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In the context of the deep-sea transportation supply chain, this paper addresses the complex decision-making problem of vessel allocation and carbon emission optimization for container shipping routes. A bi-level programming model is established, with the upper level aiming to minimize the total operational cost and the lower level focusing on minimizing carbon emissions. Using an example of an operator with five different types of vessels, a genetic algorithm is employed to determine the optimal vessel allocation scheme. The results indicate that the vessel allocation scheme obtained through multiple iterations of the model effectively reduces both carbon emissions and operational costs. Under the condition that the preset labor cost increases year by year, the use of model optimization can significantly reduce the growth of total operating costs. This paper provides theoretical support and practical guidance for shipping companies aiming to optimize decision-making in order to reduce operational costs and carbon emissions. [ABSTRACT FROM AUTHOR]

Water-free transportation (WFT) causes shrimp (Penaeus vannamei) flesh quality deterioration. However, the roles of endogenous protease-induced protein hydrolysis have been neglected in the research. In the present study, calpain zymography, gelatinase zymography, the hematoxylin–eosin staining method, and other methods were applied to investigate the response of various endogenous proteases (cathepsin, calpain, and gelatinase), the myofibril fragmentation index (MFI), and the microscopic morphology of shrimp muscle during WFT in comparison with the shrimp under the conventional water transportation strategy (WT). The results showed that the total activity of proteases in shrimp muscle increased significantly (p ≤ 0.05) after simulated transportation. Cathepsins and gelatinases were activated during WFT. No significant (p > 0.05) changes of the activity of caspase-3 and the muscle cell apoptosis rate were detected in shrimp muscle cells after WFT. In addition, the MFI increased and the gap among muscle fiber bundles enlarged after WFT. Compared with WFT, no significant (p > 0.05) effect on the activities of calpain, gelatinase, and caspase-3 in the muscle of shrimp was found after WT, and only the activity of cathepsin L significantly increased (p ≤ 0.05). Based on the findings, we concluded that the activation of various endogenous proteases was induced during WFT. [ABSTRACT FROM AUTHOR]

The rhizosheath, the layer of soil tightly attached to the roots, protects plants against abiotic stress and other adverse conditions by providing a bridge from the plant root system to the soil. It reduces the formation of air gaps between the root and soil and facilitates the transportation of water at the root–soil interface. It also serves as a favourable niche for plant-growth-promoting rhizobacteria in the surrounding soil, which facilitate the absorption of soil water and nutrients. This review compares the difference between the rhizosheath and rhizosphere, and summarises the molecular and physiological mechanisms of rhizosheath formation, and identifying the causes of rhizosheath formation/non-formation in plants. We summarise the chemical and physical factors (root hair, soil-related factors, root exudates, and microorganisms) that determine rhizosheath formation, and focus on the important functions of the rhizosheath in plants under abiotic stress, especially in drought stress, phosphorus deficiency, aluminium stress, and salinity stress. Understanding the roles played by the rhizosheath and the mechanisms of its formation provides new perspectives for improving plant stress tolerance in the field, which will mitigate the increasing environmental stress conditions associated with on-going global climate change. [ABSTRACT FROM AUTHOR]

Corresponding to marine environmental regulations is important in shipbuilding and marine industries. The application of lightweight composite materials on ships is an effective approach to reducing the emission of greenhouse gases. The mechanical fastening method is a good candidate to assemble composites and conventional metals. The joint geometric and environmental effects are two important factors in mechanically fastened ship and marine structures. In this study, we evaluated the W/D (hole diameter to width ratio) and environmental effects on the bearing strength and failure mode of a mechanically fastened non-crimp fabric (NCF) composite material. To consider the effect of joint geometry, wherein hole diameters of 5, 6, 8, and 10 mm were machined. Further, by selecting three environmental conditions (UV, saltwater and low temperature), we evaluated environmental effects on bearing strength and failure modes of NCF composite specimens. The bearing strength increased as W/D decreased, and the bearing strength of the specimen exposed to low temperature and UV environments increased, while that of the specimen exposed to saltwater remained the same. From the failure mode analysis, the specimen that was exposed to salt fog showed the same failure mode as the unaged specimen. It was observed that the changes in the transition section and new failure mode in the xenon arc and low-temperature specimens. [ABSTRACT FROM AUTHOR]

Cargo terminals, as pivotal hubs of mechanical activities, maritime shipping, and land transportation, are significant sources of air pollutants, exhibiting considerable spatiotemporal heterogeneity due to the complex and irregular nature of emissions. This study employed a high-density air sensor network with 17 sites across four functional zones in two Shanghai cargo terminals to monitor NO and NO2 concentrations with high spatiotemporal resolution post sensor data validation against regulatory monitoring stations. Notably, NO and NO2 concentrations within the terminal surged during the night, peaking at 06:00 h, likely due to local regulations on heavy-duty diesel trucks. Spatial analysis revealed the highest NO concentrations in the core operational areas and adjacent roads, with significantly lower levels in the outer ring, indicating strong emission sources and limited dispersion. Employing the lowest percentile method for baseline extraction from high-resolution data, this study identified local emissions as the primary source of NO, constituting over 80% of total emissions. Elevated background concentrations of NO2 suggested a gradual oxidation of NO into NO2, with local emissions contributing to 32–70% of the total NO2 concentration. These findings provide valuable insights into the NO and NO2 emission characteristics across different terminal areas, aiding decision-makers in developing targeted emission control policies. [ABSTRACT FROM AUTHOR]

With the development and application of artificial intelligence (AI) in the shipping industry, using AI to replace traditional draft survey methods in bulk carriers can significantly reduce manpower, lower the risks associated with visual observations, improve measurement accuracy, and minimize the impact of human subjective factors. Ultimately, the integration of software and hardware technologies will replace human visual observations with automated draft measurement calculations. A similar anti-fluctuation device described in this article has been used in ship draft observation based on AI-assisted proving, which can ease the fluctuation of the wave inside the pipe. Observers can directly read the water surface inside the pipe and compare it to the ship's draft mark to obtain the final draft, effectively improving draft observation accuracy. However, some surveyors refuse to accept the readings obtained from this device, citing a lack of theoretical basis or the absence of accreditation from relevant technical authorities, leading to the rejection of results. To address these issues, this paper integrates wave energy attenuation theory with PaddlePaddle-OCR recognition to further validate the anti-fluctuation device for accurate ship draft observation. The experimental results are as follows: first, the pipe effectively suppresses the amplitude of external water surface fluctuations by 75%, explaining the fundamental theory that wave heights within the anti-fluctuation device are consistent with external swell heights. When taking a draft measurement, the system dynamically adjusts the position of the main tube in response to the ship's movements, maintaining the stability of the measurement section and significantly reducing the difficulty of observations. Due to the reduction in fluctuation amplitude, there is a noticeable improvement in observation accuracy. [ABSTRACT FROM AUTHOR]

