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

European Union cargo and container ports are under pressure to reduce GHG emissions and achieve carbon neutrality by 2050, as mandated by the European Commission. The pace of progress varies among ports. This study examined the characteristics influencing GHG reduction measures in European cargo and container ports and their implications for sustainable investing. The methods used in this study, such as linear regression models to analyze predictive variables, can be applied in sustainable investing to assess which factors most strongly predict a company's environmental, social, and governance performance. Using linear regression models to analyze data from the 33 busiest European ports, we identified five predictive variables: port size, cargo mix, surrounding population density, access to the sea, and the economic wealth of the host country. Our findings revealed that the port size significantly correlates with the adoption of measures to reduce scope 1, 2, and 3 emissions. This study underscores the importance of contextual and operational factors in evaluating sustainability efforts across sectors. The results contribute to drawing parallels with the field of sustainable investing within finance. This offers valuable insights for sustainable investing, emphasizing the importance of considering various contextual and operational factors when evaluating the sustainability efforts of entities in different sectors. [ABSTRACT FROM AUTHOR]

Similar to world trade, container transportation and the tendency to transport various cargoes with containers is increasing in Türkiye. Moreover, in a world where production centers will be shifting with the Covid-19 pandemic, it can be said that Türkiye's production will increase and over and above expectations, container traffic in its ports will expand. In this context, it is anticipated that the urban of Kocaeli will need more container transportation between container ports and logistics centers. Development processes need to be well planned so that this increase in container transportation does not disrupt the traffic of cities, ports and logistics centers. This planning should be carried out by reconciling the current situation, the demands of the logistic stakeholders and the future vision. This study aims to reveal whether Kocaeli container ports, logistics centers and the urban need alternative transportation methods for economic and sustainable development and to offer solution suggestions by analyzing the opinions of all logistics stakeholders. The data collected in the research were analyzed using the Kruskal Wallis H test in the IBM SPSS 22.0 program, and the hypotheses were questioned. Reconsidering alternative opportunities in transportation for the development of ports and logistics stakeholders of Kocaeli urban in a competitive structure, increasing the road and railway transportation capacities between the ports and Köseköy Logistics center will be appropriate, a new/alternative transportation method will have a positive impact on the efficiency of the ports/logistics businesses, inland waterway/canal to the logistics center. It has been concluded that integration with transportation may be beneficial in the future and may have a moderate impact on business volume and productivity. [ABSTRACT FROM AUTHOR]

This article focuses on the investigation and analysis of vibrations transmitted to cargo during off-road transportation, with particular emphasis on the impact of vehicle and road surface interactions. The primary objective of the research is to quantify and characterize the amplitudes of vibrations generated by the interaction between heavyduty truck tires and rough terrain, and their subsequent transmission to cargo containers. To achieve this, a virtual model of a tactical transportation truck was created using TruckSim software. Two characteristic off-road tracks were simulated, based on driving conditions typically experienced by heavy-duty vehicles in demanding logistical scenarios. The experimental validation of the virtual model was conducted using a heavy-duty truck outfitted with a 20 ft (6096 mm) cargo container. The results of the work include recorded acceleration data, suspension behavior, and the maximum driving speed at which the vehicle remained stable on both tracks. Moreover, the work is a direct response to the needs of the automotive industry and the military. [ABSTRACT FROM AUTHOR]

Considering the unobserved spatial heterogeneity, this study aims to build a Bayesian spatial multinomial logistic (BSMNL) model by utilizing the geographic information from historical maritime accidents. The proposed BSMNL model can be applied to investigate the determinants of human errors involved in maritime accidents. Compared to the traditional multinomial logistic (MNL) model, the proposed BSMNL model produces a more accurate estimate of the effects of environmental and accident factors on the occurrence likelihood of human errors in maritime accidents. Results show that accidents involving cargo and container ships; tankers carrying liquefied natural gas (LNG), liquefied petroleum gas (LPG), or oil; and fishing vessels are more likely to be associated with human errors. Further, one important finding is that the involvement of fishing vessels significantly increases the occurrence probability of both negligence errors and judgment or operational errors. In addition, the occurrence likelihood of human errors is generally higher in springtime, conditions of poor visibility, the absence of strong winds or waves, and the moored or docked status. [ABSTRACT FROM AUTHOR]

