Maritime Transport Research Articles

Tracking Whale Calls in the Lower St. Lawrence Seaway at Land Seismometers

The Lower St. Lawrence Seaway (LSLS) is critical to Canada’s economy both as part of a major marine shipping corridor and a site of intensive fishing. Every year, fin whales and blue whales frequent the LSLS feeding ground. Understanding the mechanisms driving whale habitat usage is key for making informed decisions on shipping and fishing, reducing whale collision risks and mitigating noise pollution. We detect whales in the LSLS with land seismometers by using a method that relies on the intervals of the regularly repeating low frequency calls. The resulting catalogue contains 14,076 fin whale detections and 3,739 blue whale detections between February 2020 and January 2022. These detections follow the overall pattern of hydrophones, with most detections from fall to early winter in the Estuary and until mid-winter/spring in the Gulf. High detection rates in the Northwest Gulf throughout the winter months demonstrate that this region is potentially utilized year-round. This labelled catalogue may be suitable for developing a deep learning-based whale call detection algorithm. Making use of seismometers and deep learning can increase whale monitoring coverage within the LSLS and elsewhere.

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.

System-based ship design of a deep-sea mining vessel

ABSTRACT This paper applies the system-based ship design (SBSD) method to the conceptual design of a deep-sea mining vessel. The anticipated mine site is situated on the Norwegian extended continental shelf, where three production scenarios are assessed. The design process is documented, including a problem statement, mission description, functions, space requirements of various sub-systems, stability calculations, and preliminary cost estimates. A combination of data from existing technologies and estimates is used to set the relevant parameters, and the applicability of SBSD in the conceptual design of novel vessels is discussed. We find that when data is lacking in conceptual ship design, inspiration can be found from similar systems in established maritime industries, such as the offshore oil and gas industry.

PROTOTYPE PARKING SENSOR ON A SHIP AT THE DOCK USING SENSOR BASED ON ARDUINO UNO R3

The main issue that needs to be addressed in this research is to enhance the safety and efficiency of the vessel berthing process by reducing the risk of collisions with the dock. With the advancement of technology in the maritime industry, there is still a reliance on various parties such as tugboats, ship crew, and dock authorities to ensure safe vessel berthing. Therefore, it is necessary to design a modern technology-based parking sensor system to provide assistance in the vessel berthing process. By using a parking sensor system based on the Arduino Uno R3 and ultrasonic sensors JSN-SR04T and AJ-SR04M, this research aims to address the risk of collisions with the dock, which can result in serious damage to the vessel, dock, and the surrounding environment. This parking sensor system is designed to reduce this risk by providing early warnings to the users. Furthermore, the research aims to reduce dependence on human factors and minimize human errors. Lastly, the research also aims to improve the efficiency of the vessel berthing process. By designing and implementing this prototype, the research aims to provide a technological solution to address the above-mentioned issues, enhance safety, and optimize the vessel berthing process around Motor Vessel BIN NO.2 EKS. SANYO MARU NO.8.

A benchmark study on the energy efficiency and environmental impacts of alternative fuels in gulet-type sailing yachts

Gulet-type yachts are one of the symbols of maritime culture with their unique hull forms and schooner or ketch-type riggings. In parallel with the targets aiming for decarbonization in the maritime industry, energy efficiency and emission control are on the agenda for these types of yachts. Driven by this motivation, a novel benchmark study for the gulet-type yachts is conducted to evaluate the energy efficiency and environmental impacts associated with the adoption of LNG or methanol as primary fuel alternatives to MDO. The benchmark study is constructed in two steps: Presenting the design and propulsion characteristics of existing gulets, followed by a detailed analysis of the energy efficiency and environmental impacts of using alternative fuels. Therefore, 57 gulets with round and transom sterns whose hull forms are analyzed, modeled and general characteristics are presented. After modeling, the resistance and effective power of hull forms are predicted using the Holtrop-Mennen method and CFD. The flow characteristics around the hulls are obtained and the results are validated using the previous experimental studies in the first step. Then, installed and computed engine capacities are compared, and the Annual Emission Ratio and Energy Efficiency Index (EEI) are calculated for environmental impact assessments. Finally, the applicability of using LNG or MeOH-fueled propulsion systems for gulet-type yachts is discussed considering energy efficiency and design. According to the results, transitioning to alternative fuels can increase the Energy Efficiency Index of gulet-type yachts by over 20%.

