Twenty-foot Equivalent Units Research Articles

Analysis of Trends in Mega-Sized Container Ships Using the K-Means Clustering Algorithm

The size of ships is increasing rapidly, and over 400 m length overall mega-sized container ships are predicted to appear in the near future. Consequently, studies on large container ships have been conducted; however, based on the 30,000-TEU (twenty-foot equivalent unit) class container ship’s length overall, the deviation of the predicted range showed an 83.9 m difference from 453.0 m to 536.9 m. This is because simple linear regression analysis does not consider trends according to the type of cargo or the size of the cargo. In this study, 5497 container ships up to 20 years of age with an International Maritime Organization (IMO) number registered were clustered according to the change in ship dimensions by k-means clustering algorithm. Based on the clustered data, deadweight tonnage, TEU, length overall, length between perpendiculars, breadth, and maximum draft of container ships with a coverage rate of 75% were analyzed to predict the change in the main dimensions. The results indicated that for a 30,000-TEU container ship, the predicted length overall is 428.4 m, breadth is 67.6 m, and draft is 17.0 m. This study can help minimize the social costs of designing ports in consideration of future mega-sized container ships.

New finding of peridomestic Triatoma infestans (Klug, 1834) (Hemiptera: Reduviidae) in Mexico: Molecular approach using cytochrome B and cytochrome oxidase I.

A previous work morphologically identified some specimens colonizing peridomestic sites of Manzanillo Colima, Mexico, as Triatoma infestans (Klug). In the present study, a molecular approach using cytochrome B and cytochrome oxidase I was implemented for the genetic identification and determination of the origin of that population. Phylogenetic analyses positively identified our studied specimens as belonging to the T. infestans clade based on genetic markers with high posterior probability values, and the haplotype network showed Uruguay, Chile and Argentina as probable countries of origin of the populations in Mexico, which was supported by gene flow and migration index analyses. Due to the proximity of the port of Manzanillo to the collection sites, the introduced specimens were hypothesized to have travelled from the countries of origin to Mexico in a seed shipment inside a TEU (twenty-foot equivalent unit) maritime container. The identification of T. infestans in Mexico represents a serious health problem, and the findings presented here indicate a novel pathway for displacing this vector with the possibility of transmission to any other part of the world, which should be further investigated.

Optimal Slow Steaming Speed for Container Ships under the EU Emission Trading System

Slow steaming is an operational measure in ocean-going vessels sailing at slow speeds. It can help climate mitigation efforts by cutting down marine fuel consumption and consequently reducing CO2 and other Greenhouse Gas Emissions (GHG). Due to climate change both the European Union (EU) and the International Maritime Organization (IMO) are analysing the inclusion of international shipping in the EU Emissions Trading System (ETS) in the near future or alternatively implementing a carbon tax. The paper proposes a methodology to decide the optimal speed of a vessel taking into account its characteristics and the factors that determine its economic results. The calculated cash flow can be used in valuation models. The methodology is applied for a case study for any container ship in a range from 2000 to 20,000 Twenty-foot Equivalent Units (TEU) on a leg of a round trip from Shanghai to Rotterdam. We calculate how speed reduction, CO2 emissions and ship owner’s earnings per year may vary between a business-as-usual scenario and a scenario in which shipping is included in the ETS. The analysis reveals that the optimal speed varies with the size of the vessel and depends on several variables such as marine fuel prices, cargo freight rates and other voyage costs. Results show that the highest optimal speed is in the range of 5500–13,000 TEUs whether or not the ETS is applied. As the number of TEUs transported in a vessel increases emissions per TEU decrease. In an established freight rate market, the optimal speed fluctuates by 1.8 knots. Finally, the medium- and long-term expectations for slow steaming are analysed based on future market prices.

