Search Results (53)

In the context of increasingly complex and dynamic maritime logistics, seaports serve as critical nodes for intermodal transport, energy distribution, and global trade. Ensuring the safe and uninterrupted operation of port infrastructure—particularly berths—is vital for maintaining supply chain resilience. This study explores the impact of multiple risk categories on berth efficiency in a seaport, aligning with the growing emphasis on maritime safety and risk-informed decision-making. A two-stage methodology is adopted. In the first phase, the DEA CCR input-oriented model is employed to assess the efficiency of selected berths considered as Decision Making Units (DMUs). In the second phase, the Analytical Hierarchy Process (AHP) is used to categorize and quantify the impact of four major risk classes—operational, technical, safety, and environmental—on berth efficiency. The results demonstrate that operational and safety risks contribute 63.91% of the composite weight in the AHP risk assessment hierarchy. These findings are highly relevant to contemporary efforts in maritime risk modeling, especially for individual ports and port systems with high berth utilization and vulnerability to system disruptions. The proposed integrated approach offers a scalable and replicable decision-support tool for port authorities, port operators, planners, and maritime safety stakeholders, enabling proactive risk mitigation, optimal utilization of available resources in a port, and improved berth performance. Its methodological design is appropriately suited to support further applications in port resilience frameworks and maritime safety strategies, being one of the bases for establishing collision avoidance strategies related to an individual port and/or port system, too. Full article

Autonomous ship berthing requires advanced path planning to balance multiple objectives, such as minimizing berthing time, reducing energy consumption, and ensuring safety under dynamic environmental constraints. However, traditional planning and learning methods often suffer from inefficient search or sparse rewards in such constrained and high-dimensional settings. This study introduces a double deep Q-network (DDQN)-guided dual-population constrained multi-objective evolutionary algorithm (CMOEA) framework for autonomous ship berthing. By integrating deep reinforcement learning (DRL) with CMOEA, the framework employs DDQN to dynamically guide operator selection, enhancing search efficiency and solution diversity. The designed reward function optimizes thrust, time, and heading accuracy while accounting for vessel kinematics, water currents, and obstacles. Simulations on the CSAD vessel model demonstrate that this framework outperforms baseline algorithms such as evolutionary multitasking constrained multi-objective optimization (EMCMO), DQN, Q-learning, and non-dominated sorting genetic algorithm II (NSGA-II), achieving superior efficiency and stability while maintaining the required berthing angle. The framework also exhibits strong adaptability across varying environmental conditions, making it a promising solution for autonomous ship berthing in port environments. Full article

This study aims to experimentally evaluate a personal comfort system based on a radiant panel (R-PCS) that can regulate the thermal environment of the sleep zone during summer, with a focus on improving both the thermal comfort and energy efficiency of this system. To investigate thermal comfort under the coupling effect of different covering conditions and operating parameters of the R-PCS, the changing pattern of thermal environment parameters in the berth area and human skin temperature are analyzed. Then, the Predicted Mean Vote (PMV) -Predicted Percent Dissatisfied (PPD) index is employed for assessing the thermal comfort of the human body and energy-saving efficiency of the system. The results show that this system can satisfy the thermal comfort requirements of the human body in the berth area. Meanwhile, the corresponding cooling energy consumption of the R-PCS is significantly lower than that of the traditional HVAC system, indicating that the developed system has significant energy-saving potential in building design. Full article

In some ports, there are separate very narrow places between the quays and other navigational obstacles, where the distance between the quays or between the quays and navigational obstacles is very small. Narrow gaps or channels in the water area, where quays are built and ships are berthing, make it difficult for ships to berth at such quays. Accurate knowledge of a ship’s manoeuvrability characteristics, combined with the application of these characteristics in berthing operations and the optimal use of tugboat capabilities, allows for better utilization of restricted port spaces. The article presents a developed ship berthing methodology designed for ship berthing in extremely limited conditions, utilizing the ship’s manoeuvrability capabilities and maximizing the capabilities of tugboats when mooring ships in extremely limited conditions. The developed methodology was tested with real ships and tugboats in specific port conditions and using calibrated simulators, and the results of the experimental research and theoretical calculations are presented in the article as a case study. The research results (methodology) obtained and presented in the article can be applied to any ships and ports, precisely adapting them to specific port situations. The article studies ship manoeuvrability and tugboat capabilities under various hydrometeorological and hydrological conditions, assesses the impact of shallow depths (shallowness), and determines the boundary conditions for ship berthing. Full article