Reconstruction of significant wave height distribution from sparse buoy data by using deep learning

Significant wave height plays a crucial role in influencing marine ecosystems, ocean shipping, and other maritime activities. The distribution of buoy observation data tends to be sparse. Gridded wave data obtained through numerical simulation typically offer broader applicability, albeit with higher computational demands. In this paper, a deep learning model based on Full Connected and Convolutional Neural Networks is proposed, utilizing sparse buoy observation data as input to reconstruct the distribution of significant wave height in the sea area. The model reconstruction results are validated using ERA5 data, demonstrating excellent performance. Additionally, we explore the influence of the model's spatial boundaries and the number of input buoys on reconstruction accuracy, as well as the adaptability of the model to different sea areas. This study provides a novel method and approach for the rapid and cost-effective retrieval of regional significant wave height.

Developing circularity metrics for the maritime industry: A stakeholder focused study

Embracing circular practices is crucial for reducing the maritime industry's environmental impact. However, the industry lacks tailored circular economy metrics to effectively measure its circularity practices and performance. To address this gap, a comprehensive review was conducted, analysing over 400 circularity metrics used in various other industries. From this extensive review, these metrics were refined and adapted to develop 57 circularity metrics tailored to the maritime sector. These novel metrics aim to guide maritime stakeholders in assessing and improving their circularity performance. Their relevance was validated through stakeholder engagement and consultations, and practicality was demonstrated through a detailed case study in three private shipyards. This case study showcased the metrics' applicability and highlighted their potential benefits in real-world scenarios by providing suggestions for improving the circularity performance of the facilities. This study marks the first comprehensive maritime circularity assessment, providing a structured pathway for the future adoption and implementation of circularity principles within the maritime industry. By establishing these metrics, the study sets a foundational framework for stakeholders to enhance sustainability and promote circular economy practices in maritime operations. Quantifying circular economy performance will enable stakeholders to track progress, identify best practices, and drive transition.

Quantifying the environmental footprints of biofuels for sustainable passenger ship operations

This study investigates the potential of biofuels to mitigate the environmental impact of passenger vessels. Employing a life cycle assessment methodology, this research comprehensively analyzes the environmental footprint of various fuels throughout the life cycle of a passenger vessel, encompassing construction, fuel production, operation, maintenance, and decommissioning. This study demonstrates the application of life cycle impact assessment to evaluate the environmental footprint of a bio-fueled passenger vessel operating on the Baltic Sea route from Tallinn-Helsinki, Helsinki-Åland, and Åland-Stockholm, totaling a round-trip distance of around 700 nautical miles. Ten different fuels, including several biofuel options, were evaluated using two established impact assessment methodologies. This life cycle assessment study focused on five major environmental impact categories: eutrophication, ozone depletion, climate change, and human and eco-toxicity. A comparative analysis encompassed Heavy fuel oil, bio-hydrotreated vegetable oil, bio-dimethyl ether, marine diesel oil, biodiesel, liquefied natural gas, methanol, bio-methanol, ethanol, and bio-ethanol. Based on impact categories like Global warming potential (GWP 100) and Global temperature potential (GTP 100), the findings suggest significantly lower environmental impacts of biofuels than all other fuel options. Notably, biofuels significantly reduced environmental impact, ranging from 70 % to 90 % per tonne-kilometer across most categories. These results highlight the promise of biofuels as a sustainable alternative fuel source for the maritime transportation sector, potentially reducing their environmental footprints significantly. In summary, biofuels offer a pragmatic and timely approach to enhancing passenger vessels' sustainability and operational efficiency amidst the maritime sector's transition towards a cleaner future.