Traditional accuracy check methods for cargo hold in container ships rely solely on manual and visual operations, which are time-consuming and resource-intensive. Addressing the challenge of extracting and analyzing key data, such as cell guides and container pedestals, fromlarge-scale point clouds obtained through three-dimensional (3D) laser scanning in container ship trial runs, this paper proposes an algorithmic framework based on 3D laser scanning. Building upon this framework, an improved coordinate-axis filtering RANSAC algorithm is employed to optimize the extraction of cell guide planes. Additionally, an algorithmic process based on Bhattacharyya distance is utilized to automatically extract container pedestal point clouds. Furthermore, a combination of the genetic algorithm and the ICP algorithm is proposed to achieve the fitting of the container pedestal edge contour through point cloud registration. Experimental results demonstrate the consistency between the extracted cell guide and container pedestal data and the actual results, indicating the high practical value of the proposed methodology. [ABSTRACT FROM AUTHOR]

This paper develops a unified port performance index (PPI) considering different cargo categories and the multi-dimensional nature of port performance indicators/dimensions. This study has used the quintile method to construct PPI. Further, the PPI obtained from the quintile method is compared with weighted unified index (PPIPCA) using principal component analysis (PCA), extensively used for index development in the literature. A pilot index development is demonstrated using secondary panel data for 12 major Indian ports on five significant dimensions, namely, operations, physical infrastructure, technical infrastructure, finance, and socio-economic. Results show that the JNPT port outperforms all other ports under the container cargo category. Likewise, Kandla port in the liquid port category and Paradip port in the other (dry & break bulk) cargo category are on top. Also, qualitatively similar results and insights are obtained with the PPIPCA. Subsequently, the panel data regression and efficiency analysis are performed to demonstrate the utility of the proposed index. The results affirm that the operations, physical infrastructure, and socio-economic dimensions have a positive and significant impact on port financial performance. The present study operationalises some key unexplored port performance indicators/dimensions that can enable effective decision-making. [ABSTRACT FROM AUTHOR]

Cambodia has maintained steady economic growth in the past few years; however, its logistics infrastructure is still underdeveloped. Therefore, many logistics projects are being planned and implemented in Cambodia to improve its infrastructure. Because of a growing need to evaluate the effects of these projects quantitatively, this study forecasts the container flows in Cambodia in 2025, by taking into account the economic growth and progress of these projects. This study uses a combination of the Global Trade Analysis Project recursive dynamic (GTAP-RD) model and the global logistics intermodal network simulation (GLINS) model to estimate the impact of various policies related to infrastructure. The authors examine five future policy scenarios and found the policies that will have a significant effect on international container shipping, such as reducing border-crossing time and cost at national borders between Cambodia and Vietnam or Thailand and doubling the frequency of the liner services calling at the Sihanoukville port. [ABSTRACT FROM AUTHOR]