On-board emission measurements were conducted at the exhaust of a passenger ship operating under real-world conditions. The chemical composition of exhaust particulate emissions from a turbocharged four-stroke marine diesel engine, operated on Marine Gas Oil was studied. A variety of organic compounds, including alkanes, alkenes, alcohols, cycloalkanes, cycloalkenes, esters, ketones, carboxylic acids, etc., were analyzed. Alkanes were the most abundant organic compounds, followed by alkenes, esters, and alcohols. Emission factors for these compounds were determined under two operating conditions: low engine load (at berth at 400 rpm/4% load, and during port maneuvers at 800 rpm/14% load) and high engine load (during cruising at 1000 rpm, 68% load). A clear increase in organic-compound emission factors was observed at lower loads. The total particulate matter emission factors were between 0.02 and 0.03 g/kWh at high-load points and exhibited significant variability under low-load conditions, from 0.02 to 2.83 g/kWh. The effect of a marine fuel additive was evaluated in this study. Using this fuel additive resulted in a significant decrease in both particulate matter and organic-compound emission factors, especially at low engine loads. Furthermore, the marine fuel additive decreased the total emission factors (${EF}_{TOCs}$) by a factor of 56 under low-load conditions. For high loads, the additive had no effect on the EF_TOCs. Full article

Ports are essential nodes in global trade, linking maritime and land transport. As maritime logistics increasingly drive global supply chains, optimizing port operations has become vital for enhancing economic efficiency and environmental sustainability. This study presents a Mixed Integer Linear Programming (MILP) model to address inefficiencies in berth allocation and stevedoring processes at the Port of Leixões, Portugal. By integrating real operational data, the model reduces vessel waiting times by 47.56% (from 8.1 to 4.2 h) and operational delays by 37.39% (from 11.5 to 7.2 h). These optimizations also result in a 41.85% reduction in greenhouse gas emissions per ship, aligning with global emissions regulations and promoting sustainable port management. The model’s innovations include real-time data integration and a holistic resource allocation approach to mitigate congestion and inefficiencies. Key findings demonstrate the model’s potential to streamline operations and minimize environmental impacts. These advancements align economic efficiency with environmental sustainability, addressing global emissions regulations. However, the study acknowledges limitations, such as excluding unpredictable factors like weather conditions and equipment failures. Future research should explore dynamic variables, such as weather conditions and mechanical failures, and expand the model’s applicability to other seaports worldwide. Full article

Research on autonomous ships has primarily focused on developing response technologies for navigation from pilot station to pilot station. This study developed an automatic berthing support program that calculates the necessary thruster output values for the bow and stern to achieve the desired berthing speed under varying external force conditions, requiring only essential ship information as input. The program determines the thruster output by analyzing the forces and moments acting on the hull during the berthing process. An experimental setup equipped with the automatic berthing support program was installed on a ship. The outputs of the bow thruster (Thruster(F)) and stern tug (Tug(A)) were 300–544 hp on average, whereas the values calculated by the automatic berthing program (Program(F), Program(A)) were 105–131 hp. The calculation results of the automatic berthing support program of the ship were approximately 3–5 times greater than the horsepower values of the thruster and tug used during actual berthing, probably because the actual berthing speed was 0.25–1.13 m/s, which is more than five times higher than the set speed of 0.05–0.15 m/s. The results indicate that the automatic berthing support program is promising for future applications in automatic berthing systems for autonomous ships. Full article

Image-based ship monitoring technology has extensive applications, and is widely used in various aspects of port management, including illegal activity surveillance, vessel identification at entry and exit points, channel and berth management, unmanned vessel control, and incident warning and emergency response. However, most current ship identification technologies rely on a single information source, reducing detection accuracy in the complex and variable marine environment. To address this issue, this paper proposes a knowledge transfer-based ship identification system integrating three modules. The system enables synchronized monitoring of visible light coastal images, satellite cloud images, and infrared spectrum images, thereby mitigating problems such as low detection accuracy and poor adaptability of image recognition. Additionally, extensive supplementary experiments were conducted to evaluate the effectiveness of the preprocessing and data augmentation modules as well as the transfer learning module. The study also discusses the limitations of current deep learning-based ship monitoring models, particularly their poor adaptability to image recognition and inability to achieve all-weather, round-the-clock monitoring. Experimental results based on three ship monitoring datasets demonstrate that the proposed system, by integrating three distinct detection conditions, outperforms other models with an F1-score of 98.74%, approximately 10% higher than most existing ship detection systems. Full article

