The traditional A* algorithm applied to the path planning of offshore wind farm operation and maintenance ships has not yet taken into account the dynamic obstacles, water currents, and crossing navigation channels, therefore, this paper proposes a path planning method that considers navigational risks, heading angle constraints, and path smoothing. On the basis of constructing the map of offshore wind farm water environment by raster method, weight coefficients are introduced to change the proportion of estimated surrogate value in the total cost function of the A* algorithm to achieve the purpose of balancing the strength of heuristic information and shortening the pathfinding time, and the risk of obstacles containing water currents is taken into account in order to improve the actual cost function of the A* algorithm and enhance the security of the planned paths. Meanwhile, the heading angle constraint is considered in the A* algorithm to reduce the total number of traversal nodes, the eight-neighborhood search is constrained to three neighboring nodes conforming to the path direction, the inflection points are extracted and visibility check is performed to remove the redundant inflection points in the path, and the smooth planning path is obtained using a uniform B-spline curve. Taking the Donghai Bridge No.5 and No.6 wind farm waters as an example, a high tide path planning scenario is established, and the operation and maintenance ship needs to pass through 9 wind turbines in order to complete the operation and maintenance tasks; 4 indexes (path length, total risk value of the path, total number of traversed nodes, and total number of inflection points) are utilized for evaluating the planning path, so as to validate the effectiveness of the improved A* algorithm. The simulation results show that in the high tide scenario, the planning path smoothness of the improved A* algorithm is improved by 77.69%, the total risk value of the planning path is reduced by 52.83%, and the total number of traversal nodes is reduced by 30.58%, but the planning path length of the improved A* algorithm is 252.89 m longer than that of the traditional A* algorithm.

In order to improve the safety of water transportation and reduce collision accidents, a quantitative model of ship collision hazard based on complex network is proposed. By constructing the complex network and calculating the relationship strength to reflect the relationship between ships, the RDF (Radial Distribution Function) is used to analyze the density factor of the ship and discuss the traffic situation around the ship; the centrality of the network is used to analyze the conflict factor of the ship; and the affiliation function based on the power law of Stevens is used to integrate the density factor and the conflict factor to improve the collision hazard quantification method based on ship pairs. In order to prove the accuracy of the model, example verification is carried out and compared with the method based on the superposition calculation of ship pairs, and the results show that the present model has a certain degree of accuracy. By analyzing the actual water situation, the corresponding warning mechanism is discussed, which can be used for monitoring the water traffic situation and hazard warning.

Based on the typical container terminal loading and unloading process, starting from the transport ships, loading and unloading equipments, yard layout parameters, loading and unloading work characteristics, standardized experimental test methods and experimental parameters of energy consumption of loading and unloading machinery in container terminal are formulated, and based on the formulated experimental methods, energy consumption test experiments of loading and unloading machinery in container terminal are carried out, and the sample data of energy consumption of loading and unloading machinery in container terminal are obtained. The kurtosis and skewness test method was applied to analyze and verify the distribution law of the energy consumption test data, and the energy consumption limit value of container terminal loading and unloading equipments was finally obtained based on the statistical quota of the energy consumption test data and the corresponding national standards, combined with the relevant theory of probability theory.

In a road transport port collection-distribution system involving container trucks and a drayage fleet, it is necessary to conduct joint scheduling of trucks, tractors, and semi-trailers to achieve coordinated optimization of transport structure and routing simultaneously. This paper proposes a joint scheduling optimization model for multi-fleet combined transport, formulated as a mixed integer programming model. A simulated annealing algorithm based on heuristic rules is designed to solve the proposed problem. The impacts of different transport demands on the total transport cost and the number of workable vehicles under different freight modes are explored. Results show that, compared with the single freight mode, the multi-fleet combined freight mode demonstrates significant advantages in effectively reducing transport costs by 13.3% for tasks uniformly distributed in the freight network. Additionally, by optimizing the allocation of its own vehicle resources, the multi-fleet combined transport mode can mitigate the influence of fixed cost weight coefficient changes and transport demand compactness on the total transport cost.

To predict the delivered power of full-formed ships using a combined EFD/CFD method, this work investigated methods of obtaining the hull form factor (1+k) for three full-formed ships under various loading conditions, and analyzed their applicability. The hull form factors of each vessel were obtained using model test and numerical simulation, respectively. They were compared and then utilized to perform full-scale predictions of the delivered power using the combined method. The research indicated that the hull form factor obtained from numerical simulation resulted in a closer match between the predicted full-scale delivered power and the trial data, with an allowable difference. The research also validated the applicability of the delivered power prediction of full-formed ships using the combined method.

In order to solve the key problem of collision avoidance action of close ships, the steering avoidance process during collision encounter is studied, combining with the ship's maneuvering performance, the time characteristics of the ship's initial turning semicircle elements and turning angle are analyzed; through the decomposition of the relative motion diagram and the inverse approximation algorithm, the mathematical model of the close-quarter situation distance and collision distance is obtained when the ship is steering avoidance. The application of the model is also given; the results of the model application are verified by arithmetic examples and simulation tests. The results show that the proposed two distance models can be used to guide the collision avoidance actions of ships at close range, and provide a theoretical basis for the study of collision risk and the establishment of an automatic collision avoidance decision-making system for ships. At the same time, according to the model, the collision avoidance actions that should be taken by the ship at different stages of the encounter are analyzed for the target ships with different speed ratios and different bearings when there is a collision danger, and the close-range ship collision avoidance action mode is also given. It also gives the model of close-range ship collision avoidance action. It provides the ship deck officers with the support of close-range ship collision danger prediction and ship collision avoidance decision-making. The research results are of great significance to ship navigation safety and navigation intelligence.