Structural Characteristics and Evolution of a Weighted Sino-US Container Shipping Network

This study selected the Sino-US route data from the top 30 global container liner companies between December 1,2019,and December 29,2019,as the data source utilizing the complex network research methodology.It constructs a Sino-US container shipping network through voyage weighting and analyzes the essential structural characteristics to explore the network’s complex structural fea-tures.The network’s evolution is examined from three perspectives,namely,time,space,and event influence,aiming to comprehens-ively explore the network’s evolution mechanism.The results revealed that:1)the weighted Sino-US container shipping network exhib-its small-world and scale-free properties.Key hub ports in the United States include NEW YORK NY,SAVANNAH GA,LOS ANGELES CA,and OAKLAND CA,whereas SHANGHAI serving as the hub port in China.The geographical distribution of these hub ports is uneven.2)Concerning the evolution of the weighted Sino-US container shipping network,from a temporal perspective,the evolution of the regional structure of the entire Sino-US region and the Inland United States is in a stage of radiative expansion and de-velopment,with a need for further enhancement in competitiveness and development speed.The evolution of the regional structure of southern China and Europe is transitioning from the stage of radiative expansion and development to an advanced equilibrium stage.The shipping development in Northern China,the Western and Eastern United States,and Asia is undergoing significant changes but faces challenges of fierce competition and imbalances.From a spatial perspective,the rationality and effectiveness of the improved weighted Barrat-Barthelemy-Vespignani(BBV)model are confirmed through theoretical derivation.The applicability of the improved evolution model is verified by simulating the evolution of the weighted Sino-US container shipping network.From an event impact per-spective,the Corona Virus Disease 2019(COVID-19)pandemic has not fundamentally affected the spatial pattern of the weighted Sino-US container shipping network but has significantly impacted the network’s connectivity.The network lacks sufficient resilience and stability in emergency situations.3)Based on the analysis of the structural characteristics and evolution of the weighted Sino-US con-tainer shipping network,recommendations for network development are proposed from three aspects:emphasizing the development of hub ports,focusing on the balanced development of the network,and optimizing the layout of Chinese ports.

Quantitative analysis of the efficiency dynamics of global liquefied natural gas shipping under COVID-19

Investigating how COVID-19 has influenced Liquefied Natural Gas(LNG)is significant for benefits evaluation for shipping companies and safety management for sustainable LNG shipping in case of accidents.This paper proposes a quantitative method to model the impact of COVID-19 on global LNG shipping efficiency based on the spatiotemporal characteristics of behavior mining for LNG ships.The time cost for LNG carriers serving inside LNG terminals is calculated based on the status of LNG carriers specifically based on arrival and departure times.Then,the time series analysis method is employed to extract the statistical characteristics of the COVID-19 severity index and time cost for LNG carriers inside LNG terminals.Finally,the impact of COVID-19 on global LNG shipping is explored through the Vector Autoregressive Model(VAR)combined with the sliding window.The results demonstrate that the COVID-19 pandemic has a certain influence on the service time for LNG carriers with time lags worldwide.The impact is spatial heterogeneity on a large scale or small scale across global,countries,and trading terminals.It can be used for decision-making in energy safety and LNG intelligent shipping management under unexpected global public health events in the future.The results provide support for intelligent decision-making for safety management under unexpected public health events,such as reducing the seafarer’s explosion to risk events and taking efficient actions to ensure the shipping flow to avoid the energy supply shortage.

Corporate Social Responsibility and Shipping Supply Chain Risks

This study aims to investigate whether Corporate Social Responsibility(CSR)activities reduce supply chain disruptions by examining the impact of the Suez Canal obstruction on the Ever Given container ship in March 2021.This study conclude that the more responsible companies have higher returns and are less affected by this event than the less responsible companies;the less responsible companies have lower returns.The companies with better CSR have a lower impact on their supply chains when faced with disruptions in the supply chain.