Effective berth allocation in container terminals is crucial for optimizing port operations, given the limited space and the increasing volume of container traffic. This study addresses the discrete dynamic berth allocation problem (DDBAP) under uncertain ship arrival times and varying load capacities. A novel deep Q-network (DQN)-based model is proposed, leveraging a custom state space, rule-based actions, and an optimized reward function to dynamically allocate berths and schedule vessel arrivals. Comparative experiments were conducted with traditional algorithms, including ant colony optimization (ACO), parallel ant colony optimization (PACO), and ant colony optimization combined with genetic algorithm (ACOGA). The results show that DQN outperforms these methods significantly, achieving superior efficiency and effectiveness, particularly under high variability in ship arrivals and load conditions. Specifically, the DQN model reduced the total waiting time of vessels by 58.3% compared to ACO (262.85 h), by 57.9% compared to PACO (259.5 h), and by 57.4% compared to ACOGA (257.4 h), with a total waiting time of 109.45 h. Despite its impressive performance, DQN requires substantial computational power during the training phase and is sensitive to data quality. These findings underscore the potential of reinforcement learning to optimize berth allocation under dynamic conditions. Future work will explore multi-agent reinforcement learning (MARL) and real-time adaptive mechanisms to further enhance the robustness and scalability of the model. Full article

Coastal water accidents have occurred frequently in recent years, and human factors are still the main cause of these accidents. The purpose of this study is to provide a better and safer solution for the symmetry problem of unmanned surface vessels during automatic berthing in coastal waters. In automatic berthing, the symmetry problem refers to whether the USVs can maintain a stable state during motion and positioning, including dynamic symmetry and environmental symmetry. A finite-time controller based on a global nonsingular terminal sliding mode is designed to improve response speed and state consistency. Dynamic uncertainty and disturbance are considered in the design process, which can optimize the control law and effectively ensure the symmetry of the vessel in different states. Then, an event-triggering mechanism based on a dynamic threshold is adopted. In practice, there is excessive operation of the actuator. This mechanism ensures that the actuator is triggered only when the threshold is reached. USVs can adaptively adjust control strategies based on the real-time status, thereby improving symmetry during berthing. In simulation analysis, a pod-driven unmanned surface vessel with good maneuverability is taken as the research object. The results indicate that this control strategy can ensure rapid and consistent response of the vessel when subjected to external disturbances, which helps to maintain the symmetry of the automatic berthing motion under different conditions. Full article

With the continuous development of the shipping market, bow thrusters have become more important for ship maneuvering. Therefore, the performance of bow thrusters is studied in this paper. In order to obtain an unsteady performance of the bow thruster under different ship speed conditions, the SST k-ω turbulence model is adopted to predict the hydrodynamics of the bow thruster. With the ship’s speed increasing gradually, the variation characteristics of hydrodynamic coefficients and the flow field distribution at key positions are analyzed. The results show that with an increase in ship speed to three knots, the thrust coefficient and torque coefficient of the bow thruster decrease by 2.69~4.07% and 2.34~3.08%. In addition, the blade vibration amplitude intensifies. In the departure direction, the propeller load is more susceptible to being influenced and decreases by an additional 2.34~4.16% compared with that in the berthing direction. Meanwhile, it is found that the velocity distribution is asymmetrical. The inlet velocity at the bow side is faster, which results in the maximum peak pressure being about three times the minimum peak pressure. In addition, the pressure’s nonuniformity in the tunnel increases gradually with the increase in ship speed. Compared with the pressure distribution in the berthing direction, the pressure distribution before and after the propeller is more uniform, which is consistent with the results of hydrodynamic change and velocity distribution. The research in this paper has a certain reference significance for understanding the hydrodynamic performance of bow thrust operation. Full article

Harbour tugs are usually used to moor ships if large ships do not have their own additional propulsion devices (thrusters). Alternatively, during ship loading operations, ships sometimes have to be transferred from one quay to another, and in some cases, port users (shipping companies or other companies) have to pay for port tug services. In such cases, it is very important to guarantee the safety of shipping during mooring operations and to use tugboats optimally and at the same time reduce the cost of tugboat services for ship operators and other companies. For the optimal use of tugboats, it is very important to accurately estimate the required traction force (bollard pull) of tugboats and their quantity, taking into account the parameters of moored ships, the locations of berths, hydro-meteorological and hydrological conditions, and clearance (the gap between the ship’s hull and the bottom of the water area), in order to guarantee the safety of navigation and not to order an excess of tugboats in terms of their quantity and powers. This article presents a methodology developed for estimating the required bollard pull and the number of tugs, taking into account the parameters of the ship, hydro-meteorological and hydrological conditions, clearance, and the locations of berths. The developed methodology for estimating the number of tugboats and their traction force (bollard pull) was tested in real conditions (with real ships and tugboats) and using a calibrated simulator, and we found that it can be successfully applied in any port or other complex shipping area by adapting it to specific conditions. The developed methodology for calculating the traction power (bollard pull) of tugboats allows us to determine the required traction force of tugboats in advance with sufficient accuracy, achieved by assessing the specific parameters and environmental conditions of the vessel served by tugboats. In the most difficult areas of the port, in terms of the use of tugboats, this methodology allows us to make reasonable decisions regarding the number of tugboats and the traction force (bollard pull) required and at the same time reduces the risk of emergency situations. Full article

