International Maritime Organization Research Articles

Application of Self-Polishing Copolymer and Tin-Free Nanotechnology Paint for Ships

During a ship’s voyage, it is difficult to maintain its hull, and prolonged exposure to seawater can lead to the attachment of marine organisms, which can negatively impact the ship’s speed. The original self-polishing copolymer was a tributyltin-containing paint used for applying two layers of protective coating onto a ship’s bottom plate. According to International Maritime Organization (abbreviated as IMO) regulations, users are no longer allowed to use paints containing tributyltin. Therefore, manufacturers have developed a tributyltin-free paint, known as tin-free nanotechnology paint, which can be used as a replacement for the base coat on ship bottom plates. This study involves the use of a self-polishing copolymer spray and tin-free nanotechnology paint. A model coated with these two types of paint will be observed underwater to study the growth of marine organisms. Additionally, fuel consumption will be analyzed through underwater inspections and sea trials. Based on the experimental data, it is known that tin-free nanotechnology paint can significantly reduce the need for repairs in factories and greatly decrease maintenance costs when compared to self-polishing copolymers.

Transformative Impact of the EU AI Act on Maritime Autonomous Surface Ships

The International Maritime Organization collaborates with member states to develop the Maritime Autonomous Surface Ships (MASS) Code to establish an international agreement framework. In December 2023, an agreement was reached on the European Union (EU) Artificial Intelligence (AI) Act within the MASS Code. It was officially finalized and implemented on 1 August 2024. While the Act’s full application is set for two years later, certain provisions regarding safety against AI risks will take effect sooner. This study utilized a multiple-streams analysis method to examine how the EU AI Act impacted shipyards and shipping companies, focusing on ethical AI use and user safety. The findings indicate that technical completeness, safety enhancement, and AI system regulation through risk classification influence autonomous ship innovation. The challenges of reviewing the commercialization of new technologies for autonomous ships may result in market failures or decreased industry competitiveness. The study emphasizes the need to balance AI safety and ethical responsibility with autonomous ship development innovations. To ensure the sustainable application of AI technology, innovators must adapt to the EU AI Directive. Hence, this study confirms that the ethical and legal regulation of AI technology is crucial in technological innovation and development related to autonomous ships.

Artificial Neural Network-Based Route Optimization of a Wind-Assisted Ship

The International Maritime Organization aims for net-zero carbon emissions in the maritime industry by 2050. Among various alternatives, route optimization holds an important place as it does not require any additional component-related costs. Especially for wind-assisted ships, the effectiveness of different sailing systems can be improved significantly through route optimization. However, finding the ship’s optimal route is computationally expensive when the totality of possible weather conditions is taken into consideration. To determine the optimal route that minimizes energy consumption, an energy model based on the environmental conditions, ship route and ship speed was built using artificial neural networks. The energy consumed for given input data was calculated using a ship dynamics model and a database was generated to train the artificial neural networks, which predict how much energy is consumed depending on the route followed in given environmental conditions. Then, such networks were exploited to derive the optimal routes for all the relevant operational conditions. It was found that route optimization can reduce the overall ship energy consumption depending on the weather conditions of the environment by up to 9.7% without any increase in voyage time and by up to 35% with a 10% delay in voyage time. The proposed methodology can be applied to any ship by training real weather conditions and provides a framework for reducing energy consumption and greenhouse gas emissions during the service life of ships.

Efficiency Comparison between Simplified and Advanced Evacuation Analysis Models: A Case Study of Guryong Station, Republic of Korea

Modern subway systems have increased in size and complexity, and this growth presents significant challenges for planners of emergency evacuations. In this study, the effectiveness of the simplified and advanced evacuation analysis methods recommended by the International Maritime Organization (IMO) are evaluated for Guryong Station in Seoul, South Korea. The simplified evacuation analysis method facilitates rapid assessments by using general parameters, while the advanced evacuation analysis entails performing detailed simulations of human behavior and physical interactions. Our findings indicate that the results of the simplified evacuation analysis method are reasonably close to those of the more time-consuming advanced evacuation analysis method, thereby demonstrating the practical applicability of the former method for conducting initial evacuation safety assessments. Specifically, both the simplified and advanced methods showed a 20% reduction in Total Evacuation Time when tunnel evacuation routes were utilized. This finding demonstrates that the simplified method can produce results comparable to the advanced method, making it a reliable tool for initial assessments and for evaluating alternative strategies to reduce evacuation time. By demonstrating that the simplified evacuation analysis method can yield reliable results, we provide valuable insights for developing smart, resilient cities with efficient emergency-response capabilities.

