Containerized Research Articles

The effects of tropical cyclone on the container shipping network: A case study of typhoon Ma-on (2022)

As climate change intensifies, tropical cyclones pose increasing challenges to container shipping networks (CSN). However, research related in this area remains insufficient. In this study, we analyzed the effects of Typhoon Ma-on on the CSN using over 776 million Automatic Identification System (AIS) trajectory signals. Our findings reveal that the typhoon not only altered the network structure of the CSN but also affected the importance of container ports, vessel flow, and travel distance fluctuations along shipping routes. After the typhoon, the recovery of the network’s connectivity and stability, as well as travel time fluctuations, was less robust compared to other aspects. Additionally, the impact ranges for port importance, vessel flow, and travel distance fluctuations were 1,750 km, 500 km, and 2,250 km, respectively, following an inverse distance decay pattern. These findings offer new insights for stakeholders to enhance the effectiveness of disaster prevention and mitigation policies.

Research on parametric roll of the polar environmental transport ship based on time-domain Rankine panel method

In this study, the roll damping of a polar environmental transport ship (PETS) is estimated using viscous CFD method, and the parametric roll is simulated based on time-domain Rankine panel method. This method's reliability is validated by contrasting the simulation results with the experimental data of C11 container ship. The roll damping of C11 container ship is estimated using CFD method and improved Ikeda's method, respectively. Then, the time-domain Rankine panel method is adopted to simulate the roll motions of C11 container ship, and the simulation results are contrasted with experimental data. It confirms that the roll damping is calculated by CFD method and the roll motions of ships are simulated based on time-domain Rankine panel method has good applicability. Finally, the influence of wave steepness, wavelength, and the ratio of encounter frequency ωe to natural roll frequency ωroll on the parametric roll of PETS are studied. It is found that the maximum roll angle of PETS increases along with wave steepness. As the wavelength increases, the possibility of parametric roll for PETS is also increasing. When the parametric roll of PETS occurs, the ωe/ωroll tends to increase.

Onboard amino acid salt-based CO2 integrated absorption and mineralization: Kinetics, mechanism, economics and life cycle

The International Maritime Organization's ambitious greenhouse gas reduction strategy is driving efforts to capture carbon from marine engine exhaust gas. Onboard carbon capture and storage (OCCS) faced significant challenges, particularly due to the substantial thermal energy requirements during the capture process and the complexities of transporting captured CO2 to storage facilities. The integrated CO2 absorption and mineralization (IAM) process, a thermodynamically downhill process, offered a potential solution for rapidly absorbing and sequestering CO2 in-situ. In this study, a single-step amino acid salt-based IAM process was employed to address carbon emissions from ships. Under optimized conditions, over 85 % of the CO2 in simulated marine engine exhaust gas was captured and completely converted to calcium carbonate using a potassium glycinate/ calcium hydroxide blend absorption slurry. This approach tackled the key challenges of effectively capturing CO2 from ships, while minimizing energy consumption, and ensuring the safe storage of the captured CO2. A case study on a 1700 TEU container ship evaluated the economic benefits and global warming potential of the OCCS system, indicating that capturing CO2 from ships could be profitable (87.2 $/ton CO2) and calcium carbonate could be a commercial product. Despite high-carbon-intensity absorbents (such as calcium hydroxide) partially offset the carbon reduction effort, resulting in a decline of carbon capture efficiency from 85 % to 44 %. The proposed amino acid salt-based IAM method could be considered a promising technique for reducing carbon emissions from ships, providing a feasible technical means for achieving the International Maritime Organization's ambition strategy for zero-carbon shipping.