The Impact of Barriers and Drivers of AI Technology Utilization on Adoption of AI through Educational Institutions’ Readiness: A Case Study of the Arab Academy for Science, Technology, and Maritime Transport

The Impact of Barriers and Drivers of AI Technology Utilization on Adoption of AI through Educational Institutions’ Readiness: A Case Study of the Arab Academy for Science, Technology, and Maritime Transport

A Fault Diagnosis Approach Utilizing Artificial Intelligence for Maritime Power Systems within an Integrated Digital Twin Framework

This research focuses on enhancing the preventive maintenance strategies currently employed for induction motors within ship propulsion systems, advocating for a shift towards a predictive maintenance model. It introduces a real-time monitoring framework that continuously observes the induction motor, providing essential support to maintenance personnel. The motor operates under a range of environmental and operational conditions, including temperature fluctuations, rotational speeds, and mechanical loads. These variations can obscure the current time series data, potentially masking signs of actual damage and hindering effective damage detection. To tackle this issue, the proposed framework utilizes artificial intelligence (AI) technology, specifically the well-established autoencoder, in conjunction with the Mahalanobis statistical distance. This approach accounts for the diverse operating conditions during the training phase, allowing it to model complex, non-linear relationships and effectively differentiate between normal and anomalous states. The framework is integrated into a decision support platform designed for real-time operations in maritime settings, offering a sophisticated system architecture that aims to align advanced damage detection methodologies with the maritime industry’s need for real-time, user-friendly solutions.

Protection of Seafarers' Rights and Interests by International Treaties

In 2006, the ILO adopted the Maritime Labour Convention, which has had an important impact on the rights of seafarers worldwide and the promotion of the international maritime industry. In recent years, China's labor and social security legal system has been gradually improved, and legal norms such as the Regulations on Seafarers and the Maritime Traffic Safety Law have been promulgated and implemented successively, laying a certain foundation for the system of labor norms for seafarers. However, these special legislation has some limitations, such as not strong operability and not identical with the international treaty system. This paper mainly studies the framework structure and implementation mechanism of maritime labor conventions, finds out China's application method of international law, and puts forward the shortcomings of China's implementation process and corresponding countermeasures and suggestions suitable for the current situation of Chinese seafarers. By combining theory with practice, this paper uses literature analysis and analysis deduction to find out the strategies that can optimize the implementation mechanism in China. At present, China has made a lot of preparations for the implementation of maritime labor conventions, carried out a lot of legislative activities, and has already acquired relevant legislative experience and technology. Improving the labor supervision system and making full use of the tripartite mechanism platform and industry associations are the top priorities for China to better implement international conventions and protect the rights and interests of seafarers in the next stage.

GIS-Based Optimal Siting of Offshore Wind Farms to Support Zero-Emission Ferry Routes

To achieve net zero emissions from ships by 2050 and align with the IMO 2023 GHG strategy, the maritime industry must significantly increase zero-emission vessels by 2030. Transitioning to fully electric ferry lines requires enhanced energy supply through renewable energy sources (RES) for complete GHG mitigation and net-zero emissions. This study presents a GIS-based framework for optimally selecting offshore wind farm locations to meet the energy demands of electric ferry operations along coastal routes. The framework involves two stages: designing feasible zero-emission ferry routes between islands or to the mainland and identifying optimal offshore wind farm sites by evaluating technical, spatial, economic, social, and environmental criteria based on national legislation and the academic literature. The aim is to create a flexible framework to support decision making for establishing sustainable electric ferry operations at a regional level, backed by strategically located offshore wind farms. The study applies this framework to the Greek Coastal Shipping Network, focusing on areas with potential for future electrification. The findings can aid policymakers in utilizing spatial decision support systems (SDSS) to enhance efficient transportation and develop sustainable island communities.

Maritime transportation risk assessment: A multilevel node relationship-based fuzzy bayesian network

Maritime transportation safety has encountered unprecedented challenges arising from abrupt changes in various risk attributes in recent years, including natural weather and non-traditional security threats. This study presents a novel two-phase framework for assessing the maritime transportation risk. Firstly, a fuzzy Bayesian network considering multi-level node relationships was constructed to more accurately assess the transportation risk in various sea areas. In the second phase, RF-Shapley was developed to identify crucial risk nodes that exert substantial influence on transportation risk within individual sea areas. The results showed that transportation risk was the lowest in the South Asian and the highest in the Middle East waters. Critical risk nodes were different for each sea area, such as pirate attack node in Southeast Asian waters, extreme weather node in Northeast Asia, changing these nodes would be more helpful in improving transportation safety. Moreover, the contribution of critical risk nodes exhibited variations, such as combating terrorism and piracy were more conducive to reducing transportation risk in Middle Eastern waters, while ship accidents node be low contribution. These results offer valuable insights for evaluating transportation risk in uncertain environments and can serve as a reference for stakeholders to devise tailored policies and action plans.

