This article focuses on the significant revisions to the time limit system in the new Maritime Code of China, systematically examining the institutional restructuring in four key areas: the one-year time limit for the carriage of goods by sea, the recourse time limitation, special causes for the interruption of maritime time limitations, and the commencement of the time limitation for marine insurance claims. The research shows that the new Code has made important progress in maintaining the internationally accepted one-year benchmark, constructing a balanced bilateral time limit structure, appropriately broadening the causes for interruption, and unifying the commencement standard for insurance claims, thereby significantly enhancing the legal system's certainty and international harmonization. However, the new Code might face challenges in local adaptation, including the absence of an agreement-based extension mechanism, limited recourse time limitation relief space, and unclear special rules for liability insurance and subrogation. By analyzing the new legal system and evaluating its effectiveness and potential limitations, this article aims to provide response strategies for the shipping industry and judicial practice, promoting the continuous optimization of China's maritime legal environment.

To accurately predict the thermal fire hazard of these containers under different stowage methods on a ship, this paper establishes typical working conditions, such as the position of the fire container, stowage height and wind speed. It then simulates the fire scene of lithium battery containers on the deck using FLACS 10.9 and establishes a prediction model for the temperature and heat flow density of the fire flow field using the CatBoost algorithm. The results demonstrate that the air volume within the upper and lower spaces of the lithium battery container is directly proportional to the change in fire temperature. The maximum temperature occurs when the fire layer is in the 7th layer, and the range of damage caused by high temperatures and heat flux is minimised when the fire layer is between the 7th and 8th layers. Increasing the stowage height decreases airflow, resulting in higher maximum fire temperatures, a larger temperature influence range and a longer vertical diffusion distance of heat flux. When the wind speed is in the range of 1-4 m/s, it helps to dissipate heat and reduce the maximum temperature. However, when the wind speed reaches 5 m/s, the oxygen uptake rate of the flame increases, resulting in a higher maximum temperature. When the wind speed reaches 6 m/s, the heat dissipation effect dominates and the maximum fire temperature decreases again. The higher the wind speed, the smaller the area of damage caused by high temperatures and heat flux. Comparing the temperature and heat flux density values predicted by the CatBoost algorithm with the measured samples shows that the model is highly accurate and can identify overheating spots. These research results can inform the determination of lithium battery container accumulation modes and the corresponding fire monitoring.

To enhance the safety and efficiency of maritime route planning, this study proposes a hybrid clustering method integrating multiple algorithms to evaluate the impact of tropical cyclones in the Western Pacific. Firstly, using tropical cyclone data from the National Oceanic and Atmospheric Administration (NOAA), we characterize genesis patterns, intensity variations, and track features of tropical cyclones from 1924 to 2023. Secondly, the K-means clustering algorithm is employed to analyze spatiotemporal distribution, movement speed and direction, while a Gaussian Mixture Model（GMM）is used to identify hotspot regions and high-frequency activity belts. Finally, to overcome the limitations of two-dimensional clustering, we propose a hybrid clustering approach combining 2D and 3D clustering analyses. By overlaying tropical cyclone tracks with major shipping routes, we reveal their potential impacts on maritime safety. Experimental results demonstrate that tropical cyclones primarily affect latitudes between 10°N and 25°N, with seasonal variations:cyclones are generally weaker and more localized in winter-spring, whereas typhoons are stronger and more frequent in summer-autumn. In terms of movement direction, low-latitude cyclones initially move westward from east and then recurve northward near 15°N, while high-latitude cyclones move westward before turning northeastward. The hybrid clustering method effectively identifies tropical cyclone risk zones, providing critical references for shipping route planning and risk management.