Estimation of land-based emissions during container terminal operations in the Ambarlı Port, Turkey

Many types of mobile vehicles are used simultaneously in container terminal operations. Because most of these mobile vehicles have diesel engines, they emit a significant amount of pollutant emissions into the atmosphere during their operation. They are considered as land-based mobile emission sources (MobES) and should be included in the total port emission inventory. The emission inventory is a basic requirement in developing an environmental management strategy to improve emission control. In this context, this study aims to estimate the emission inventories of mobile vehicles used in terminal operations in the Ambarlı container ports located in the city of Istanbul, which is one of the most populous cities in the world. In this respect, the amounts of the emissions of all the container handling equipment with diesel engines in the port areas, including external trucks delivering/receiving containers to/from the port were estimated using an activity-based method. It has been found that approximately 42.39% of the total CO2 emission is owing to terminal tractors and the total annual CO2 value per TEU (Twenty-foot Equivalent Unit) of MobES is 0.01259 tons. The CO2 value per TEU can serve as a CO2 emission performance indicator for land-based MobES in process of the evaluation of emission inventories in container ports.

Statistical estimation of container condensation in marine transportation between Far East Asia and Europe

AbstractCondensation inside marine containers occurs during voyages owing to weather changes. In this study, we define the condensation probability along one of the major routes for container ships between Asia and Europe. First, the inside and outside air conditions were measured on land in Japan, and a correlation analysis was conducted to derive their relationship. Second, onboard measurements were conducted for 20,000 twenty-foot equivalent unit (TEU) ships to determine the variation in outside air conditions. Complicated patterns of weather change were observed with changes in latitude, sea area, and season. Third, condensation probability was estimated based on a multi-regression analysis with land and onboard measured data. The maximum condensation probability in westbound or eastbound voyages in winter was found to be approximately 50%. The condensation probability estimation method established in this study can contribute to the quantification of cargo damage risks for the planning of marine container transportation voyages.

Zero emissions wellboat powered by hydrogen fuel cells hybridised with batteries

Due to the more stringent regulations on pollutant and greenhouse gas emissions in the maritime transport sector, solutions are being sought to reduce or avoid the emissions generated during the operation of ships. The onboard installation of hydrogen-fuelled fuel cells is a solution respectful with the environment and the marine ecosystem through which ships navigate. In this work, the design of a wellboat and its power plant based on fuel cells fed with hydrogen and hybridised with batteries is conducted, making it a zero-emissions ship that can navigate Emission Control Areas (ECAs). The fuel cells used are polymer electrolyte membrane fuel cells (PEMFCs), and the hydrogen they consume is stored in tanks pressurised at 35 MPa, grouping these tanks into three standard containers (Twenty-Foot Equivalent Units) installed on an exposed deck. The electrical and propulsion needs of the ship are covered by the installed power plant, providing an average power of 1266 kW and a peak power of 2624 kW, making it possible to avoid the emission of 10.8 t of CO2, 195 kg of NOx and 9 kg of SOx per 14 h mission.

Particle-Gaseous pollutant emissions and cost of global biomass supply chain via maritime transportation: Full-scale synergy model

Environmental and economic issues in the maritime transportation and logistics industry have historically received less stakeholder attention than aviation and overland freight sectors. Stakeholders in the port industry have gradually started paying attention to emissions and cost issues across all the sectors, such as supply chains. Global biomass supply chain is one of the main sectors which has not been addressed in publishedliterature.To address this gap, this study aims to develop a dynamic full-scale synergy model to assess cost-mass flow, particulate matter emissions, and air pollutants for maritime transportation of the global crude palm oil biomass supply chain. Focusing on leading producers of palm oil worldwide, we have analyzed a total of 93 sea routes from Malaysia and Indonesia to main export markets in the US, Europe, and Asia. The analysis distinguishes three freight categories: light, medium-weight, and heavy for different sizes of capacity and types of container ships based on the twenty-foot equivalent unit (TEU). The findings highlight the dependency of greenhouse gas (GHG) emissions level on other factors such as technology, size, and mass flow used for container ships. The results also show a strong relationship between GHG emitted and the type of container ship in a systemic view. A ship with higher TEU contributes to the higher transported amount and lower GHG emissions in the long term. To conclude, the results would increase port industry stakeholders’ understanding of developing energy policies and managerial strategies for low cost and low carbon fuels technologies.

