Tianjin Port Research Articles

A Ternary Diagram Approach to Investigate the Competition within the Bohai Sea Rim Multi-Port Group

The Bohai Rim region constitutes the third prominent “growth pole” in China’s economic landscape, wherein the Bohai Rim multi-port system, encompassing Tianjin Port, Dalian Port, and Qingdao Port, engages in intense competition to establish itself as the foremost shipping hub in northern China. This study compares the ternary diagram method and employs the comprehensive concentration index (CCI), Lerner index (LI), and spatial shift-share analysis (SSSA) methods to delve into the intricacies of concentration, inequality, and evolving competitive dynamics within the Bohai Rim multi-port system over the four decades spanning from 1981 to 2023. The aim is to analyze the evolutionary trajectory and underlying dynamic mechanisms of this multipartite port system. The analysis delineates the development trajectory of the system into three stages: the dominant stage of Tianjin Port from 1981 to 1990, the efficiency competition stage from 1991 to 1996, and the ascendancy of Qingdao Port from 1997 to 2023. The results indicate that: (i) the Bohai Rim multi-port system exhibits a relatively low level of concentration, ensuring balanced growth within a non-monopolistic competitive environment; (ii) the internal competitiveness of the Bohai Rim multi-port system has gradually shifted from Tianjin Port to Qingdao Port, with Dalian Port experiencing steady development in its container transport capabilities. (iii) Dalian Port has witnessed a decline in container throughput since 2015, indicating a weakening competitive posture. These revelations suggest that Qingdao Port is a viable candidate for development into the northern China shipping center, leveraging its increasing competitiveness and strategic location. The method applied in this study may also prove beneficial for similar multi-port systems elsewhere.

Analysis of the evolution, losses and gains of tidal wetlands in the Bohai Rim based on image data cube

Under the influence of challenges posed by both human and natural factors, tidal wetlands in the Bohai Rim have been confronting severe threats. It is imperative to comprehend the evolution, as well as the losses and gains of tidal wetlands in the Bohai Rim, for effective coastal management and planning. However, the dynamic fluctuations in the losses and gains of tidal wetlands in this region are frequently overlooked. In this study, employing image data cubes and frequency method, we systematically monitored tidal wetlands in the Bohai Rim spanning the period from 1986 to 2022. Additionally, we performed an exhaustive analysis of the evolution, losses, and gains of tidal wetlands within the provinces and municipality surrounding the Bohai Rim, as well as a detailed analysis of typical areas. This study unveiled three key findings. Firstly, tidal wetlands in Liaoning, Hebei, Tianjin, and Shandong had experienced significant declines of 42%, 66.3%, 71.08% and 60.52% from 1986 to 2022, respectively; they had contracted spatially and changed from a contiguous complete distribution to a scattered fragmented distribution. Secondly, reclamation and erosion had led to the loss of tidal wetlands, while sedimentation had led to the gain of tidal wetlands. The loss area of tidal wetlands caused by reclamation and erosion, as well as the gain area of tidal wetlands caused by sedimentation, had exhibited fluctuating changes from 1986 to 2022. Finally, the area of tidal wetlands in the Liaohe River Delta, Tianjin Port, and Yellow River Delta had decreased by 46.48%, 74.96% and 22.36% from 1986 to 2022, respectively; and tidal wetlands in these three typical areas had spatially contracted. Our findings offer a fresh perspective and a solid scientific foundation for the effective management and strategic planning of tidal wetlands in the Bohai Rim region.

Port Throughput Forecast Based on ARIMA Model-Take Tianjin Port as an Example

Port Throughput Forecast Based on ARIMA Model-Take Tianjin Port as an Example

Smart ports for sustainable shipping: concept and practices revisited through the case study of China’s Tianjin port

Smart ports for sustainable shipping: concept and practices revisited through the case study of China’s Tianjin port

Incorporation of adaptive compression into a GPU parallel computing framework for analyzing large-scale vessel trajectories

