The wave added resistance is calculated based on full-scale ship navigation data, using two methods: numerical calculation and empirical formula, and the calculation accuracies achieved by the two methods are investigated. A bulk carrier is selected for illustration. The ship type information of the bulk carrier is collected. Based on the ship type information, the wave added resistance response curve is calculated; The navigation monitoring data of bulk carriers are collected, and the corresponding wave added resistance response curves for each sampled data are calculated using Python programming. The corresponding wave added resistance values are obtained according to the wave height and wave period of each sampled data usingITTC (International Towing Tank Conference) dual parameter wave spectrum; Then, based on the ISO 15016:2015 regulations, wind, waves, temperature, and water density are corrected, and the shaft power is corrected to the ideal calm water power through wave added resistance correction, water temperature correction, wind resistance correction, etc. Finally, the correction results are compared with the resistance analysis results of the fast model test for bulk carriers, verifying that the SNNM(SHOPERA-NTUA-NTU-MARIC) method is better corelated to the wave added resistance on the actual ship than the slice method used.

In order to meet the demand for intelligent development in the field of tunnel engineering traffic monitoring in China, a traffic monitoring platform based on microservice architecture is designed to address the problems of low emergency rescue efficiency, insufficient intelligent control, and inadequate data analysis capabilities of traditional monolithic traffic monitoring systems. The traffic monitoring platform adopts a layered architecture design and modular design. By integrating GIS (Geographic Information System), video, Internet of Things, digital twins, and data governance services, sub platforms such as road network monitoring, tunnel monitoring, and emergency response are built to connect rescue parties quickly, improve the emergency rescue efficiency and enhance the intelligent control. The system can predict traffic situations through big data analysis and effectively improve the platform’s intelligence level. The platform has been deployed in Qinghai and Chongqing, and the results show that it can significantly improve the intelligence level of traffic management through full factor data perception and full process business control.

A summary of recent researches and achievements in the field of two types of ship wind-assisted propulsion devices-rotor sails and arc-shaped sails are summarized. The literature on the subject is reviewed. The scopes and the methodologies of the works are studied. The contributions of these works to the field are analyzes. The review indicates that the aerodynamic performance and its influencing factors of rotor sails and arc-shaped sails have been researched comprehensively. The development of research methods such as model testing and numerical calculations has reached a mature stage, with numerical calculations generally demonstrating high accuracy in most cases. Further in-depth research on the numerical calculation of aerodynamic performance for rotor sails at high Reynolds numbers is warranted.

This paper Explores the application of RAG (Retrieval-Augmented Generation) technology in building a large-scale shipping professional knowledge base, providing support for the intelligent development of the shipping industry. The principle of RAG technology is introduced systematically. The limitations of traditional RAG knowledge bases in text slicing, retrieval accuracy, and global understanding are analyzed. Advanced solutions such as introducing reordering models, database MPC (Multi-Process Communication) Server architecture, and super large context models are proposed to establish a shipping professional knowledge base. The research results indicate that the construction of a shipping professional knowledge base based on the RAG big model can significantly enhance the information retrieval and knowledge generation capabilities in the shipping professional field, providing strong support for the digital transformation of the shipping industry.

This paper proposes a distributed energy storage control strategy for the coordination of distributed energy storage in ship integrated electric propulsion systems containing AC and DC bus-bars. Simulation models of the parts of the ship’s integrated electric propulsion system are built, including power generation system, energy storage system, etc.; A distributed energy storage control strategy is designed for the system, which achieves the automation of the energy storage system by collecting information such as bus voltage and energy storage status; A system simulation model of the ship’s integrated electric propulsion system is constructed and operated. The simulation results show that the fluctuation of DC bus voltage is less than 2%. The system’s AC and DC bus voltage can meet the operational requirements. The distributed energy storage management method proposed in this paper can effectively manage energy storage systems and achieve stable operation.

