Characteristics Of Ship Research Articles

Map Space Modeling Method Reflecting Safety Margin in Coastal Water Based on Electronic Chart for Path Planning.

Map space composition is the first step in ship route planning. In this study, a map modeling method for path planning is proposed. This method incorporates the safety margin based on the theory of geographic space existing in coastal waters, maneuvering space according to ship characteristics, and the psychological buffer space of a ship navigator. First, the obstacle area was segmented using the binary method-a segmentation method-based on the international standard electronic chart image. Next, the margin space was incorporated through the morphological algorithm for the obstacle area. Finally, to minimize the space lost during the route search, the boundary simplification of the obstacle area was performed through the concave hull method. The experimental results of the proposed method resulted in a map that minimized the area lost due to obstacles. In addition, it was found that the distance and path-finding time were reduced compared to the conventional convex hull method. The study shows that the map modeling method is feasible, and that it can be applied to path planning.

Sentinel-2 Research on the Detection and Classification Methods of Maritime Ship Targets from Remote Sensing Images

There are problems such as low recognition accuracy and large classification error in the existing classification methods for ship identification based on optical remote sensing images. In this paper, we will analyze the characteristics of ships and determine the indicative factors for applying remote sensing to monitor ships in combination with optical remote sensing images. Using optical remote sensing image data, combined with U-Net and AttU-Net deep neural network models, we assist in extracting new remote sensing indices with strong generality and clear physical meaning, and establishing rules for monitoring ships, so as to establish a more general and clear physical meaning of the monitoring and identification method of remote sensing satellite images. The method is applied and evaluated with port optical remote sensing image data. The data show that compared with traditional machine learning methods, the accuracy of ship monitoring using U-Net and AttU-Net deep learning models in this paper reaches 89.04%, and the recall rate and accuracy rate are better than SVM. it shows that the model can detect ships effectively.

A Research on Autonomous Collision Avoidance under the Constraint of COLREGs

In this paper, a decision-making model suitable for the collision avoidance (CA) of numerous target ships (TSs) is proposed, based on the principle of ship collision avoidance geometry and the characteristics of numerous target ships’ collision avoidance at sea. To ensure that the collision avoidance behaviors of own-ship (OS) are subject to the International Regulations for Preventing Collisions at Sea (COLREGS), this paper gives full consideration to the requirements of COLREGS within the scope of CA action and the time of collision avoidance. A ship CA simulation is established based on the Mathematical Modeling Group (MMG) model. To optimize the CA decision-making model, the influence of hydrodynamic force on steering time required to reach the new course is integrated into the collision avoidance simulation system. The simulation results show that the method can quickly and effectively determine a collision avoidance decision under the complex situation of numerous target ships and static obstacles, and it can consider the unpredictable strategies used by other vessels.

Multi-scale ship target detection using SAR images based on improved Yolov5

Synthetic aperture radar (SAR) imaging is used to identify ships, which is a vital task in the maritime industry for managing maritime fisheries, marine transit, and rescue operations. However, some problems, like complex background interferences, various size ship feature variations, and indistinct tiny ship characteristics, continue to be challenges that tend to defy accuracy improvements in SAR ship detection. This research study for multiscale SAR ships detection has developed an upgraded YOLOv5s technique to address these issues. Using the C3 and FPN + PAN structures and attention mechanism, the generic YOLOv5 model has been enhanced in the backbone and neck section to achieve high identification rates. The SAR ship detection datasets and AirSARship datasets, along with two SAR large scene images acquired from the Chinese GF-3 satellite, are utilized to determine the experimental results. This model’s applicability is assessed using a variety of validation metrics, including accuracy, different training and test sets, and TF values, as well as comparisons with other cutting-edge classification models (ARPN, DAPN, Quad-FPN, HR-SDNet, Grid R-CNN, Cascade R-CNN, Multi-Stage YOLOv4-LITE, EfficientDet, Free-Anchor, Lite-Yolov5). The performance values demonstrate that the suggested model performed superior to the benchmark model used in this study, with higher identification rates. Additionally, these excellent identification rates demonstrate the recommended model’s applicability for maritime surveillance.