The level of competition in the transport market requires delivery organizers to implement better approaches based on modern management methodologies, in particular, agile, which makes it possible to provide a modern level of service to cargo owners. The object of this research is the processes of organizing multimodal delivery. The subject of the study is the area of compromise in the processes of organizing multimodal delivery based on the agile approach. The term «compromise area» is introduced, which reflects the numerical limits of product parameters in the general case. For the transportation domain under consideration, the «trade-off area» reflects the limits of the characteristics of multimodal delivery, which is the «product» for the multimodal operator. A set of alternative options for multimodal delivery forms the basis for establishing the dependence of the cost of delivery on time and its reliability (possible time deviation). The area in the «time-reliability-cost» space, which is formed on the basis of this dependence, on the one hand, and the requirements of the cargo owner, taking into account their possible adjustment, on the other hand, is the area of compromise. This area is proposed for use in agile approaches to the organization of multimodal delivery. Balancing the interests of the cargo owner and the multimodal operator allows changing the limits of the compromise area within the framework of the proposed scheme of agile cycles in the process of planning and organizing delivery. On the example of delivering a container with cargo from China to Kyiv, regression linear models were built. These models formalize the dependence of delivery cost on reliability and/or time. Using the example of varying the requirements of the cargo owner regarding the limitations of some delivery characteristics, the formation of the compromise area and its adjustment was carried out, which demonstrated the practical aspects of the formation of the compromise area for multimodal delivery. The results are the basis for the implementation of the agile approach in the field of multimodal transportation. The further development of these results consists in the construction of mathematical models that could form the basis for finding solutions in the area of compromise. [ABSTRACT FROM AUTHOR]

This paper shows the development of a numerical analysis model, which enables the calculation of the cargo transport capacity of a vehicle that circulates through a vacuum tube at high speed, whose effectiveness in transport is analyzed. The simulated transportation system is based on vehicles moving in vacuum tubes at high speed, a concept commonly known as Hyperloop, but assuming the vehicles for cargo containers. For the specific vehicle proposed, which does not include a compressor and levitates on magnets, the system formed by the vehicle and the vacuum tube has been conceptually developed, establishing the corresponding mathematical relationships that define its behavior. To properly model the performance of this transport system, it has been necessary to establish the relationships between the design variables and the associated constraints, such as the Kantrowitz limit, aerodynamics, transport, energy consumption, etc. Once the model was built and validated, it was used to analyze the effects of the variation of the number of containers, the operating speed and the tube length, considering the total and specific consumption of energy. After finding the most efficient configuration regarding energy consumption and transport effectiveness, the complete system was calculated. The results obtained constitute a first approximation for the predesign of this transport system and the built model allows different alternatives to be compared according to the design variables. [ABSTRACT FROM AUTHOR]

Handling luggage systems is a critical component of a passenger terminal's operations. The proposed study attempts to find the optimal solution for a manually operated terminal concerning the luggage offloading process from arrival flights carried by a limited number of ground handling agents. Handling agents start the offloading process from the aircraft to the cargo luggage containers carried by a cargo car that will take the containers' trolleys to the cargo area to offload them into the reserved luggage belt carousel. This study aims to improve airport service quality by minimizing the baggage handling process time for arrival flights which leads to minimizing passenger waiting time in the baggage claim area. We proposed both a deterministic and stochastic approach. The integer programming method is provided to minimize the total number of flights assigned to the belt carousel under the realistic constraint of minimizing the luggage load on each belt carousel. Simulation tools were used so that the offloading process could be modeled to study the effects of various parameters such as the number of ground handling agents for different flights with different amounts of luggage. [ABSTRACT FROM AUTHOR]

Focusing on 23 greening measures, this paper systematically compares the greening efforts of the busiest container and cargo ports in the United States (US) and the European Union (EU). We move beyond accounts for general environmental differences between the EU and the US to examine how specific environmental decisions are shaped by the effects of regulatory characteristics in each region. We identify systematic variation in number and type of port greening measures adopted in the two regions. We demonstrate that differences in the number and type of measures adopted reflect the level of policy making with local policy making playing a more important role in the US compared to the EU, thus proposing a pathway through which the form of regulatory approach could influence content and extent of regulation. The EU adopts regulation that is broader in scope while US ports are more likely to address problems affecting local populations. [ABSTRACT FROM AUTHOR]

