General Cargo Research Articles

GLSD: a global large-scale ship database with baseline evaluations

ABSTRACT In this paper, we introduce a challenging Global Large-scale Ship Database (GLSD), designed specifically for ship detection tasks. The designed GLSD database includes a total of 212,357 annotated instances from 152,576 images. Based on the collected images, we propose 13 ship categories that widely exist in international routes. These categories include Sailing boat, Fishing boat, Passenger ship, Warship, General cargo ship, Container ship, Bulk cargo carrier, Barge, Ore carrier, Speed boat, Canoe, Oil carrier, and Tug. The motivations for developing GLSD include the following: 1) providing a refined and extensive ship detection database that benefits the object detection community, 2) establishing a database with exhaustive labels (bounding boxes and ship class categories) in a uniform classification scheme, and 3) providing a large-scale ship database with geographic information (covering more than 3000 ports and 33 routes) that benefits multi-modal analysis. Additionally, we discuss the evaluation protocols corresponding to image characteristics in GLSD and analyze the performance of selected state-of-the-art object detection algorithms on GLSD, aiming to establish baselines for future studies.

Evaluation of the powering extrapolation of a ship with a gate rudder system, including ageing and fouling effects

This paper is based on the evaluation results of the calm water powering extrapolation of a 90-m general cargo vessel, originally built with a conventional rudder system (CRS) and later retrofitted with an innovative energy-saving device (ESD) known as the Gate Rudder System® (GRS), as part of the EU H2020 Project GATERS. The power estimation of the vessel was conducted using an adapted extrapolation procedure based on the scaled model tests of the vessel in a towing tank, validated by the three sets of sea trials. The first sea trial was performed when the ship was new, while the latter two were conducted during the project timeline, before and after the GRS retrofit. This paper aims to adapt the ITTC-78 power extrapolation method to predict the power performance of a ship retrofitted with the GRS for the first time in the maritime industry. Within this framework, the specific objectives of the paper are to describe and validate the proposed method using relevant power-speed data of the GATERS project target vessel (M/V ERGE) initially equipped with the CRS and later replaced by the retrofit GRS to achieve the project objective. Due to the real-world circumstances of retrofitting a 13-year-old ship with a novel energy-saving device, investigating the effects of ageing, hull roughness, and fouling has also become one of the key objectives of the paper. The findings demonstrate the ageing effect on the target ship's powering performance after retrofitting with GRS, highlighting the need for special consideration of power extrapolation alongside the hull fouling effects. The paper also demonstrates that the GRS is an emerging ESD, as a retrofit beside newly built ships with GRS, which improved the powering performance of the project target vessel, achieving a remarkable 25% power saving based on the comparative full-scale sea trials.

Energy Use and Carbon Footprint Assessment in Retrofitting a Novel Energy Saving Device to a Ship

The Gate rudder system (GRS) was recently introduced as an innovative energy-saving device (ESD) for ships, and it is the most attractive ESD currently used in the market, with double figures of fuel savings in full-scale (>10–35%) compared with a ship with a conventional rudder system (CRS). Although there are few new ship applications of GRS, the recently completed EC-H2020 GATERS project successfully demonstrated its unique energy-saving and manoeuvrability benefits as a “retrofit” solution for an existing general cargo vessel for the first time. The project results suggested that the GRS holds significant potential for retrofitting existing ships to enhance fuel efficiency (~35%) and improve manoeuvrability. Nevertheless, the application was a comprehensive undertaking requiring various work tasks such as component manufacturing, removing existing systems, and modification and upgrading works, with substantial energy consumption and environmental impacts. Therefore, it was insightful to study energy use and environmental impacts in a GRS retrofit process. This study developed and implemented a comprehensive energy consumption and carbon footprint assessment framework for the GRS retrofit in the GATERS project. A detailed assessment of energy consumption and related carbon emissions was performed during the major stages of manufacturing, system removals, and modifications and assembly in the GRS retrofit. Also, the potential savings in energy use and emissions were addressed. The results demonstrated that the manufacturing stage was the most energy-intensive phase, being responsible for 91.4% of total electricity and 46.7% of fuel-based thermal energy use. The system removals accounted for 53.3% of the fuel-based thermal energy, whereas the modification and assembly work accounted for about 7.7% of the total electricity use. Additionally, various measures such as clean electrification, energy efficiency, mould/tool reuse, and component reuse to reduce the energy consumption and related carbon emissions in future GRS retrofit applications were addressed and discussed together with their reduction potentials.