Automatic Identification System (AIS) offers a wealth of vessel navigation data, which underpins research in maritime data mining, situational awareness, and knowledge discovery within the realm of intelligent transportation systems. The flourishing marine industry has prompted AIS satellites and base stations to generate massive amounts of vessel trajectory data, escalating both data storage and calculation costs. The conventional Douglas-Peucker (DP) algorithm used for trajectory compression sets a uniform threshold, which hampers effective compression. Additionally, compressing and accelerating the computation of large datasets poses a significant challenge in real-world applications. To address these limitations, this paper aims to develop a new Graphics Processing Unit (GPU) parallel computing and compression framework that enables the acceleration of the optimal threshold calculation for each trajectory automatically in maritime big data mining. It achieves this by incorporating a new Adaptive DP with Speed and Course (ADPSC) algorithm, which utilizes the dynamic navigation characteristics of different vessels. It can effectively solve the associated computational time cost concern when using the ADPSC algorithm to compress vast trajectory datasets in the real world. Additionally, this paper proposes a novel evaluation metric for assessing compression efficacy based on the Dynamic Time Warping (DTW) method. Comprehensive experiments encompass vessel trajectory datasets from three representative research areas: Tianjin Port, Chengshan Jiao Promontory, and Caofeidian Port. The experimental results demonstrate that 1) the newly developed ADPSC method outperforms in terms of compression, and 2) the designed GPU parallel computing framework can significantly shorten the compression time for extensive datasets. The GPU-accelerated compression methodology not only minimizes storage and transmission costs for data from both manned and unmanned vessels but also enhances data processing speed, supporting real-time decision-making. From a theoretical perspective, it provides the key to the puzzle of realizing the real-time anti-collision of manned and unmanned ships, particularly in complex waters. It hence makes significant contributions to maritime safety in the autonomous shipping era.

Distributionally robust optimization scheduling of port energy system considering hydrogen production and ammonia synthesis

In order to effectively address the uncertainty risks of port energy system caused by intermittence and fluctuation of renewable energy, this paper proposes a scheduling method for port energy system based on distributionally robust optimization (DRO) considering ammonia synthesis after hydrogen production by water electrolysis (P2H2A), and uses real data from Tianjin Port for example analysis. The calculation results show that 1 h selected for the scheduling interval of P2H2A is reasonable, it can ensure that the ammonia synthesis reaction transitions smoothly to the new steady state, and the temperature and pressure of the ammonia converter meet safety constraints. The two-stage scheduling of port energy system based on DRO can be divided into pre-scheduling in the day-ahead stage and rescheduling in the intraday stage, which can improve the capacity of anti-risk for stochastic optimization and overcome the conservatism of robust optimization, and consider economy and robustness. Moreover, the rescheduling decision can be transformed to a prediction error function, the result of two-stage scheduling based on DRO is the pre-scheduling result, which is between the cost of stochastic optimization and robust optimization. As the Wasserstein distance-based sphere radius increases, the pre-scheduling cost of DRO gradually deviates from risk neutral stochastic optimization and leans towards risk averse robust optimization. When the Wasserstein distance-based sphere radius remains constant, the variance gradually decreases as the number of scenarios increases, which can promote the Wasserstein distance-based fuzzy set to converge to the true distribution. When the number of scenarios is greater than 15, the pre-scheduling cost will no longer fluctuate significantly, and the calculation time is in the range of 1200 s–6600 s. It can meet the demands of day-ahead scheduling calculation time. Therefore, the scheduling model has outstanding advantages in the computing time to improve the flexibility and economy of Tianjin Port's energy system scheduling, considering ammonia synthesis after hydrogen production using renewable energy.

A Simulation Model of the Influence of LNG Ships on Traffic Efficiency at Tianjin Port

Tianjin Port is one of the largest ports in northern China. Liquefied natural gas (LNG) ships are one of the most special ship types, and their navigation safety and efficiency has become the top concern of the port authority. There are two LNG berths at the port, and the annual arrivals, which reach more than 100, increasingly influence other ships. The objective of this study is to evaluate the influence of LNG ships on other ships in a quantitative way. To realize this, a simulation system is established by analyzing the factors affecting waterway transit efficiency. The software Arena is adopted to simulate the arrival and departure of the ships at Tianjin Port and to simulate how the average waiting time and the average queue length in the port area are affected by the LNG ships. A traffic system for the two ship types is formulated, and the mutual influences between them are expressed by the inbound and outbound waterway states. The simulations are performed under both existing and new ship traffic regulations. Cases in which the number of LNG ships gradually increases are simulated comprehensively. The simulation model as well as the results can serve as a good reference for the local port authority in the formulation of traffic regulations.