Multi-Objective Route Planning Model for Ocean-Going Ships Based on Bidirectional A-Star Algorithm Considering Meteorological Risk and IMO Guidelines

In this study, a new route planning model is proposed to help ocean-going ships avoid dangerous weather conditions and ensure safe ship navigation. First, we integrate ocean-going ship vulnerability into the study of the influence of meteorological and oceanic factors on navigational risk. A multi-layer fuzzy comprehensive evaluation model for weather risk assessment is established. A multi-objective nonlinear route planning model is then constructed by comprehensively considering the challenges of fuel consumption, risk, and time during ship navigation. The International Maritime Organization (IMO) guidelines are highlighted as constraints in the calculations, and wind, wave, and calm water resistance to ships in the latest ITTC method is added to the fuel consumption and sailing time in the objective function. Finally, considering the large amount of data required for ocean voyages, the bidirectional A* algorithm is applied to solve the model and reduce the planning time. Furthermore, our model is applied to the case of an accident reported in the Singapore Maritime Investigation Report, and the results show that the model-planned route is very close to the original planned route using the Towing Manual, with an average fit of 98.22%, and the overall meteorological risk of the model-planned route is 11.19% smaller than the original route; our model can therefore be used to plan a safer route for the vessel. In addition, the importance of risk assessments and the IMO guidelines as well as the efficiency of the bidirectional A* algorithm were analyzed and discussed. The results show that the model effectively lowers the meteorological risk, is more efficient than the traditional route planning algorithm, and is 86.82% faster than the Dijkstra algorithm and 49.16% faster than the A* algorithm.

Optimising ship principal dimensions with a Dung Beetle Optimizer and random forest proxy model

ABSTRACT Shipping serves as an important component of global trade, with speed being a key attribute closely tied to navigational resistance. Amid rising marine pollution, the International Maritime Organisation (IMO) requires shipowners to modify ships to comply with existing requirements. Herein, focusing on the static water sailing resistance, whole-ship hull line optimisation was conducted for Japan Bulk Carrier (JBC). The optimisation included the bulbous bow, inflow and outflow sections, and the parallel mid-body. Initially, a random forest resistance proxy model was introduced to replace traditional Computational Fluid Dynamics (CFD) methods. The model’s hyperparameters were optimised using the Dung Beetle Optimizer algorithm. Subsequently, this algorithm was employed to optimise ship design parameters. Finally, comparisons confirmed the proxy model’s high precision, and the optimisation yielded substantial outcomes, achieving a 4.7% decrease in resistance.

Determination of Demand for LNG in Poland

This study was aimed at improving the energy efficiency of the distribution of liquefied natural gas (LNG) as shipping fuel in the southern Baltic Sea. The objective of this study was to determine the demand for LNG for maritime shipping by analyzing the distribution of the resource from the water side (ship-to-ship). LNG was chosen due to the location of the LNG terminal in Świnoujście within the analyzed water area, where a problem has arisen in the southern part of the Baltic Sea regarding fuel supply for vessels due to the lack of developed infrastructure along the coast. An analysis was conducted to optimize the size of the LNG fleet and infrastructure facilities. Seeking compliance with Annex VI to the MARPOL 73/78 Convention, adopted by the International Maritime Organization (IMO), shipowners see potential in the switch from conventional fuels to LNG. As one of the alternative solutions, it will contribute to reducing harmful emissions. Determination of the LNG distribution volume requires the identification of LNG storage facility locations, specifying the number of LNG-powered ships (broken down by type) and the number of LNG bunkering ships. The first part of this study contains a detailed analysis of the number of sea-going ships that provide services in the southern part of the Baltic Sea and the world’s number of LNG bunkering ships. The database contains a set of the characteristics required to determine the optimal demand for LNG, where LNG bunkering vessels are capable of supplying fuel within the shortest possible time and covering the shortest possible distance to LNG-powered ships. The characteristics include the type of ship, requested LNG volume, the speed of LNG bunkering ships, the distance between LNG facilities, and the loading rate (the volume of fuel received per time unit). Based on the collected data, the volume of LNG distribution was determined using MATLAB R2019a software. The remainder of this study contains a description of the conducted research and results of an analysis of the traffic density in the Baltic Sea. The results were obtained on the basis of data from the Statistical Yearbook of Maritime Economy and IALA IWRAP Mk2 2020 software. The number of LNG-powered ships and number of LNG bunkering ships were specified, and the demand for LNG for the area under analysis was determined.