Marine sources contribute approximately 2% of global energy-related CO₂ emissions, with the shipping industry accounting for 87% of this total, making it the fifth-largest emitter globally. Environmental regulations by the International Maritime Organization (IMO), such as the MARPOL (International Convention for the Prevention of Pollution from Ships) treaty, have driven the exploration of alternative green energy solutions, including nuclear-powered ships. These ships offer advantages like long operational periods without refueling and increased cargo space, with around 200 reactors already in use on naval vessels worldwide. Among advanced reactor concepts, the molten salt reactor (MSR) is particularly suited for marine applications due to its inherent safety features, compact design, high energy density, and potential to mitigate nuclear waste and proliferation concerns. However, MSR systems face significant challenges, including tritium production, corrosion issues, and complex behavior of volatile fission products. Understanding the impact of marine-induced motion on the thermal–hydraulic behavior of MSRs is crucial, as it can lead to transient design basis accident scenarios. Furthermore, the adoption of MSR technology in the shipping industry requires overcoming regulatory hurdles and achieving global consensus on safety and environmental standards. This review assesses the current progress, challenges, and technological readiness of MSRs for marine applications, highlighting future research directions. The overall technology readiness level (TRL) of MSRs is currently at 3. Achieving TRL 6 is essential for progress, with individual components needing TRLs of 4–8 for a demonstration reactor. Community Readiness Levels (CRLs) must also be addressed, focusing on public acceptance, safety, sustainability, and alignment with decarbonization goals. [ABSTRACT FROM AUTHOR]

The ability to classify and recognize maritime targets based on visual images plays an important role in advancing ship intelligence and digitalization. The current target recognition algorithms for common maritime targets, such as buoys, reefs, other ships, and bridges of different colors, face challenges such as incomplete classification, low recognition accuracy, and a large number of model parameters. To address these issues, this paper proposes a novel maritime target recognition method called DTI-YOLO (DualConv Triple Attention InnerEIOU-You Only Look Once). This method is based on a triple attention mechanism designed to enhance the model's ability to classify and recognize buoys of different colors in the channel while also making the feature extraction network more lightweight. First, the lightweight double convolution kernel feature extraction layer is constructed using group convolution technology to replace the Conv structure of YOLOv9 (You Only Look Once Version 9), effectively reducing the number of parameters in the original model. Second, an improved three-branch structure is designed to capture cross-dimensional interactions of input image features. This structure forms a triple attention mechanism that accounts for the mutual dependencies between input channels and spatial positions, allowing for the calculation of attention weights for targets such as bridges, buoys, and other ships. Finally, InnerEIoU is used to replace CIoU to improve the loss function, thereby optimizing loss regression for targets with large scale differences. To verify the effectiveness of these algorithmic improvements, the DTI-YOLO algorithm was tested on a self-made dataset of 2300 ship navigation images. The experimental results show that the average accuracy of this method in identifying seven types of targets—including buoys, bridges, islands and reefs, container ships, bulk carriers, passenger ships, and other ships—reached 92.1%, with a 12% reduction in the number of parameters. This enhancement improves the model's ability to recognize and distinguish different targets and buoy colors. [ABSTRACT FROM AUTHOR]

The rapid development of artificial intelligence has greatly ensured maritime safety and made outstanding contributions to the protection of the marine environment. However, improving maritime safety still faces many challenges. In this paper, the development background and industry needs of smart ships are first studied. Then, it analyzes the development of smart ships for navigation from various fields such as the technology industry and regulation. Then, the importance of navigation technology is analyzed, and the current status of key technologies of navigation systems is deeply analyzed. Meanwhile, this paper also focuses on single perception technology and integrated perception technology based on single perception technology. As the development of artificial intelligence means that intelligent shipping is inevitably the trend for future shipping, this paper analyzes the future development trend of smart ships and visual navigation systems, providing a clear perspective on the future direction of visual navigation technology for smart ships. [ABSTRACT FROM AUTHOR]

The application of artificial intelligence models for the fault diagnosis of marine machinery increased expeditiously within the shipping industry. This relates to the effectiveness of artificial intelligence in capturing fault patterns in marine systems that are becoming more complex and where the application of traditional methods is becoming unfeasible. However, despite these advances, the lack of fault labelling data is still a major concern due to confidentiality issues, and lack of appropriate data, for instance. In this study, a method based on histogram similarity and hierarchical clustering is proposed as an attempt to label the distinct anomalies and faults that occur in the dataset so that supervised learning can then be implemented. To validate the proposed methodology, a case study on a main engine of a tanker vessel is considered. The results indicate that the method can be a preliminary option to classify and label distinct types of faults and anomalies that may appear in the dataset, as the model achieved an accuracy of approximately 95% for the case study presented. [ABSTRACT FROM AUTHOR]

This paper aims to systematically review and analyze the literature on green shipping, focusing on research trends, key areas, and future directions. A bibliometric analysis is conducted on 1339 articles published between 2000 and 2023, using data from the SCI-EXPANDED and SSCI core collections on the Web of Science platform. Co-occurrence analyses are performed for authors, countries, institutions, and keywords. The analysis reveals exponential growth in green shipping research over the past decade, with a significant increase since 2019. China leads in publication output and international collaboration. Key research areas identified include sustainable development, green energy, green ports, and green supply chain management. Green shipping research is rapidly expanding, emphasizing sustainable practices and technological advancements. Future research is expected to integrate artificial intelligence, big data analytics, and other advanced technologies to further promote sustainability. Strengthening international cooperation and interdisciplinary integration will be crucial for advancing the global green shipping agenda. [ABSTRACT FROM AUTHOR]

Ship detection faces significant challenges such as dense arrangements, varying dimensions, and interference from the sea surface background. Existing ship detection methods often fail to accurately identify ships in these complex marine environments. This paper presents OptiShipNet, an efficient network for detecting ships in complex marine environments using optical remote sensing images. First, to effectively capture ship features from complex environments, we designed a DFC-ConvNeXt module as the network's backbone, where decoupled fully connected (DFC) attention captures long-distance information in both vertical and horizontal directions, thereby enhancing its expressive capabilities. Moreover, a simple, parameter-free attention module (SimAM) is integrated into the network's neck to enhance focus on ships within challenging backgrounds. To achieve precise ship localization, we employ WIoU loss, enhancing the ship positioning accuracy in complex environments. Acknowledging the lack of suitable datasets for intricate backgrounds, we construct the HRSC-CB dataset, featuring high-resolution optical remote sensing images. This dataset contains 3786 images, each measuring 1000 × 600 pixels. Experiments demonstrate that the proposed model accurately detects ships under complex scenes, achieving an average precision (AP) of 94.1%, a 3.2% improvement over YOLOv5. Furthermore, the model's frame per second (FPS) rate reaches 80.35, compared to 67.84 for YOLOv5, thus verifying the approach's effectiveness. [ABSTRACT FROM AUTHOR]