Rapid cargo verification with cosmic ray muon scattering and absorption tomography

Cosmic ray muon tomography is considered a promising method for the non-invasive inspection of shipping containers and trucks. It utilizes highly penetrating cosmic-ray muons and their interactions with various materials to generate three-dimensional images of large and dense materials, like inter-modal shipping containers, typically not transparent with conventional X-ray radiography techniques. The commonly used methods for imaging with muons are based on muon scattering or absorption-transmission data analysis. Due to large thickness of cargo material in shipping container substantial scattering and absorption occur when muons are passing through cargo. One of the key tasks of customs and border security is to verify shipping container declarations to prevent illegal trafficking, and muon tomography could be a viable choice for this task. In this paper, we demonstrate through Monte Carlo simulations using the GEANT4 toolkit that a combined analysis of muon scattering and absorption data can improve the identification of cargo materials compared to using scattering or absorption data alone. The statistical differences in scattering and absorption data for several cargo materials are quantified. For a particular smuggling scenario where tobacco declared as paper towel rolls, it is demonstrated that the combined analysis can accurately distinguish between tobacco and paper towel rolls with 5.5σ accuracy for detector spatial resolution (FWHM) of 0.235 mm, 4.5σ for 1.175 mm resolution (FWHM), and 3.9σ accuracy for 2.35 mm spatial resolution (FWHM), in a short scanning time of 10 seconds. This rapid detection capability has significant implications for anti-smuggling efforts and cargo inspection.

Numerical simulation and analysis of motion responses and added resistance of a KRISO container ship in regular waves

Abstract In order to explore the influence of vessel speed on seakeeping characteristics and provide valuable insights for ship performance evaluation, the accurate prediction of ship motion and resistance in wave conditions is essential. In this study, the variations in ship motion and resistance with respect to ship speed are analyzed during navigation in regular waves. The results suggest that the added resistance coefficient of the KCS demonstrates an initial rise, succeeded by a subsequent decline, with the expansion of wavelength. Moreover, the peak non-dimensional resistance coefficient, observed at different ship speeds, demonstrates an upward trend with the augmentation of ship velocity. This research methodology provides a valuable tool for numerically predicting the hydrodynamic performance of vessels in regular wave conditions.

Evaluating Environmental Impact and the Significance of Shipboard Carbon Capture and Storage for Emission Reduction in Maritime Sector

Abstract This study conducts Life Cycle Assessment (LCA) to evaluate the environmental impacts of Shipboard Carbon Capture & Storage (SCCS) across its entire lifecycle. It examines the full-spectrum carbon capture and storage effects from well-to-tank and tank-to-propeller for four types of marine fuels: Very Low Sulphur Fuel Oil (VLSFO), Marine Gas Oil (MGO), Liquefied Natural Gas (LNG), and Methanol. Additionally, the study examines the Energy Efficiency Existing Ship Index (EEXI) and Carbon Intensity Indicator (CII) of a current ocean-going container ship to quantify the potential benefits of SCCS in reducing ship carbon emissions. The results indicate that the application of SCCS can significantly reduce emissions from carbon-based fuels during ship operations. In particular, ships using VLSFO as fuel can achieve 61.0% reduction in emissions by installing SCCS. However, the application of SCCS leads to 7.8% increase in fuel consumption due to additional energy requirement. In addition, this study also found while fossil methanol reduces emissions during ship combustion, its life cycle emissions are 17.5%-19.6% higher than conventional fossil fuel due to production emissions. The overall SCCS has a positive impact on emission reduction for ships and is reflected in the improvements in EEXI and CII. With the implementation of SCCS, ships fuelled by VLSFO and MGO can remain compliant with IMO Greenhouse Gases emission strategy until 2030. For ships fuelled by LNG and Methanol, compliance can remain beyond 2030.

Air Pollutant Emission Factors of Inland River Ships under Compliance

Inland river ships (IRSs) use diesel with a lower sulfur content and emit relatively low emissions, making it challenging to monitor their emissions. Sniffer monitoring equipment was installed from August 2020 to June 2022 at the Gezhou Dam of the Yangtze River and monitored emissions from 8,238 IRSs passing through the lock. We partnered with the maritime department to select 100 ships passing through the lock to extract fuel oil samples for direct fuel sulfur content (FSC) detection, which determined the actual FSC of the passing ships. The monitoring data from these 100 ships indicated that the relative error of the SO2 emission factors (EFs) and FSC results is significant at the 10-parts-per-million level. The monitoring data from the remaining 8,138 ships showed that the EFs of NO, NO2, PM2.5, and PM10 were 24.02 ± 16.92 g kg−1, 10.30 ± 18.08 g kg−1, 0.72 ± 0.60 g kg−1, and 0.92 ± 0.70 g kg−1, respectively. The NOx EFs of container ships are higher than those of other ship types, while the PM EFs for different ship types do not significantly differ. Based on these EFs, we calculated the average emission rates for different types of ships passing through locks, which is a real-time measurement method for estimating ship emissions. In addition, a comparison of ship EF measurements over the past 20 years revealed that EF values for SO2, NOx, and PM exhibited a downward trend, with the calculated results of the current study determined to be the lowest numerical level.

