Containerized Research Articles

Analysis of emission characteristics associated with vessel activities states in port waters

This study investigates AIS data from March 2019 to February 2020 in Shanghai Port waters. The ship activities of berthing, waiting, and ingress/egress are extracted in detail to elucidate the emission characteristics of ships in Shanghai Port, differentiating emissions patterns across various ship activity. The findings reveal that the top three pollutants within Shanghai Port are CO2, NOX, and SO2. Container ships have the highest emissions, followed by bulk carriers. Berthed container ships and oil tankers exhibit the highest emission. Waiting container ships emit the most, followed by oil tankers and bulk carriers. Among ships entering and leaving the port, low-speed navigation produces the most emissions, followed by maneuvering and steady-speed navigation. Emission hotspots include the Yangtze River Estuary Anchorage and the main navigation channel into and out of the port. This study offers robust data support for an in-depth understanding and evaluation of ship emission characteristics in Shanghai Port.

Enhancing object detection and classification using deep learning: A novel approach with annotated dataset and YOLO-C3GTR architecture

In the rapidly evolving field of computer vision, the need for advancements in object detection is paramount. For a variety of reasons, including security, maritime surveillance, and environmental monitoring, the identification and categorization of ships in aerial pictures is an essential component. In this study, two distinctive approaches are proposed to improve the accuracy of ship detection and categorization in satellite imagery. In the beginning, the dataset for ship detection that was provided by Airbus was separated into five distinct categories: oil tanker, bulk carrier, container ship, sand carrier, and general ship class. Setting up this division was done with the idea of increasing the precision of the ship classification in the imagery. Moreover, we deployed the YOLO-C3GTR model, which is part of our Object Detection framework and helped us to distinguish ships using the technique of Object Detection. The application of the methodology that we have proposed has the potential to significantly improve the precision of these systems when they are used in real-world scenarios and to make a novel addition to the field of ship identification and classification. We have used multiple algorithms of YOLOv5 tested on this dataset like TPHYOLOv5, YOLOv5x, YOLOv5l and our proposed architecture YOLO-C3GTR and it surpassed all the existing approaches by the mAP of 0.83. Furthermore, we intend to perform additional research in this field while simultaneously working to improve our technique. A comparison was made between the performance of the model and that of other deep learning approaches. The model was evaluated and trained with the categorized dataset.

Consequences of freight rate volatility in liner shipping and the role of strategic alliances

The purpose of this paper is to analyze and understand how the infamous fluctuations in freight rates influence (spill over) upstream (shipper and ship-manufacturing) and downstream (ports and ship-recycling) from the perspective of a vertical maritime supply chain. Rate volatility spillovers are examined in the time and frequency domains. As to be expected, the intensity and direction of spillovers differ across time. In general, however, freight rates exert a spillover effect on both the shipbuilding and ship-recycling markets, with a more pronounced impact on the former. We find that the period after 2013 saw a negative impact of freight rates on shippers and ports, primarily due to increased volatility in the global shipping market, which introduced significant unpredictability in shipping costs and operational planning. In the frequency domain, we establish a complex long-term trend and market cyclicality, linked to the general economic cycle. In addition, we calculate industry concentration in the ocean transportation of containers, to understand the impact of alliances and acquisitions (A&A) on freight rates and their spillover effects. Less evidence of industry concentration efforts is observed in prosperous shipping markets where freight rates are sufficiently rewarding. Instead, a higher level of activity towards concentration is observed in periods of market downturns. In such periods, A&As are seen to have a more profound effect on rate spillovers. The study furnishes empirical evidence concerning the spillover effects of freight rates across diverse markets, shedding light on the interconnectedness and dynamics within the various segments of the maritime supply chain. Moreover, we elucidate the significant role played by strategic alliances and acquisitions in the maritime sector, providing a nuanced comprehension of how industry structure influences business behavior and market volatility. The insights garnered from this research hold substantial value for policymakers and business strategists navigating the shipping industry's intricacies, offering them crucial data to support their decision-making processes.

