Search Results (297)

Maritime transport plays a pivotal role in global trade, where efficiency and accuracy in port operations are crucial. Among the various tasks carried out in ports, container code recognition is essential for tracking and handling cargo. Manual inspections of container codes are becoming increasingly impractical, as they induce delays and raise the risk of human error. To address these issues, this work proposes a hybrid Optical Character Recognition system that integrates YOLOv7 for text detection with the transformer-based TrOCR for recognition of the container codes, enabling accurate and efficient automated recognition. This design addresses the real-world challenges, such as varying light, distortions, and multi-orientation of container codes. To evaluate the system, we conducted a comprehensive evaluation on datasets that simulate the conditions found in port environments. The results demonstrate that the proposed hybrid model delivers significant improvements in detection and recognition accuracy and robustness compared to traditional OCR methods. In particular, the reliability in recognizing multi-oriented codes marks a notable advancement compared to existing solutions. Overall, this study presents an approach to automating container code recognition, contributing to the efficiency and modernization of port operations, with the potential to streamline port operations, reduce human error, and enhance the overall logistics workflow. Full article

Maritime transportation plays a vital role in international trade and commerce, with ports serving as critical points of connection between land and sea transportation systems. The operational efficiency of port facilities is essential to ensure the uninterrupted flow of goods and services, making port safety a top priority for governments, authorities, and shipping companies. Due to the importance of Occupational Health and Safety (OHS) within port environments, it is crucial to develop a structured framework in order to collect and analyze port accidents data. Today there are several different national agencies, private organizations, and/or local regulatory bodies taking charge of these data over different areas, each with variations in how they document and classify the events; in addition these are frequently limited to only major disasters and/or summary statistics. This paper aims to create a general framework to collect and fuse open-source port accident data from different sources in a structured way and to analyze the safety conditions of port facilities by conducting a comparative evaluation based on design of experiment (DoE). Through this analysis, we identify common causes of accidents and injuries in port facilities, as well as any differences in safety conditions across regions, types of port facilities, and other relevant factors. This information can be used to inform policies and practices aimed at improving port safety, reducing accidents and injuries, and ultimately enhancing the efficiency and sustainability of maritime transportation systems. The motivation to develop this research relies on the necessity to define requirements for the development of innovative solutions to be developed by the authors using modeling and simulation (M&S) and XR (extended reality) in order to increase safety in these contexts. Full article

With the development of global maritime trade, ship emissions pose an increasing threat to the global atmospheric environment, especially in international navigation waters and important port areas, where their impact on coastal air quality and ecosystems is becoming increasingly significant. This study proposes a high-throughput gridding algorithm (H-Grid) based on spatial hashing to rapidly generate ship emission inventories, which overcomes the inefficiency of traditional methods caused by complex index building and maintenance. The H-Grid algorithm achieves a constant processing time per data point and possesses inherent parallelism. Based on the H-Grid algorithm, taking the Yellow Sea area between China and Republic of Korea as a case study, the emissions of atmospheric pollutants from ships in 2024 were calculated, and their spatiotemporal distribution characteristics were analyzed. In our empirical study, the algorithm’s computational efficiency for processing millions of AIS records was improved by over 10 times compared to traditional geometric calculations, and by more than 4 times when compared to mainstream database spatial queries. Our findings provide an efficient tool for large-scale maritime emission analysis, strongly supporting the green development of global shipping. Full article

Global shipping is an essential, energy-efficient enabler of trade, yet it remains a hard-to-abate sector. With shipping demand projected to continue to rise in the coming decades, identifying scalable and sustainable fuel alternatives is critical. Biofuels, and particularly biomethanol, offer a promising option due to their compatibility with existing infrastructure. However, their sustainability critically hinges on land use impacts. From this Perspective, we argue that biomethanol derived from a dedicated crop could contribute to maritime decarbonisation, with ~71–77% well-to-wake greenhouse gases (GHG) reductions under cropland-only constraints. We further point to the fact that a wider adoption faces challenges such as higher costs, limited availability, and lower energy density relative to fossil fuels. Continued research and monitoring are essential to ensure that biofuel production does not inadvertently contribute to deforestation or biodiversity loss. We underscore the need for spatially sensitive biofuel deployment strategies that align maritime decarbonisation with land-system sustainability and climate objectives. Full article

Amid the urgent demands for global trade transformation and zero-carbon transition, sustainable maritime supply chains face challenges of high costs and complex coordination, necessitating the elimination of “isolated decision-making” to achieve sustainable development goals. This study constructs a profit analysis model under centralized and decentralized decision-making scenarios and various intelligent omni-channel models, exploring the profit composition, optimal pricing, and operational strategies of carriers and forwarders. Case analysis validates that collaborative optimization, particularly when forwarders leverage online channels and customer proximity, enables sustainable maritime transport and significantly enhances overall profits and efficiency in sustainable maritime supply chains. This research provides a theoretical and practical framework for collaborative optimization strategies contributing to sustainable maritime transport and port intelligence in marine engineering contexts. By this framework, it will be possible to advance green transformation, smart operations management, and digital innovation in the global maritime and marine industries. Full article