Review and Analysis: Fate of Arsenic Applied to Canal Shipping Lane Vegetation and United States Military Base Grounds in the Panama Canal Zone

The opening of the Panama Canal in 1913 increased the availability of internationally traded goods and transformed ocean-shipping by shortening travel time between the Atlantic Ocean and Pacific Ocean. The canal sparked the growth of port authorities and increased ship tonnage on both coasts of Panama. Since the construction of the Panama Canal, in the 1910s, pesticides, herbicides and chemicals, including arsenic, have been essential for controlling wetland vegetation, including hyacinth, which blocked rivers, lakes, and the canal as well as managing mosquitoes. Pesticides and chemicals flowed into Lake Gatun (reservoir) either attached to sediment or in solution during the monsoon season. Lake Gatun was the drinking water source for most of the people living in the Panama Canal Zone. The United States military base commanders had the ability to order and use cacodylic acid (arsenic based) from the Naval Depot Supply Federal and Stock Catalog and the later Federal Supply Catalog on the military base grounds in the Panama Canal Zone. Cacodylic acid was shipped to Panama Canal Zone ports, including Balboa and Cristobal, and distributed to the military bases by rail or truck. The objective of this study is to determine the fate of arsenic: 1) applied between 1914 and 1935 to Panama Canal shipping lane hyacinth and other wetland vegetation and 2) cacodylic acid (arsenic) sprayed from 1948 to 1999 on the US military base grounds in the Panama Canal Zone.

Dilemma and Solutions of Greenhouse Gas Emission Reduction of International Shipping

How to build an international maritime GHG(greenhouse gas)emission reduction cooperation mechanism is an important international issue at present.Firstly,we describe the current situation of maritime transport GHG emission reduction and analyze the problems that still exist in international maritime transport emission reduction from four aspects:political,economic,legal and technical.For example,geopolitical aggravation hinders the solution of the FOC(Flag of Convenience)issue;maritime emissions are not included in the carbon emission trading system;the synergy of maritime emission reduction principles under the IMO(International Maritime Organization)framework and the technical level of maritime emission reduction needs to be improved.The motivation and essence of the divergent international actions on maritime emission reduction are discussed.Finally,it is proposed to implement the“true linkage principle”to solve the problem of FOCs;to promote the development of regional carbon markets and link them to the international maritime carbon emission trading market economically;to implement the CBDR(the common but differentiated responsibilities)principle legally to promote the international emission reduction work in an orderly manner;and the technical innovation of ships and increase the technical support.

多个零售商竞争下的Drop-shipping供应链协调

D rop-sh ipp ing是互联网上广泛采用的一种商业模式。Netessine(2004)对这种模式的供应链进行了研究,分析了多周期供应商和零售商之间的相互作用。本文扩展了Netessine的研究,分析了一对多的D rop-sh ip-p ing供应链,零售商之间存在促销竞争,讨论了Nash均衡的存在性和唯一性。研究发现在一对多的情况下,Netessine设计的合同的局限性。数值分析发现保持一定数量的零售商对供应商有好外,但零售商太多也会存在弊端。

Two-Staged Method for Ice Channel Identification Based on Image Segmentation and Corner Point Regression

Identification of the ice channel is the basic technology for developing intelligent ships in ice-covered waters,which is important to ensure the safety and economy of navigation.In the Arctic,merchant ships with low ice class often navigate in channels opened up by icebreakers.Navigation in the ice channel often depends on good maneuverability skills and abundant experience from the captain to a large extent.The ship may get stuck if steered into ice fields off the channel.Under this circumstance,it is very important to study how to identify the boundary lines of ice channels with a reliable method.In this paper,a two-staged ice channel identification method is developed based on image segmentation and corner point regression.The first stage employs the image segmentation method to extract channel regions.In the second stage,an intelligent corner regression network is proposed to extract the channel boundary lines from the channel region.A non-intelligent angle-based filtering and clustering method is proposed and compared with corner point regression network.The training and evaluation of the segmentation method and corner regression network are carried out on the synthetic and real ice channel dataset.The evaluation results show that the accuracy of the method using the corner point regression network in the second stage is achieved as high as 73.33%on the synthetic ice channel dataset and 70.66%on the real ice channel dataset,and the processing speed can reach up to 14.58frames per second.

赛德西港用于船舶减排的陆上可再生能源供电评估

Air pollution from shipping is becoming a critical issue,particularly in dense hub port cities.One proposed solution to minimize ship-based emissions at ports is the implementation of an Onshore Power Supply(OPS)system.OPS allows ships to shut off their auxiliary engines and instead connect to the port grid.While there have been numerous studies conducted on ports in Europe and the United States,little research has been done on Egyptian ports.Therefore,this paper aims to investigate the feasibility of implementing OPS at Port Said West Port in Egypt,aligning with Egypt Vision 2030’s goals for addressing climate change.The research primarily focuses on analyzing data collected from calling ships to generate socio-economic and cost-effectiveness analyses of OPS.To further enhance the environmental benefits of OPS,the paper proposes the use of solar energy as the OPS electricity source.The findings of the study revealed that by relying on the national grid,emissions can be reduced by 28%.Moreover,it is predicted that this reduction could reach 100%if electricity generation is solely based on solar energy.Additionally,the economic analysis demonstrates promising profitability,with a payback period of approximately two years.

