multiphase flow models.

The “breakwater + wind turbine” integrated utilization model has gradually become a focal point in offshore wind energy research. To explore the dynamic response characteristics of the breakwater-wind turbine system under the combined action of wind and seismic loads, this paper developed a three-dimensional coupled numerical model of the integrated breakwater-wind turbine structure by using PLAXIS. The horizontal displacements at the top of the tower and breakwater were used as the primary indicators to conduct a comparative analysis of the system’s dynamic response under various site and loading conditions. The results show that due to the difference in stiffness between the tower and the breakwater, the displacement at the top of the tower is significantly larger than that at the breakwater. Compared with the effects of wind load or seismic load alone, the combined wind-seismic loading significantly amplifies the system’s displacement peak, and this amplification is not simply a linear superposition. Furthermore, the wind-seismic interaction alters the sensitivity of the dynamic response of the breakwater-wind turbine system to the properties of the site soil. Therefore, in practical engineering design, the combined effect of different loads must be considered comprehensively. The conclusions of this paper can provide valuable references and guidance for the dynamic response analysis and design of “breakwater + wind turbine” integrated projects.

Traditional cement-based piezoelectric composites (0-3 and 1-3 types) suffered from limited stress transfer efficiency and low piezoelectric output due to random piezoelectric phase distribution and fiber breakage. To address this issue, this paper developed a new cement-based piezoelectric composite based on the topological structure of triply periodic minimal surfaces (TPMS). Two typical TPMS configurations, Diamond and Karcher-Tuite, were parametrically modeled by using Python and the level-set method, and a piezoelectric-structure coupling finite element model was established by using Abaqus to evaluate the effects of piezoelectric phase volume fraction (10.0%~29.2%) on stress distribution and output performance (d₃₃, g₃₃, V). Results show that the continuous three-dimensional network of TPMS structures can effectively optimize the stress transfer path and avoid local stress concentration, thereby achieving excellent mechano-electrical conversion efficiency. When the volume fraction of the piezoelectric phase is 29.2%, the piezoelectric coefficient d₃₃ of Diamond and Karcher-Tuite composites reaches 148.5 pC/N and 103.7 pC/N, respectively, which is significantly superior to those of traditional 0-3 and 1-3 configurations. Through systematic numerical simulations, this paper reveals the intrinsic correlation between the topological characteristics of TPMS and the macroscopic piezoelectric properties, providing a theoretical basis for the configuration optimization and experimental design of self-powered sensing materials with high sensitivity and high durability.

Spraying is a common method for fabricating superhydrophobic surfaces, yet it suffers from low bonding strength between coatings and substrates, poor durability and unstable air cushions in water. A composite fabrication strategy combining micro-arc oxidation (MAO) and two-step spraying was proposed for aluminum substrates. Firstly, porous structures were constructed on aluminum substrates via micro-arc oxidation. Secondly, fluorocarbon resin doped with hydrophobic SiO₂ nanoparticles and SiO₂ nanoparticle superhydrophobic solution were sprayed sequentially, and superhydrophobic surfaces were obtained after curing at room temperature, with a static water contact angle of 162.5° and a sliding angle of merely 1.8°. The comprehensive performances were systematically investigated through friction test, gravel impact test, self-cleaning test, electrochemical corrosion test, salt water immersion test and drag reduction test. The results show that the as prepared double layer SiO₂ superhydrophobic surface possesses excellent mechanical durability. Its corrosion current density is reduced by three orders of magnitude compared with the bare aluminum substrate. The drag reduction rate reaches 69.5% at a water flow velocity of 0.5 m/s in specimen scale tests, and achieves 54.8% at a sailing speed of 0.3 m/s in ship model tests. The porous structure formed by micro-arc oxidation enhances the interfacial bonding strength between coating and substrate. Moreover, the SiO₂ nanoparticles embedded in the resin can strengthen the coating and dynamically repair damaged micro/nanostructures, synergistically endowing the surface with stable superhydrophobicity. By rational coating structure design, the overall performances of superhydrophobic surfaces are effectively improved. This study provides experimental basis and theoretical support for the engineering application of superhydrophobic surfaces in marine fields.

To improve the anti-friction and wear resistance performance of marine internal combustion engine bearing bushes under harsh operating conditions, this paper adopted the scraping and thermal curing process to prepare a polyimide/epoxy resin/tungsten disulfide (PI/EP/WS₂) composite coating on the surface of an aluminum alloy substrate, and explored the influence law of the bonding agent ratios on its mechanical and tribological properties. Scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) were used to analyze the morphology and element distribution of the coating surface, cross-section and wear scars, a microhardness tester was employed to measure the coating hardness, and a friction and wear tester was adopted to investigate the friction coefficient and wear rate of the coating under different loads and frequencies under dry friction conditions. Results show that with the increase of load and frequency, the wear rate and friction coefficient of the coating gradually increase, and the bonding agent ratios has a significant impact on the coating properties. When the bonding agent ratios is 2, the tungsten disulfide solid lubricant in the coating is uniformly dispersed in the polymer, the coating structure is dense, and the microhardness is the highest, reaching 56.7 HV. Under dry friction conditions at a reciprocating frequency of 3 Hz and a load of 5 N, the coating with bonding agent ratios of 2 exhibites the best overall tribological performance, with an average friction coefficient of 0.06 and a wear rate of 1.50×10^-4 mm³/(N·m). The superior performance can be attributed to the following factors: in terms of friction reduction, the layered WS₂ with weak interlayer van der Waals forces facilitates easy shearing, endowing the coating with excellent anti-friction properties. Regarding wear resistance, when the polymer content is too high, the insufficient hardness of the polymer matrix leads to plastic deformation and adhesive wear; conversely, when the polymer content is too low, the bonding strength between the coating and the substrate is inadequate, resulting in coating spallation. This study can provide experimental evidence and data support for developing high-performance protective coatings for marine engine bearing bushes.

Pirate attacks pose a serious threat to maritime shipping security. An accurate risk assessment model is critical for route planning and emergency decision-making. To scientifically assess piracy risks, a pirate attack risk assessment model based on an improved Bayesian network was proposed in this study. The Fisher optimal segmentation algorithm was introducedto enhance the model’s node-state settings, classification accuracy and scientific validity. Based on the screened samples and node-state settings, the expectationmaximization (EM) algorithm was used for Bayesian network parameter learning. Meanwhile, an improved tree structure learning algorithm was adopted to reduce the complexity of model structure learning. The proposed model improves prediction accuracy by 5.44% compared with the traditional Bayesian networks while reducing structure learning complexity by 21.43%. In addition, compared with random forest and backpropagation (BP) neural network models, it achieves improvements of 1.23% and 2.83% in prediction accuracy, respectively. This study provides robust decision support for the scientific prediction of piracy risks.