An integrated intermodal freight transportation system to avoid container supply chain disruptions in Chattogram Port of Bangladesh

An integrated intermodal freight transportation system is a derived demand to transport shipping containers from/to the seaport to/from the hinterland, instead of undertaking cargo loading and unloading activities in port-protected areas. The concept of the intermodal system is to transfer containers to nearby hinterland nodes, such as dry ports, inland rail, road, and river terminals as a part of port development, as well as increasing port efficiency and productivity. Lloyd’s List ranked Chattogram Port as the 67th busiest container port in the world as per container port throughput in 2022. Chattogram Port has small-scale intermodal facilities for off-docks/ICDs in the port city only. In addition, a pure intermodal system has been developed by one rail ICD in the capital city, Dhaka, and two RICTs nearby Dhaka, but less than 5 % of port throughput. A large-scale intermodal for serving the major cities, SEZs, EPZs, and industrial areas is absent due to planning and policy problems, as well as the unavailability of intermodal infrastructure and network. Due to an improper hinterland intermodal chain, the port faced container supply chain disruptions at the port yard and exceeded port capacity, resulting in container vessel congestion at the outer anchorage of Chattogram Port. By developing rail and road infrastructure, and utilizing natural river connectivity, it is possible to develop road, rail, and river intermodal systems, and shape an integrated intermodal freight transportation system to avoid container supply chain disruptions in Chattogram Port. To develop an integrated intermodal system, this research chose a quantitative research methodology for port throughput data analysis and forecasting future throughputs that are advanced to the intermodal model for Chattogram Port. Overall, this paper aims to develop an integrated intermodal freight transportation system to support Chattogram Port to keep and increase the record of port productivity, efficiency, and competitiveness actively. Highlights Intermodal system is a derived demand for managing hinterland and port terminals of a seaport that needs to be implemented in Chattogram Port Container supply chain disruptions to be avoided to increase the port productivity and efficiency Inland intermodal connectivity will help to increase hinterland of a seaport It is necessary to develop an integrated intermodal freight transportation system to support Chattogram Port to keep and increase the record of port productivity, efficiency, and competitiveness globally

CargoLinker: Streamlined Container Booking App

The global shipping and logistics industry play a vital role in facilitating international trade, yet small-scale exporters often face challenges in booking cargo container space efficiently. CargoLinker is a web and mobile application designed to bridge this gap, connecting exporters with available cargo container space in a streamlined manner. It is developed using an open source framework named Flutter , CargoLinker aims to enhance the efficiency and affordability of cargo shipping for small-scale exporters. The main aim of this application is to minimize the cost for small traders and maximize the profit for the company. This paper presents an overview of CargoLinker, its features, benefits, development process, challenges, and future directions

Exploring the technical feasibility of carbon capture onboard ships

International shipping is crucial for freight transport, but it relies primarily on fossil fuels, contributing 3% of global greenhouse gas emissions. This calls for urgent action to decarbonize the shipping industry. While renewable-based e-fuels are a strong candidate for decarbonization of this sector in the long run, deploying these to the required scale will take significant time, considering technical modifications onboard the vessels, as well as the changes in fuel production and infrastructure for distribution. Carbon capture from ships is another route to emission reduction that can be implemented faster due to the relatively high maturity of the technology. Tankers, dry bulk carriers, and container vessels contribute a majority of global shipping emissions and are therefore prime candidates for carbon capture and storage. Solvent-based post-combustion capture is chosen for this study as it is mature and suitable for marine applications, though technical, economic, environmental, and practical challenges remain. This paper assesses the technical feasibility of the capture system for ships; both retrofit and newbuild vessels. While achieving zero-emissions presents a significant challenge, it is feasible to attain 70%–90% CO2 reduction through carbon capture in the near term. This reduction is crucial for transforming the industry into a more sustainable and environmentally friendly state. The limitation of space onboard is identified as a key factor in determining the viability, and the 70%–100% increase in energy consumption between existing ships and newbuild will be a substantial operational challenge. However, the high fuel consumption of the capture system could be economically acceptable if the price of alternative fuels remains high.

Analysis of the Impact of Large Container Ships on Port Capacity

Facing the fierce competition in the shipping market, major container liner companies are constantly increasing the scale of container ship construction in pursuit of scale effect, and the trend of large-scale development of container ships is increasingly obvious. The enlargement of container ships not only intensifies the competition of shipping companies, but also brings profound changes to the port's facilities and equipment. This paper analyzes the development process, background and reasons of the large-scale container ships, as well as the future development trend of large-scale ships. The qualitative and quantitative method was used to analyze the current status of ship enlargement on the development status. Through the corresponding data and cases, combined with the current rise of international trade protectionism and the global spread of new pneumonia, the impact of ship enlargement on port development was analyzed with a view to the port Development provides corresponding theoretical references and suggestions.