Dispersion of anhydrous ammonia inside a confined space onboard a hypothetical ammonia-powered vessel

Abstract In order to ensure the responsible use of anhydrous ammonia as clean marine fuel, safety aspects in respect of its post-release consequence cannot be understated. This contribution is aimed to address the gaps of understanding associated to events of ammonia loss of containment (LoC) in enclosed spaces onboard ammonia-fuelled vessels. A forced ventilated fuel preparation room (FPR) onboard a container vessel is chosen as a study case with minor and major release scenarios, which is based on the orifice size. The dispersion analysis was performed using three-dimensional computational fluid dynamics. The analysis revealed that toxicity associated to the rapid and persistent ammonia vapor cloud buildup is by far the most significant hazard in the space. In the major release scenario, gradual evaporation of rainout pool increases the vapor cloud persistence even far beyond the leak isolation time. The results and finding above underlines the importance of concerted effort in mitigating not only the ammonia vapor cloud, but also the accumulated ammonia liquid pool.

Анализ уровня развития мультимодальных перевозок в потенциальных маршрутах "Новый Шелковый путь"

The routes and significance of the New Silk Road project are examined. The objectives of Kazakhstan in the direction of development of the transport and logistics system have been identified. The economic efficiency of container transportation has been assessed. The existing transport corridors for container shipping in the China-Europe direction are described. The requirements for multimodal transportation and ways of their implementation are shown. The carrying capacity of the railway for intermodal transport was taken into account.

Digital twin-driven safety management and decision support approach for port operations and logistics

Ports are of great significance in processing cargo containers and facilitating global marine logistics. Nevertheless, the susceptibility of the container shipping network for hazardous cargo is likely to intensify in the event of a significant disruption at a major port, such as adverse weather conditions, inadequate management practices, or unforeseen catastrophes. Such situations require the deployment of port protection emergency response and prevention in advance. This study proposes a digital twin (DT) model that employs extensive and trajectory data within containers to comprehensively analyze the occurrence of hazardous cargo failures within the port storage process. The virtual models of physical entities in the port are created through a data-driven approach, and the behavior of these entities in a port environment with big data is then simulated. A combination of a convolutional neural network (CNN) and a long short-term memory (LSTM) algorithm is employed to provide predictions for the service layer of the DT system. The predicted correlation coefficients of temperature and humidity in the container reach 0.9855 and 0.9181, respectively. The developed system driven by DT models integrated with a CNN and the LSTM algorithm can more effectively assist the safety manager in achieving prevention in port operations. This study enables marine authorities and decision-makers to optimize emergency procedures, thereby reducing the probability of accidents in port operations and logistics.

Impact of Blockchain Technology on Logistics and Foreign Trade Turnover in Kazakhstan

The purpose of this study is to analyze the impact of logistical factors on Kazakhstan's foreign trade turnover for the period from 2013 to 2023, with a particular focus on cargo transportation volumes, freight turnover, container traffic, and transit transport volumes. The research employs a comprehensive and robust methodology that includes data collection, regression analysis, and model refinement to ensure the validity and reliability of the results. The regression analysis initially included all collected variables, but the model was refined to address multicollinearity and retain statistically significant predictors. The model initially included all variables, but was later refined to address multicollinearity, retaining only statistically significant predictors. The results of the analysis showed that the volume of transit transport is a significant factor affecting the foreign trade turnover of Kazakhstan. The model demonstrated a positive and statistically significant coefficient for the volume of transit transport (0.004534, p-value = 0.025962), which confirms the hypothesis of its crucial role. Additionally, the potential integration of blockchain technology in logistics processes is explored, suggesting that such advancements could enhance transparency, efficiency, and reliability in managing transit goods. By adopting a comprehensive approach that examines multiple logistics factors simultaneously and leveraging a long-term dataset, this research offers novel insights into the logistics-trade relationship in Kazakhstan.