Narcotics should be strictly controlled as they can cause great disruption to society. Narcotics mostly flow into ports from major narcotic makers via transit points and through cargo containers. To prevent narcotic entry through smuggling, airports use animals or detect narcotics through X-rays. However, the use of animals in ports is not practical, and the method using X-rays sometimes does not detect substance narcotics with low atomic numbers. In this paper, we aimed to detect and classify narcotics using ion mobility spectrometry (IMS) data generated by inhaling air inside the container. To classify narcotic IMS data consisting of time-series data, the performance was improved using a time-series classification machine learning algorithm instead of the threshold method previously used. To this end, K-nearest neighbor, time-series forest, and random convolutional kernel algorithms were applied to the proposed algorithm considering the features of narcotic IMS data. The results demonstrate that the proposed algorithm outperforms the existing algorithm, and it reduces the classification performance processing time up to 5 s with more than 0.9 accuracy level. [ABSTRACT FROM AUTHOR]

In the maritime industry, optimizing vessel fuel oil consumption is crucial for improving energy efficiency and reducing shipping emissions. However, effectively utilizing operational data to advance performance monitoring and optimization remains a challenge. An XGBoost Regressor model was developed using a comprehensive dataset, delivering strong predictive performance (R2 = 0.95, MAE = 10.78 kg/h). This predictive model considers operational (controllable) and environmental (uncontrollable) variables, offering insights into complex FOC factors. To enhance interpretability, SHAP analysis is employed, revealing 'Average Draught (Aft and Fore)' as the key controllable factor and emphasizing 'Relative Wind Speed' as the dominant uncontrollable factor impacting vessel FOC. This research extends to further analysis of the extremely high FOC point, identifying patterns in the Strait of Malacca and the South China Sea. These findings provide region-specific insights, guiding energy efficiency improvement, operational strategy refinement, and sea resistance mitigation. In summary, our study introduces a groundbreaking framework leveraging machine learning and SHAP analysis to advance FOC understanding and enhance maritime decision making, contributing significantly to energy efficiency and operational strategies—a substantial contribution to a responsible shipping performance assessment under tightening regulations. [ABSTRACT FROM AUTHOR]

This paper measures economic efficiency of container throughputs with the aid of input-output efficiency ratio of selected terminals across Nigerian seaports. Productivity of a terminal does not equal to its efficiency. Different efficiencies like allocative and technical characterized economic efficiency of a port system. Overall economic efficiency means there is no delay at the port in processing container as all ship, labour and machines are optimally utilized. This research determined the overall efficiencies of container throughputs Apapa, Warri, Onne, Calabal and Tin Can Island using secondary data (2012-2022) from Nigerian Bureau of Statistics on container cargo throughputs in Nigeria. Total container outputs in (Tonnes) from different terminals with their corresponding inputs variables from number of ship per annum, cranes used and the dock workers net gang hour (ngh) were aggregated together in form of input-output ratio and arrived at each port's level of overall economic efficiency. The analysis was executed with the aid of R using Stochastic Frontier Analysis (SFA) for each termina/seaport collected data. It was found from the results that; terminals at Onne are most efficient followed by Calabar. Tin can Island terminal efficiency was a slightly higher than that of Apapa as both had a little above average mean efficiency value. Warri terminals are the least while Rivers was not considered for unavailability of data. There may be other unexplained factors causing inefficiencies of mostly Apapa, Tin Can and Warri seaports not explained but can be investigated in future research. [ABSTRACT FROM AUTHOR]

The current research is focused on the identification of cargo containers in a stack from their images in the infrared and visible spectra, in order to locate the container-origin of ignition within the cargo temperature control and fire safety system. The relevance of the topic is reinforced by the functional requirements for shipboard safety, which are embodied in Chapter II-2 of the Safety of Life at Sea (SOLAS) Convention, and demanded by the necessity of enhancing safety measures during cargo transportation by the world container fleet. The thermal imager's field of view (FOV) and the coordinate dependencies between the object and its image have been studied and modelled, and an algorithm for fire detection has been defined within the scope of the current research in connection with the containers within the camera's FOV. A corresponding verification has been carried out by means of simulation modelling using the Unity and C# programming language capabilities. [ABSTRACT FROM AUTHOR]