Coupling of RANS and BEM Solvers for Simulation of Propeller Behind the Hull in Full Appended Model

To design a propeller for ship power plant,the interaction between ship hull and propeller must be taken into account.The main concern is to apply the wake effect of ship stern on the propeller performance.In this paper,a coupled BEM(Boundary Element Method)/RANS(Renolds-Averaged Navier−Stokes)solver is used to simulate propeller behind the hull in the self-propulsion test.The motivation of this work is to develop a practical tool to design marine propulsion system without suffering long computational time.An unsteady boundary element method which is also known as panel method is chosen to estimate the propeller forces.Propeller wakes are treated using a time marching wake alignment method.Also,a RANS code coupled with VoF equation is developed to consider the ship motions and wake field effects in the problem.A coupling algorithm is developed to interchange ship wake field to the potential flow solver and propeller thrust to the RANS code.Based on the difference between hull resistance and the propeller thrust,a PI controller is developed to compute the propeller RPM in every time step.Verification of the solver is carried out using the towing tank test report of a 50 m oceanography research vessel.Wake factor and trust deduction coefficient are estimated numerically.Also,the wake rollup pattern of the propeller in open water is compared with the propeller in real wake field.

A Time-Domain Numerical Simulation for Free Motion Responses of Two Ships Advancing in Head Waves

The constant panel method within the framework of potential flow theory in the time domain is developed for solving the hydrodynamic interactions between two parallel ships with forward speed.When solving problems within a time domain framework,the free water surface needs to simultaneously satisfy both the kinematic and dynamic boundary conditions of the free water surface.This provides conditions for adding artificial damping layers.Using the Runge−Kutta method to solve equations related to time.An upwind differential scheme is used in the present method to deal with the convection terms on the free surface to prevent waves upstream.Through the comparison with the available experimental data and other numerical methods,the present method is proved to have good mesh convergence,and satisfactory results can be obtained.The constant panel method is applied to calculate the hydrodynamic interaction responses of two parallel ships advancing in head waves.Numerical simulations are conducted on the effects of forward speed,different longitudinal and lateral distances on the motion response of two modified Wigley ships in head waves.Then further investigations are conducted on the effects of different ship types on the motion response.

Unmanned Ship Identification Based on Improved YOLOv8s Algorithm

Aiming at defects such as low contrast in infrared ship images,uneven distribution of ship size,and lack of texture details,which will lead to unmanned ship leakage misdetection and slow detection,this paper proposes an infrared ship detection model based on the improved YOLOv8 algorithm(R_YOLO).The algorithm incorporates the Efficient Multi-Scale Attention mechanism(EMA),the efficient Reparameterized Generalized-feature extraction module(CSPStage),the small target detection header,the Repulsion Loss function,and the context aggregation block(CABlock),which are designed to improve the model’s ability to detect targets at multiple scales and the speed of model inference.The algorithm is validated in detail on two vessel datasets.The comprehensive experimental results demonstrate that,in the infrared dataset,the YOLOv8s algorithm exhibits improvements in various performance metrics.Specifically,compared to the baseline algorithm,there is a 3.1%increase in mean average precision at a threshold of 0.5(mAP(0.5)),a 5.4%increase in recall rate,and a 2.2%increase in mAP(0.5:0.95).Simultaneously,while less than 5 times parameters,the mAP(0.5)and frames per second(FPS)exhibit an increase of 1.7%and more than 3 times,respectively,compared to the CAA_YOLO algorithm.Finally,the evaluation indexes on the visible light data set have shown an average improvement of 4.5%.

Efficient Ship:A Hybrid Deep Learning Framework for Ship Detection in the River

Optical image-based ship detection can ensure the safety of ships and promote the orderly management of ships in offshore waters.Current deep learning researches on optical image-based ship detection mainly focus on improving one-stage detectors for real-time ship detection but sacrifices the accuracy of detection.To solve this problem,we present a hybrid ship detection framework which is named EfficientShip in this paper.The core parts of the EfficientShip are DLA-backboned object location(DBOL)and CascadeRCNN-guided object classification(CROC).The DBOL is responsible for finding potential ship objects,and the CROC is used to categorize the potential ship objects.We also design a pixel-spatial-level data augmentation(PSDA)to reduce the risk of detection model overfitting.We compare the proposed EfficientShip with state-of-the-art(SOTA)literature on a ship detection dataset called Seaships.Experiments show our ship detection framework achieves a result of 99.63%(mAP)at 45 fps,which is much better than 8 SOTA approaches on detection accuracy and can also meet the requirements of real-time application scenarios.