Shanghai Containerised Freight Index Forecasting Based on Deep Learning Methods: Evidence from Chinese Futures Markets

Shanghai Containerised Freight Index Forecasting Based on Deep Learning Methods: Evidence from Chinese Futures Markets

Simulation-based evaluation of road transportation logistics in a dry port with topographic challenges

The extension of existing container terminals or the creation of new ones introduces new logistical challenges, including topographic issues and increased distances between the quays and storage yards located several kilometers away from the quay (dry port). These challenges are complex to evaluate analytically and directly impact the acceleration, deceleration, and average speed of a truck which in turn affect the productivity and synchronization of the overall terminal logistics. This paper proposes a transportation simulation model that incorporates detailed descriptions of the topographical and geometrical restrictions. Our simulation model evaluates various scenarios for container transportation logistics, including varying road design terminals and truck fleet size to enhance productivity. A case study from a potential container terminal on Canada’s St. Lawrence River is used to demonstrate the simulation model. Several scenarios with different designs are tested and the simulation provides numerical results for supporting decision makers.

AGV Scheduling for Optimizing Irregular Air Cargo Containers Handling at Airport Transshipment Centers

Airport transshipment centers play a pivotal role in global logistics networks, enabling the swift and efficient transfer of cargo, which is essential for maintaining supply-chain continuity and reducing delivery times. The handling of irregularly shaped air cargo containers presents new constraints for automated guided vehicles (AGVs), as these shapes can complicate loading and unloading processes, directly impacting overall operational efficiency, turnaround times, and the reliability of cargo handling. This study focuses on optimizing the scheduling of AGVs to enhance cargo-handling efficiency at these hubs, particularly for managing irregular air cargo containers. A mixed-integer linear programming (MILP) model is developed, validated for feasibility with the Gurobi solver, and designed to handle large-scale operations. It incorporates a novel approach by integrating a simulated annealing optimized genetic algorithm (GA). The experimental results demonstrate that the designed algorithm can solve models of considerable size within 8 s, offering superior time efficiency compared to the solver, and an average solution quality improvement of 12.62% over the genetic algorithm, significantly enhancing both the model’s efficiency and scalability. The enhanced AGV scheduling not only boosts operational efficiency but also ensures better integration within the global logistics framework. This research provides a robust foundation for future advancements in logistics technology, offering both theoretical and practical insights into optimizing complex transportation networks.

Identification modeling of ship manoeuvring motion based on ISSA-SVR

This paper introduces the sparrow search algorithm–support vector regression (SSA-SVR) for the first time to improve the precision of mathematical modelling for ship motion through parameter identification. To address the nonsmoothness in ship motion, this study proposes a multistrategy enhanced modelling method named the improved SSA-SVR (ISSA-SVR) for predicting ship motion. Using the KRISO container ship (KCS) test data, this study establishes first-order linear response, second-order nonlinear response, and manoeuvring model group mathematical models through ISSA-SVR identification. The generalisability of the models derived from support vector regression, backpropagation neural networks, particle swarm optimisation-SVR, SSA-SVR, and ISSA-SVR is validated using distinct data from different samples. The results show that the algorithmic model proposed herein excels in prediction compared with other algorithms, thus highlighting its superior generalisation. Furthermore, the proposed method offers solutions with increased accuracy and improved stability for modelling ship motion.

Energy Analysis of Standardized Shipping Containers for Housing

Energy Analysis of Standardized Shipping Containers for Housing

Potential for the Development of International Transport Corridors in Current Market Conditions

This research is devoted to the prospects for the development of international transport corridors (ITC) through the prism of the dynamics of market forces in the transport industry and world trade. International logistics is currently undergoing a global transformation, and therefore the effective use by Russia of its transport potential is still the most urgent and practical task. In this regard, this research is focused on internal and external factors that influence the realization of this potential. The research presents the factors that contributed in retrospect for more than 10 years to the dynamic development of freight transportation through the ITC “East – West”. Additionally, the impact of exogenous factors such as epidemiological restrictions on a global scale and economic sanctions against Russia on the logistics of container transportation in recent years is considered in more detail. On the basis of a retrospective analysis of the development of cargo transportation through the ITC “East – West” generalized conditions are formulated that allow to assess the potential for the development of transport cargo fl ows on other key ITC. An analysis of the current dynamics and problems of the development of transportation along the corridors East – West, Northern Sea Route and North-South is carried out. Further prospects for their increase from the point of view of transport marketing is provided. Among the conclusions, the importance of developing and expanding the infrastructure of the ITC “East – West”, as well as proposals for the intensifi cation of cargo transportation through other ITC, is highlighted.