Performance measurement of international shipping companies before and during COVID‐19: A DEA Malmquist index and window analysis approach

AbstractFor the past several decades, the container shipping industry has grown rapidly. As a result, container shipping companies (CSCs) play a vital role in the global cargo transportation market. Thus, measuring the efficiency of CSCs is a primary concern of managers and practitioners. When the COVID‐19 pandemic broke out, the industry was severely disrupted and presented with unprecedented challenges. For this reason, evaluating how CSCs performed and learning the practices they took to achieve successful business results during this period have become necessary. To serve that purpose, this article used a hybrid method that combined data envelopment analysis Malmquist index with window analysis to analyze the world's nine leading CSCs' performance over time and their efficiency relative to each other, using data collected within a 5‐year period from 2016 to 2020. Our findings revealed different characteristics and trends in efficiency among these CSCs in terms of technical efficiency change, technological change, and total productivity change. Then, managerial implications were discussed to understand the best practices of successful CSCs as well as the circumstances in which some of them underperformed during this time. In closing, the study summarized a fact‐based guideline CSCs could take as management reference should a similar crisis occur.

Dominant conditions for strong resonance of an advancing containership under small-amplitude regular waves

ABSTRACT Seakeeping of a ship under waves is vital for safety, with strong resonance occurring when two conditions are met: (1) large wave loads, and (2) wave frequency being close to the natural frequency. Prior research focused on resonant phenomena, nonlinear traits, and failure modes, but the dominant condition for resonance in ocean-going ships is unclear. This study developed a mathematical model using the boundary element method (BEM) for an advancing ship under small-amplitude waves. An open-source solution was proposed, utilizing NEMOH for hydrodynamic coefficients and a Python code for dynamic equation solving. Validated with KRISO Container Ship (KCS) data, the mathematical model accurately predicts ship motions. Findings show that ship heave resonance is influenced by both conditions, but the second condition affects rolling more, and the first condition controls pitch more. This is more evident in high-speed ships and is less affected by ship size variations.

Pandemic performance portals

ABSTRACT This collaborative co-authored article argues that performance is a portal that can connect ‘infinite' and ‘far’ communities, and that portals can invite a sense of world-building through digital connections. For two months, a gold shipping container in Glasgow connected to other portals in Iraq, Rwanda, Mexico City, Palestine and Uganda for intimate performance encounters. Using performances created for the Climate Portals festival at the Royal Conservatoire of Scotland during COP26 in November 2021, this article considers performance as a portal that provokes reconsiderations of space, place, and time.

A Ship Path Tracking Control Method Using a Fuzzy Control Integrated Line-of-Sight Guidance Law

A fuzzy control improvement method is proposed with an integral line-of-sight (ILOS) guidance principle to meet the needs of autonomous navigation and high-precision control of ship trajectories. Firstly, a three-degree-of-freedom ship motion model was established with the battery-powered container ship ZYHY LVSHUI 01 built by the COSCO Shipping Group. Secondly, a ship path-following controller based on the ILOS algorithm was designed. To satisfy the time-varying demand of the look-ahead distance parameters during the following process, especially under different navigation conditions, fuzzy logic controllers were designed for different navigation conditions to automatically adjust the look-ahead distance parameters. Thirdly, a controller was applied that uses a five-state extended Kalman filter (EKF) to estimate the heading, speed, and heading rate based on the ship’s motion model with the assistance of Global Navigation Satellite System (GNSS) position measurements. This provides the necessary navigational information, reduces the algorithm’s dependence on sensors, and improves its generalizability. Finally, path-following experiments were carried out in the MATLAB experimental platform, and the results were compared with different following algorithms. The simulation results showed that the new algorithm has a better following performance, and it can maintain a smooth rudder angle output. The research results provide a reference for the path-following control of ships.

Criteria pollutant and greenhouse gas emissions from cargo handling equipment operating at the Ports of Los Angeles and Long Beach

This study reports in-use emissions from eight pieces of diesel or natural gas cargo handling equipment (CHE) moving containerized freight at the Ports of Los Angeles and Long Beach. Equipment had engines certified to the legacy on-road model year (MY) 2010 or the off-road Tier 3, Tier 4 Interim, or Tier 4 Final emission standards. Overall, load factors were about half of the values in the California Air Resources Board's (CARB) current CHE emissions inventory, oxides of nitrogen (NOx) emissions were 2.7 times higher than certification standards, and tailpipe-emitted fine particulate matter (PM2.5) emissions were 2.2 times higher than certification standards. This is yet another study, the first dedicated to in-use operations by CHE at a large commercial seaport, showing elevated in-use emissions from combustion-powered mobile sources compared to certification levels. These results underscore the need to perform routine surveillance emissions testing of any off-road mobile source fleet when developing emission inventories and air quality programs for any jurisdiction worldwide. The Energy Economy Ratio (EER) – or ratio of increased efficiency from converting combustion to zero-emission battery-electric equipment – ranged from 2.8 to 3.7, which highlights potential energy savings and therefore greenhouse gas benefits of transitioning CHE and other freight sectors to zero-emission technologies.