A novel Boundary Element Method (BEM) is presented for predicting the hydrodynamic behavior of twin-hull vessels, traveling at low speeds, aiming to quantify the benefits of integrating solar technology onboard. In particular, the power requirements of an electric 33 m long twin-hull ship are examined. The study discusses the placement of solar panels on deck and assesses their utilization in terms of real-time energy generation, aiming to extend the autonomy range while also reducing carbon emissions. The discussed methodology predicts the power needs by considering various operational variables, design specifications and hydrodynamic principles. In addition, it addresses the viability and possible advantages of integrating solar technology onboard and provides preliminary estimates regarding the extent to which solar energy may compensate for power needs, based on several factors, including the velocity, the prevailing sea state and the incident solar irradiance. The results provide useful information regarding the utilization of solar energy in the shipping sector, in addition to advancing sustainable maritime propulsion. [ABSTRACT FROM AUTHOR]

The water exit problem, which is ubiquitous in ocean engineering, is a significant research topics in the interaction between navigators and water. The study of the water exit problem can help to improve the structural design of marine ships and underwater weapons, allowing for better strength and movement status. However, the water exit problem involves complex processes such as three-phase gas–liquid–solid coupling, cavitation, water separation, liquid surface deformation, and fragmentation, making it challenging to study. Following work carried out by many researchers on this issue, we summarize recent developments from three aspects: theoretical research, numerical simulation, and experimental results. In theoretical research, the improved von Karman model and linearized water exit model are introduced. Several classical experimental devices, data acquisition means, and cavitation approaches are introduced in the context of experimental development. Three numerical simulation methods, namely, the BEM (Boundary Element Method), VOF (Volume of Fluid), and FVM (Finite Volume Method) with LES (Large Eddy Simulation) are presented, and the respective limitations and shortcomings of these three aspects are analyzed. Finally, an outlook on future research improvements and developments of the water exit problem is provided. [ABSTRACT FROM AUTHOR]

Maritime transport is the most widely used means of transporting goods, and forecasts indicate that it will continue to grow in the coming years, which is why the IMO is regulating energy efficiency and emissions from maritime transport with exhaustive monitoring. The most widely used measure of energy efficiency during operation on a ship is the Energy Efficiency Operational Indicator (EEOI); however, the difficulty in obtaining references for this indicator, together with the great variability that exists between shipowners when choosing terms such as "cargo transported", among others, means that this operational indicator of energy efficiency in ships does not have the expected results. This work develops a two-phase procedure for the selection of representative EEOI values for ships, taking into account parameters such as ship speed, cargo, mode of operation and the subsequent determination of a suitable control system that allows the continuous and real-time implementation of measures to improve energy and environmental efficiency on the ship. The proposed final procedure is effective in terms of improving energy efficiency and emissions, on top of being simple, easily implementable, working in real time and adapting to navigation circumstances while keeping emissions under control. [ABSTRACT FROM AUTHOR]

Situated in central China, the region surrounding Mount Song is a pivotal area within the Central Plains, renowned for its extensive and high-grade cultural heritage. This study aims to analyze the spatiotemporal distribution of this heritage using advanced spatial pattern analysis methods, including the Average Nearest Neighbor Ratio and Kernel Density Estimation within ArcGIS. Our findings reveal a distinct continuity in temporal distribution and a pronounced clustering in spatial terms. By investigating the underlying factors such as the geographical setting, historical political capitals, cultural and religious influences, water transportation systems, and traditional Fengshan ceremonies, this research elucidates the dynamics shaping this distribution. This study's outcomes provide essential insights for policymakers and stakeholders involved in the protection and revitalization of cultural heritage, ensuring informed decision making for sustainable cultural conservation. [ABSTRACT FROM AUTHOR]

In recent years, large power batteries have been widely used not only in automobiles and other vehicles but also in maritime vessels. The thermal uniformity of large marine battery packs significantly affects the performance, safety, and longevity of the electric ship. As a result, the thermal management of large power batteries has become a crucial technical challenge with traditional battery management system (BMS) that cannot effectively solve the battery heating problem caused by electrochemical reactions and joule heating during operation. To address this gap, a battery thermal management system (BTMS) has been newly designed. This article presents the design of a large marine battery pack, which features a liquid cooling system integrated into both the bottom and side plates of each pack. The flow plate is constructed from five independent units, each connected by manifold structures at both ends. These connections ensure the formation of a stable and cohesive flow plate assembly. Although research on the BTMS is relatively advanced, there is a notable lack of studies examining the effects of liquid temperature, flow rate, and battery discharge rate on the temperature consistency and uniformity of large marine battery packs. This work seeks to design the cooling system for the battery pack and analyzes the impact of the temperature, flow rate, and battery discharge rate of the liquid fluid on the consistency and uniformity of the battery pack temperature on the overall structure of the battery pack. It was found that, in low discharge conditions, there was good temperature consistency between the battery packs and between the different batteries within the battery pack, and the temperature difference did not exceed 1 °C. However, under high discharge rates, a C-rate of 4C, there might have been a decrease in temperature consistency; the temperature rise rate even exceeded 50% compared to when the discharge rate was low. The flow rate in the liquid flow characteristics had little effect on the temperature consistency between the batteries and the temperature uniformity on the battery surface, and the temperature fluctuation was maintained within 1 °C. Conversely, the liquid flow temperature had little effect on the temperature distribution between the batteries, but it caused discrepancies in the surface temperature of the batteries. In addition, the liquid flow temperature could cause the overall temperature of the battery to increase or decrease, which also occurs under different discharge rates. [ABSTRACT FROM AUTHOR]

There is a growing need to implement modern technologies, such as digital twinning, to improve the efficiency of transport fleet maintenance processes and maintain company operational capacity at the required level. A comprehensive review of the existing literature is conducted to address this, offering an up-to-date analysis of relevant content in this field. The methodology employed is a systematic literature review using the Primo multi-search tool, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The selection criteria focused on English studies published between 2012 and 2024, resulting in 201 highly relevant papers. These papers were categorized into seven groups: (a) air transportation, (b) railway transportation, (c) land transportation (road), (d) in-house logistics, (e) water and intermodal transportation, (f) supply chain operation, and (g) other applications. A notable strength of this study is its use of diverse scientific databases facilitated by the multi-search tool. Additionally, a bibliometric analysis was performed, revealing the evolution of DT applications over the past decade and identifying key areas such as predictive maintenance, condition monitoring, and decision-making processes. This study highlights the varied levels of adoption across different transport sectors and underscores promising areas for future development, particularly in underrepresented domains like supply chains and water transport. Additionally, this paper identifies significant research gaps, including integration challenges, real-time data processing, and standardization needs. Future research directions are proposed, focusing on enhancing predictive diagnostics, automating maintenance processes, and optimizing inventory management. This study also outlines a framework for DT in transportation systems, detailing key components and functionalities essential for effective maintenance management. The findings provide a roadmap for future innovations and improvements in DT applications within the transportation industry. This study ends with conclusions and future research directions. [ABSTRACT FROM AUTHOR]