Logistics workers who handle cargo containers are at risk of toxic inhalation injuries, although prevalence and severities of these injuries are not well characterized. We report on a previously healthy 37-year-old supervisor who was acutely exposed to sodium metabisulphite and its thermal degradation by-products during a routine inspection of a shipping container. The employee developed chemical pneumonitis with acute non-cardiogenic pulmonary oedema and subsequent severe reactive airway dysfunction syndrome. [ABSTRACT FROM AUTHOR]

This paper deals with modeling and solving a multi-stage stochastic inventory management problem for transport companies, including several different transport modes. This model aims to determine the amount of stored cargo and transport containers and trucks to the appropriate locations. Due to the uncertainty of environmental conditions, the demand and transfer costs parameters are considered uncertainly in different scenarios in the proposed model. Since the uncertain model is insoluble, a new robust-fuzzy-probabilistic method has been used to control the model's parameters. As a result, the final model minimizes the total cost of maintaining cargo and transporting trucks and containers. Three genetic algorithms, particle swarm optimization and gray wolf optimization have been employed to solve the proposed stochastic inventory management model. The results of the problem analysis show that the increase of uncertainty rate in different scenarios due to the increase in the amount of demand from cargo, transmission, and maintenance costs have increased. In return, the total network costs have also increased. [ABSTRACT FROM AUTHOR]

Copyright of Forensic Science & Technology is the property of Institute of Forensic Science, Ministry of Public Security and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cyber-Physical Systems (CPS) are physical systems whose operations are coordinated, monitored, and controlled by computing and communication functions. These systems are typically heterogeneous, including Internet of Things and information technology subsystems, and can present a myriad of implementation details, making them very complex systems. An important type of CPS is a maritime container terminal (cargo port), which is a facility where cargo containers are transported between ships and land vehicles for onward transportation and vice versa. A cargo port performs four basic functions: receiving, storing, staging, and loading for both import and export containers. We present here process patterns that describe the functional aspects of cargo ports and a pattern that describes their structural properties (patterns are encapsulated solutions to recurrent problems). These patterns describe semantic aspects found in any cargo port and can be adapted to describe other CPSs. We decompose these process patterns into use cases that describe their interactions with the system. We then integrate the process patterns with structural patterns to assemble a partial reference architecture (RA) that shows the interactions of all the patterns while also indicating the typical stakeholders found in all ports. We validate the proposed reference architecture, highlighting its theoretical and practical value. Software and system designers of cargo ports need to start from a conceptual and abstract view that is subsequently refined to add more details. The use of reference architectures and patterns is an effective way to organize and describe the functional and non-functional aspects of a system, as well as to unify the design of all its aspects. This is, until now, the only published RA for cargo ports, and it can be a useful guideline for the designers of any type of cargo port. [ABSTRACT FROM AUTHOR]

Copyright of Rolling Stock (1002-7602) is the property of Rolling Stock Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

High-value sensitive cargoes are often damaged by low-frequency vibration and shock of containers during land and rail transport processes or mixed transport processes. Therefore, a dedicated cylindrical elastomer spring that absorbs vibration transmitted into the container has been developed. This study developed an optimal shape using a polyurethane material instead of the existing rubber spring. Elastomer spring requires an optimal design that satisfies the design target stiffness and strength by nonlinear finite element analysis. In order to develop an elastomer spring for a cargo container, the material constant was obtained by a hyperelastic behavior test of natural rubber, and based on this, the necessary optimal material constant of the new spring was predicted. In addition, nonlinear structural analysis was performed using ABAQUS to obtain the optimal shape of the spring, and optimal design was performed with I-SIGHT software. As a result of the sum of squared difference minimization with the comparison algorithm, it was found that the polyurethane material constant C10, C20, and C30 with the same characteristics as natural rubber was obtained. In addition, analysis using three optimization algorithms, Hooke–Jeeves algorithm, multi-island genetic algorithm, and optimal Latin hypercube, yielded a maximum principal strain of 0.244 of the spring obtained through the optimal cross-sectional shape design. It was found that this value was about 39% lower than the natural rubber spring in use. As a result of the compression load-displacement test of the actually developed product, it was confirmed that the correlation coefficient between the predicted value and the measured value was 0.928. [ABSTRACT FROM AUTHOR]