There has been significant interest in the research field of ship automatic navigation, particularly in the area of autonomous berthing. To address the key challenges of path planning and control during ship berthing, we propose an enhanced Linear−Quadratic Regulator (LQR) control approach, reinforced by the Covariance Matrix Adaptation Evolution Strategy (CMA−ES), along with an adaptive berthing strategy decision model. This integrated framework encompasses ship motion control, path planning, and berthing strategy selection to facilitate adaptive and autonomous ship berthing. Initially, a dynamic mathematical model of ship motion is established, taking into account wind and current interference effects. Subsequently, an adaptive environment−aware berthing strategy model is introduced to enable automatic selection of berthing strategies based on spatial relationships between environmental factors and the berth. By utilizing the refined LQR method, autonomous motion control for ship berthing is achieved. To validate the effectiveness of our controller, comprehensive simulation analyses are conducted under varying operating conditions to encompass crucial factors such as large drift angle characteristics of ships, shallow water effects, and bank effects across seven diverse working conditions. The simulation results underscore the robustness of our proposed method in responding to environmental interference while demonstrating its capability to select appropriate berthing strategies based on varying operational scenarios. Full article

Motivated by the need for a green and low-carbon economy, we explore the co-scheduling optimization of berths and cranes. Our aim is to balance the carbon tax and operating costs of ports under uncertain conditions, proposing an innovative nonlinear mixed-integer programming formulation. To address this optimization challenge, we have developed an enhanced version of the adaptive spiral flying dung beetle algorithm (ASFDBO). In order to evaluate the performance of the ASFDBO algorithm, we performed a benchmark function test and a convergence analysis with other recognized metaheuristics. In addition, we verified the practical applicability of the ASFDBO algorithm in different test scenarios. Through numerical experiments, we analyze the feasibility and effectiveness of the algorithm’s scheduling solutions and improvement strategies. Results indicate that our collaborative scheduling optimization, which considers both carbon and production costs, achieves feasible solutions and reduces carbon expenses. Finally, we investigate the impact of different carbon tax rates on the joint scheduling optimization of berths and quay cranes, and the results show that a reasonable carbon tax policy can effectively reduce the carbon emissions of ports. Full article

There is growing concern regarding air pollutants (NOx, SOx, and PM) and carbon emissions from ocean-going vessels in harbor areas and the role of high-voltage shore connection (HVSC) systems in mitigating these emissions during vessel berthing. The HVSC operates as a TN grounding system in humid environments, and it needs a proper grounding design to ensure safety when faults occur. This article intends to examine the overvoltage resulting from fault currents and its implications for the safety of operators when a single line-to-ground fault takes place within the design of HVSC grounding systems. The assessment is carried out by employing actual scenarios and parameters from a container berth at Kaohsiung Harbor in Taiwan. Considering site conditions, such as the wet ground surface, human body resistance, and electric shock duration, the tolerable safe voltage level is derived using IEEE Std. 80 and IEC 60479-1. Based on the shore power system grounding architecture specified in IEEE/IEC 80005-1, an equivalent circuit model is constructed to calculate the fault currents using symmetrical component analysis. The actual touch voltages generated in various locations are analyzed under scenarios of connecting or disconnecting the equipotential bonding between the ship and the shore using neutral grounding resistor (NGR) designs. This article delves into the scenarios of electric shock that may occur during the operation of an actual container ship’s shore power system. It evaluates whether various contact voltage values exceed current international standards and verifies the grounding design and safety voltage specifications of IEEE/IEC 80005-1. According to the results of this study, the use of NGR and protective earthed neutral (PEN) conductors in HVSC is crucial. This can limit fault currents, reduce touch voltage, and ensure the safety of personnel and equipment. Therefore, ensuring and monitoring equipment conductors and adopting NGRs of appropriate sizes are crucial elements in maintaining electrical safety in HVSC systems. Full article