A Rational Approach to the Ecological Transition in the Cruise Market: Technologies and Design Compromises for the Fuel Switch

Supporting policies to achieve a green revolution and ecological transition is a global trend. Although the maritime transport of goods and people can rightly be counted among the least polluting sectors, much can be done to further reduce its environmental footprint. Moreover, to boost the ecological transition of vessels, a whole series of international regulations and national laws have been promulgated. Among these, the most impactful on both design and operational management of ships concern the containment of air-polluting emissions in terms of GHG, NOx, SOx and PM. To address this challenge, it might seem that many technologies already successfully used in other transport sectors could be applied. However, the peculiar characteristics of ships make this statement not entirely true. In fact, technological solutions recently adopted, for example, in the automotive sector must deal with the large size of vessels and the consequent large amount of energy necessary for their operation. In this paper, with reference to the case study of a medium/large-sized passenger cruise ship, the use of different fuels (LNG, ammonia, hydrogen) and technologies (internal combustion engines, fuel cells) for propulsion and energy generation on board will be compared. By imposing the design constraint of not modifying the payload and the speed of the ship, the criticalities linked to the use of one fuel rather than another will be highlighted. The current limits of application of some fuels will be made evident, with reference to the state of maturity of the relevant technologies. Furthermore, the operational consequences in terms of autonomy reduction will be presented. The obtained results underline the necessity for shipowners and shipbuilders to reflect on the compromises required by the challenges of the ecological transition, which will force them to choose between reducing payload or reducing performance.

MTU-Net: Multilevel TransUNet for Space-Based Infrared Tiny Ship Detection

Space-based infrared tiny ship detection aims at separating tiny ships from the images captured by Earth-orbiting satellites. Due to the extremely large image coverage area (e.g., thousands of square kilometers), candidate targets in these images are much smaller, dimer, and more changeable than those targets observed by aerial- and land-based imaging devices. Existing short imaging distance-based infrared datasets and target detection methods cannot be well adopted to the space-based surveillance task. To address these problems, we develop a space-based infrared tiny ship detection dataset (namely, NUDT-SIRST-Sea) with 48 space-based infrared images and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$17\,598$ </tex-math></inline-formula> pixel-level tiny ship annotations. Each image covers about <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10\,000$ </tex-math></inline-formula> km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of area with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10 \ 000\,\, \times \ 10 \ 000$ </tex-math></inline-formula> pixels. Considering the extreme characteristics (e.g., small, dim, and changeable) of those tiny ships in such challenging scenes, we propose a multilevel TransUNet (MTU-Net) in this article. Specifically, we design a vision Transformer (ViT) convolutional neural network (CNN) hybrid encoder to extract multilevel features. Local feature maps are first extracted by several convolution layers and then fed into the multilevel feature extraction module [multilevel ViT module (MVTM)] to capture long-distance dependency. We further propose a copy–rotate–resize–paste (CRRP) data augmentation approach to accelerate the training phase, which effectively alleviates the issue of sample imbalance between targets and background. Besides, we design a FocalIoU loss to achieve both target localization and shape description. Experimental results on the NUDT-SIRST-Sea dataset show that our MTU-Net outperforms traditional and existing deep learning-based single-frame infrared small target (SIRST) methods in terms of probability of detection, false alarm rate, and intersection over union. Our code is available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/TianhaoWu16/Multi-level-TransUNet-for-Space-based-Infrared-Tiny-ship-Detection</uri>

Analysis of the Experimental Data of Slamming Loads on a Liquefied Natural Gas Carrier in Abnormal Waves

Abstract The objective of the paper is to identify slamming characteristics of ships in abnormal waves by analyzing the experimental slamming loads for a liquefied natural gas (LNG) carrier from the model tests of the ship, which were conducted at the Ocean Engineering Division of the Technical University Berlin at a model scale of 1:70. To validate the experiments, the numerical results from a time domain nonlinear strip theory code are compared with the measurement of the ship motions and vertical bending moment amidships of the LNG carrier in the New Year wave. The time series of the slamming pressures on different locations (on the bow and stern) obtained in the experiments are analyzed and discussed by studying the peaks using the analytical distribution models, namely, Weibull distribution, generalized extreme value distribution, and the Gumbel distribution. The extreme values of the pressure peaks obtained using the three distribution models are compared. Discussion is also provided for the results with two different Froude numbers in order to check the effects of the ship speed on the phenomenon.

Analysis of the impact of operation conditions on the bulk carriers design characteristics

The paper presents the results of a comparative analysis of the design characteristics of ships currently used for coal transporting from the ports of Far East of Russia to the Asia-Pacific countries with mathematical modeling and optimization results oriented to the economic criteria. The effectiveness and expediency of using ships in the certain directions of coal transportation is considered. The results of the analysis of the influence of operating conditions to the optimal values of the design characteristics (speed and payload capacity) and economic criteria of the functional efficiency of bulk carriers are given. The mathematical model for optimal values of the design characteristics of bulk carriers was used. The model takes into an account basic calculations of ship design and theory disciplines which are used at the initial stages of design. The calculations were made for the operating conditions of a specialized high-tech coal transshipment terminal with is located in the south part of Primorsky Krai. The economic efficiency affecting factors and their variations ranges were analysed. The research results can be used at the preliminary stages of ship design for general characteristics calculation and transportation costs optimization.