Hydrogen (H2) storage is one of the most problematic issues regarding the widespread use of hydrogen, and solid-state hydrogen storage materials are promising in this regard. Hydrogen storage by sodium borohydride (NaBH4) takes attention with its advantages and idiosyncratic properties. In this study, potentials and challenges of sodium borohydride are evaluated considering storage conditions, safety, hydrogen purity, storage capacity, efficiency, cost, and the maturity. Moreover, marine use of NaBH4 is demonstrated, and the pros and cons of the NaBH4 hydrogen storage method are stated. According to evaluations, whereas advantages can be sorted as fuel availability, fuel recyclability, mild storage conditions, exothermicity of reaction, pressure flexibility, and H2 purity, challenges can be sorted as high costs, catalyst deactivation, regeneration, and practical/technical implementation issues. The great potential of NaBH4 marine use (against road/aerial vehicles) is water availability, no need to carry all the required water for the entire journey, and reduced system weight/volume by this way. [ABSTRACT FROM AUTHOR]

The maritime industry is a major source of greenhouse gas (GHG) emissions, largely due to ships running on fossil fuels. Transitioning to hydrogen-powered marine transportation in the Mediterranean Sea requires the development of a network of hydrogen refueling stations across the region to ensure a steady supply of green hydrogen. This paper explores the technoeconomic viability of harnessing wave energy from the Mediterranean Sea to produce green hydrogen for hydrogen-powered ships. Four promising island locations—near Sardegna, Galite, Western Crete, and Eastern Crete—were selected based on their favorable wave potential for green hydrogen production. A thorough analysis of the costs associated with wave power facilities and hydrogen production was conducted to accurately model economic viability. The techno-economic results suggest that, with anticipated cost reductions in wave energy converters, the levelized cost of hydrogen could decrease to as low as 3.6 €/kg, 4.3 €/kg, 5.5 €/kg, and 3.9 €/kg for Sardegna, Galite, Western Crete, and Eastern Crete, respectively. Furthermore, the study estimates that, in order for the hydrogen-fueled ships to compete effectively with their oil-fueled counterparts, the levelized cost of hydrogen must drop below 3.5 €/kg. Thus, despite the competitive costs, further measures are necessary to make hydrogen-fueled ships a viable alternative to conventional diesel-fueled ships. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

As crucial water conservancy projects, ship locks play a key role in flood control, shipping, water resource allocation, and promoting regional economic development, making them an indispensable part of the modern water transportation system. Utilizing satellite remote sensing for lock extraction can significantly reduce manual workload and costs, assist in the daily dynamic maintenance of lock hubs, and provide more comprehensive data support for the construction and management of water transport infrastructure. In this context, this paper proposes a new method for ship lock object extraction. Leveraging fuzzy theory and prior knowledge of locks, the extraction of lock objects is achieved from Gaofen-1 (GF-1) high-resolution remote sensing images. The experimental results demonstrate that the proposed algorithm can effectively extract small lock objects in remote sensing images, achieving an average extraction accuracy of 80.9% in the study area. [ABSTRACT FROM AUTHOR]

To address the high energy consumption of the carbon capture and storage process in the shipping industry, the effects of several commonly used commercial catalysts, such as HZSM-5-25, γ-Al2O3, and SiO2, as well as a self-prepared catalyst, Zr-HZSM-5-25, on the regeneration of MEA solution and MEA + MDEA mixed solution were investigated in this paper. The results showed that Zr-HZSM-5-25 had the best catalytic effect on the regeneration process of the MEA aqueous solution, which could increase the instantaneous maximum CO2 regeneration rate of the MEA-rich solution by about 8.25% and the average regeneration rate by about 5.28%. For the MEA + MDEA mixed solution, the reaction between tertiary amine MDEA and CO2 produced a large amount of HCO3− in the reaction system, which could accelerate the release of CO2 to a large extent, which resulted in the catalytic effect of the Zr-HZSM-5-25 catalyst on the regeneration process of the mixed amine solution being significantly lower than that on the single MEA solution, with an increase of 4.91% in the instantaneous maximum regeneration rate. This instantaneous maximum regeneration rate was only increased by 4.91%. While Zr-HZSM-5-25 showed a better performance in the bench-scale test, it reduced CO2 regeneration energy consumption by 7.3%. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Featured Application: Featured Application: The machine learning predictive model of fuel consumption proposed can help shipping companies toward an increasingly efficient and sustainable energy consumption with reduced operational and logistics costs, supporting a more competitive position in the market in compliance with environmental and safety regulatory standards. Water navigation is crucial for the movement of people and goods in many locations, including the Amazon region. It is essential for the flow of inputs and outputs, and for certain Amazon cities, boat access is the only option. Fuel consumption accounts for over 25% of a vessel's total operational costs. Shipping companies are therefore seeking procedures and technologies to reduce energy consumption. This research aimed to develop a fuel consumption prediction model for vessels operating in the Amazon region. Machine learning techniques such as Decision Tree, Random Forest, Extra Tree, Gradient Boosting, Extreme Gradient Boosting, and CatBoost can be used for this purpose. The input variables were based on the main design characteristics of the vessels, such as length and draft. Through metrics like mean, median, and coefficient of determination (R2), six different algorithms were assessed. CatBoost was identified as the model with the best performance and suitability for the data. Indeed, it achieved an R2 value higher than 91% in predicting and optimizing fuel consumption for vessels operating in the Amazon and similar regions. [ABSTRACT FROM AUTHOR]

Despite being stored at 113 K and at atmospheric pressure, LNG cold potential is not exploited to reduce green ships' energy needs. An innovative system based on three organic Rankine cycles integrated into the regasification equipment is proposed to produce additional power and recover cooling energy from condensers. A first-law analysis identified ethylene and ethane as suitable working fluids for the first and the second ORC, making freshwater and ice available. Propane, ammonia and propylene could be arbitrarily employed in the third ORC for air conditioning. An environmental analysis that combines exergy efficiency, ecological indices and hazard aspects for the marine environment and ship passengers indicated propylene as safer and more environmentally friendly. Exergy analysis confirmed that more than 20% of the LNG potential can be recovered from every cycle to produce a net clean power of 76 kW, whereas 270 kW can be saved by recovering condensers' cooling power to satisfy some ship needs. Assuming the sailing mode, a limitation of 162 kg in LNG consumptions was determined, avoiding the emission of 1584 kg of CO2 per day. Marine thermal pollution is reduced by 3.5 times by recovering the working fluids' condensation heat for the LNG pre-heating. [ABSTRACT FROM AUTHOR]