An application of integrated AHP and TOPSIS methodology on the choice of transshipment container port in the Eastern Mediterranean basin

In container transportation by sea, it is crucial to define the transshipment design. Liner operators desire not only to reduce operational costs but also to maximize customer satisfaction. Therefore, a transshipment hub port selection problem becomes at the front to gaining productive transshipment ability. The study aims to apply an alternative approach to determine the best transshipment hub port for a northbound container ship entering the Eastern Mediterranean basin through the Suez Channel. The proposed model consists of criteria that are weighted with the AHP method and numerical data regarding each criterion is used to rank the alternatives. Thus, as a decision-maker, the line operator can determine the transshipment port quickly using an easily applicable method upon determining the port calls and the schedules. The findings imply that connectivity is the most important criterion for the choice of transshipment hub port for containerized goods. The location was also found important for this choice, but to improve transshipment function, the proper way may be to draw beneficial strategies on maritime connectivity. On the other hand, capital investments such as superstructure improvement were found to be less important for an attractive transshipment hub.

A Comprehensive Analysis of Structural Alternatives and Local Opening for a 2000 TEU Green Methanol-Powered Container Vessel

In the context of global trade and environmental concerns, this research focuses on examining the influence of the principal dimensions of a container feeder vessel whose propulsion has been modified to operate with green methanol. Methanol emerges as a sustainable marine fuel, reducing emissions and dependence on fossil fuels. The study comprehensively examines the structural challenges posed by container ships, with a particular focus on torsional stresses and hydroelasticity effects. A significant novelty of this study is the inclusion of a comparative structural analysis evaluating how changes in the vessel’s main dimensions impact its structural response. This analysis sheds some light on crucial insights into the effects of structural modifications required for accommodating these changes, ensuring the structural strength of these vessels. The research also underscores the impact of permanent and transient springing and whipping phenomena on fatigue damage. The study’s significance lies in its role in the ongoing transition to sustainable maritime transportation, as it not only examines structural challenges but also provides solutions for achieving an optimal structural configuration in this new era of environmental responsibility.

Robust Decision-Making for the Reactive Collision Avoidance of Autonomous Ships against Various Perception Sensor Noise Levels

Autonomous ships are expected to extensively rely on perception sensors for situation awareness and safety during challenging operations, such as reactive collision avoidance. However, sensor noise is inevitable and its impact on end-to-end decision-making has not been addressed yet. This study aims to develop a methodology to enhance the robustness of decision-making for the reactive collision avoidance of autonomous ships against various perception sensor noise levels. A Gaussian-based noisy perception sensor is employed, where its noisy measurements and noise variance are incorporated into the decision-making as observations. A deep reinforcement learning agent is employed, which is trained in different noise variances. Robustness metrics that quantify the robustness of the agent’s decision-making are defined. A case study of a container ship using a LIDAR in a single static obstacle environment is investigated. Simulation results indicate sophisticated decision-making of the trained agent prioritising safety over efficiency when the noise variance is higher by conducting larger evasive manoeuvres. Sensitivity analysis indicates the criticality of the noise variance observation on the agent’s decision-making. Robustness is verified against noise variance up to 132% from its maximum trained value. Robustness is verified only up to 76% when the agent is trained without the noise variance observation with lack of its prior sophisticated decision-making. This study contributes towards the development of autonomous systems that can make safe and robust decisions under uncertainty.

The impact of container call size - evidence from simulation modelling

We present an analysis of the impact of large container ship call sizes on the operational efficiency of container terminals as well as on hinterland modes of transport. We use standard container terminal simulation software, that can represent a realistic terminal operation. We include dynamic crane productivity, arrival time uncertainty, and deepsea vessel prioritisation in our model.Our experiments investigate the impact of introducing larger call sizes of container ships, increasing the uncertainty in arrival times of deepsea ships, and the impact of the phenomenon of split calls that are employed by the largest container ships in certain regions in the world. We differentiate between the impact on terminal operations, land-based hinterland traffic, and hinterland traffic over water, through barges and feeder vessels.Our results show that introducing large ships with large container call sizes comes with benefits and drawbacks. Benefits can be found in planning advantages for both the deepsea ships and barges and feeders handled in the terminal. Drawbacks occur as a result of operational peaks in subsystems such as the quay cranes, the stack and the land side gates. Higher uncertainty deteriorates the performance of the terminal, but the impact on the hinterland modes of transport is greater than on the large deepsea vessels. The impact of the split call is that it brings all the disadvantages of large vessels, but none of the benefits.Our analysis shows the operational impact of large call sizes on terminal operations and hinterland transport operations, based on container terminal simulations with a higher degree of realism than previous work. In addition, we offer, for the first time, insights in the impact of split calls of container ships at container terminals.