The Belt and Road Initiative (BRI) has reshaped global trade and infrastructure, with port cities as key nodes in its Maritime Silk Road. Quantifying their spatiotemporal development is challenging due to data limitations in emerging economies. This study employs VIIRS nighttime light (NTL) data from 2013 to 2023 to analyze urbanization patterns in twelve BRI port cities spanning Asia, Africa, Europe, and South America. We compile a 12-city cohort; inferential analyses are conducted for a pre-specified six-city subset, while descriptive NTL trends cover all 12. This study makes three contributions: (i) we assemble a cross-sensor harmonized VIIRS NTL record for 12 BRI port cities during 2013–2023; (ii) we integrate Standard Deviational Ellipse(SDE) parameters with rank-size dynamics as a joint diagnostic of urban hierarchy; and (iii) we triangulate NTL with external indicators (GDP, population, port throughput) to validate interpretation. Three key findings emerge: Asian ports experienced pronounced NTL growth, with Singapore approaching saturation, consistent with the luminosity-ceiling hypothesis; SDE analysis shows varied expansion patterns shaped by geophysical and policy factors; and rank-size trends indicate decentralization during the BRI decade, with |q| declining in most cities, challenging the primate-city model. To optimize development, we highlight polycentric infrastructure investment, institutionalized NTL monitoring, and green port certification aligned with sustainability goals. Full article

Modern ports are pivotal to global trade, facing increasing pressures from operational demands, resource optimization complexities, and urgent decarbonization needs. This study highlights the critical importance of digital model adoption within the maritime industry, particularly in the port sector, while integrating sustainability principles. Despite a growing body of research on digital models, industrial simulation, and green transition, a specific gap persists regarding the intersection of port management, hydrogen energy integration, and Digital Twin (DT) applications. Specifically, a bibliometric analysis provides an overview of the current research landscape through a study of the most used keywords, while the document analysis highlights three primary areas of advancement: optimization of hydrogen storage and integrated energy systems, hydrogen use in propulsion and auxiliary engines, and DT for management and validation in maritime operations. The main outcome of this research work is that while significant individual advancements have been made across critical domains such as optimizing hydrogen systems, enhancing engine performance, and developing robust DT applications for smart ports, a major challenge persists due to the limited simultaneous and integrated exploration of them. This gap notably limits the realization of their full combined benefits for green ports. By mapping current research and proposing interdisciplinary directions, this work contributes to the scientific debate on future port development, underscoring the need for integrated approaches that simultaneously address technological, environmental, and operational dimensions. Full article

With the rapid increase in global trade in recent years, the demand for maritime transportation has significantly intensified vessel activity, leading to a considerable rise in carbon emissions originating from the maritime sector. As a result, in line with the 2050 decarbonization targets set by the International Maritime Organization (IMO) and the European Union (EU), legal regulations addressing carbon emissions have been dynamically tightened and gradually enacted. This study aims to determine the significance levels of the factors affecting the maritime sector in response to carbon emission regulations and to reveal the interrelationships among these factors. In this context, the criteria regarding the impacts of climate-related carbon emission regulations were identified based on expert opinions using the Fuzzy Delphi method. The interaction strengths and significance levels among the factors were analyzed using the Fuzzy DEMATEL method, and the relationships were modeled through Interpretive Structural Modeling (ISM). According to the findings, “Fuel Preferences and Alternative Fuel Usage” (C2) emerged as the most critical factor under recent international regulations. “Adaptation to International and National Regulations” (C8) and “Port Infrastructure” (C3) were also identified as the key factors impacting shipping industry efficiency. The analysis revealed that “Logistics Costs” (C5) and “Environmental Protection and Sustainability” (C7) are the most significantly affected outcome factors within the system. The hierarchical structural modeling revealed that “Port Infrastructure” (C3) serves as a defining starting point within the system. This study contributes to the literature by uncovering the causal relationships among the factors determining the effectiveness of ever-evolving carbon emission regulations. It offers a valuable decision-support tool for maritime companies and policymakers. Accordingly, it provides an alternative roadmap and a structural model indicating which strategic areas should be prioritized to achieve the targeted low-carbon emission goals in maritime transportation. Full article