Semantic Recognition of Ship Motion Patterns Entering and Leaving Port Based on Topic Model

Recognition and understanding of ship motion patterns have excellent application value for ship navigation and maritime supervision, i.e., route planning and maritime risk assessment. This paper proposes a semantic recognition method for ship motion patterns entering and leavingport based on a probabilistic topic model. The method enables the discovery of ship motion patterns from a large amount of trajectory data in an unsupervised manner and makes the results more interpretable. The method includes three modules: trajectory preprocessing, semantic process, and knowledge discovery. Firstly, based on the activity types and characteristics of ships in the harbor waters, we propose a multi-criteria ship motion state recognition and voyage division algorithm (McSMSRVD), and ship trajectory is divided into three sub-trajectories: hoteling, maneuvering, and normal-speed sailing. Secondly, considering the influence of port traffic rules on ship motion, the semantic transformation and enrichment of port traffic rules and ship location, course, and speed are combined to construct the trajectory text document. Ship motion patterns hidden in the trajectory document set are recognized using the Latent Dirichlet allocation (LDA) topic model. Meanwhile, topic coherence and topic correlation metrics are introduced to optimize the number of topics. Thirdly, a visualization platform based on ArcGIS and Electronic Navigational Charts (ENCs) is designed to analyze the knowledge of ship motion patterns. Finally, the Tianjin port in northern China is used as the experimental object, and the results show that the method is able to identify 17 representative inbound and outbound motion patterns from AIS data and discover the ship motion details in each pattern.

Polarimetric SAR Ship Detection Based on Scattering Characteristics

A synthetic aperture radar is crucial for detecting ships. In this study, to improve the detection capability of weakly scattering targets and reduce false alarms, a detector <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$F_{vh}$ </tex-math></inline-formula> based on the scattering characteristics of ships is proposed after an in-depth study of the differences between ship and sea surface scattering mechanisms. The volume scattering mechanism and the helix scattering mechanism are fused, and the volume scattering power is used to describe the scattering structure on the ship, and the helix scattering power is used to increase the difference between the ship and the sea surface. We test on 4 GF-3 fully polarized synthetic aperture radar data. The experimental results show that <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$F_{vh}$ </tex-math></inline-formula> has improved detection capability and can successfully minimize false alarm generation.

A Quasi-Intelligent Maritime Route Extraction from AIS Data.

The rapid development and adoption of automatic identification systems as surveillance tools have resulted in the widespread application of data analysis technology in maritime surveillance and route planning. Traditional, manual, experience-based route planning has been widely used owing to its simplicity. However, the method is heavily dependent on officer experience and is time-consuming. This study aims to extract shipping routes using unsupervised machine-learning algorithms. The proposed three-step approach: maneuvering point detection, waypoint discovery, and traffic network construction was used to construct a maritime traffic network from historical AIS data, which quantitatively reflects ship characteristics by ship length and ship type, and can be used for route planning. When the constructed maritime traffic network was compared to the macroscopic ship traffic flow, the Symmetrized Segment-Path Distance (SSPD) metric returned lower values, indicating that the constructed traffic network closely resembles the routes ships transit. The result indicates that the proposed approach is effective in extracting a route from the maritime traffic network.

Mechanical Mechanism and Dynamic Characteristics of Barge–Whole Bridge Collision Behaviours

Collision between a moving ship and a bridge in inner rivers is a frequent occurrence that seriously endanger the safety of the bridge. Existing studies mostly address the action of a ship colliding with a bridge pier that is used as a substitution of the associated whole bridge. Such a simplification necessarily induces errors in reflecting the mechanical mechanism and dynamic characteristics of ship–whole bridge collisions. To circumvent this problem, the mechanical behavior of collision between a barge and a whole bridge was studied via elaborating a delicate barge–whole bridge collision simulation underpinned by impact mechanics and materials theories. The main contributions of this study are fourfold: (i) the entire process of the collision between the barge and a whole bridge was fully inspected; (ii) the progressive evolution of collision-induced damage in the bridge pier as well as in the barge was investigated; (iii) the effect of impact velocity, impact angle and barge mass on the collision behavior were elucidated, and (iv) the influences of the superstructure of the whole bridge on the peak value and temporal feature of the impact force, evolution of damage, and top displacement of the bridge pier were clarified. This study yielded more accurate, comprehensive, and reliable results on dynamics and damage evolution of collision in comparison with the outcome of a barge colliding a pier. These findings collectively reveal the mechanical mechanism and dynamic characteristics of collision, providing a scientific basis for developing post-collision damage assessment methods and anti-collision facilities.