Optimizing inland container shipping through reinforcement learning

In this study, we investigate the container delivery problem and explore ways to optimize the complex and nuanced system of inland container shipping. Our aim is to fulfill customer demand while maximizing customer service and minimizing logistics costs. To address the challenges posed by an unpredictable and rapidly-evolving environment, we examine the potential of leveraging reinforcement learning (RL) to automate the decision-making process and craft agile, efficient delivery schedules. Through a rigorous and comprehensive numerical study, we evaluate the efficacy of this approach by comparing the performance of several high-performance heuristic policies with that of agents trained using reinforcement learning, under various problem settings. Our results demonstrate that a reinforcement learning approach is robust and particularly useful for decision makers who must match logistics demand with capacity dynamically and have multiple objectives.

Research on Ship Resistance Prediction Using Machine Learning with Different Samples

Resistance serves as a critical performance metric for ships. Swift and accurate resistance prediction can enhance ship design efficiency. Currently, methods for determining ship resistance encompass model tests, estimation techniques, and computational fluid dynamics (CFDs) simulations. There is a need to improve the prediction speed or accuracy of these methods. Machine learning is gradually emerging as a method applied in the field of ship research. This study aims to investigate ship resistance prediction methods utilizing machine learning across various datasets. This study proposes two methods: employing stacking ensemble learning to enhance resistance prediction accuracy with identical ship samples and utilizing various ship resistance prediction models for accurate resistance prediction through transfer learning. Initially focusing on container ships as the research subject, the stacking ensemble learning model outperforms the basic machine learning model, the Holtrop and Mennen method, and the updated Guldhammer and Harvald method based on comparative prediction results. Subsequently, the container ship resistance prediction model achieves precise resistance prediction for bulk carriers. This study offers dependable guidance for applying machine learning in predicting ship hydrodynamic performance.

LEGAL POSSIBILITIES FOR CREATING A SINGLE OPERATOR FOR THE TRANSPORTATION OF CONTAINERS BY RUSSIAN COMPANIES ALONG THE NORTHERN SEA ROUTE

Purpose of the research. This article discusses current issues of organizing the transportation of container cargo by a Russian operating company along the Northern Sea Route. The advantages of using the Northern Sea Route as an international transport and logistics corridor have been identified. The problems of organizing and implementing the transportation of containers along the Northern Sea Route have been identified. A scheme for legal regulation of the activities of a Russian operator for the transportation of containers along the Northern Sea Route has been developed. Results. It has been established that in the Russian Federation there is a necessary system of legal regulation of the functioning of the operator for the transportation of containers along the Northern Sea Route, which makes it possible to create a state-owned Arctic Container Shipping Company on the basis of the Rosatom, which will be a national operator for the transportation of containers and will be able to most successfully and efficiently establish a Unified a system for transporting container cargo along the Northern Sea Route.

Integration effect of shipping network based on shipping alliances

ABSTRACT Shipping alliances and shipping lines are one major research field concerning marine management. This paper examines the role played by shipping lines in shaping the global container shipping network, and focuses on the significant impact of shipping alliances on the global shipping market. The scientific evaluation of the effects of shipping alliances construction and reorganization on network integration remains inadequate. To bridge this gap, our study uses AIS big data to construct a comprehensive model of the container shipping network from the perspective of multilayer, focusing on two levels: shipping alliances and shipping lines. Our findings show that while shipping lines have been competing for shipping markets fiercely, the construction of shipping alliances eases the competition among them and promotes their cooperation. The three alliances have formed a new oligopoly pattern, combining to build a complete and mature network with increased efficiency, density, and stability. Shipping alliances promote spatial complementarity, expand network coverage, and develop branches. We also identify distinct spatial patterns for each alliance, with differentiated complementary structures. This study sheds light on the spatial effect of shipping network integration, offering a new perspective and method for understanding the organization of the global shipping network.