This document is a summary of a special issue of the Journal of Marine Science & Engineering titled "Intelligent Ships and Waterways: Design, Operation and Advanced Technology." The special issue focuses on advanced technologies for the design and sustainable operation of intelligent ships and waterways. It includes 20 research articles and 2 review articles covering topics such as waterway and port monitoring, ships' navigation environment perception, ships' navigation decision making and motion planning, and ships' motion modeling and control problems. The articles discuss various methods and technologies, including artificial intelligence, big data analysis, mixed reality, building information modeling, and digital twins, to improve the safety, efficiency, and sustainability of intelligent ships throughout their lifetime. The articles also address specific challenges in navigation safety, ship collision risk identification, ship identification in marine radars, collision risks between merchant and fishing vessels, situational awareness in inland waterways, ship trajectory prediction, oil spill detection, port terminal monitoring, and more. The authors of the articles have provided their contributions to the document. [Extracted from the article]

In addressing the high costs, inefficiencies, and limitations of purely digital simulations in maritime trials for unmanned vessel path planning, this paper introduces a ship virtual path planning simulation test system. This system, unbound by temporal and spatial constraints, vividly showcases the navigational performance of vessels. After analyzing the virtual testing requirements for the autonomous navigation performance of unmanned surface vehicles (USVs), we established the overall framework of this system. Data-driven by a numerical simulation platform, the system achieves synchronized operation between physical and virtual platforms and supports interactive path planning simulations between USVs and the virtual testing system. Furthermore, to address the limitations of traditional ship trajectory planning evaluation, this paper develops a global path planning fitness evaluation function that comprehensively considers trajectory safety, navigation distance, and vessel stability, achieving optimal comprehensive routes through the particle swarm optimization algorithm. Test results indicate an average roll reduction of 14.31% in the planned routes, with a slight increase in navigation distance. By integrating two-dimensional curve simulation with three-dimensional visualization, this paper not only overcomes the limitations of purely physical and purely virtual simulations but also enhances the overall credibility and intuitiveness of the simulation. Experimental results validate the system's effectiveness, providing a novel method for autonomous navigation testing and evaluation of USVs. [ABSTRACT FROM AUTHOR]

Losses in irrigation canals occur during the process of water transportation. In irrigation conveyance water losses, seepage loss is the main contributor to total water loss. The most problematic factors are cracks and settlement of the lined canal in canal lining structures. Water loss occurs in earth channels, mainly due to erosion and the permeability of the material. The concrete, as it does not present cracks, will have a less impermeable layer. Usually, seepage loss comprises 20–30% of the total water loss, and it can be reduced to 15–20% with canal linings. By enhancing the flexure and split tensile strength of concrete, the rate of cracking in the canal lining can be controlled. Concrete's split tensile strength is one of the most important factors in crack control. The behavior (compressive, flexural, and split tensile properties, water absorption, linear shrinkage mass loss, etc.) of hybrid polypropylene and jute fiber-reinforced concrete (HPJF-RC) for the application of canal linings was studied. In this experimental work, a total of nine mixes were made with different lengths and contents of hybrid polypropylene and jute fiber-reinforced concrete (HPJF-RC) and a control mix. The SEM analysis was performed to explore the hybrid fiber cracking mechanism and the bonding of fibers with the concrete. The crack arresting mechanism of the HPJF-RC will help to reduce water losses in concrete canal linings. With this modern material, the water losses in canal linings can be minimized. The results of this experimental work would be helpful as a reference for both industry experts and academic researchers interested in the advancement of HPJF-RC composites. [ABSTRACT FROM AUTHOR]

Computer vision (CV) techniques have been widely studied and applied in the shipping industry and maritime research. The existing literature has primarily focused on enhancing image recognition accuracy and precision for water surface targets by refining CV models themselves. This paper introduces innovative methods to further improve the accuracy of detection and recognition using CV models, including using ensemble learning and integrating shipping domain knowledge. Additionally, we present a novel application of CV techniques in the maritime domain, expanding the research perspective beyond the traditional focus on the accurate detection and recognition of water surface targets. Specifically, a novel solution integrating a CV model and the transfer learning method is proposed in this paper to address the challenge of relatively low-speed and high-charge internet services on ocean-going vessels, aiming to improve the online video viewing experience while conserving network resources. This paper is of importance for advancing further research and application of CV techniques in the shipping industry. [ABSTRACT FROM AUTHOR]

Sail-assisted propulsion is an important energy-saving technology in the shipping industry, and the development of foldable wingsails has recently become a hot topic. This type of sail is usually composed of multiple elements, and its performance at different folding configurations is very sensitive to changes in incoming airflow, which result in practical operational challenges. Therefore, original and optimized three-element wingsails (bare and concave) are modeled and simulated using the unsteady RANS method with the k-ω SST turbulence model. Next, certain key design and structural parameters (such as angle of attack, apparent wind angle, and camber) are employed to characterize the auxiliary propulsion performance, and the differences are explained in combination with the flow field details. The results show that, in the unfolded state, the aerodynamic performance of the concave wingsail is better than that of the bare wingsail, exhibiting higher lift coefficients, lower drag coefficients, and a more stable surface flow. In the fully folded state, wherein both the nose and flap are rotated, the thrust performance of the concave wingsail remains superior. Specifically, at an angle of attack of 8 degrees, the thrust coefficient of the concave wingsail is approximately 23.5% higher than that of the bare wingsail, indicating improved wind energy utilization. The research results are of great significance for engineering applications and subsequent optimization design. [ABSTRACT FROM AUTHOR]

In complex maritime scenarios where the grayscale polarity of ships is unknown, existing infrared ship detection methods may struggle to accurately detect ships among significant interference. To address this issue, this paper first proposes an infrared image smoothing method composed of Grayscale Morphological Reconstruction (GMR) and a Relative Total Variation (RTV). Additionally, a detection method considering the grayscale uniformity of ships and integrating shape and spatiotemporal features is established for detecting bright and dark ships in complex maritime scenarios. Initially, the input infrared images undergo opening (closing)-based GMR to preserve dark (bright) blobs with the opposite suppressed, followed by smoothing the image with the relative total variation model to reduce clutter and enhance the contrast of the ship. Subsequently, Maximally Stable Extremal Regions (MSER) are extracted from the smoothed image as candidate targets, and the results from the bright and dark channels are merged. Shape features are then utilized to eliminate clutter interference, yielding single-frame detection results. Finally, leveraging the stability of ships and the fluctuation of clutter, true targets are preserved through a multi-frame matching strategy. Experimental results demonstrate that the proposed method outperforms ITDBE, MRMF, and TFMSER in seven image sequences, achieving accurate and effective detection of both bright and dark polarity ship targets. [ABSTRACT FROM AUTHOR]