To address the safety and economic requirements for ships navigating the complex ice environments of Arctic waters, this paper proposes a multi-objective improved Sparrow Search Algorithm (SSA) to optimize both wind resistance and ice resistance. The Risk Index Outcome (RIO), calculated by the Polar Operational Limit Assessment Risk Indexing System (POLARIS), and the safe water depth threshold are adopted as constraints to ensure navigation safety and mitigate the impact of resistance on navigation efficiency along Arctic routes. First, meteorological and ice data for the Arctic route are processed, and a grid environment map is constructed according to ship type. Second, safe navigable areas are identified, and a multi-objective function model is established. Finally, the improved sparrow search algorithm is applied to optimize the route and is compared with other typical path planning algorithms to verify the effectiveness and feasibility of the proposed method. The results indicate that the optimal path generated by the improved sparrow search algorithm, based on the multi-objective model of wind and ice resistance, can significantly reduce ship resistance during navigation-achieving a reduction of up to 10.9%. Moreover, there is no significant difference in path length or running time compared with other algorithms. This study provides an economical and reliable optimization solution for ship navigation in Arctic routes.

Accurate forecasting of port container throughput is of great significance for port operators and government administrations in making scientific decisions. Existing forecasting methods, however, often pay insufficient attention to short-calendar-time PCT and exhibit limited accuracy in handling nonlinear and non-stationary fluctuation series. This paper takes the container throughput of Shanghai Port as the research object and proposes a novel deep learning model based on secondary decomposition using CCVMD and STL. Using the correlation coefficient as a reference, variational mode decomposition is first applied to the original time series. Subsequently, a secondary decomposition divides the data into seasonal, trend, and residual components. An algorithm-optimized long short-term memory neural network is then employed to predict each component separately, and the final prediction results are aggregated. Experimental results show that the combined decomposition model with data preprocessing significantly outperforms other models in PCT forecasting. The proposed model achieves a mean absolute percentage error of 0.021 703, a root mean square error percentage of 0.026 852, and a mean absolute error percentage of 0.022 14, indicating superior overall performance compared to 12 benchmark models and several models from prior studies. Furthermore, the secondary decomposition approach demonstrates enhanced reliability in tracking extreme values, removing and reducing noise, and improving interpretability.

Against the backdrop of increasing global supply chain uncertainties, how to enhance the ability of ports to cope with external shocks has become a hot topic in both academia and industry. To this end, this study is based on panel data of 16 listed Chinese port companies from 2004 to 2023. A web crawling technique was used to obtain the text of corporate annual reports. The term frequency-inverse document frequency method was applied to extract the frequency of digitalization-related keywords, so as to quantify the degree of digital technology application. Meanwhile, the sensitivity index method was used to measure the level of port resilience. On this basis, a fixed-effects model was further constructed to empirically examine the empowering effect of digital technology on port resilience and its underlying mechanism. The results show that the application of digital technology significantly improves the resilience of major Chinese ports. For each standard deviation increase in the digital technology level, port resilience increases by about 0. 2 standard deviations. This finding remains valid after a series of robustness tests. Digital technology exerts its effect by strengthening absorptive capacity and adaptive capacity, among which the enhancing effect on adaptive capacity is particularly prominent. However, the path of improving resilience through innovation capacity has not yet emerged. Under the impact of the 2020 global public health event, the empowering effect of digital technology on port resilience was significantly enhanced. In contrast, under the impact of climate change and the 2008 financial crisis, the empowering effect of digital technology on port resilience did not change significantly. These conclusions provide a new perspective for seeking to improve port resilience in the current context of sharply increasing global uncertainties.

This study employs the MARIS model and a convective diffusion model to simulate the diffusion of nuclear wastewater released from Japan. Based on the simulation results, it proposes optimized methods for ballast water exchange to prevent the direct discharge of radioactive ballast water into ports, thereby mitigating potential threats to the ecological environment. The research focuses on the Fukushima nuclear incident and the subsequent continuous release of 1.3 million tons of nuclear wastewater into the ocean. Results indicate that radioactive substances are mainly concentrated in the surface layer of the ocean, with detectable enrichment of radioactive elements such as cesium in seawater and aquatic organisms near the Fukushima nuclear power plant. Consequently, ships operating near eastern Japanese ports are taking in ballast water contaminated with radioactive materials, including cesium-134 and cesium-137. Using a convective diffusion module, the study simulates the variation in radioactive substance concentrations during ballast water exchange at different distances, providing theoretical support for optimizing exchange strategies. The findings show that performing a secondary ballast water exchange more than 20 nautical miles from Japan's coast can reduce radioactive substance concentrations in ballast water to one ten-thousandth of the pre-exchange levels. The conclusions of this study can assist maritime regulatory authorities in formulating effective management measures, thereby contributing to the protection of marine ecosystems.