To address the safety risks of leakage, phase imbalance, and explosion associated with ammonia fuel injection operations, for the injection scenario of a certain type of ammonia powered tugboat tanker truck, a collaborative plan for process optimization and risk prevention is developed. Based on CFD (Computational Fluid Dynamics) numerical simulation (SST k-ω turbulence model), the diffusion law of ammonia leakage is quantified, and a three-level dynamic safety control zone is designed to solve the multiphase flow balance problem of liquid ammonia injection. By means of a nitrogen dual loop purging system with real-time monitoring technology based on laser absorption spectroscopy, a leak prevention and control closed-loop mechanism is formed. The research results indicate that this scheme can effectively control the risks of leakage, explosion, and low temperature during the process of liquid ammonia refueling, providing a highly applicable and safe technological paradigm for ammonia fuel ship refueling, and supporting the low-carbon transformation of the shipping industry.

The impact of errors in measurements of swing amplitude, cycloid length, and arm of force on the calculation results of the metacentric height h_GM of the ship in inclining tests is studied. The 5 000 ton barge “Shipping Barge 1” is analyzed for illustration. The influencing factors for the ship’s inclining test are analyzed. A mathematical model based on error propagation theory is built for analyzing the influence of measurement errors in swing amplitude, cycloid length, and arm of force on h_GM under the test conditions, The sensitivity analysis is conducted to clarify the degree of influence of each factor. The results are verified through calculation of some typical ship cases. The research results indicate that the swing error has the greatest impact on the calculation results of h_GM; The larger the h_GM, the greater the calculation error of h_GM the swing amplitude change causes.

In response to the demands of large-scale Liquefied Natural Gas (LNG) ship development, as a support to major projects of national ministries and commissions in the 14th Five Year Plan, development and application of domestically produced propellers for large-scale LNG ships is carried out. For particular ship under construction, the technical design objective is set that the propeller efficiency and weight indicators should be no lower than those of similar foreign ship designs. A systematic study is conducted on the quantitative influence of parameters on the propulsion efficiency and excitation force of large LNG ships, including the number of propeller blades, diameter, disc ratio, side inclination angle, longitudinal inclination, profile form, and radial load. The basic design scheme is completed based on the researches, and the stability of the back plate air bubbles in the basic design scheme is improved by optimizing the chordwise load. The model test results show that the final propeller design scheme has excellent performance in terms of propulsion efficiency, excitation force, and weight. The propeller manufacturing process complies with ISO 484 class S precision requirements; The weight deviation between the left and right propellers is only 0.06%. The results of the actual ship trial show that the propeller operates stably and the speed index meets the design requirements.

The linear engineering project plan is a strip-shaped design drawing with a large aspect ratio. It requires dozens of sheets when printed on the standard A-series size paper, which means a large amount of manual labor. To improve the drafting efficiency of the linear engineering, programs are used to optimize the time-consuming framing and layout operations. First, the drawing sheet format and scale are configured, and the length and width of the print area are defined. Then, the centerline is segmented and the drawing simplified according to the stake number with coordinates exported sequentially by chainage. The drawing can be segmented into sheets by using two layout methods: Fixed-size (constrained length and width) or Adaptive-length (width-constrained only). Seamless joint of adjacent sheets’ print areas is guaranteed. The alignment azimuth is determined by the start and the end stake points of each drawing sheet, while the geometric center is calculated based on the stake point set. The alignment azimuth and the geometric center are used to adjust the position of the print, making it vertically centered from left to right within the viewport in paper space. Compared to traditional methods, new method improves workflow efficiency by nearly two orders.

Regions in Shanghai are classified based on their characteristics in terms of usage—production area, living quarter or ecological zone. The land use distribution pattern and its evolution characteristic in Shanghai in the period of 2010—2020 are studied from two aspects of spatial layout and quantitative structure using the land use transition matrix and land use dynamic degree. The research shows the facts as follows: The change of space distribution in Shanghai was significant in the period of 2010—2020. The area of ecological zone was relatively small, mainly covered by Shanghai Jiuduansha Wetland National Nature Reserve. However, it had expanded and further expansion is expected. The area of ecological production space and production ecological space reduced in the process of development, and the living and production space expanded. Among four types of spaces, the transition from production ecological space to living production space accounted for the largest proportion, the conversion from ecological production space to production ecological space follow. The ecological space had been transferred out to some extent in the 10 years, but the amount of transfer in is larger, so the overall area has increased. As for the periods from 2010 to 2015 and from 2015 to 2020, the ecological space area showed increasing trends in both periods. The area of ecological production space and production ecological space continued to decrease, while the area of living and production space continued to increase. The intensity of overall land use change was at a low level in both periods.