Ship routing optimisation based on forecasted weather data and considering safety criteria

AbstractA weather routing tool is presented based on forecasted weather data along the route and considering safety aspects. The tool aims to determine the optimal path for the minimisation of the fuel oil consumption, ensuring a safe passage. It is developed in MATLAB and considers detailed ship characteristics. Specifically, ship's motions and fuel oil consumption of the main engine during a potential path are estimated. For the latter, a physics-based model for a specific vessel is developed where tools of different level of detail are utilised to calculate the various resistance components. A speed management strategy along the route is specified as well as safety criteria representing acceptable limits of ship's responses. When the set criteria and constraints have been set, a genetic algorithm is used to find the optimal route by means of ship's heading or by considering both heading and ship's power settings as variables to minimise the fuel oil consumption. The search space of the algorithm lies within a predefined envelop, but still the evolutionary optimisation approach used has no pre-assigned values to any possible candidate waypoint.

Numerical Simulation on Dynamic Characteristics of Longitudinal Launching of Large Container Ships

The upsizing and rapid development of container ships has resulted in many large ships launching in small slipways due to the lagging of advanced equipment. In particular, the dynamic characteristics of these large ships in the longitudinal launching operation under restricted water are yet to be studied in detail. In this study, a ship model to simulate the longitudinal launching process of an 8500 TEU container ship was created based on the URANS method. The ship resistance in calm water was determined and validated against the experimental data. The influence of the stern appendage on the ship’s resistance and the flow field around the hull, with and without the aft poppet, under various water-depth-to-draught ratios was analyzed. A comparison of the ship’s resistance between the numerical and the experimental data shows that the difference is minimal, within 1.5%. The numerical results revealed that the aft poppets change the flow pattern and effectively reduce the pressure drag in the drifting stage. The shallow water causes a restraining effect on the ship. The proposed analytical approach in the numerical analysis, considering the aft poppet and the water depth, could provide a better simulation for a large ship’s longitudinal launching operation.

Stress-distribution characteristics of cruise ship based on multiple-beam method

Cruise ship usually has a plump superstructure with multiple decks, and the effective degree of each deck participating in the longitudinal bending is a complicated but unavoidable issue in initial design. This paper proposes one multiple-beam method to examine the stress-distribution characteristics and the bending efficiency of the superstructure. The method assumes that the main hull and each deck of the superstructure can be regarded as thin-walled beams, with vertical forces and horizontal shear forces interacting between adjacent decks. The purpose of the method is to simplify the multiple-beam problem through reasonable assumptions, so as to obtain an approximate solution method with sufficient accuracy. The distribution of longitudinal stress and the bending efficiency of the superstructure of one inland cruise ship is calculated via classical beam theory, two-beam theory, and the multiple-beam method proposed in this paper, and the results are compared with those obtained by the finite-element method. The present research is of reference significance for structural safety and reliability design of cruise ship.

Construction of Knowledge Graph for Flag State Control (FSC) Inspection for Ships: A Case Study from China

The flag state control (FSC) inspection is an important measure to ensure maritime safety. However, it is difficult to improve ship safety management efficiency using data mining due to the scattered and multi-source ship inspection knowledge. In this paper, the emerging knowledge graph technology is used to integrate multi-source knowledge for the FSC inspection. Firstly, an ontology model is built to systematically describe the knowledge and guide the construction of the data layer of the knowledge graph. Then, the BERT-BiGRU-CRF model is used to extract entities from the unstructured data of the FSC inspection. The extracted results are associated with structured and semi-structured data and stored in the graph database Neo4j to construct the knowledge graph. In addition, a case study of the FSC inspection knowledge graph of Dafeng Port in Yancheng, China, is conducted to verify the strength of the proposed method. The results show that the knowledge graph can correlate trivial knowledge and benefit the efficiency of the FSC inspection. Moreover, the knowledge graph can reflect the deficiency characteristics of ships and support the safety management of water transportation.