Voyage scheduling and energy management co-optimization in hydrogen-powered ships

The maritime sector is striving to lessen its dependence on fossil fuels, motivated by both economic factors related to fuel efficiency and the policies established by the International Maritime Organization (IMO). Consequently, there has been a growing focus on developing and deploying all-electric ships (AES) as a more sustainable alternative to conventional fossil fuel-powered vessels. AES presents several advantages over conventional ships, including zero emissions, enhanced energy efficiency, and greater sustainability. However, the implementation of AES also brings new challenges, such as the necessity to manage a hybrid microgrid and optimize voyage scheduling. Hybrid fuel cell (FC)-battery energy storage (BES) technology can significantly contribute to addressing these requirements. To tackle these challenges, this article introduces a comprehensive framework for the optimal planning of hybrid microgrids and voyage scheduling in AES. The framework incorporates multi-objective optimization techniques based on genetic algorithms to achieve a balance between cost and voyage time. The proposed framework is applied to a case study of a ship operating on a fixed route between two ports. The simulation results indicated that the total cost per voyage, associated with the objective function of cost minimization and voyage time reduction, has decreased by 12% and increased by 40%, respectively, when compared to the regular ship speed profile. Additionally, the travel time has been reduced by half an hour and 2 h, respectively, in comparison to the regular ship speed profile. To verify the results, the optimization problem for cost and voyage scheduling is also solved by Mayfly Algorithm (MA) separately. Thus, it can be illustrated the effectiveness of the framework in enhancing energy efficiency and fuel economy while preserving the ship's performance.

USE OF METHANOL AS MOTOR FUEL FOR MARINE INTERNAL COMBUSTION ENGINES

The international maritime organization's intention to reduce greenhouse gas emissions to the atmosphere by two times compared to 2008 by 2050 prompted manufacturers of marine engines to start actively searching for ways to solve this problem. Since significant global changes in the structure of ship power equipment are not expected during this period, the main efforts of researchers are aimed at solving the problem of reducing emissions based on piston engines, which today form the basis of ship power. The technology of the first stage of reducing greenhouse gas emissions was the conversion of marine diesels to gas fuels, and primarily to methane. These technologies, which are already widely used in water transport today, make it possible to reduce greenhouse gas emissions by 20...25%, but do not solve the problem completely. Today it is clear that a global solution to the problem is possible only when using as motor fuel compounds that are either carbon-free, i.e. do not contain carbon in their composition at all, or are carbon neutral, i.e. contain carbon extracted from the atmosphere by biological or technological means. One such compound is methyl alcohol or methanol. Today, most of the methanol in the world is produced either from coal or from natural gas, so the total emissions of greenhouse gases when burning such methanol even exceed emissions from burning petroleum fuels, however, unlike the latter, this compound can be obtained from biological raw materials, or by binding atmospheric carbon. Today, such methanol, which has received the name «green», is too expensive, and its production technologies require further development. This can happen only if there is international stimulation and regulation of this area of production. But the introduction of such regulation requires a clear understanding of the technical feasibility and economic and environmental feasibility of using methanol as a motor fuel. That is why leading manufacturers today are working on solving these issues. Their solution is considered the second stage on the way to the complete decarbonization of shipping, and at this stage there has been significant progress in recent years. This article is devoted to the analysis of the current state of the question regarding the use of methanol as motor fuel for ship engines of all types and sizes.