In order to detect special nuclear materials and other radioactive materials in Security and Defense scenarios, normally, a combination of neutron and gamma-ray detection systems is used. In particular, to avoid illicit traffic of special nuclear materials and radioactive sources/materials, radiation portal monitors are placed at seaports to inspect shipping-container cargo. Despite their large volume (high efficiency), these detection systems are expensive, and therefore only a fraction of these containers are inspected. In this work, a novel mobile radiation detection system is presented, based on an EJ-200 plastic scintillator for the detection of gamma rays and beta particles, and a neutron detector EJ-426HD plastic scintillator (with 6Li) embedded in a compact and modular moderator. The use of silicon photomultipliers in both detectors presented advantages such as lightweight, compactness, and low power consumption. The developed detection system was integrated in a highly maneuverable multirotor. Monte Carlo simulations were validated by laboratory measurements and field tests were performed using real gamma-ray and neutron sources. The detection and localization within one meter was achieved using a maximum likelihood estimation algorithm for 137Cs sources (4 MBq), as well as the detection of 241Am–beryllium (1.45 GBq) source placed inside the shipping container. [ABSTRACT FROM AUTHOR]

The Panama Canal has played an important role in the history of the shipping industry. Therefore, it was reasonable to forecast that the Panama Canal expansion would impact port throughput in the six transshipment ports located in Panama. To examine this impact, two periods were analyzed. The first period covered October 2010 to June 2016. The second period covered July 2016 to March 2022. The Wilcoxon signed-rank test and the IBM SPSS Statistics software were used to analyze public data from the Central American Maritime Transport Commission (COCATRAM) measuring port throughput. The research concluded that the Panama Canal expansion has not produced a statistically significant impact on the port throughput of (a) cargo tonnage, (b) cargo TEU and (c) vessel calls. [ABSTRACT FROM AUTHOR]

Introducing a new genetically encoded material containing a photoactivatable label as a model cargo protein, based on Myxococcus xanthus (Mx) encapsulin system stably expressed in human 293T cells. Encapsulin from Mx is known to be a protein-based container for a ferritin-like cargo in its shell which could be replaced with an exogenous cargo protein, resulting in a modified encapsulin system. We replaced Mx natural cargo with a foreign photoactivatable mCherry (PAmCherry) fluorescent protein and isolated encapsulins, containing PAmCherry, from 293T cells. Isolated Mx encapsulin shells containing photoactivatable label can be internalized by macrophages, wherein the PAmCherry fluorescent signal remains clearly visible. We believe that a genetically encoded nanocarrier system obtained in this study, can be used as a platform for controllable delivery of protein/peptide therapeutics in vitro. [ABSTRACT FROM AUTHOR]

As the maritime transport of containers continues to grow and container ships change in terms of design and construction, it is important to ensure the appropriate level of safety for this type of transport. Over the decades, the size and cargo capacity of container ships have been changing, and so have their manoeuvring restrictions and required stability criteria. It seems that changes in the regulations, technological development and increased stability requirements are not yielding satisfactory results – the causes of container ship accidents continue to show similar patterns. The present article refers to the problem of ensuring safety in sea container transport, with a particular focus on cargo processes. Its purpose is to determine cause-and-effect relations leading to the loss of containers at sea, and to develop a model of loading that could significantly raise the level of safety of container transport. The article provides a general description of threats to ships related to weather conditions, loading methods or stability limitations. A statistical analysis of the occurrence of damage and/or loss of cargo from container ships was carried out and the risk of cargo loss was assessed on the basis of data from 2015‒2019. A Pareto diagram was used for this purpose. The authors present the concept of the container ship loading model, which may contribute to increasing the safety of shipping in the future. [ABSTRACT FROM AUTHOR]