Decarbonising aquaculture support vessels is pivotal to reducing greenhouse gas (GHG) emissions across both the aquaculture and maritime sectors. This study evaluates the technical and economic feasibility of deploying hydrogen as a marine fuel for a 14.95 m net cleaning vessel (NCV) operating in Tasmania, Australia. The analysis retains the vessel’s original layout and subdivision to enable a like-for-like comparison between conventional diesel and hydrogen-based systems. Two options are evaluated: (i) replacing both the main propulsion engines and auxiliary generator sets with hydrogen-based systems—either proton exchange membrane fuel cells (PEMFCs) or internal combustion engines (ICEs); and (ii) replacing only the diesel generator sets with hydrogen power systems. The assessment covers system sizing, onboard hydrogen storage integration, operational constraints, lifecycle cost, and GHG abatement. Option (i) is constrained by the sizes and weights of PEMFC systems and hydrogen-fuelled ICEs, rendering full conversion unfeasible within current spatial and technological limits. Option (ii) is technically feasible: sixteen 700 bar cylinders (131.2 kg H₂ total) meet one day of onboard power demand for net-cleaning operations, with bunkering via swap-and-go skids at the berth. The annualised total cost of ownership for the PEMFC systems is 1.98 times that of diesel generator sets, while enabling annual CO₂ reductions of 433 t. The findings provide a practical decarbonisation pathway for small- to medium-sized service vessels in niche maritime sectors such as aquaculture, while clarifying near-term trade-offs between cost and emissions. Full article

Hydrogen fuel presents a promising pathway for achieving long-term decarbonization in the maritime sector. However, its use in diesel engines introduces challenges due to high reactivity, leading to increased NOx emissions and combustion instability. The aim of this study is to identify settings so that the investigated engine operates with 60% hydrogen energy fraction at high load through CFD modelling. The model is utilized to simulate a four-stroke, 10.5 MW marine engine at 90% load, incorporating 60% hydrogen injection by energy at the engine intake port. The CFD model is verified using experimental data from diesel operation of the marine engine and hydrogen operation of a light-duty engine. The engine performance was determined and detailed emissions analysis was conducted, including NO, NO₂, HO₂, and OH. The findings indicate a substantial rise in NOx emissions as opposed to diesel operation, due to elevated combustion temperatures and increased residence time at elevated temperature of the mixture in-cylinder. The presence of HO₂ and OH highlights critical zones of combustion, which contribute to operational stability. The novelty of this study is supported by the examination of the high hydrogen energy fraction, the advanced emissions analysis, and the insights into the emissions–performance trade-offs in hydrogen-fueled dual-fuel marine engines. The results offer guidance for the development of sustainable hydrogen-based marine propulsion systems. Full article

Coastal upwelling off La Guajira, Colombia, is an atypical system where persistent easterly winds drive upwelling along a zonally oriented coastline. To characterize its seasonal cycle and variability, the ROMS AGRIF hydrodynamic model was implemented under climatological forcing. Three indicators were analyzed: the 25 °C isotherm, the 36.5 isohaline, and sea-level anomalies. The simulations showed that upwelling initiates in December, reaches maximum intensity during February–April, and weakens from September to November. At maturity, vertical velocities up to 8.5 m·day⁻¹ and the shoaling of Subtropical Underwater (T = 22–25 °C; S = 36.5–37.0) dominate the coastal domain, producing widespread surface cooling (23–24 °C) and salinity enhancement. During relaxation, weaker winds and the influence of the Caribbean Coastal Undercurrent displace the upwelled waters to below 80–100 m in depth, with surface temperatures above 27 °C. Model performance against MODIS Aqua SST was high (d > 0.99; RMSE < 1.7 °C), confirming its reliability to reproduce the observed thermal cycle. The multiparametric approach reveals that upwelling persistence depends on both seasonal trade wind forcing and regional circulation. This framework provides a more integrated description of the Guajira upwelling system than previous studies and supports applications in fisheries management, ecosystem monitoring, and maritime operations. Full article

Selecting an appropriate Multi-Criteria Decision-Making (MCDM) algorithm for optimizing marine diesel engine operation presents a complex challenge due to the diversity in mathematical formulations, normalization schemes, and trade-off resolutions across methods. This study systematically evaluates fourteen MCDM algorithms, which are grouped into five primary methodological categories: Scoring-Based, Distance-Based, Pairwise Comparison, Outranking, and Hybrid/Intelligent System-Based methods. The goal is to identify the most suitable algorithm for real-time performance optimization of two stroke marine diesel engines. Using Diesel-RK software, calibrated for marine diesel applications, simulations were performed on a variant of the MAN-B&W-S60-MC-C8-8 engine. A refined five-dimensional parameter space was constructed by systematically varying five key control variables: Start of Injection (SOI), Dwell Time, Fuel Mass Fraction, Fuel Rail Pressure, and Exhaust Valve Timing. A subset of 4454 high-potential alternatives was systematically evaluated according to three equally important criteria: Specific Fuel Consumption (SFC), Nitrogen Oxides (NO_x), and Particulate Matter (PM). The MCDM algorithms were evaluated based on ranking consistency and stability. Among them, Proximity Indexed Value (PIV), Integrated Simple Weighted Sum Product (WISP), and TriMetric Fusion (TMF) emerged as the most stable and consistently aligned with the overall consensus. These methods reliably identified optimal engine control strategies with minimal sensitivity to normalization, making them the most suitable candidates for integration into automated marine engine decision-support systems. The results underscore the importance of algorithm selection and provide a rigorous basis for establishing MCDM in emission-constrained maritime environments. This study is the first comprehensive, simulation-based evaluation of fourteen MCDM algorithms applied specifically to the optimization of two stroke marine diesel engines using Diesel-RK software. Full article