A Feature-Extraction-Based Lightweight Convolutional and Recurrent Neural Networks Adaptive Computing Model for Container Terminal Liner Handling Volume Forecasting

The synergy of computational logistics and deep learning provides a new methodology and solution to the operational decisions of container terminal handling systems (CTHS) at the strategic, tactical, and executive levels. Above all, the container terminal logistics tactical operational complexity is discussed by computational logistics, and the liner handling volume (LHV) has important influences on a series of terminal scheduling decision problems. Subsequently, a feature-extraction-based lightweight convolutional and recurrent neural network adaptive computing model (FEB-LCR-ACM) is presented initially to predict the LHV by the fusion of multiple deep learning algorithms and mechanisms, especially for the specific feature extraction package of tsfresh. Consequently, the container-terminal-oriented logistics service scheduling decision support design paradigm is put forward tentatively by FEB-LCR-ACM. Finally, a typical large-scale container terminal of China is chosen to implement, execute, and evaluate the FEB-LCR-ACM based on the terminal running log around the indicator of LHV. In the case of severe vibration of LHV between 2 twenty-foot equivalent units (TEUs) and 4215 TEUs, while forecasting the LHV of 300 liners by the log of five years, the forecasting error within 100 TEUs almost accounts for 80%. When predicting the operation of 350 ships by the log of six years, the forecasting deviation within 100 TEUs reaches up to nearly 90%. The abovementioned two deep learning experimental performances with FEB-LCR-ACM are so far ahead of the forecasting results by the classical machine learning algorithm that is similar to Gaussian support vector machine. Consequently, the FEB-LCR-ACM achieves sufficiently good performance for the LHV prediction with a lightweight deep learning architecture based on the typical small datasets, and then it is supposed to overcome the operational nonlinearity, dynamics, coupling, and complexity of CTHS partially.

Key Performance Indicators Analysis for Quay Container Crane Performance Assessment (Case Study at Jakarta International Container Terminal)

<p><span lang="PT-BR">PT Jakarta International Container Terminal (JICT) is the largest container port in Indonesia. Currently, JICT capacity is 2.5 million TEUs (Twenty-foot Equivalent Units) per year, it continues to strive to improve international services and is supported by adequate container loading and unloading equipment. The requirement to establish common standards in different types of container port equipment and identify performance indicators to assess the performance of container handling equipment has increased. Although the Quay Container Crane (QCC) operating system may be different at each container terminal, there are similarities in its main movements, namely: Main Hoist, Trolley, Gantry, and Boom. By knowing the clock metric for each movement, it is possible to determine the Key Performance Indicator (KPI) that has been adopted and assess the performance of the Quay Container Crane (QCC). The results of the study identified that the value of MMBF (Mean Move Between Failures) decreased due to the accumulation of long-lasting heavy load operations, while the number of maintenance activities for machine parts and working hours continued to increase. Key Performance Indicator (KPI) as a management tool can guide QCC inspections and the results can provide useful insights for improving the performance of equipment and container loading and unloading operations in the future.</span></p>

Politics of scale: Colossal containerships and the crisis in global shipping

This article addresses overcapacity and crisis in global shipping through the case of the HMM Algeciras, the world's largest containership inaugurated in 2020. When she left the South Korean shipyard where she was built, the HMM Algeciras (with a size of two soccer fields) could carry 24,000 twenty‐foot equivalent units (TEUs) across the world's oceans. By following the mega‐containership's links to two South Korean shipping companies, Hyundai Merchant Marine and Hanjin Shipping, and her connections to a southern European port, the authors unpack some of the current flip sides of global maritime shipping. In this article, the authors argue that the promise of profit and endless growth, which has led to overcapacity in global maritime shipping, is spurred on by what they call ‘false economies of scale’. Claims of the future profitability of colossal containerships are, they argue, state‐driven political performances of scale.