Comparative Analysis of Space-Based Battery, Fuel Cell, and Conventional Propulsion System for General Cargo Ships Of Approximately 100 Meters

Comparative Analysis of Space-Based Battery, Fuel Cell, and Conventional Propulsion System for General Cargo Ships Of Approximately 100 Meters

Safety evaluation on ammonia-fueled ship: Gas dispersion analysis through vent mast

The maritime industry is exploring ammonia as an alternative fuel to reduce greenhouse gas emissions. However, the high toxicity of ammonia poses significant safety challenges for onboard handling and storage. This study investigates ammonia dispersion and toxicity levels from vent mast releases on ships, aiming to enhance safety measures for future ammonia-fueled vessels. Using CFD analysis on a 31,000-dwt general cargo ship model, the research examines various release scenarios, considering regulatory requirements, vent mast design, and environmental conditions. Results show that direct ammonia release from the vent mast poses fatal risks to the crew in the accommodation area and on adjacent ships, regardless of current regulatory stipulations. The study recommends installing an ammonia-catching system to reduce concentrations to safe levels of 30 ppm before release. These findings offer crucial insights for improving the safety of using ammonia as marine fuel through risk assessment and management.

Hub-and-spoke maritime network with heterogeneous commodity on island shipping

ABSTRACT This paper presents an extension to a classic hub-and-spoke maritime network, by adding the feeder node and heterogeneous commodity to the network on an island shipping network. The cargo is delivered from origin (hub) to destination (feeder), which can be compounded in hub node and sent using container in container ship to a spoke node. In the spoke node, the container is de-containerized into general cargo package, representing heterogeneous commodity, and finally shipped using cargo ship to the feeder node. This system is suitable for island shipping network, consisting of several small ports with marginal hinterland, where the development of container facility is not financially feasible. The proposed model generates the optimum number and location of spoke, alongside with its allocated feeder node, to minimize the total shipping cost. As a case study, an actual island network in Southeast Sulawesi, Indonesia, is utilized, resulting in a recommendation of one additional spoke to the existing network. The result also suggests a backup spoke if the single spoke scheme is selected, anticipating any disruption on the selected spoke node. A trade-off between shipping cost reduction and spoke investment cost should be considered by policymakers in the adoption of the system.

Effect of fuel prices on sailing speeds in short-sea shipping

ABSTRACT In this paper, we estimate fuel price elasticities of sailing speed for general cargo vessels using data covering the Baltic Sea and Norwegian coastal areas during the years 2007–2018. To disentangle the correlation between fuel prices and freight rates arising from changes in global demand, we instrument fuel prices on price changes triggered by supply shocks. The shocks are derived from the structural vector autoregressive (SVAR) model proposed by Kilian (2009). In a sensitivity analysis, we use unanticipated oil supply shocks derived from oil supply outages as an alternative instrument for fuel prices. We find that disregarding the correlation between fuel prices and freight rates yields biased parameter estimates, which can partly explain the mixed results in the previous literature. Our preferred estimate for the fuel price elasticity of speed is −0.08.

A data-driven Bayesian network model for pattern recognition of maritime accidents: A case study of Liaoning Sea area

A data-driven Bayesian network (BN) model is developed to capture the individual and collective impacts of accident influential factors (AIFs) on different attributes of maritime accidents, including accident type, severity, and loss. To develop the data-driven BN model, a dataset comprising 980 accidents from 2000 to 2023 in the Liaoning Sea area is initially established. Subsequently, the data-driven BN model is constructed using the Tree Augmented Network (TAN) learning algorithm and expectation-maximization (EM) algorithm. Finally, comprehensive BN analysis encompassing strength of influence assessment, sensitivity analysis, scenario simulation, and model verification is conducted based on the developed TAN-BN model. The results demonstrate that distinct types of maritime accidents exhibit varying sensitivities to seasonal variations and time of day; contact and groundings are primarily encountered by general cargo ships while fire and explosions are more prevalent among bulk carriers. Fishing boats tend to be vulnerable to collisions whereas sinking accidents are most commonly associated with sand carriers.