After the decline of water transportation along the Grand Canal, the integration of urban development and the preservation of cultural heritage along the canal has become imperative. This paper takes the titled landscape as its research perspective and investigates the cultural significance of the canal through its historical, spatial, artistic, and spiritual dimensions, identifying the "Ten Canal Scenes" (TCS) that encapsulate both the canal's heritage and the unique characteristics of Hangzhou, with the aim of establishing notable urban cultural landmarks. Archival analysis, average nearest neighbor (ANN) analysis, nuclear density analysis, and clustering of resource sites are first used to identify cultural landscape features. Evaluation and decision-making techniques are then used to comprehensively assess and categorize the conservation and utilization value for the TCS based on the value evaluation framework. Finally, it proposes strategies for enhancing the comprehensive values of titled landscapes and addressing socio-economic and cultural dimensions. These efforts seek to reconcile the preservation of the canal's cultural heritage with the ongoing regeneration and development of the city and propose references for a localized canal development model based on titled landscapes. [ABSTRACT FROM AUTHOR]

The logistics transportation system is critical to the United States economy. Underground Logistics Transportation (ULT) is a class of automated transportation systems in which vehicles carry freight through pipelines and tunnels between terminals. Being able to use a part of the underground space of existing highways will greatly facilitate the construction of such pipelines and tunnels and reduce their construction costs. Underground Logistics Transportation (ULT) could be the answer to make freight transport more sustainable and competitive. Texas highways and railroads are expected to increase by nearly 207% from 2003 to 2030. Truck tonnage will grow by 251%, while rail tonnage is forecasted to increase 118%. The number of trucks carrying NAFTA goods will increase by 263%, and the number of rail units will grow by 195%. This will have a profound impact on the highway and rail systems. The objective of this paper is to present requirements and operational components for three types of ULT lines: standard shipping containers, a standard crate size, and a standard pallet size. This study examines the use of ULT as a mode of underground transportation with the help of three case studies. This research shows that ULT is financially viable, feasible, greener, cost effective, and can become an important part of intermodal freight mobility. [ABSTRACT FROM AUTHOR]

Providing electrical power to ships while they are docked, cold ironing allows ships to turn off their engines and reduces emissions of air pollutants and greenhouse gases. This study identifies and assesses ship and port emissions and analyzes the potential for emission reduction achievable by cold ironing in European ports. It includes (1) a review of the current state of cold ironing in European ports; (2) an analysis of the time spent in ports by ships; (3) a quantification of emissions potentially avoided by means of a larger-scale use of cold ironing in Europe; (4) an estimation of the benefits achievable and the perspective to play a role in meeting emission reduction targets, improving air quality in port cities; (5) an analysis of the challenges and limitations of larger-scale cold ironing implementation; (6) potential solutions to overcome them. The results of this study could have important implications for (a) the shipping industry, which could benefit from the need for additional standardized electrical equipment onboard; (b) port authorities, which could benefit from providing additional services to the ships; (c) policymakers working to reduce emissions and promote energy efficiency, who could better approach their local and global targets. [ABSTRACT FROM AUTHOR]

Jinan City in China is known for its abundant spring water, and the protection of underground spring water transport channels is a key issue that needs to be paid attention to in Jinan subway construction. In areas where underground spring water transport channels are easily disturbed, when the shield tunnel passes through a composite formation with a permeable layer in the middle and an impermeable layer in the upper and lower parts, the underground spring water transportation channel is blocked, the spring veins are damaged, and the underground spring water is blocked in the upstream, resulting in an increase in the water pressure difference on both sides of the tunnel. In this paper, based on the working principle of a new type of pipe segment with a diversion function, a diversion function pipe model test box is designed and fabricated. Using this model box, the working state of the diversion function pipe segments is simulated. An earth pressure box and pore water pressure gauges are embedded in the model box to measure the earth pressure and pore pressure around the pipe under seepage unsymmetrical pressure. Strain gauges are attached in a circular shape on the inner side of the pipe to measure and calculate the strain and stress of the pipe. Through model tests, the effective repair of the diversion pipe on blocking groundwater flow and the relief effect of the unsymmetrical pressure of the pipe are verified. [ABSTRACT FROM AUTHOR]

The development of a country is affected by various multifaceted factors, which are likely to generate the highest benefits. For example, developing water resources by constructing embankments to store water and for transportation must consider high resilience, particularly with the current challenges arising from climate change. Another factor that must be considered is the shortage of essential materials for embankment cores, such as clay, which is the primary material for constructing such cores. This study aims to analyze the stability of soil embankments between the change of materials, namely clay and asphaltic concrete, by varying the water level and increasing the embankment load. The result shows that the asphaltic concrete core exhibits a significantly higher stability than the clay core, such as its reduced water seepage and lower deformation. In the worst-case scenario, the asphalt concrete core has a thickness of 0.3 m and a seepage rate of 15.1 × 10−4 m3/day. Comparatively, the seepage rate of the clay core is approximately 10-times lower. [ABSTRACT FROM AUTHOR]

The current research investigates the effects of materials and riblets on cavitation-induced erosion morphology, depth, and cross-sectional area through experimental approaches. To achieve these aims, the erosion of pure aluminum (1xxxAl or Al) and alpha brass (CuZn37 or CZ108), in the presence and absence of bio-inspired sawtooth riblets, was examined after exposure to multiple collapses of single cavitation bubbles with a wall distance of 1.8 (dimensionless). The results indicate that the erosion morphology resembles a rounded cone with a circular cross-section. Brass provides 21.6% more erosion resistance compared to that of Al in terms of material properties. Furthermore, the erosion for both Al (depth by 3.8% and width by 18.3%) and brass (depth by 7.9% and width by 27.4%) decreases in the presence of riblets compared to the results for flat surfaces. The greater erosion resistance of brass compared to Al is attributed to the superior mechanical stability of brass, making it a potentially suitable alloy for use in propellers and hulls in the shipping industry. In summary, the results reveal that riblet-equipped materials with high mechanical durability are promising erosion-resistant materials for the shipping industry. However, the potential for chemical reactions in a cathodic environment should be addressed to provide a comprehensive perspective in regards to reducing corrosion intensity. [ABSTRACT FROM AUTHOR]