Study on rapid policy-based strategic environmental assessment-taking China's regional development policy of Zhejiang Pilot Free Trade Zone as an example

Strategic Environmental Assessment(SEA) is acknowledged to be an important decision support tool. SEA concerns potential environmental impacts of decisions made by policy, plan and programs. At present, policy-based SEA is still in the exploratory stage in China. The development of policy-based SEA is extremely slow due to institutional and technical difficulties. In practice, the time from policy proposals to policy implementation is relatively short. So the corresponding policy-based SEA should reflect the characteristics of rapidity, centre on the seriously negative impact that may be caused policy implementation, and provide early and initial warnings.A simple and rapid framework was designed for policy-based SEA in this study. The framework includes four parts, namely, policy analysis, eco-environmental impact identification, eco-environmental sensitivity assessment, policy recommendations. Following this framework, regional development policy of Zhejiang Pilot Free Trade Zone (FTZ) was assessed. Results reveal that: 1)seriously negative environment impacts may arise from petroleum refining and chemical industry, oil and gas storage and transportation, iron ore transportation, liquid bulk commodities transportation. 2) Central Daishan area, Shengsi archipelago, Taohua Island, Liuheng island in Zhejiang FTZ is relatively of high eco-sensitivity, thus the fore-mentioned activities should be environmentally friendly or restricted in these areas. 3)In the future, continuous efforts should be made to promote sealing and automation of petroleum refining, chemical industry. Green petrochemical manufacturing technology utilization is recommended to reduce pollution from the source. Further, accelerating the construction of transportation pipelines is suggested in order to reduce air pollutants emissions caused by vehicle transportation activities. Fishery stock enhancement and releasing is recommended to counteract negative impact on fishery caused by iron and liquid bulk commodity marine transportation.

Optimal Deployment of Container Weighing Equipment: Models and Properties

Container weighing is crucial to the safety of the shipping system and has garnered significant attention in the maritime industry. This research develops a container weighing optimization model and validates several propositions derived from this model. Then, a case study is conducted on ports along the Yangtze River, and the sensitivity analysis of the model is provided. We report the following findings. First, the model can be solved efficiently for large-scale optimization problems. Second, as the number of weighing machines increases, the container weighing mode changes—from selectively weighing containers at their origin ports, then weighing containers at their transshipment ports or destination ports, to all of the containers weighed at their origin ports. Third, in order to improve the safety benefits of weighing containers, port authorities can increase the weighing capacity of weighing machines. The research provides theoretical guidance for shipping system managers to design container weighing plans that enhance maritime safety.

Reliability and validity assessment of instrument to measure sustainability practices at shipping ports in India

Sustainability has emerged as one of the most critical factors influencing the competitiveness of maritime shipping ports. This emergence has led to a surge in research publications on port sustainability-related topics. However, despite the increasing awareness and adoption of sustainability practices, documented literature on empirical studies with survey and interview data is very limited. Moreover, the existence of validated instruments to objectively assess sustainability through sustainability practices for shipping ports in India needs to be traced. This study contributes by validating an instrument to evaluate objectively sustainability practices in shipping ports by adopting a four-stage process, starting with item identification based on an extensive literature review, instrument evaluation by subject matter experts, assessing of the instrument with suitable content validation indices, and finally evaluating the validity and reliability of the hypothesized theoretical model. For content validation, Content Validity Index, Cohens Kappa coefficient, and Lawshe’s Content Validity Ratio were computed with the assessment by a subject matter expert panel comprising six members from the port industry as well as academicians cum researchers in the field of shipping ports. The content-validated instrument was administered to 200 samples comprising officer category port employees. The measurement model was evaluated and validated using the Confirmatory Factor Analysis to assess the extent to which the measured variables represent the theoretical construct of the study and ascertain the factor structure. The empirically validated instrument met the required guidelines of model fit, reliability, and construct validity measures and was found to be a confirmed model for measuring sustainability practices in shipping ports. Structural Equation Modeling methodology was adopted to explain the variance and the path relationship between the higher-order and lower-order constructs of sustainability. The results indicate that the economic dimensions are the major contributors to the overall sustainability of the port as they drive investments in environmental and social dimensions, leading to overall sustainable development. The study’s findings will be helpful for researchers, academicians, policymakers, and industry practitioners working towards sustainability practices that contribute to sustainable growth and development in the shipping industry.