Crude oil and grain, as two pivotal global commodities, exhibit significant price co-movement that profoundly affects national economic stability and food security. From the perspective of systems theory, the energy and grain markets do not exist in isolation but rather form a highly coupled complex system, characterized by nonlinear feedback, cross-market risk contagion, and cascading effects. This study systematically investigates the transmission mechanisms from international crude oil prices to the domestic prices of Chinese four major grains, employing the DY spillover index, Vector Error Correction Model (VECM), and a mediation effect framework. The empirical findings reveal three key insights. First, rising international crude oil prices significantly strengthen the pass-through of global grain prices to domestic markets, while simultaneously weakening the effectiveness of domestic price stabilization policies. Second, higher crude oil prices amplify international-to-domestic price spillovers by increasing maritime freight costs, a key channel in global grain trade logistics. Third, elevated oil prices stimulate demand for renewable biofuels, including biodiesel and ethanol, thereby boosting international demand for corn and soybeans and intensifying the transmission of price fluctuations in these commodities to the domestic market. These findings reveal the key pathways through which shocks in the energy market affect food security and highlight the necessity of studying the “energy–food” coupling mechanism within a systems framework, enabling a more comprehensive understanding of cross-market risk transmission. Full article

Growing global supply chain uncertainties significantly threaten China’s forage import security. The evolving characteristics of the global forage trade network directly impact the stability of China’s supply. This study constructs a directed, weighted trade network based on global forage products trade data (2000–2024). Using complex network analysis methods, it systematically analyzes the network’s topological structure and evolutionary patterns, with a focus on their impact on China’s import security. The study addresses the following questions: What evolutionary patterns does the global forage trade network exhibit in terms of its topological structure? How does the evolution of this network impact the import security of forage products in China, specifically regarding supply chain stability and risk resilience? The research findings indicate the following: (1) From 2000 to 2024, the total volume of global forage products trade increased by 48.17%, primarily driven by forage products excluding alfalfa meal and pellets, which accounted for an average of 82.04% of volume annually. Additionally, the number of participating countries grew by 21.95%. (2) The global forage products trade network follows a power–law distribution, characterized by increasing network density, a clustering coefficient that initially declines and then rises, and a shortening of the average path length. (3) The core structure of the global forage products trade network shows an evolutionary trend of diffusion from core nodes in North America, Oceania, and Asia to multiple core nodes, including those in North America, Oceania, Europe, Africa, and Asia. (4) China’s forage products trade network displays distinct phase characteristics; however, imports face significant risks from high supply chain dependency and exposure to international price fluctuations. Based on these conclusions, it is recommended that China actively expands trade relations with potential product-exporting countries in Africa, encouraging enterprises to “go global.” Additionally, China should establish a three-dimensional supply chain security system, comprising maritime, land, and storage components, to enhance risk resistance and import safety. Full article

With the surge in global maritime trade of new energy vehicles (NEVs), the roll-on/roll-off (Ro-Ro) shipping market faces a severe supply–demand imbalance, pushing shipping rates to persistently high levels. To tackle this challenge, NEV manufacturers and other automakers have begun establishing their own Ro-Ro fleets, creating an urgent need for optimized operational scheduling of these proprietary fleets. Against this context, this study focuses on optimizing the operational scheduling of automakers’ self-owned Ro-Ro fleets. Under the premise of deterministic automobile export transportation demands, a mixed-integer programming model is developed to minimize total fleet operational costs, with decision variables covering vessel port call sequence/selection, port loading and unloading quantities, and voyage speeds. A genetic algorithm is designed to solve the model, and the effectiveness of the proposed approach is validated through a real-world case study. The results demonstrate that the optimization method generates clear, actionable scheduling schemes for self-owned Ro-Ro fleets, effectively helping automakers refine their maritime logistics strategies for proprietary fleets. This study contributes to the field by focusing on automaker-owned Ro-Ro fleets and filling the research gap in cargo-owner-centric scheduling, providing a practical tool for automakers’ overseas logistics operations. Full article