A large amount of cargo is transported between European and Southeast Asian countries. Ships sometimes take different routes when sailing between ports due to the best commercial speed; navigational, economical, and hydrometeorological conditions; and political and military situations. Several routes are available for sailing between Europe and Southeast Asia: sailing the Suez Canal, sailing around the African continent, sailing the Panama Canal, as well as sailing the Northern Sea route. This article analyzes the possible sailing routes between Southeast Asia and Europe and presents a developed methodology for the evaluation of sailing routes. This sea route evaluation methodology is based on a comparative mathematical model that evaluates the main factors of cargo transportation by sea: transportation cost and time, possible maximum ship parameters, transportation energy (fuel) demand, and other possible factors, such as the probability of various restrictions. This paper presents a case study of cargo transportation between Rotterdam (The Netherlands) and Shanghai (China) using different possible sea routes. Assessments of various possible routes are presented; the main topics of discussion and conclusions are formulated. [ABSTRACT FROM AUTHOR]

As part of the strategy to achieve net-zero Greenhouse Gas (GHG) emissions in international maritime shipping, there is ongoing exploration into the use of wind propulsion systems as auxiliary ship propulsion devices. When considering a rigid sail as the wind propulsion system, evaluating the performance of a single sail is relatively simple. However, assessing the performance of multiple sails is more challenging due to the interference between the sails and between the sails and the hull. In this study, the thrust characteristics of two rigid sails attached to a ship are investigated by using Computational Fluid Dynamics (CFD). This includes considering the interference effects between the sails themselves and between the sails and the hull. The research reveals the innovative optimized angle of attack for maximizing thrust under tailwind conditions. At 150° in relative wind direction, the best performance is achieved with a low angle of attack on the fore side sail and a high angle of attack on the aft side sail. At 180° in relative wind direction, a high angle of attack on the fore side sail and a low angle of attack on the aft side sail yield the best results. Here, a "low" angle of attack means that the lift force is greater than the drag force, while a "high" angle of attack means the drag force is greater than the lift force. In this study, the force in the ship's forward direction is only focused on optimizing the angles of attack of the two sails. However, the side forces caused by the sails are also significant for the ship's sailing conditions. Therefore, future work will involve optimizing the angles of attack under drifting conditions. [ABSTRACT FROM AUTHOR]

Day after day, stricter environmental regulations and rising operating costs and fuel prices are forcing the shipping industry to find more effective ways of designing and operating energy-efficient ships. One of the ways to produce electricity efficiently is to create a waste heat-driven liquid metal–water binary vapor power plant. The liquid metal Rankine cycle systems could be considered topping cycles. Liquid metal binary cycles share characteristics like those of the steam Rankine power plants. They have the potential for high conversion efficiency, they will likely produce lower-cost power in plants of large capacity rather than small, and they will operate more efficiently at design capacity rather than at partial load. As a result, liquid metal topping cycles may find application primarily as base-load plants onboard ships. In this study, a waste heat-driven liquid metal–water binary vapor power plant onboard a ship is designed and thermodynamically analyzed. The waste heat onboard the vessel is the exhaust gas of the LM2500 marine gas turbine. Mercury and Cesium are selected as liquid metals in the topping cycle, while water is used in the bottoming cycle in binary power plants. Engineering Equation Solver (EES) software (V11.898) is used to perform analyses. For the turbine inlet temperature of 550 °C, while the total net work output of the binary cycle system is calculated to be 104.84 kJ/kg liquid metal and 1740.29 kJ/kg liquid metal for mercury and cesium, respectively, the efficiency of the binary cycle system is calculated to be 31.9% and 26.3% for mercury and cesium as liquid metal, respectively. This study shows that the binary cycle has a thermal efficiency of 26.32% and 31.91% for cesium and mercury, respectively, depending on liquid metal condensing pressure, and a binary cycle thermal efficiency of 25.9% and 30.9% for cesium and mercury, respectively, depending on liquid metal turbine inlet temperature, and these are possible with marine engine waste heat-driven liquid metal–water binary vapor cycles. [ABSTRACT FROM AUTHOR]

Ship path planning is the core problem of autonomous driving of smart ships and the basis for avoiding obstacles and other ships reasonably. To achieve this goal, this study improved the traditional A* algorithm to propose a new method for ship collision avoidance path planning by combining the multi-target point artificial potential field algorithm (MPAPF). The global planning path was smoothed and segmented into multi-target sequence points with the help of an improved A* algorithm and fewer turning nodes. The improved APF algorithm was used to plan the path of multi-target points locally, and the ship motion constraints were considered to generate a path that was more in line with the ship kinematics. In addition, this method also considered the collision avoidance situation when ships meet, carried out collision avoidance operations according to the International Regulations for Preventing Collisions at Sea (COLREGs), and introduced the collision risk index (CRI) to evaluate the collision risk and obtain a safe and reliable path. Through the simulation of a static environment and ship encounter, the experimental results show that the proposed method not only has good performance in a static environment but can also generate a safe path to avoid collision in more complex encounter scenarios. [ABSTRACT FROM AUTHOR]

In scenarios such as nearshore and inland waterways, the ship spots in a marine radar are easily confused with reefs and shorelines, leading to difficulties in ship identification. In such settings, the conventional ARPA method based on fractal detection and filter tracking performs relatively poorly. To accurately identify radar targets in such scenarios, a novel algorithm, namely YOSMR, based on the deep convolutional network, is proposed. The YOSMR uses the MobileNetV3(Large) network to extract ship imaging data of diverse depths and acquire feature data of various ships. Meanwhile, taking into account the issue of feature suppression for small-scale targets in algorithms composed of deep convolutional networks, the feature fusion module known as PANet has been subject to a lightweight reconstruction leveraging depthwise separable convolutions to enhance the extraction of salient features for small-scale ships while reducing model parameters and computational complexity to mitigate overfitting problems. To enhance the scale invariance of convolutional features, the feature extraction backbone is followed by an SPP module, which employs a design of four max-pooling constructs to preserve the prominent ship features within the feature representations. In the prediction head, the Cluster-NMS method and α-DIoU function are used to optimize non-maximum suppression (NMS) and positioning loss of prediction boxes, improving the accuracy and convergence speed of the algorithm. The experiments showed that the recall, accuracy, and precision of YOSMR reached 0.9308, 0.9204, and 0.9215, respectively. The identification efficacy of this algorithm exceeds that of various YOLO algorithms and other lightweight algorithms. In addition, the parameter size and calculational consumption were controlled to only 12.4 M and 8.63 G, respectively, exhibiting an 80.18% and 86.9% decrease compared to the standard YOLO model. As a result, the YOSMR displays a substantial advantage in terms of convolutional computation. Hence, the algorithm achieves an accurate identification of ships with different trail features and various scenes in marine radar images, especially in different interference and extreme scenarios, showing good robustness and applicability. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Ports play an important role in maintaining the effectiveness of maritime logistics. When ports encounter congestion, strikes, or natural disasters, the maritime container transportation network might be significantly affected. The Beibu Gulf sea area is a key channel to supporting China's participation in international economic cooperation in the western region. It is highly susceptible to the influence of the political and economic instability. This study introduces a dual-component framework to analyze the inherent structure and potential vulnerabilities of the container transportation network in the Beibu Gulf Sea areas. The findings show that the core layer of the network exhibited circular solidification characteristics. The entire network heavily relies on some core ports, such as Haiphong Port, Ho Chi Minh Port, and Qinzhou Port, and it highlights the potential increases in vulnerability. The finding shows that deliberate attacks have a greater impact than random attacks on the normal operations of maritime networks. If ports with high intermediary centrality are attacked, the connectivity and transportation efficiency of the Beibu Gulf maritime network will be significantly affected. However, under such circumstances, redistributing cargo transportation through route adjustments can deal with the transmission of cascading failures and maintain the network's resilience. Based on the existing knowledge and the data collected in a case study, this research stands out as the first to provide a critical examination of the spatial structure and vulnerability of container shipping networks in the Beibu Gulf sea. [ABSTRACT FROM AUTHOR]