Path Optimization of Container Multimodal Transportation Considering Differences in Cargo Time Sensitivity

To optimize the container multimodal transportation path selection problem with differences in cargo time sensitivity, this paper introduces the concept of mixed time windows and establishes an integer programming model from the perspective of carriers. The objective is to minimize the total transportation cost while meeting the customer’s on-time delivery requirements. The model imposes hard time window constraints on cargoes with on-time delivery requirements and soft time window constraints on general cargoes. A bi-level genetic algorithm is employed to solve the model. A case study is conducted to demonstrate the effectiveness of the proposed approach. Experimental results show that the bi-level genetic algorithm’s convergence ability, efficiency, stability, and global search capabilities are far superior to those of traditional single-level genetic algorithms. This indicates that the use of multi-stage solution approaches can mitigate the shortcomings of genetic algorithms in dealing with high-dimensional problems. In addition, when analyzing the effects of time penalty intensity and time window on decision-making results, it is found that the more time-sensitive cargoes are more likely to be affected by the time window setting, and will tend to sacrifice costs to ensure that the time demand is met. At the same time an increase in demand for time-sensitive services is accompanied by an increase in operating costs. Accurate assessment and classification of time sensitivity of cargoes can effectively prevent wasting resources in unnecessary areas, and ultimately maximize decision outcomes and ensure the most efficient use of resources.

Small sea with high traffic - what is the biofouling potential of commercial ships in the Baltic Sea

Despite the Baltic Sea being one of the most intensive shipping regions in the world the potential magnitude of the biofouled hulls in this region is unknown. This study estimated the biofouling load to Baltic Sea Region (BSR) based on the wetted surface area (WSA) method with regard to country, ship type and donor bioregion. WSA flux reached 656 km2, of which 86% was associated with ships operating inside and 14% was WSA flux brought by ships from outside of the Baltic Sea. Most of the WSA was transported to Swedish, Finnish and Danish ports as well. The highest WSA flux was assigned to roll-on/roll-off, passenger and general cargo ships. The high biofouling potential in BSR indicates a potential high risk to the environment and, therefore there is an urgent need for appropriate guidelines to be introduced into daily use by the commercial shipping community.

Optimization of The General Cargo Loading Process to Increase Efficiency on The MV Hanglima Ship

Optimization of The General Cargo Loading Process to Increase Efficiency on The MV Hanglima Ship

Hydrogen Fuel Cell as an Electric Generator: A Case Study for a General Cargo Ship

In this study, real voyage data and ship specifications of a general cargo ship are employed, and it is assumed that diesel generators are replaced with hydrogen proton exchange membrane fuel cells. The effect of the replacement on CO2, NOX, SOX, and PM emissions and the CII value is calculated. Emission calculations show that there is a significant reduction in emissions when hydrogen fuel cells are used instead of diesel generators on the case ship. By using hydrogen fuel cells, there is a 37.4% reduction in CO2 emissions, 32.5% in NOX emissions, 37.3% in SOX emissions, and 37.4% in PM emissions. If hydrogen fuel cells are not used instead of diesel generators, the ship will receive an A rating between 2023 and 2026, a B rating in 2027, a C rating in 2028–2029, and an E rating in 2030. On the other hand, if hydrogen fuel cells are used, the ship will always remain at an A rating between 2023 and 2030. The capital expenditure (CAPEX) and operational expenditure (OPEX) of the fuel cell system are USD 1,305,720 and USD 2,470,320, respectively, for a 15-year lifetime, and the hydrogen fuel expenses are competitive at USD 260,981, while marine diesel oil (MDO) fuel expenses are USD 206,435.