Investigation of Non-Linear Ship Hydroelasticity by CFD-FEM Coupling Method

With the increase of ship size, the stiffness of the hull structure becomes smaller. This means that the frequency of wave excitation tends to be closer to the natural frequency of the hull vibration, which in turn makes the hydroelastic responses more significant. An accurate assessment of the wave loads and motion responses of hulls is the key to ship design and safety assessment. In this paper, the coupled CFD (Computational Fluid Dynamics)-FEM (Finite Element Method) method is used to investigate the non-linear hydroelasticity effect of a 6750-TEU (Twenty-foot Equivalent Unit) container ship. First, by comparing the heave, pitch, and vertical bending moment at midship section (VBM4) against experimental results reported in the literature, the validity of the numerical method in this paper is illustrated. Secondly, the ship responses under different wave length–ship length ratio, wave frequency-structure natural frequency, wave steepness, and ship speeds are studied. It is found that the wave length–ship length ratio has a more important influence on the hydroelastic response than that from wave frequency-structure natural frequency ratio, and the effect of wave non-linearity will behave differently under different wave length–ship length ratio. The increase of rigid body motion caused by forward speed will not correspondingly increase the non-linearity of the hydroelastic response.

Influence of Ships Docking System in the Reduction of CO2 Emissions in Container Ports

Taking into account the increase in the emission of greenhouse gases produced by ships, during navigation and maneuvering in port, a direct consequence of the increase in maritime traffic, the international community has developed a broad set of regulations to limit such emissions. The installation in commercial ports of automatic mooring systems by means of vacuum suction cups, thus considerably reducing the time required to carry out ship mooring and unmooring maneuvers, is a factor that is considerably influencing the decrease in emissions of polluting gases in commercial ports with high traffic. The objective of the present work is to verify the influence of the use of the automatic mooring systems via vacuum suction cups on the emissions of polluting gases produced in the facilities destined to the traffic of container ships. To do this, two different calculation methods were used, Environmental Protection Agency and Environmental and Engineering Consultancy, to then compare the results of the two and thus obtain the reduction in emissions per twenty-foot equivalent unit in these terminals during mooring maneuvers. The paper concludes with a discussion on the values of the reductions in emissions obtained and the advantages of the installation of automatic mooring systems using vacuum suction cups in commercial ports located near population centers.

Development Status and Future Trends for Eurasian Container Land Bridge Transport

For decades, trade between Europe and China has grown consistently, which has resulted in increased container transportation volumes. Such transportation has been dominated by sea-based options. However, over the years, an air-based mode of transport was developed, while it has lately become increasingly popular to use railways utilizing the Trans-Siberian land bridge. This latter approach boomed amid the COVID-19 crisis in 2020. However, the railway container boom in Eurasia has deeper roots than just the COVID-19 era. As is illustrated in this research work, international trade containers (trade between Russia and other countries, mostly China) and transit containers (e.g., serving the Chinese–EU route) were already showing some significance as early as 2003–2004. In 2020, their volume was already measured in the millions, regardless of the railway data source being used. This is well above the starting period in the 1980s and 1990s, when total annual volumes were around 0.1 million twenty-foot equivalent units (TEU). Container capacity has developed over the years, first being used for international trade and only lately for transit. As a preliminary comparison to air freight, the growth rate was roughly double that in the two-decade observation period.