Study of the Lift Force Induced by An Interceptor on A High-Speed Mono-Hull:The Affecting Factors and Estimation Formula

To find a better way to estimate the lift force induced by an interceptor on a high-speed mono-hull ship,a series of high-speed mono-hull ship models are designed and investigated under different conditions.Different lift forces are obtained by numerical calculations and validated by a model test in a towing tank.The factors that influence the force are the interceptor height,velocity,draft,and deadrise angle.The relationship between each factor and the induced lift force is investigated and obtained.We found that the induced lift mainly depends on the interceptor height and advancing velocity,and is proportional to the square of the interceptor height and velocity.The results also showed that the effects of the draft and deadrise angle are relatively less important,and the relationship between the induced lift and these two factors is generally linear.Based on the results,a formula including the combined effect of all factors used to estimate the lift force induced by the interceptor is developed based on systematic analysis.The proposed formula could be used to estimate the lift force induced by interceptors,especially under high-speed condition.

超声空化在船舶与海洋工程中的应用

Biofouling on ships and offshore structures has always been a difficult problem to solve,which not only jeopardizes the structural strength but also brings great economic losses.Ultrasonic cavitation is expected to solve this problem due to its characteristics of no damage to structures and no pollution.Starting from the phenomenon and mechanism of ultrasonic cleaning,this paper introduces the application of ultrasonic cavitation in ship,pipeline and oil cleaning as well as ballast water treatment.By reviewing the existing studies,limitations such as insufficient ultrasonic parameter studies,lack of uniform cleanliness standards,and insufficient cavitation studies are summarized to provide traceable research ideas for improving ultrasonic cavitation technology and to guide the expansion and improvement of its applications.

船舶进气畸变模拟板结构设计与参数分析

Significant aerodynamic engine instability can occur during the operation of marine gas turbines as airflow enters the compressor through a 90°turning and causes inlet distortion.This study adopts the method of simulating board equivalence to provide the target distortion flow field for ship compressors.The characteristics of the flow field behind the simulated board are obtained through experiments and numerical simulations,through which the relationship between the height of the simulated board and the total pressure distortion is elucidated.Subsequently,the study summarizes the prediction formula to achieve a distortion prediction of 0.8%–7.8%.In addition,this work analyzes the effects of drilling methods and diameters on flow nonuniformity by drilling holes into the simulation board.The results indicate that drilling holes on the board can weaken the nonuniformity of the flow field within a certain range and change the distribution pattern of total pressure in the cross-section.Furthermore,the total pressure distortion no longer changes significantly when the number of holes is too large.The proposed double simulation board structure is capable of obtaining the following two types of distorted flow fields:symmetrical dual lowpressure zones and low-pressure zones with high distortion intensity at the compressor inlet.The distortion equivalent simulation method proposed in this work can obtain various types of distortion spectra,thereby meeting the distortion parameter requirements for the antidistortion testing of marine engines.

Fine-Grained Ship Recognition Based on Visible and Near-Infrared Multimodal Remote Sensing Images: Dataset,Methodology and Evaluation

Fine-grained recognition of ships based on remote sensing images is crucial to safeguarding maritime rights and interests and maintaining national security.Currently,with the emergence of massive high-resolution multi-modality images,the use of multi-modality images for fine-grained recognition has become a promising technology.Fine-grained recognition of multi-modality images imposes higher requirements on the dataset samples.The key to the problem is how to extract and fuse the complementary features of multi-modality images to obtain more discriminative fusion features.The attention mechanism helps the model to pinpoint the key information in the image,resulting in a significant improvement in the model’s performance.In this paper,a dataset for fine-grained recognition of ships based on visible and near-infrared multi-modality remote sensing images has been proposed first,named Dataset for Multimodal Fine-grained Recognition of Ships(DMFGRS).It includes 1,635 pairs of visible and near-infrared remote sensing images divided into 20 categories,collated from digital orthophotos model provided by commercial remote sensing satellites.DMFGRS provides two types of annotation format files,as well as segmentation mask images corresponding to the ship targets.Then,a Multimodal Information Cross-Enhancement Network(MICE-Net)fusing features of visible and near-infrared remote sensing images,has been proposed.In the network,a dual-branch feature extraction and fusion module has been designed to obtain more expressive features.The Feature Cross Enhancement Module(FCEM)achieves the fusion enhancement of the two modal features by making the channel attention and spatial attention work cross-functionally on the feature map.A benchmark is established by evaluating state-of-the-art object recognition algorithms on DMFGRS.MICE-Net conducted experiments on DMFGRS,and the precision,recall,mAP0.5 and mAP0.5:0.95 reached 87%,77.1%,83.8%and 63.9%,respectively.Extensive experiments demonstrate that the proposed MICE-Net has more excellent performance on DMFGRS.Built on lightweight network YOLO,the model has excellent generalizability,and thus has good potential for application in real-life scenarios.