Utilizing the thermal energy from natural gas engines and the cold energy of liquid natural gas to satisfy the heat, power, and cooling demands of carbon capture and storage in maritime decarbonization: engineering, enhancement, and 4E analysis

Abstract The MEPC 80 session has revised the International Maritime Organization (IMO) greenhouse gas strategy, setting more ambitious decarbonization goals. Carbon capture and storage (CCS) technologies have shown promise in reducing maritime carbon emissions, although their high-energy requirements have often been neglected in previous research. This study introduces a novel system integrating a natural gas engine, CCS, an Organic Rankine Cycle (ORC), and a power turbine (PT). An exhaust gas bypass strategy is used to enhance engine performance at low and medium loads, channeling exhaust to the PT for power generation. The engine’s waste heat is fully utilized for CCS via cold, heat, and power. The study compares various absorbents in the CCS system, including monoethanolamine and piperazine solutions, which show different carbon capture efficiencies. Additionally, CO2 storage conditions are analyzed and compared. The proposed system shows potential for significantly reducing the Energy Efficiency Design Index for general cargo ships. The study addresses the high-energy demands of CCS by utilizing the engine’s waste heat, transforming a potential drawback into a beneficial resource. By integrating the ORC and PT, the system not only captures carbon but also improves overall energy efficiency, presenting a promising solution for maritime decarbonization. The analysis of CO2 storage conditions further enhances the understanding of effective carbon management. This innovative system demonstrates that with strategic integration and optimization, significant progress can be made toward achieving the stricter decarbonization targets set by the IMO while also enhancing the energy efficiency of maritime operations.

Model-based Parametric Study for Comparison of System Configurations and Control of a Hydrogen Hybrid Cargo Vessel

The current state of research in marine energy systems has concentrated on conventional diesel systems, while limited literature is available on the configuration and control of alternative energy sources such as hydrogen hybrid systems, which have attracted increasing interest recently owing to the energy transition. This paper presents a modelling and control study for conceptual retrofitting of a general cargo vessel to a hydrogen-hybrid version. Generic fuel cell, battery, and converter models are used, enabling easy adaptation to various powerplant sizes and ship types. A robustly coordinated Energy Management Strategy (EMS), which can be implemented for different vessel’s power profiles, was developed for power sharing, DC bus voltage control, and battery State of Charge (SoC) regulation. The total installed fuel cell power and battery capacity were heuristically selected from a range of power profiles of the ship. A database of fuel cells with stacks from different manufacturers was created to test different combinations in terms of fuel consumption, cost, and weight, based on the framework of the problem. Uncertainties in terms of fuel prices are presented using normal distribution graphs. The system configurations and control results are presented for one power profile of the vessel and the average fuel costs. It is demonstrated that with the proposed control method, the power losses are less than 1%, the DC bus voltage fluctuations are less than 0.5%, and the battery SoC remains between 35-65% for the entire duration of the analysed power profile. The configuration with eight stacks of 150 kW has the lowest total fuel cost (730 $) with an average difference of 7.1% from the other solutions, and the lowest total weight (10.54 tons) with an average difference of 15.4% from the other configurations. Overall, this study demonstrates the efficient configuration and control of hybrid energy systems using parameterized components.

An evaluation of operational risks for general cargo ship operators

As general cargo ships (GCSs) hold certain advantages over more mainstream shipping services, GCSs have a considerable degree of importance in the shipping market. This paper focuses on the use of risk evaluation procedures to perform empirical analysis of the operational risk faced by GCS operators, which is a subject that has garnered relatively little academic attention. After identifying risk factors, four risk aspects and 16 operational risk factors are determined and used to construct an Analytic Hierarchy Process (AHP)-based risk matrix evaluation model. An expert questionnaire addressing both subjective and objective facets is then used to perform evaluation of the model, enabling conversion of the relative weights to risk scales. Lastly, the determination of each risk factor’s risk areas allows the proposal of risk management strategies. The results indicate that four of the risk factors are in the high risk area; these consisted of the loading stage factor “delays at port of loading,” the laden voyage stage factor “poor stowage and securing,” the laden voyage stage factor “perils of the sea,” and the discharging stage factor “delays at port of discharge.” This paper also proposes risk management strategies on the basis of the experts’ recommendations, and its findings can provide shipowners and charterers with a reference for the drafting of risk clauses when entering into a charter party.