An approach for traffic pattern recognition integration of ship AIS data and port geospatial features

ABSTRACT Recognition of ship traffic patterns can provide insights into the rules of navigation, maneuvering, and collision avoidance for ships at sea. This is essential for ensuring safe navigation at sea and improving navigational efficiency. With the popularization of the Automatic Identification System (AIS), numerous studies utilized ship trajectories to identify maritime traffic patterns. However, the current research focuses on the spatiotemporal behavioral feature clustering of ship trajectory points or segments while lacking consideration for multiple factors that influence ship behavior, such as ship static and maritime geospatial features, resulting in insufficient precision in ship traffic pattern recognition. This study proposes a ship traffic pattern recognition method that considers multi-attribute trajectory similarity (STPMTS), which considers ship static feature, dynamic feature, port geospatial feature, as well as semantic relationships between these features. First, A ship trajectory reconstruction method based on grid compression was introduced to eliminate redundant data and enhance the efficiency of trajectory similarity measurements. Subsequently, to quantify the degree of similarity of ship trajectories, a trajectory similarity measurement method is proposed that combines ship static and dynamic information with port geospatial features. Furthermore, trajectory clustering with hierarchical methods was applied based on the trajectory similarity matrix for dividing trajectories into different clusters. The quality of the similarity measurement results was evaluated by quality criterion to recognize the optimal number of ship traffic patterns. Finally, the effectiveness of the proposed method was verified using actual port ship trajectory data from the Tianjin Port of China, ranging from September to November 2016. Compared with other methods, the proposed method exhibits significant advantages in identifying traffic patterns of ships entering and leaving the port in terms of geometric features, dynamic features, and adherence to navigation rules. This study could serve as an inspiration for a comprehensive exploration of maritime transportation knowledge from multiple perspectives.

Study on the freezing resistance and repair technology of prestressed high-strength concrete pipe piles

This article takes a prestressed high-strength concrete tube pile (PHC tube pile) in Tianjin Port as the research object, considers the influence of the type of admixture, forming process, and maintenance method in the process of concrete fabrication, and carries out a rapid freeze-thaw test of PHC tube pile concrete. The changes in the mass loss rate, relative compressive strength, and relative dynamic modulus of elasticity with the number of freeze-thaw cycles, as well as the influence characteristics and mechanism of the admixture type, forming process, and curing method, were obtained. Based on this study, the repair and reinforcement of the base concrete were carried out using ultrahigh toughness cementitious composites and cementitious permeable crystalline composites, and a rapid freeze-thaw test was conducted on the repaired concrete specimens to verify the repair and reinforcement effects of the two materials. The study showed that the mass loss rate, relative strength, and relative dynamic elastic modulus can better characterize the freezing resistance of PHC piles, and it is safer to use the relative dynamic elastic modulus as the evaluation index of the freezing resistance of PHC pile concrete than the mass loss rate. The concrete admixture, forming process, and maintenance method have significant effects on the freezing resistance of the PHC pipe pile mix. The splitting damage surface of both ultrahigh-toughness cementitious composites (UHTTC) and cementitious capillary crystalline waterproofing (CCCW) repaired concrete is a reinforced surface, and both repair materials can improve the freezing resistance of PHC pipe piles through the crack arresting effect and reduction in initial porosity.

Trends and Prospects of Port Digital Transformation

In the field of shipping, an increasing number of ports are transitioning from traditional manual container terminals to automated and intelligent container terminals. Automated container terminals are a new generation of ports that are based on modern infrastructure and powered by advanced information technology and port transportation. This article attaches importance to introducing the research background of automation and intelligence in container terminals and explains the application of advanced intelligent technologies and automation machinery. Next, it analyzes the current status of automation in container terminals, using four automated ports: TraPac Port, Long Beach Port in the United States, Nansha Port, and Tianjin Port in China. Finally, it discusses the challenges faced by automation and intelligence in container terminals and highlights the need for government support in terms of economy and policy.

An Improved NSGA-III Algorithm for Scheduling Ships Arrival and Departure the Main Channel of Tianjin Port

An Improved NSGA-III Algorithm for Scheduling Ships Arrival and Departure the Main Channel of Tianjin Port

Analysis of Navigation Aid Effectiveness of Tianjin Port Water Depth Signal Tower and Development Protection under New Technical Conditions

The Tianjin Port Water Depth Signal Tower is a navigational aid facility that provides tidal level information. In the last century, it made great contributions to the shipping industry of Tianjin Port and played an indispensable role in local flood control work; However, with the improvement of the accuracy of marine radar sounders, the influence of background lights, the increase of surrounding buildings, and the continuous widening and deepening of navigation channels, it is becoming increasingly rare for ship drivers to obtain tidal level information through their eyes or with the help of telescopes. In addition, whether drivers can obtain tidal level information through these methods is also a topic worthy of attention and research.