基于水动力载荷混合数据集的高精度神经网络代理模型构建

In this work,we constructed a neural network proxy model(NNPM)to estimate the hydrodynamic resistance in the ship hull structure design process,which is based on the hydrodynamic load data obtained from both the potential flow method(PFM)and the viscous flow method(VFM).Here the PFM dataset is applied for the tuning,pre-training,and the VFM dataset is applied for the fine-training.By adopting the PFM and VFM datasets simultaneously,we aim to construct an NNPM to achieve the high-accuracy prediction on hydrodynamic load on ship hull structures exerted from the viscous flow,while ensuring a moderate data-acquiring workload.The high accuracy prediction on hydrodynamic loads and the relatively low dataset establishment cost of the NNPM developed demonstrated the effectiveness and feasibility of hybrid dataset based NNPM achieving a high precision prediction of hydrodynamic loads on ship hull structures.The successful construction of the high precision hydrodynamic prediction NNPM advances the artificial intelligence-assisted design(AIAD)technology for various marine structures.

预测规则波浪中船舶运动和载荷的频域三维计算机程序

The development of an in-house computer program for determining the motions and loads of advancing ships through sea waves in the frequency domain,is described in this paper.The code is based on the potential flow formulation and originates from a double-body code enhanced with the regular part of the velocity potential computed using the pulsing source Green function.The code is fully developed in C++language with extensive use of the object-oriented paradigm.The code is capable of estimating the excitation and inertial radiation loads or arbitrary incoming wave frequencies and incidence angles.The hydrodynamic responses such as hydrodynamic coefficients,ship motions,the vertical shear force and the vertical bending moment are estimated.A benchmark container ship and an LNG carrier are selected for testing and validating the computer code.The obtained results are compared with the available experimental data which demonstrate the acceptable compliance for the zero speed whereas there are some discrepancies over the range of frequencies for the advancing ship in different heading angles.

不同装载条件下小型渔船参数横摇的非定常RANS CFD仿真

Fishing boats have unique features that make them prone to changing loading conditions.When the boat leaves the port,the empty fish tank gradually fills up during fishing operations which may result in parametric roll(PR).This dangerous phenomenon that can lead to capsizing.The present study aims to understand better the behaviour of parametric roll in fishing boats and its relation to changing loading conditions.The study considers the effects of displacement and the GM/KM ratio on parametric roll,as well as the longitudinal flare distribution at the waterline.Two assessments to detect the parametric roll occurrence in early stage were carried out by using the level 1 assessment of parametric roll based on the Second Generation of Intact Stability criteria(SGIS)from International maritime Organisation(IMO)and the Susceptibility criteria of Parametric roll from the American Bureau of Shipping(ABS).Then,the CFD method is used to predict the amplitude of the parametric roll phenomenon.The results provide important insights to fishing vessel operators on how to manage loading conditions to maintain stability and avoid hazardous situations.By following the guidelines outlined in this study,fishing boats can operate more safely and efficiently,reducing the risk of accidents and improving the overall sustainability of the fishing industry.

Ship recognition based on HRRP via multi-scale sparse preserving method

In order to extract the richer feature information of ship targets from sea clutter, and address the high dimensional data problem, a method termed as multi-scale fusion kernel sparse preserving projection(MSFKSPP) based on the maximum margin criterion(MMC) is proposed for recognizing the class of ship targets utilizing the high-resolution range profile(HRRP). Multi-scale fusion is introduced to capture the local and detailed information in small-scale features, and the global and contour information in large-scale features, offering help to extract the edge information from sea clutter and further improving the target recognition accuracy. The proposed method can maximally preserve the multi-scale fusion sparse of data and maximize the class separability in the reduced dimensionality by reproducing kernel Hilbert space. Experimental results on the measured radar data show that the proposed method can effectively extract the features of ship target from sea clutter, further reduce the feature dimensionality, and improve target recognition performance.