An Application of the DEA-Cross Efficiency Approach in Turkish Dry-Bulk and General Cargo Terminals

Dry bulk and general cargo terminals are the facilities that should quickly adapt to global supply chain dynamics. Each loading/unloading, conveying, horizontal carriage and temporary storage process involves complex organizational structures and procedures. Planned physical investments may lead to inefficiency under dynamic environmental conditions and may also result in a waste of resources. This study aims to examine the technical efficiency of dry-bulk and general cargo terminals in Türkiye with DEA cross-efficiency and DEA Slacks-based models. The findings imply that the terminals handling iron and steel are more efficient than the others. Besides, on average, the dry bulk and general cargo terminals can achieve higher output levels with fewer infrastructures and handling equipment. Therefore, it may be appropriate for the terminals examined to revise their resource utilization rates and short-term investment strategies. Moreover, since it allows pair-wise comparisons of terminals handling similarly featured cargo, DEA cross-efficiency can play a crucial role in dry-bulk performance measurement. Input slacks of relatively inefficient terminals are also calculated.

Trim Optimization Investigation on Resistance and Energy Efficiency of Full-Scale General Cargo Using Computational Fluids Dynamics

Trim Optimization Investigation on Resistance and Energy Efficiency of Full-Scale General Cargo Using Computational Fluids Dynamics

ANALYSIS OF MARITIME ACCIDENTS IN MALAYSIAN WATERS

Throughout the South China Sea and the Malacca Strait, more than 60% of all maritime trade passes each year. The rapid growth in fleet size and ship size may lead to an increase in maritime accidents. Since many maritime accidents cause serious injuries, fatalities, damage of property and monetary losses, it is essential and crucial to discuss about marine safety. In this study, a statistical analysis was performed in order to assess the number of maritime accidents that occurred in Malaysia between 2018 and 2021, as well as the percentage of accidents that occurred in each accident category and for each type of ship. The analysis also considers the age of the ship. The data that were presented also looks into a potential relationship between the age of the ship and the accident percentage. The results demonstrate that general cargo ships were the ship categories that are most vulnerable to maritime accidents; collisions were the accident type that occurs most frequently, and there were several relationships between the accident percentage and ship age. The results may be utilized to help seafarers, related government agencies and other relevant organizations promote risk prevention, create efficient risk response plans, and establish strategies to enhance the marine mechanism for managing safety in Malaysian waterways.

Ship Classification Based on AIS Data and Machine Learning Methods

AIS ship-type code categorizes ships into broad classes, such as fishing, passenger, and cargo, yet struggles with finer distinctions among cargo ships, such as bulk carriers and containers. Different ship types significantly impact acceleration, steering performance, and stopping distance, thus making precise identification of unfamiliar ship types crucial for maritime monitoring. This study introduces an original classification study based on AIS data for cargo ships, presenting a classifier tailored for bulk carriers, containers, general cargo, and vehicle carriers. The model’s efficacy was tested within the Changhua Wind Farm Channel using eight classification algorithms across tree-structure-based, proximity-based, and regression-based categories and employing standard metrics (Accuracy, Precision, Recall, F1-score) to assess the performance. The results show that tree-structure-based algorithms, particularly XGBoost and Random Forest, demonstrated superior performance. This study also implemented a feature selection strategy with five methods, revealing that a model trained with only four features (three ship-geometric features and one trajectory behavior feature) can achieve high accuracy. Conclusively, the classifier effectively overcame the challenges of limited AIS data labels, achieving a classification accuracy of 97% for ships in the Changhua Wind Farm Channel. These results are pivotal in identifying abnormal ship behavior, highlighting the classifier’s potential for maritime monitoring applications.

Evaluating the Technical Efficiency of Dry-Bulk and General Cargo Terminals in Türkiye using Interval DEA

Evaluating the Technical Efficiency of Dry-Bulk and General Cargo Terminals in Türkiye using Interval DEA