In order to improve the operational management level and asset utilization efficiency of container asset management enterprises, considering the uncertainty of the behavior in returning container upon lease termination and the influence of other internal and external factors, a predictive analysis is conducted on the behavior of returning container upon lease termination. An intelligent prediction model is developed based on customer historical data and comprehensive variables such as regional container return limits and monthly container return limits of ports for particular container types. The container return volume is predicted through specific calculation methods. The practical application results have proved that the model can perform prediction and analysis of action of returning container upon lease termination, assist container asset management enterprises in predicting the future evolution trend of lease termination, help them adjust management and operation strategies in a timely manner, and improve operational management efficiency and asset utilization.

This study examines the decline of the U.S. shipbuilding industry since World War II (WWII), analyzes its key influencing factors, and evaluates recent policies aimed at revitalization. The research reveals: Post-WWII, U.S. commercial shipbuilding relied on the Jones Act (1920) to retain domestic markets, while prioritizing military contracts. This imbalance led to stagnation in civilian sectors. High labor costs, lagging technological innovation, and the unintended consequences of protectionist policies (e.g., the Jones Act) have hindered industrial competitiveness in recent decades. Recent measures include the Fair Act for Offshore Workers in America (2023), Section 301 investigations against foreign competitors, the introduction of “shipbuilding managers,” and the establishment of a White House Office of Shipbuilding. However, these policies struggle to reverse industrial hollowing-out due to entrenched militarization and technological path dependence. The study concludes that the U.S. shipbuilding dilemma reflects a fundamental tension between strategic security and market efficiency, offering cautionary insights for China’s shipbuilding development.

A fuel consumption prediction method based on high-density operating condition recognition is proposed to address the complexity of multiple factors affecting ship navigation fuel consumption. Spearman correlation analysis is used to explore the degree of correlation between various feature factors and the fuel consumption. The features with high correlation degree are selected to characterize the engine operating conditions; Cluster analysis is performed on the selected features. Time axis projection and kernel density estimation techniques are introduced to accurately identify typical operating conditions by calculating the probability density distribution of each operating condition in the time dimension; A Long Short Term Memory (LSTM) network type fuel consumption prediction model for specific scenarios is constructed based on typical operating conditions, achieving a synergetic combination of operating condition recognition and prediction modeling. Experimental results show that the LSTM model with clustering technology can significantly improve the prediction accuracy compared to the model without clustering. The root mean square error decreases from 2.42 to 1.52; the average absolute error decreases from 2.12 to 1.78, and the coefficient of determination R² increases from 0.52 to 0.71. The introduction of feature screening and operating condition partitioning enables LSTM to more accurately capture the time series patterns of fuel consumption under similar operating conditions.

When measuring empty ship weight and center of gravity position in ship inclining tests, and, further, calculating the integrity and damage stability of the ship, the density of water is one of the essential parameters. But the density of water is changing because of tides. The effect of this phenomenon is analyzed. The research is conducted on four states: high tide to low tide, low tide to high tide, middle tide returning to middle tide after low tide, and middle tide returning to middle tide after high tide. The specific impact of density changes related to the tides states on the results of ship tilt tests are examed.

In response to shipyards’ demand for correcting the extensive data management and uneven granularity in the process of group erection assembly and welding, the structured format, integration and control of the assembly and welding data are researched to achieve full sharing of various data and promote the intelligent transformation of shipbuilding. Based on the structured analysis method Integration DEfinition Method (IDEF0), a process model of the group assembly and welding operations is built to achieve effective hierarchical control of the overall process and operation details. The composition of the data is analyzed and, with the Systems Modeling Language (SysML), a data model for the group assembly welding system is constructed from four aspects: process, resources, planning, and execution, to achieve a unified structured description of the diverse, heterogeneous, and multi-source unstructured data; A data collection plan for the ship group assembly and welding process is established to achieve comprehensive data collection; A group erection assembly and welding data control system is developed to achieve transparent and refined integrated control of the system's data. The practical application results show that the system can effectively improve the data management capability of the assembly welding workshop, making data recording and querying clear and fast.