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.

Clean energy ship application to promote carbon neutrality in global maritime industry: State governance or international supervision？

The global maritime industry is facing the goal to achieve "carbon neutrality", and substituting traditional ship fuel with clean energy is the most important solution. Whether to promote clean-energy ships through state governance or unified international supervision to achieve carbon neutrality has been a long-standing debate. This study employs both a tripartite evolutionary game model and a quadrilateral evolutionary game model to compare the effectiveness of state governance and unified international supervision in promoting clean-energy ships. The tripartite model simulates interactions between local governments, shipping companies, and shippers, revealing that high subsidy costs reduce local governments' incentives to promote clean-energy ships. The quadrilateral model introduces international supervision, demonstrating that a unified international oversight mechanism can accelerate the global maritime industry's progress toward carbon neutrality. Numerical simulations indicate that lowering the purchase costs of clean-energy ships and introducing government subsidies significantly influence the adoption of clean-energy ships, while supervision costs impact the effectiveness of international regulations. These findings provide critical insights for policymakers aiming to balance financial incentives and global supervision strategies to foster low-carbon development in the maritime sector.

INVESTIGATION OF BLUE ECONOMY AND ITS IMPACT ON GLOBAL MARITIME TRANSPORTATION

According to sustainability, the Strategy to protect the oceans, water surfaces, and water resources that constitute 70% of the world is generally called a Blue Economy (BE). This Strategy maximizes the return from the aquatic environment, which can only be achieved when economic activity is perfectly balanced with the long-term activity of ocean ecosystems. Threats arising during and after studies and activities should be anticipated and actively reduced. This proactive stance is fundamental to the Blue Economy philosophy and allows us to reap its benefits while protecting our oceans. One of the most essential elements of the Blue Economy philosophy is maritime transportation, Ships, and Ports. The maritime industry should remain sustainable and green as it develops. The study investigated the impact of the Blue Economy on maritime transportation and how maritime transportation affects world trade.

An experimental study on the wear performance of 3D printed polylactic acid and carbon fiber reinforced polylactic acid parts: Effect of infill rate and water absorption time

AbstractRapid prototyping, also known as additive manufacturing, is a nascent technology that is gaining traction in the context of environmental concerns and waste reduction, as well as the growing trend towards customized design. The additive manufacturing method, which has applications in diverse fields such as aviation, architecture, biomedical and automotive engineering, has also begun to be utilized in the construction of yachts and yacht hulls within the maritime industry. In this experimental study, the influences of sea water on polylactic acid (PLA) and carbon fiber reinforced polylactic acid (PLA/CF) parts manufactured at different infill rates (20%, 60% and 100%) were investigated. The parts were exposed to sea water for three different periods (1, 5, and 10 days) and subsequently subjected to wear tests. The dimensional accuracy, surface roughness, hardness, water absorption, volume loss, and friction coefficient of parts were measured and calculated. Additionally, the worn surfaces of the parts were investigated using field emission scanning electron microscope (FESEM) images. The findings indicate that PLA and PLA/CF parts can be produced with high dimensional accuracy. Furthermore, it can be reported that the water absorption of PLA/CF parts increased, particularly with an increase in the infill rate, while the volume loss decreased. Obtained results indicate the necessity of optimizing the 3D printing parameters and the relationship between the ambient conditions and the wear performance of the 3D printed parts.Highlights 3D printing is a highly promising method for the production of polymer composites. A pioneering study into the effect of infill rate and water absorption on the wear performance. Coefficient of friction values of PLA and PLA/CF parts ranged between 0.37 and 0.75. PLA/CF mostly exhibited higher volume loss than PLA with water absorption. Volume loss declines with a raise in the infill rate from 20% to 100%.