Numerical investigation on behaviour of mooring line system for container ship at berth

The constant growth of the world’s maritime industry has led to the need to increase the size of ships as wellas accelerate the trend of moving ports to open sea areas and outside estuaries. Increasing the size of ships,especially container ships, has the potential to cause unsafe ship anchoring in ports. Furthermore, the mooringof ships at the harbor also lacks international guidelines on the layout of the mooring system. Meanwhile, relocating seaports outside estuaries and open seas can create conditions for high winds, high tidal fluctuationsand strong currents to penetrate the port basin. This paper presents a study using the MIKE 21 MA numericalmodel to determine the most optimal mooring layout for a container ship as well as clarify the influence offactors (wind, current, water level and ship’s draft) on the tension force of the mooring lines. The most optimal mooring layout in the study scenarios was uncovered from the simulation results. In addition, wind wasidentified as the factor with the greatest influence on the tension force of the mooring system.

Анализ технологических процессов погрузочно-разгрузочных, транспортных, перегрузочных и складских операций на основе контейнерных перевозок

The article discusses key technological operations, including loading and unloading, transportation, transshipment and storage of goods in containers, as well as analyzes modern approaches to managing and optimizing these processes. The main attention is paid to the automation and mechanization of loading and unloading operations, the use of multimodal transportation to improve the efficiency of transport processes, the development of strategies for optimizing routes and logistics schemes, as well as the use of modern information technologies for cargo tracking and inventory management. The authors of the article emphasize the importance of integrating logistics operations and creating a unified information system for coordinating all stages of container transportation. As a result of the analysis, ways to improve technological processes aimed at reducing costs, increasing the speed of cargo delivery and increasing the overall efficiency of logistics chains are proposed. The article contains recommendations on the introduction of innovative solutions and technologies that can help optimize the work of enterprises engaged in container transportation. The research is based on the analysis of real data, including statistics on the operation of ports, transport companies and warehouse complexes, as well as on the study of best practices in this area. The article provides examples of successful implementation of the proposed approaches in practice, which makes it useful for specialists in the field of logistics, supply chain management and transportation.

Toward green container liner shipping: joint optimization of heterogeneous fleet deployment, speed optimization, and fuel bunkering

AbstractContainer liner shipping companies, under the international shipping carbon reduction indicators proposed by the International Maritime Organization, must transform two key aspects: technology and operations. This paper defines a green liner shipping problem (GLSP) that integrates the deployment of a heterogeneous fleet, speed determination, and fuel bunkering. The objective is to achieve low‐carbon operations in liner shipping, taking into consideration the diversification of power systems, the use of alternative fuels in ships, and the continuous improvement of alternative fuel bunkering systems. For this purpose, we present a bi‐objective mixed integer nonlinear programming model and develop two methodologies: an epsilon‐constraint approach and a heuristic‐based multi‐objective genetic algorithm. We validate the effectiveness of our model and methods through a case study involving container ships of various sizes deployed on intra‐Asian short sea routes by SITC International Holdings Co., Ltd. The experimental results highlight the crucial role of dual‐fuel (DF) ships in the pursuit of low‐carbon strategies by liner companies, with liquefied natural gas and ammonia DF ships being the most widely used. Additionally, fuel cell (FC) ships, particularly those powered by ammonia and hydrogen, demonstrate significant carbon reduction potential. Furthermore, ships with larger container capacities have a greater cost advantage. For the GLSP, speed determination is an auxiliary decision, and the lowest speed is not necessarily the optimal choice. Decision‐makers must carefully balance competing economic and carbon emission reduction objectives, as deploying more alternative fuel ships may increase fuel bunkering and fuel consumption, resulting in a higher total operating cost.