In order to deal with the shortcomings of traditional data quality governance methods in terms of efficiency, coverage and adaptability, an automatic method of data quality rule recommendation based on intelligent algorithms is introduced. By constructing a dynamically evolving enterprise-level data asset feature repository, the accuracy rule recommendation algorithm based on similarity calculation and the timeliness rule prediction algorithm based on lineage analysis are combined to realize the whole process automation from metadata extraction, rule generation to recommendation execution. The core innovations include: establishing a multi-dimensional feature extraction mechanism to support unified modeling of structured attributes, business semantics, and data kinship; a dual-algorithm collaborative recommendation strategy design to solve the structural quality problem and the timeliness constraint problem respectively. Development of compact recommendation engine components to achieve seamless integration with existing data center systems. The research results have been applied to a group enterprise’s big data platform and supply chain collaborative business platform. The results show that the proposed method can shorten the average generation time of a single rule to less than 10 seconds, and the overall configuration efficiency is about 5 times higher than that of the traditional manual method, thus promoting the evolution of data quality governance from “human experience-driven ” to “ intelligent algorithm-driven ” which has good practicabilityand generalization possibility.

Current application status of data-driven artificial intelligence technology in the shipping industry is systematically analyzed, and the disruptive impact of this technology’s application on the industry’s employment pattern is deeply explored. Focusing on phenomena such as job substitution, job creation, skill redefinition, and organizational restructuring, this paper aims to revealing the risks of structural unemployment, job mismatch, and the impact of these factors on traditional human resource systems. Countermeasures are proposed from two levels: enterprise microcosmic response and national policy support. At the enterprise level, large shipping companies should build a “three transformations” response framework of “digitization of job position setting, professionalization of employee, and flexibilization of organization”, and adhere to the core logic of “people-oriented, digital intelligence first”; At the national level, taking China as an example, it is recommended to include the development of shipping professionals in top-level planning, and improve relevant laws and regulations as well as industry-education integration mechanisms to provide institutional support for enterprise transformation.

A nanoporous carbon is synthesized taking Metal Organic Framework-5(MOF-5) as templates without any carbon precursor, and carbonized at a low temperature (540 ℃) (denoted as NPC-540). NPC-540 possesses high specific surface area (1509.5 m²/g) and large pore volume, showing a good adsorption performance (243.9 mg/g), which is higher than conventional market available Powder Active Carbon (PAC) (226.2 mg/g). Experiments show that the adsorption process is monolayer adsorption. p-Nitrophenol (PNP)/NPC-540 system indicates the spontaneous and endothermic nature of the process, and the adsorption of PNP on NPC-540 involves both physisorption and chemisorption. Besides, kinetics of the adsorption process follows the pseudo-second-order kinetics model. Moreover, salt ionic strength is beneficial for adsorption. When the concentration of NaCl is increased from 0.02 mol/L to 0.35 mol/L, its capacity increases about 57 mg/g. More importantly, NPC-540 can be regenerated easily and remain high capacities (200 mg/g) after three cycles. Therefore, NPC-540 has great potential in organics removal.

A collision risk assessment model for fishing vessels is established and applied to the development and construction of a collision risk assessment and safety management system based on Automatic Identification System (AIS) data. In risk assessment the data of accident causation factors are deeply explored, and the AIS ship data center reconstruct. The fishing boat collision risk is predicted and risk causation assessment is performed by using the Analytic Hierarchy Process and Fuzzy Mathematics methods. The results of the actual ship tests show that the established collision risk assessment model for fishing boats has strong practicality, high estimation accuracy, and can provide theoretical data and technical support for the causal assessment and safety management of risk factors in fishing boat navigation and operations.

Resistance optimization is carried out for a low-speed, full-formed twin-skeg ship at the target draft and target speed. Based on Computational Fluid Dynamics (CFD) simulations, the surface pressure distribution, wave-making distribution, and flow field around the hull of the parent ship are analyzed, and resistance optimization directions and strategies are formulated accordingly. Under constraints such as displacement and hard points, modifications are made to the bow entrance angle, bow shape, and the length of run body at the stern. Additionally, the fullness of the skeg is increased, the skeg shoulder is reduced, and the run angle is decreased. Comparative analysis reveals that the modified design can significantly improve the free-surface wave-making, result in more uniform surface pressure distribution at the bow, and avoid noticeable flow separation near the stern. The total resistance can be reduced by more than 5%, achieving the goal of resistance reduction and energy savings.