Navigating New Waters: IMO’s Efforts to Regulate Autonomous Shipping

Abstract New technological development in autonomous and unmanned vessels challenges the international legal framework prevailing at sea. Currently, the regulations applicable to international shipping constitute regulatory barriers preventing their operation on a worldwide scale. Hence, the International Maritime Organization (IMO), responsible for international shipping, has been working to accommodate these new types of vessels within the existing legal instruments. This paper traces the IMO’s steps to establish a new regulatory framework for them.

Insights to ballast water: metagenomics as a pressing priority

Metagenomics represents a pivotal development in genomics, offering unprecedented insights into a diverse spectrum of microorganisms, including bacteria, viruses, and fungi, that were previously challenging or impossible to study outside natural environments. Its applications span a remarkable range, from exploring cosmic entities to the depths of our oceans, incorporating numerous analyses. Yet, its utilization in the context of ballast water analysis remains scarce. This highlights the crux of the present review, which aims to showcase the need for metagenomics in ballast water analysis. As is known, ballast water is essential for maintaining ship stability under no cargo conditions or during adverse weather, with daily global movements estimated to be between 3 to 10 billion tonnes. A single bulk cargo ship can transport up to 60,000 tonnes of ballast water for a 200,000-tonne load. It is estimated that over 7,000 species are transported globally in ships' ballast water daily, posing significant ecological risks when these organisms are discharged into new environments where they can become invasive species, disrupting local ecosystems, economies, and human health. Despite the International Maritime Organization setting D-2 standard guidelines and endorsing several ballast water management practices for its safe discharge, the issue persists. This underscores the necessity of employing metagenomics to enhance the monitoring of microbial content in ballast water. The review summarizes some research conducted worldwide to analyze ballast water by metagenomics, all exhibiting diverse microbes, including potent pathogenic bacterial and viral forms. The findings support our view, making metagenomics an invaluable tool to monitor ballast water treatment effectiveness in compliance with evolving environmental regulations. Though the challenges facing metagenomic applications—namely cost, complexity, and the need for comprehensive reference databases—are significant, they will surely be surmountable considering continual technological and methodological advancements. Embracing metagenomics offers a pathway to not only address the ecological threats posed by ballast water transfers but also to safeguard the future of global shipping industries.

Out of Sync: The Making and Remaking of Data and Regulations on Greenhouse Gases at the International Maritime Organization

Out of Sync: The Making and Remaking of Data and Regulations on Greenhouse Gases at the International Maritime Organization

Potential Contributions of IMO Area-Based Shipping Management and Port State Jurisdiction to the Regulation of Ship-Borne Tourism in Antarctica

Given the rapid growth of ship-borne tourism in Antarctica, the International Maritime Organization (IMO) area-based management tools (ABMTs) could be a timely and effective contribution to mitigate some of the associated risks. Utilization of IMO ABMTs in Antarctic waters, which constitute high seas, raises several legal and practical issues. The central challenge is how to ensure compliance with IMO measures on the high seas, given the lack of generally accepted coastal state jurisdiction in Antarctica and shortcomings in flag state control. This article addresses these questions and analyzes port state jurisdiction as a potential mechanism to enforce IMO ABMTs in the Antarctic. The article concludes that Antarctic port states have sufficient legal arguments to justify the exercise of jurisdiction in relation to IMO ABMTs, and that significant constraints lie in the economic and political dimensions of regulation rather than in regulation itself.

How to implement the 2023 IMO GHG strategy? Insights on the importance of combining policy instruments and on the role of uncertainty

In its 2023 strategy for reducing GHG emissions from ships, the International Maritime Organization aims for the uptake of zero or near-zero GHG emissions technologies, fuels or energy to represent at least 5 %, striving for 10 %, of the energy used by 2030. Measures proposed to reach this target combine two kinds of policy instruments: an emission intensity standard and GHG emissions pricing. Proposals vary in terms of the design of the pricing scheme and the subsequent uncertainty that would affect the price signal. This paper assesses the extent to which emissions pricing effectively complements a more restrictive standard on the intensity of GHG emissions to boost transition to low-carbon vessels. Attention is paid to the role of the volatility of the price signal of GHG emissions and fuels prices. For this purpose, the paper applies a multiple real options model to the decision to renew a ship under various sources of uncertainty. Simulations carried out based on a case study show that the price signal effectively complements the more restrictive standard but that the decarbonization objectives are only achieved with a quite ambitious level of pricing. The role of the volatility of the price signal of GHG emissions appears negligible compared to other sources of volatility.