Formation of the infrastructure complex inland water transport

The article presents the results of a study on the prospects for the formation of a single infrastructure complex of inland waterway transport. The purpose of the study is to identify the prerequisites for the development of container transportation by inland waterways of Russia and substantiate the characteristics of the infrastructure framework of the inland waterway transport. The objectives of the study were the analysis of the provisions of the draft Transport Strategy until 2035, the analysis of foreign experience in the development and problems of functioning of foreign water transport systems, the identification of problems and urgent tasks of the development of transportation involving inland waterway transport. The article suggests the directions of scientific developments relevant to the domestic water transport system within the framework of the general research topic related to the renewal of infrastructure for the development of combined and multimodal transportation on the inland waterways of Russia, the justification of the parameters and characteristics of container ships, the justification of effective multi-modal schemes and container lines on the river-sea sections, modeling of standard (standardized) multimodal river terminals, the formation of digital platforms for the organization of cargo transportation in containers along the river routes of the country, as well as the formation of a system of regulations governing direct mixed and multimodal cargo transportation. As the results of the study, the standardization of the parameters of which will allow forming on its basis the framework of a multimodal system for the delivery of bulk carriers in containers with the participation of inland waterway transport.

A ROUTE PLANNING METHOD FOR COASTAL NAVIGATION OF SMALL SHIPS

This study proposes route planning considering the characteristics of small ships sailing on coasts. An electronic chart based on the S-57 standard object and attributes catalogue was used. A Quadtree data structure was used for modelling an environment for route planning. The main idea of Hierarchical Pathfinding A* (HPA*) was adapted to our route planning algorithm. The route planning method proposed in this study can find route for small ships within a short time that the users can understand. In addition, it consumes little computer resources so that there is no difficulty in operating it on the computer of the small ships. In addition, the program was verified by conducting route planning tests in various areas along the coastal areas of Korea.

Framework for data-driven propeller and rudder modeling for ship maneuvering

The maneuvering characteristics of a vessel must be understood for safe and efficient operation in the ocean environment. During a maneuver, the propeller and rudder can operate in off-design conditions. Computational Fluid Dynamics is a useful tool to capture flow effects like viscous separation, but it is too costly to perform a large number of maneuvering simulations with a discretized propeller. The propeller has much smaller time and length scales compared to the maneuver, which drives up the computational cost when the propeller is discretized. Body-force propeller models provide a less expensive means of modeling a maneuvering vessel with CFD, but many propeller models can be inaccurate when the propeller operates off-design. This work develops a framework for a data-driven propeller and rudder model which is trained with high-fidelity simulations of the propeller and deflected rudder operating in the wake of the hull. The dimensionless velocity and oblique flow angle are used as features for the propeller and rudder model. The uncertainty of the data-driven model is dependent upon the error inherent in the training and validation data as well as the uncertainty induced by using a surrogate model to determine the response surface. The underlying uncertainties are examined. The calculated propeller and rudder forces from the data-driven model are compared to the experimental forces. The turning circle characteristics of the KRISO Container ship at model scale are examined with the implemented data-driven propeller and rudder model. The accuracy of the method used to train the model is maintained and the computational cost of modeling a maneuvering vessel is dramatically reduced compared to using a discretized propeller.

Parametric trend life cycle assessment for hydrogen fuel cell towards cleaner shipping

Given the rapidly increasing concern of the climate change, this paper is aimed to answer whether hydrogen fuel cells can truly be a green solution in the shipping sector from a life cycle perspective. To achieve this goal, the parametric trend life cycle assessment which is LCA-based methodology was applied for around 2000 ships presently engaged in international and domestic services. The lifecycle environmental impacts of various hydrogen production methods were evaluated, including steam methane reforming, coal gasification, methanol cracking, and electrolysis via wind energy. The performance of three representative types of fuel cell systems, proton exchange membrane fuel, molten carbonate fuel cell, and solid oxide fuel cell were taken into account. The steam methane reforming and coal gasification processes were found to have the greatest environmental potentials across their lifetime. However, this paper points out that steam methane reforming could make better lifecycle merits than conventional diesel or LNG products, if production pathways are properly proposed. Additionally, when using LNG as the primary fuel source for fuel cells, it was found that the LNG upstream phase would produce about 100 times more emissions than the downstream phase. The research findings were summarized and condensed into a form of lifetime environmental indicators which enable us to understand/evaluate the quantified correlations between holistic environmental impacts of fuel cells and ship characteristics. The research findings are expected to assist stakeholders in making informed decisions, while also providing an insight into near-future regulatory frameworks and policy making for a green hydrogen maritime economy.