To improve transportation capacity, dual overhead crane systems (DOCSs) are playing an increasingly important role in the transportation of large/heavy cargos and containers. Unfortunately, when trying to deal with the control problem, current methods fail to fully consider such factors as external disturbances, input dead zones, parameter uncertainties, and other unmodeled dynamics that DOCSs usually suffer from. As a result, dramatic degradation is caused in the control performance, which badly hinders the practical applications of DOCSs. Motivated by this fact, this paper designs a neural network-based adaptive sliding mode control (SMC) method for DOCS to solve the aforementioned issues, which achieves satisfactory control performance for both actuated and underactuated state variables, even in the presence of matched and mismatched disturbances. The asymptotic stability of the desired equilibrium point is proved with rigorous Lyapunov-based analysis. Finally, extensive hardware experimental results are collected to verify the efficiency and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

The authors have studied the methods of loading bulk cargo in the railway transport. The developed method of loading bulk cargoes into containers transported by railway platforms has been developed. The article deals with experimental studies of maximum stresses in the design of the proposed stationary hoist. The studies have been carried out in the ANSYS software environment with development of simulation models of the hoist design. [ABSTRACT FROM AUTHOR]

With the complex and variable climate, the trend of short -term heavy rainfall, super typhoon and other extreme weather is obvious. Undoubtedly, the risk of future disasters will increase, resulting in the shutdown of coastal ports, damage to power supply facilities such as port substations, communications and infrastructure damaged, and flooding of container cargo and food cargo to varying degrees. By means of field investigation and data collection, it analyzes the factors affecting the land production of coastal port facilities in South China by typhoon, aiming at summarizing the land area elevation design standards of coastal ports, and the countermeasures and suggestions that can be taken by existing and new projects under the influence ofty phoon, to provide reference for similar projects. [ABSTRACT FROM AUTHOR]

Continuity of marine port operations and recovery in the event of disaster and flooding are dependent upon planning for acute or chronic disruptions. Ports are developing the capacity to integrate climate change adaptation with strategic planning and making capital investments in infrastructure. Geospatial risk assessments have demonstrated utility for planning marine port terminal facilities. Such assessments have tended to be coarse and comprehensive (whole port cities) or narrow, site-specific and single-hazard approaches (single terminal or site scale). This study develops a methodology for major container port terminals on the Eastern Seaboard of the United States to advance a screening approach to sea level rise, identify exposure to terminals and associated surface transportation, and enable comparative assessment. The study leverages geospatial data, elevation, imagery, transportation databases, tide gauges, and sea level rise projections. The approach extends prior methods to quantify exposure across multiple ports and terminals. Hypsographs and modelled future tidal flooding are derived for each port. Results highlight the need for port planning to develop GIS, monitor sea level rise trends, engage in integrative assessments, and optimize mitigation and adaptation actions. Results show similarities across yet also differentially increasing threats of relative sea level rise and tidal flooding at individual terminals. [ABSTRACT FROM AUTHOR]

The digital twin (DT) approach has risen in popularity for applications in many industrial process managements. By applying the "Shipyard 4.0" digital transformation trend, the ship industry is developing techniques able to reduce risks by improving operation process management. This study proposes a combination of a DT approach and practical experiment as part of a five-tier framework for DT-driven process management in the ship industry. This study focuses on the characteristic scenarios and crucial parameters within the ship engine system and shipping cargo container in operation procedures. DT-based models and platforms are established in this study based on the basic modeling of Maya and scene rendering of Unity 3D. To address the fusion issue of multi-source heterogeneous data in the ship operation process, a Bayesian neural network (BNN) method is introduced into DT's virtual model layer and data support layer. By integrating an improved BNN-based algorithm into DT-based models, the collected data can be extracted and aggregated accordingly. In the ship engine room, the operating temperature is selected as a critical parameter, with the best mean percentage deviation (MPD) between DT-driven predictions and test value of 3.18%. During the shipping cargo container process, the results indicate that DT-based models have acceptable performances under different conditions, with optimal MPDs of 5.22%. [ABSTRACT FROM AUTHOR]