In the port domain, quayside container cranes are an indispensable component of maritime freight transport. These cranes are not only costly but also associated with safety accidents that often result in casualties and property loss, severely impacting port operations and the surrounding environment. Given their complex operational environment, rapid technological updates, high dependency on human factors, and the challenges of maintenance and inspection, the safety of quayside container cranes is a significant concern for port enterprises and managers. This paper, based on the operational modes and structural characteristics of the cranes, divides them into five main systems and identifies twenty-eight safety evaluation indicators, covering a comprehensive range of risk factors from equipment integrity to operator behavior, as well as environmental factors. However, numerous pain points exist in the safety risk evaluation process of quayside container cranes, such as fuzziness, uncertainty, and complex multi-criteria decision-making (MCDM) environments. These issues make traditional safety evaluation methods inadequate in accurately reflecting the actual safety conditions. Therefore, this paper proposes a safety evaluation method for quayside container cranes based on the Best–Worst Method (BWM) and Pythagorean hesitant fuzzy VIKOR. This method effectively overcomes the uncertainties and fuzziness of traditional safety evaluation methods by integrating the decision maker’s preference information from the BWM and the fuzzy handling capability of Pythagorean hesitant fuzzy sets, enhancing the accuracy and reliability of the evaluation results. A case study was conducted on a quayside container crane at a specific port. Through empirical analysis, the feasibility of the proposed method was validated. Overall, the safety evaluation method for quayside container cranes based on the BWM and Pythagorean hesitant fuzzy VIKOR proposed in this paper enriches the theoretical research on the safety risk assessment of quayside container cranes and offers a new approach and tool for port enterprises and managers in practice.

With the daily use of liquid cargoes such as crude oil and their derivatives, the global transportation of liquid cargoes has developed rapidly. Liquid cargoes are mainly transported via tankers and pipelines. In the liquid terminal, the handling operations and internal transportation operations are conducted using oil transfer arms and pipelines, and the pipeline path of the cargo is selected using valves. The number of times a valve opens and closes and the length of pipeline paths are the main factors that affect handling time and cost. In addition, different types of valves have different operating costs and levels of operating energy consumption. At this stage, most of the valve selection work is still manually completed, which consumes a lot of time and generates high labor costs, and the actual operation efficiency is low. In this paper, the cargo unloading pipeline path is the main research object, the problem of oil transfer arms–valves–pipeline (PAVP) is proposed, and a dual-objective model is established, accounting for total time in port and the unloading cost of the vessel. An NSGA-II-Dijkstra hybrid algorithm is employed to solve the PAVP, and the improved algorithm (INIIDA) is designed to improve the solution speed via an adaptive dynamic probability based on the Pareto level and heaps in the shortest path. The results show that the INIIDA could better address the PAVP than the NSGA-II-Dijkstra hybrid algorithm. Innovative fusion algorithms are employed to improve the efficiency of port operations.

Driven by the surging global demand for crude oil and its byproducts, liquid tanker vessels have undergone a marked shift toward ultra-large dimensions. This growth, while enhancing transport capacity, has also intensified congestion across many liquid terminals. As the Dead Weight Tonnage (DWT) of vessels rises, so does their draft, often requiring tide-dependent navigation for safe entry into ports. To address the resulting operational complexities, this study investigates the coordinated scheduling of three critical resources—channels, tugboats, and berths—at liquid terminals. A novel optimization framework, termed the Channel-Tugboat-Berth-Tide (CUBT) model, is proposed. The primary objective is to minimize the total operational cost over a planning horizon, accounting for anchorage waiting time, channel occupancy, tugboat utilization, and penalties from delayed departures. To solve this model efficiently, we adopt an enhanced variant of the Logistic-Hybrid-Adaptive Black Widow Optimization Algorithm (LHA-BWOA), incorporating Logistic-Sine-Cosine Chaotic Map (LSC-CM) initialization, hybrid reproduction mechanisms, and dynamic parameter adaptation. A series of case studies involving varying planning cycles are conducted to validate the model’s practical viability. Furthermore, sensitivity analyses are performed to evaluate the impact of channel choice, tugboat allocation, and vessel waiting time. Results indicate that tugboat operations account for the largest portion of the total costs. Notably, while two-way channels result in lower direct channel costs, they do not always yield the lowest overall expenditure. Among the service strategies evaluated, the First-In–First-Out (FIFO) rule is found to be the most cost-efficient. The results offer practical guidance for port improving the operational efficiency of liquid terminals under complex tidal and resource constraints.

To address the challenge of real-time and global monitoring of the structural stress state of large port gantry cranes in complex working environments, this paper proposes a digital twin system framework covering the physical layer, data layer, model layer, and application layer, utilizing a container gantry crane as the case study. A multi-dimensional working condition space covering key working condition parameters such as lifting load and trolley position is designed, and a stress surrogate model based on the Radial Basis Function (RBF) neural network is constructed. This realizes a rapid mapping from low-dimensional operating parameters to high-dimensional full-field stress distributions. The surrogate model is integrated into the visualization platform, achieving real-time dynamic rendering and threshold exceedance warning of the stress of the key structures of the crane. The results show that the constructed surrogate model ensures the prediction accuracy (R² > 0.94) and achieves millisecond-level calculation response, demonstrating good real-time performance and reliability. It provides a reference for the digital monitoring of large-scale equipment.

Gear meshing stiffness is one of the important causes of noise, and the structure optimization of gears, such as spoke hole structures, has been proven to be an effective method to reduce gear meshing noise. In this paper, the meshing dynamics model of spur gears with spoke structures was established, and the quasi-static dynamics simulation of the meshing process was carried out by ANSYS. The results show that more spoke holes lead to less meshing stiffness and less stiffness fluctuation. The BEM (boundary element method) acoustic simulation of spur gears meshing was accomplished by the LMS Virtual.Lab. It shows that meshing stiffness is the dominate factor for noise and less meshing stiffness will result in louder noise. In summary, having fewer spoke holes causes less noise, and the experiment shows the same trend. This has certain reference significance for gear structure design considering NVH (noise vibration harshness) performance.

At present, there are some new research ideas in the design of luffing mechanism of portal crane, such as genetic algorithm and particle swarm optimization algorithm. The development of design software adopts Visual C++ or Visual Basic, MATLAB and other tools. These methods are advanced but inefficient because extra time and cost are required. This paper proposes a modern design method to complete the optimization of the four-bar luffing mechanism in the portal crane, which can simplify the calculation and improve the efficiency. The motion track description and mechanical properties of the four-bar luffing mechanism are obtained by the geometric analysis and the load analysis. The luffing curves, which can be re-drawn by modifying the initial parameters, are given to verify the optimized results. Results demonstrate that the modern design method can accomplish the optimal design effectively without extra time and cost, and this finding will be provided as the design guidance for the luffing mechanism.