Lessons to be Learned from Top-50 Global Container Port Terminals Efficiencies: A Multi-Period DEA-Tobit Approach

The growing competition among container port terminals enhances the pressure for optimizing their efficiency level in the performance of containers’ service. Comparing container terminals based on their performance is a complicated task due to the variety of ports’ type, scale, and service configuration. This however is an important task in the efforts of improving not only national trade transportation but also the global trade system, since valuable best practices can be identified and adopted among container terminals. Notwithstanding, available information about container port terminals’ efficiency level, based on their performance measured by the service of Twenty-foot Equivalent Units (TEUs), is yet incomplete due to the lack of information about which factors influence their efficiency the most. This additional information will support the decision-making processes of container terminals’ authorities to direct their focus on specific factors that will improve their efficiency. This paper investigates the efficiency of the top-50 global container port terminals that service the global freight supply chain in a period of 5 years (2013-2017) through a two-step procedure. First, a benchmarking analysis, namely, Data Envelopment Analysis, is implemented to estimate the efficiency level of the container port terminals. The second step involves the methodology followed in this paper which is further expanded to quantify the effects that different factors have on container terminals efficiency through the implementation of suitable Tobit regression models. The findings of this paper identify the benchmark container terminals that should be taken as examples for under-performing container port terminals and also points out the factors that must be enhanced for improving global trade system, like, number of cranes, terminal space and quay lenght.

A Study of Brittle Crack Arrestability Test Method

This study evaluated the brittle crack arrest temperature (CAT) through an isothermal crack arrest test. The concept of evaluating CAT by an isothermal crack arrest test was proposed by C. Wiesner for application to low temperature steels for LPG tanks. The proposed test method consists of arresting a double-tension-type brittle crack with EB melt-run, which acts as a crack initiator and crack runway. There are some disadvantages when evaluating CAT with electron beam welding (EBW), which requires a local brittle zone to initiate a brittle crack. A local temperature gradient (LTG) system is developed to overcome the limitations of the EBW method. LTG systems do not require additional EBW to develop a brittle zone to initiate brittle crack. Recently, brittle crack arrest (BCA) steels are being used in large container ship such as in the upper deck or hatch side coaming of 22,000 twenty-foot equivalent units to prevent fatal brittle fracture accident of those ships. The International Association of Classification Societies (IACS) defined BCA steels using Kca requirement or CAT requirement in their unified rule (UR) S33. Therefore, when a shipyard uses BCA steel in the construction of large container ships, CAT or Kca should be evaluated. In this study, a new CAT test method is introduced to evaluate brittle crack arrest temperature more easily. Furthermore, both test methods were compared for the same specimens to verify the validity of the test method. Key words: Brittle fracture, Crack Arrest Temperature (CAT), Electron Beam Welding (EBW), Embrittled zone, Local Temperature Gradient (LTG)

Lashing Force Prediction Model with Multimodal Deep Learning and AutoML for Stowage Planning Automation in Containerships

The calculation of lashing forces on containerships is one of the most important aspects in terms of cargo safety, as well as slot utilization, especially for large containerships such as more than 10,000 TEU (Twenty-foot Equivalent Unit). It is a challenge for stowage planners when large containerships are in the last port of region because mostly the ship is full and the stacks on deck are very high. However, the lashing force calculation is highly dependent on the Classification society (Class) where the ship is certified; its formula is not published and it is different per each Class (e.g., Lloyd, DNVGL, ABS, BV, and so on). Therefore, the lashing result calculation can only be verified by the Class certified by the Onboard Stability Program (OSP). To ensure that the lashing result is compiled in the stowage plan submitted, stowage planners in office must rely on the same copy of OSP. This study introduces the model to extract the features and to predict the lashing forces with machine learning without explicit calculation of lashing force. The multimodal deep learning with the ANN, CNN and RNN, and AutoML approach is proposed for the machine learning model. The trained model is able to predict the lashing force result and its result is close to the result from its Class.