Exploring seafarers' knowledge, understanding, and proficiency in SEEMP: A strategic training framework for enhancing seafarers' competence in energy-efficient ship operations

With 2.89 % of global carbon emissions caused by human activity, the maritime industry faces an imminent challenge in curbing its carbon footprint despite regulatory initiatives. As the shipping sector expands, the industry faces a projected increase in carbon emissions. Recognizing the key role of seafarers in emission reduction, this article introduces a comprehensive training framework designed to enhance awareness, knowledge, understanding, and skills for implementing energy-efficient ship operations. This study utilizes structural equation modeling to assess the effectiveness of seafarers' training on energy-efficient operation of ships (EEOS) by surveying 144 seafarers across 42 shipping companies worldwide and using structured questionnaires. This study found significant positive correlations between implementing the Ship Energy Efficiency Management Plan (SEEMP) and the training programs initiated by the International Maritime Organization (IMO) and shipping companies. The results of this study indicate that traditional institutional and specialized training programs on EEOS are relatively ineffective for seafarers in implementing SEEMP onboard ships. Furthermore, the study argues that computer and simulator-based training facilitates knowledge, understanding, and proficiency of SEEMP among seafarers more effectively than the onboard training provided by the ship's master and the chief engineer. The proposed training framework emphasizes the importance of initial training using the IMO E-Learning course and IMO “Train the Trainer” programs, followed by shipping companies' in-house training by classification societies, company project teams, and simulator-based training by service providers. The study proposes a strategic training framework that encompasses in-house training conducted by shipping companies in collaboration with partners, simulator-based training provided by specialized training providers, and ongoing onboard training facilitated by the vessel's master and chief engineer, with integration of computer-based training (CBT). This strategic approach intends to improve seafarers' competence in energy-efficient ship operations to meet predetermined carbon intensity targets, which aligns with the broader goal of leading the maritime industry toward a future of net-zero emissions.

Ship sailing speed optimization considering dynamic meteorological conditions

Sailing speed optimization is a cost-effective strategy to improve ship energy efficiency and a viable way to fulfill emission reduction requirements. This study develops a novel ship sailing speed optimization method that considers dynamic meteorological conditions. We first develop an artificial neural network model for vessel fuel consumption rate (FCR) prediction based on a fusion dataset of ship noon reports and public meteorological data. Then, based on the predicted FCRs, the method repeatedly formulates a multistage graph based on the most recent forecasts, and optimal speeds for the remaining voyage are obtained until the vessel reaches the destination port. The computational efficiency of the optimization process is enhanced by progressively removing nodes without connections to successor nodes, starting from the penultimate stage. We examine the proposed method on two 11-day voyages of a dry bulk carrier. Results show that the proposed method demonstrates significant reductions in fuel consumption by 5.35% compared with a constant sailing speed scheme and by 7.34% compared with a static speed optimization model. In addition, the proposed model achieves similar fuel savings to those achieved by speed optimization based on actual meteorological conditions, enabling shipping companies to optimize ship sailing speeds in the absence of actual meteorological conditions. The proposed method can be applied to various types of vessels due to its flexibility and adaptability, making it a valuable tool for the shipping industry to reduce greenhouse gas (GHG) emissions, thereby supporting the International Maritime Organization (IMO)’s goal of reaching net-zero GHG emissions by around 2050.