As global maritime cargo transportation intensifies, managing CO2 emissions from ships becomes increasingly crucial. This article explores optimizing bulk carrier fleets for transporting polymetallic nodules (PMNs) from the Clarion-Clipperton Zone (CCZ) to reduce CO2 emissions. Our analysis shows that larger bulk carriers, despite greater drifting forces from environmental conditions, emit less CO2 over the entire transport mission, including loading and transit. Deploying large ships in global maritime trade could significantly reduce CO2 emissions. This study also introduces a novel artificial neural network (ANN) model to estimate drifting forces during loading operations and proposes a new method for estimating CO2 emissions, considering environmental conditions and ship seakeeping properties. These findings highlight the importance of fleet size optimization and effective operational planning in achieving environmental sustainability in maritime transport. [ABSTRACT FROM AUTHOR]

Surface runoff flows must be drained safely through culverts in ephemeral flow streams and bridges in perennial streams without any damage to the road or highway infrastructure stability. In practice, bridges cross drainage basin channels reliably, and they are more carefully planned, designed, constructed, and maintained against extreme water passages, but culverts are subject to even less frequent and intensive rainfall consequent surface runoff occurrences with higher risk potential. It is, therefore, necessary to design culverts more carefully in such a way that they drain down the upstream surface water without any critical problem to the road downstream of the road stream channels. Most of the hydrological, hydraulic, and sedimentological formulations are empirical expressions that are widely valid for locations where culverts are suitably developed based on simple bivalent logical rules between factors involved in upstream inlet locations of culverts. One of the first logic rule-based methods in the literature is Talbot's procedural approach to culvert design. This approach is based not only on an explicit equation, but also on a set of linguistically proposed design rules that are expressed deterministically to effectively eliminate most of the ambiguities. This paper proposes a modified approach with additional logistic structural features based on a bivalent logic inference system, which is an improved version of the Talbot procedure and leads to better culvert transition surface flow prediction. The proposed method is applied to a local area in Tekirdağ City, Türkiye, where a serious train accident occurred due to a poorly maintained culvert. [ABSTRACT FROM AUTHOR]

Fast and accurate ship target detection technology plays an important role in improving driving safety, rescue at sea, marine environmental protection, and sea traffic control. It is also one of the key technologies for the development of ship informatization and intelligence. However, the current ship target detection models used at different scales in multiple scenarios exhibit high complexity and slow inference speed. The trade-off between model detection speed and accuracy limits the deployment of ship target detection models on edge devices. This study proposes a lightweight multi-scale ship target detection model based on the Yolov5s model. In the proposed model, the lightweight EfficientnetV2 and C3Ghost networks are integrated into the backbone and neck networks of the Yolov5s model to compress the computational and parametric quantities of the model and improve the detection speed. The Shuffle Attention mechanism is embedded in the neck network component of the model to enhance the representation of important feature information, suppress irrelevant feature information, and improve the model's detection performance. The improved method is trained and verified on the dataset collected and labeled by the authors. Compared with the baseline model, the inference speed of the proposed model increased by 29.58%, mAP0.5 improved by 0.1%, and the parameters and floating-point operations decreased by 42.82% and 68.35%, respectively. The file size of the model is 8.02MB, which is 41.46% lower than the baseline model. Compared with other lightweight models, the method proposed in this study is more favored in edge computing. [ABSTRACT FROM AUTHOR]

Growing environmental concerns have prompted the shipping industry to adopt stringent measures to address greenhouse gas emissions, with fuel-powered ships being the primary source of such emissions. Additionally, alternative forms of ship propulsion, such as internal combustion engine hybridization, low-carbon fuels, and zero-carbon fuels, face significant challenges either in terms of cost or emission-reduction capability at present. In order to decarbonize navigation, countries are focusing the maritime industry's transition towards low-carbon alternatives on transforming energy consumption, with widespread attention on the electrification of ships. Therefore, this paper provides a comprehensive review of the feasibility of fully electrifying ships, covering aspects such as technological prospects, economic viability, and emission-reduction capabilities. Firstly, the current state of research on ship electrification technology is summarized; the applicability of different battery types to electric ship technology is compared. Subsequently, the economic viability and emission-reduction capabilities of five different electric ship lifecycles are discussed separately. The results indicate that ship electrification is a key pathway to achieving zero-emission shipping, with lithium-ion batteries being the most suitable battery technology for maritime use currently. Short-to-medium-range electric ship types have demonstrated economic advantages over traditional diesel ships. As battery costs continue to decline and energy density keeps improving, the economic feasibility of ship electrification is expected to expand. [ABSTRACT FROM AUTHOR]

Sloshing of liquefied bulk granular cargoes weakens the stability of cargo carriers when at sea. Using the horizontal rectangle baffle is a promising way to restrain its sloshing motion. But the location height and optimal baffle area rate to achieve a better anti-sloshing effect should be studied first. The discrete element method was adopted to establish the simulation model, and the direct shear test was used for verification. Through the static tilt tests, the definite relationship between the effects of moisture content on cargo motion and particle friction coefficients was acquired. Then, liquefied cargo motion in a cargo hold without baffles and with one and two pairs of horizontal baffles was simulated. Based on variations in the cargo gravity center offset and the sloshing-induced force on the cargo hold, the anti-sloshing effect of different settings of the baffles was compared. Results show that the baffles have the ability to restrain cargo sloshing, and this is important for sea transportation safety. The anti-sloshing effect is better when the baffle plane is right on the cargo top surface compared to the other location heights. Further, there is an optimal length–width combination, e.g., a single baffle plane with a length of 0.26 L and a width of 0.46 B, at which a better anti-sloshing effect could be achieved with the smallest baffle area rate. This study could be useful for the practical application of horizontal baffles for bulk granular cargo carriers. [ABSTRACT FROM AUTHOR]