Konteyner Taşımacılık Şirketlerinin Rekabet Düzeyini Ölçen Yeni İndeksler

The purpose of this study is to propose novel and efficient competitiveness indexes to measure the level of competition among container shipping operators based on a specific region. These indexes should require only basic data, which is full container throughput on the basis of terminal/ hinterland and ship operator. This study takes advantages of two methods to propose novel indexes as alternatives to Herfindahl Hirschman Index (HHI), which is very popular to measure level of competition. Originally named Competition-based Overall Similarity Measurement Index (COSMI) and Entropy Competitiveness Index (ECI) utilize overall similarity measure from clustering analysis and entropy methodologies, respectively. Both indexes have been proposed with two variants for each. COSMI200+ ignores the throughput of each SO having an amount less than 200 Twentyfoot Equivalent Units (TEUs), but COSMITOP5 takes into account only the top 5 SOs in terms of local throughput in a hinterland. ECI-JOINT includes a joint entropy coefficient which is constant for each hinterland, but ECI-VAR takes into account a variable entropy coefficient defined by the number of ship operators in each hinterland. Analyzing a dataset for the terminals located in Turkey, the Entropy Competitiveness Index (by means of ECI-JOINT variant) has been exhibited as a good alternative to HHI with a great correlation coefficient with it: 0.97. Theoretically, Competitionbased Overall Similarity Measurement Index (by means of COSMITOP5 variant) seems a promising method, but it is highly affected by outliers and inconstant numbers of ship operators per route, indicating a moderate correlation coefficient with HHI: 0.45. 

RUE Index as a Tool to Improve the Energy Intensity of Container Terminals—Case Study at Port of Valencia

A container terminal is a high energy demanding organization. Giving priority to the investments that have a better impact on the minimization of energy consumption is a prime concern of the management board of the Port Authority and container terminals. This study presents a tool for the classification of the processes that take place in the port. The Relevant Use of Energy (RUE) index is described and applied to a case study, the Port Authority of Valencia, which is the main port of the Mediterranean in container traffic. Three different functional units have been discussed for the assessment: Twenty-foot Equivalent Units (TEU), cargo handled, and several container ships that operate in the port. The implementation of specific projects following the recommendation of the RUE Index validated the tool and allowed a reduction of the energy intensity of 29.5%, and a 40% reduction of the cost of energy per TEU between 2008 and 2016. However, there is still room for improvement, and project lines are proposed for this matter. A partnership between the RUE Index and an energy management system ISO 50001 certified and ensures quality data giving confidence to the decision-making process of the management board.

TECNOMUSE: a novel, RPC-based, muon tomography scanner for the control of container terminals

Every year, 700 million twenty-foot (container) equivalent units pass through the container terminals of the harbours all over the world. Only a small percentage (34%) are scanned to inspect the presence of radioactive materials. The need for controls is hampered essentially by three factors: the amount of both time and personnel necessary to control each container and the use of scanning methods based on systems potentially harmful for the personnel itself. Muon tomography can become a strategy for fast and reliable inspection of containers without using ionizing radiation. This technology takes advantage of multiple Coulomb scattering of the muons (particle produced by cosmic rays) through media to understand the composition and the geometry of the scanned volume. The TECNOMUSE project has the purpose to realize a muon tomography scanner based on a novel geometry and, for the first time, using Resistive Plate Chambers detectors. In this work, the preliminary results from the TECNOMUSE scanner are evaluated via Monte Carlo simulations. Many different simulations have been made with the aim to assess the detection capabilities of the device, its spatial resolution and the time required to reconstruct and distinguish different materials.

Container Transport System as a Means of Saving Resources

Analysing the transportation of goods as one of the constituent elements of the transport system, it can be argued that container transport today occupies a leading position in the delivery of goods throughout the world. According to statistics, the total volume of container traffic in the first two months of 2018 was approximately 26 million TEU (twenty-foot equivalent unit is a conventional unit of measure for the capacity of freight vehicles, namely, a 20-foot container), which is 6.7% more than the same index last year. Positive growth rates of container traffic indicate the relevance and scale of this type of transport. Also, thanks to the rapid development of intermodal and multimodal transportation, the volumes of cargo delivery in containers are increasing. Resulting from this, the container transport system, the main components of which are containers and container terminals, can be considered and analyzed as a technology for the conservation of resources.