With inland waterways transitioning from linear to networked operation, accurately identifying critical segments is essential for optimizing resource allocation and enhancing system resilience. Existing methods have limitations in effectively identifying segments that play a decisive role in maintaining global connectivity. To address this issue, a community bridge-based method is proposed. Firstly, a weighted topological network is constructed using waterway class and length. Then, the Louvain algorithm is applied to divide the inland waterway network into multiple communities with strong internal connectivity, and edges connecting different communities are identified as critical segments. Finally, attack simulation experiments are conducted to evaluate the effectiveness of the proposed method. Taking the Jiangsu inland waterway network as a case study, the results show a maximum modularity of 0. 901, indicating a pronounced community structure characteristics, and the network can be divided into 18 communities. Currently, 46 critical segments are identified in the network. If all critical segments fail simultaneously, both relative network efficiency and the relative size of the largest connected component decrease by nearly 80%, validating the effectiveness of the identification method. After implementing the 2017—2035 and 2023—2035 waterway network upgrades, the community structure becomes more compact, and the number of identified critical segments decreases while the results remain consistent. The identified critical segments provide theoretical support for routine maintenance and safety supervision of inland waterways, strengthening navigational assurance to enhance network resilience.

The port, industry and city are significantly related, and their integration degree reflects the coordinated evolution relationship among the three in the spiral development. Against the backdrop of deepening reforms in China's port management system, there is a growing need to scientifically assess the state of port-industry-city integration and analyze its underlying mechanisms. To address the issues of multidimensional indicator overlap and the difficulty in quantifying systemic synergy in existing research, this study constructs a coupling coordination degree model based on principal component analysis. Based on the panel data of 75 port cities in China from 2004 to 2023, the model applies principal component analysis to reduce the dimensionality of high-dimensional indicators across the port, industry, and city subsystems, thereby addressing multicollinearity issues among the indicators. Subsequently, a coupling coordination degree model is employed to quantify the level of synergy among the three subsystems, while the criteria importance through intercriteria correlation weighting method and panel entropy weight method are integrated for comprehensive weighting and robustness testing. The research shows that the overall integration level of Chinese port cities showed an upward trend during the study period, with its evolution exhibiting phased fluctuations influenced by the port management system. Significant disparities in integration were observed both across and within regions, with a maximum range of 4.65. Institutional changes in port management, path dependence in industrial development, and differences in regional institutional flexibility were identified as the core drivers of this spatial-temporal differentiation. Accordingly, policy recommendations such as establishing a cross-regional collaborative governance system and implementing differentiated industrial development strategies are proposed to advance the coordinated development of the port-industry-city system and provide a decision-making reference.

Suction pile can not only provide sufficient bearing capacity for deepwater oil and gas well construction, but also be used more and more widely in subsea production systems as the foundation of subsea structure. The stability of suction pile structure in offshore installation faces challenges due to its large span and harsh working environment and installation conditions. Taking a large suction pile with a diameter of 8 m and a total height of 19. 68 m applied to a gas field in the South China Sea as the research object, a 1∶1 finite element model was constructed. Based on the operating environment of the gas field in the South China Sea, the typical installation process of suction pile under transporting, lifting and installation during offshore construction is studied, and the worst conditions under each working condition are obtained through load calculation and analysis. The results show that the maximum stress under the transportation condition is negative transverse acceleration + vertical acceleration + Y negative wind load, and the high stress is concentrated at the fixed place between the suction pile and barge. In the lifting condition, the trapped water on the suction pile is considered for air and underwater lifting analysis. The high stress occurs at the welding point of the lifting point, which is the focus area of the field operation. The calculation of suction pile installation and inclination of manifold installation under the installation condition meets the standard requirements. Based on the above calculation, combined with the offshore installation practice, the whole offshore construction process of suction pile is safe and reliable, and the final installation precision is very high. The relevant research results can provide reference for the optimal design and offshore installation of deep-water suction piles.