Determination of Propeller-Rudder-Hull Interaction Coefficients in Ship Manoeuvring Prediction

Abstract The assessment of ship manoeuvring properties is a crucial part of the process of ship design and is usually first carried out during the model test phase of the project. According to the International Maritime Organisation (IMO), the manoeuvrability of the ship can be assessed on the basis of the standard trial manoeuvres. In order to do this, free running model tests or captive model tests are used, in conjunction with a mathematical model of ship motion; this is considered to be a reliable prediction method. In recent years, numerical-based methods have also been widely used in ship hydrodynamics and constantly improving computing power and more accurate fluid dynamics models have made the simulation of more complex cases possible. The study presented in this paper focuses on the determination of propeller-rudder-hull interaction coefficients based on the Mathematical Modelling Group (MMG) standard method in ship manoeuvring prediction. The identification of the parameters uses both captive model tests and a simplified numerical method, as well as regression formulas. The results of 35° turning and 10°/10° zig-zag manoeuvres, obtained with the use of each prediction method, are then compared. The test case used in the study is the container type cargo ship equipped with a single propeller and rudder. The model scale, for which the referenced model tests were carried out, is equal to 1:25 and a NACA 0020 rudder profile was used. This research highlights the advantages and disadvantages of each presented prediction method and their potential for future improvement.

A wind-to-wake approach for selecting future marine fuels and powertrains

Global shipping contributes (2.8%) to greenhouse gas emissions and needs to find future fuels which will allow the International Maritime organisation's 2050 net zero targets to be met. There is much uncertainty as to which fuels should be used between hydrogen, ammonia or methanol as future costs are uncertain. We propose and evaluate a Wind-to-Wake ratio that provides an objective measure based on the amount of renewable energy required to propel a ship. Time domain voyage energy demand profiles are used to simulate the fuel used and emissions for a cruise ship, a research survey vessel, a container ship and a large multi-fuel Liquefied Natural Gas carrier. Alternative ship power systems are investigated using various carbon-based fuels, ammonia and hydrogen either using conventional engines or fuel cells. For all voyage and fuel scenarios the combination of hydrogen and fuel cells uses 30% less renewable energy than ammonia and 26% less than methanol. Hydrogen only emits steam whereas the other fuel scenarios still emit significant amounts of greenhouse gasses.

Improved Whale Optimization Algorithm for Maritime Autonomous Surface Ships Using Three Objectives Path Planning Based on Meteorological Data

In recent years, global trade volume has been increasing, and marine transportation plays a significant role here. In marine transportation, the choice of transportation route has been widely discussed. Minimizing fuel consumption, minimizing voyage time, and maximizing voyage security are concerns of the International Maritime Organization (IMO) regarding Maritime Autonomous Surface Ships (MASS). These goals are contradictory and have not yet been effectively resolved. This paper describes the ship path-planning problem as a multi-objective optimization problem that considers fuel consumption, voyage time, and voyage security. The model considers wind and waves as marine environmental factors. Furthermore, this paper uses an improved Whale Optimization Algorithm to solve multi-objective problems. At the same time, it is compared to three advanced algorithms. Through seven three-objective test functions, the performance of the algorithm is tested and applied in path planning. The results indicate that the algorithm can effectively balance the fuel consumption, voyage time, and voyage security of the ship, offering reasonable paths.

IMO2020 Regulations Accelerate Global Warming by up to 3 Years in UKESM1

AbstractThe International Maritime Organization (IMO) introduced new regulations on the sulfur content of shipping emissions in 2020 (IMO2020). Estimates of the climatic impact of this global reduction in anthropogenic sulfate aerosols vary widely. Here, we contribute to narrowing this uncertainty with two sets of climate model simulations using UKESM1. Using fixed sea‐surface temperature atmosphere‐only simulations, we estimate an IMO2020 global effective radiative forcing of 0.139 ± 0.019 Wm−2 and show that most of this forcing is due to aerosol‐induced changes to cloud properties. Using coupled ocean‐atmosphere simulations, we note significant changes in cloud top droplet number concentration and size across regions with high shipping traffic density, and—in the North Atlantic and North Pacific—these microphysical changes translate to a decrease in cloud albedo. We show that IMO2020 increases global annual surface temperature on average by 0.046 ± 0.010°C across 2020–2029; approximately 2–3 years of global warming. Furthermore, our model simulations show that IMO2020 helps to explain the exceptional warming in 2023, but other factors are needed to fully account for it. The year 2023 also had an exceptionally large decrease in reflected shortwave radiation at the top‐of‐atmosphere. Our results show that IMO2020 made that more likely, yet the observations are within the variability of simulations without the reduction in shipping emissions. To better understand the climatic impacts of IMO2020, a model intercomparison project would be valuable whilst the community waits for a more complete observational record.