Maritime greenhouse gas emission estimation and forecasting through AIS data analytics: a case study of Tianjin port in the context of sustainable development

The escalating greenhouse gas (GHG) emissions from maritime trade present a serious environmental and biological threat. With increasing emission reduction initiatives, such as the European Union’s incorporation of the maritime sector into the emissions trading system, both challenges and opportunities emerge for maritime transport and associated industries. To address these concerns, this study presents a model specifically designed for estimating and projecting the spatiotemporal GHG emission inventory of ships, particularly when dealing with incomplete automatic identification system datasets. In the computational aspect of the model, various data processing techniques are employed to rectify inaccuracies arising from incomplete or erroneous AIS data, including big data cleaning, ship trajectory aggregation, multi-source spatiotemporal data fusion and missing data complementation. Utilizing a bottom-up ship dynamic approach, the model generates a high-resolution GHG emission inventory. This inventory contains key attributes such as the types of ships emitting GHGs, the locations of these emissions, the time periods during which emissions occur, and emissions. For predictive analytics, the model utilizes temporal fusion transformers equipped with the attention mechanism to accurately forecast the critical emission parameters, including emission locations, time frames, and quantities. Focusing on the sea area around Tianjin port—a region characterized by high shipping activity—this study achieves fine-grained emission source tracking via detailed emission inventory calculations. Moreover, the prediction model achieves a promising loss function of approximately 0.15 under the optimal parameter configuration, obtaining a better result than recurrent neural network (RNN) and long short-term memory network (LSTM) in the comparative experiments. The proposed method allows for a comprehensive understanding of emission patterns across diverse vessel types under various operational conditions. Coupled with the prediction results, the study offers valuable theoretical and data-driven support for formulating emission reduction strategies and optimizing resource allocation, thereby contributing to sustainable maritime transformation.

Analysis of Prevention, Detection, and Response Measures of Major Infectious Diseases by Modern Chinese Seaport Quarantine Institutions: A Case Study of Modern Tianjin Seaport Quarantine

During the late Qing Dynasty, Tianjin Customs gradually established the seaport quarantine system to prevent the spread of epidemics from Japan, Hong Kong, and the Northeast. The major infectious diseases inspected by the quarantine institution of Tianjin Port include cholera, plague, smallpox, typhus and yellow fever, of which cholera is the most frequent and influential infectious disease in modern Tianjin, followed by plague and smallpox, and no large-scale epidemics of typhus and yellow fever have been found.In the process of preventing the spreading of foreign infectious diseases, the quarantine institution of Tianjin Port has gradually developing. A set of business system has been established, which is based on ship inspection and takes preventive injection, rat flea research and disease diagnosis and treatment as the core.In conclusion,the seaport quarantine institutions in Tianjin played an active role in the prevention, detection, and response to major infectious diseases ,opened up a precedent for Chinese people to independently handle border health quarantine.Its historical practice and quarantine mode are a window for understanding the development history of quarantine infectious diseases in modern China, which has very important reference value.

Modeling and application of ship traffic conflicts in nearshore waters with heavy traffic

Ensuring the safety of ship navigation is essential to support the sustainable development of the shipping industry, and maritime safety analysis has thus received much attention in the field of shipping. Traditionally, the safety evaluation is mostly performed with the help of accident data, which is thus limited by the insufficient amount of accident data and affects the evaluation effect. In order to overcome this limitation, a ship traffic conflict model is established, which consists of three sub-models: multi-risk ship domain model, ship traffic conflict preliminary screening model and ship traffic conflict detection model. The multi-risk ship domain model is the key foundation, combining the traditional ship domain model with the water traffic conflict severity model to fully consider the severity of ship traffic conflict. To validate the proposed model, three ships in the study waters are selected as the own ships, and the severity of traffic conflicts formed with their target ships within a certain conflict time range are analyzed separately. Then, the conflict datasets obtained from the training of the ship traffic conflict model are used to analyze the traffic conflict situation in the heavily trafficked waters near Tianjin Port. Specifically, the spatial distribution characteristics are obtained using the kernel density estimation (KDE) method and the water grid method, and the temporal distribution characteristics are verified with the help of the accident statistics method. The proposed ship conflict model can provide technical support for further research in the field of ship traffic conflict, and the experimental analysis results are of great significance for strengthening maritime traffic supervision.

Ship Behavior Pattern Analysis Based on Graph Theory: A Case Study in Tianjin Port

With the rapid development of the global economy and trade, the number of ships serving ports in China is increasing continuously. Port traffic is becoming busier, and ship behavior is more complex and changeable. The analysis of ship behavior patterns in port waters has become an urgent problem to improve the efficiency and safety of port areas. In this paper, through the full integration of ship trajectory and port geographic information, the behavior chain of a single ship across the whole process of entering and exiting the port is identified. The traffic complexities and dynamics can be further analyzed by grouping the movement patterns of large ships. Based on graph theory, the port areas can be described as a transportation network in which functional areas are nodes and fairways between different areas are edges. The traffic can be analyzed through the network structure characteristics, such as node degree, node weight, and edge weight, and by their similarities and differences. This methodology provides a quantitative analysis for exploring the behavior patterns of large ships as well as the various traffic complexities. A case study in Tianjin Port has been conducted to verify the proposed model. The results show that it can accurately analyze a ship behavior’s regularity, occasion, and correlation. It provides a theoretical reference for the port to schedule and formulate emergency plans.

Analysis of coastline changes under the impact of human activities during 1985-2020 in Tianjin, China.

The accurate evaluation of shoreline movement is a crucial aspect for managing highly dynamic coasts. This study employed Landsat TM and OLI data through the Digital Shoreline Analysis System model to quantify changes in the spatiotemporal distribution of Tianjin's coastline from 1985 to 2020. The results showed that the coastline length (CL) increased by 178 km and 151% over the past 36 years, with an average increase of 5.1 km/a. Accretion and erosion processes along the entire coast were observed at rates of 83.9% and 16.1%, respectively. Notably, the Tianjin Port Area and Nangang Industrial Zone showed remarkable changes in the shoreline in 2009. Night lights (NL) were used to display the intensity of human activity in this area, and the spatial heterogeneity of night light intensity was significant. Compared to the total night light (TNL) in 1985, it increased by 116% in 2020. The relationship between TNL and CL was then established and displayed a significant positive correlation (r = 0.91). With the increasing total night light, the growth of the CL presented changes with an initial slow increase, then rapid increase, and finally slow increase. In the second phase of TNL, the CL experienced a considerable increase due to anthropogenic activities such as land reclamation and port construction, fueled primarily by government policies during the period of 2005-2013. Subsequently, there was little change in the coastline. These findings provide valuable insights into spatiotemporal coastline monitoring programs and sustainable coastal management.

Spatiotemporal layout schemes of exclusive lanes for connected automated container trucks

Connected automated container trucks (CACTs) have been widely used at container ports in China to reduce labor costs and save energy. CACT lanes, as components of intelligent infrastructure, can accelerate the application of CACTs. However, the current layout schemes cannot effectively solve the spatiotemporal imbalance issues among traffic volumes during container transportation. In this study, optimal spatiotemporal layout schemes for exclusive CACT lanes are analyzed. Considering emission, construction and travel costs, a spatiotemporal optimization model of CACT lanes is established. A solution framework that combines the improved artificial bee colony algorithm and the simulation of urban mobility (SUMO) method is proposed. Finally, the road network of the Tianjin Port Container Terminal is used as a case study. The results indicate that establishing reasonable layout schemes for CACT lanes is important for enhancing traffic efficiency and reducing pollutant emissions.

Application of Kalman filter in wharf surface displacement of Beidou automatic monitoring

To meet the requirements for real-time dynamic monitoring of wharf surface displacement, an automatic monitoring system based on Beidou satellite navigation was constructed, and it was applied to monitor the surface displacement of a wharf in Tianjin Port. Next, the sensible system noise of the Kalman filter state equation was determined by the simulation experiment. Finally, the monitoring data were processed and analyzed by Kalman filter. The results show that the accuracy of the monitoring data can be improved by more than 30% by Kalman filtering, particularly the elevation direction accuracy can reach more than 40%. The plane and elevation accuracy can be less than 1.5mm, after the Beidou automatic monitoring data has been processed by Kalman filtering, and this meets the needs for most engineering deformation monitoring. In a word, the Beidou automatic monitoring system is characterized by continuity, real-time and high precision, and can be applied to most engineering deformation monitoring requirements.

Discussion on the Optical Performance of TYH-120 Integrated beacon Light under the Backlight of Dagusha Channel in Tianjin Port and the Optimization Scheme

The light signal of navigation aids plays an important reference role for ship pilots, especially in the long channel manually dredged (Dagusha Channel of Tianjin Port). The stable performance of beacon lights is of great significance for ship pilots to identify the channel, determine the ship's position and avoid dangerous objects, which is directly related to the navigation safety of ships. Based on the observation of the backlight of Dagusha Channel in Tianjin Port and the analysis of the location of the navigation aids in the area under its jurisdiction, this paper introduces the optical performance of TYH-120 integrated beacon light in the channel, and puts forward a further optimization plan.