Ship Types Research Articles

Development of convolutional neural network algorithm on ships detection in Natuna Islands-Indonesia using land look satellite imagery

Indonesia's vast waters require much time and energy to monitor illegal fishing. Utilizing remote sensing technology is the right solution for monitoring, controlling, and surveying (MCS) systems. The phenomenon of particular concern to the ship detection process using a remote sensing system is the form of images with various positions due to the ship's rectangular and narrow dimensions and the high viewing angle from space. This condition differs if the shooting is carried out close to objects on the earth's surface. Considering the situation of recording data from a very far position, refining the convolutional neural network (CNN) method for processing remote sensing image data continues to be developed, primarily related to detecting ships. The latest development of the CNN algorithm shows its ability to see vessels by taking into account the orientation factor of objects at sea level with almost perfect accuracy. The problem is that the system needs to be able to detect in detail the movements and types of ships recorded by remote sensing satellite sensors. Therefore, an automatic ship detection instrument is needed based on Land look USGS base map high-resolution image data to maintain maritime sovereignty in Indonesia. Image data were acquired from the waters of the Natuna islands and taken at a scale of 1: 2000. The data obtained from the acquisition are five high-resolution image data 1680 × 840 pixels, in which there are 32 ship image data and 3100 non-ship image data 80 × 80 pixels. The ship image data is then processed by color and geometry augmentation to produce 1440 new data. The image processing stage afterward is reading and splitting the dataset, creating a CNN, and training and testing the CNN model. Based on the results of the ship and non-ship objects detection with the CNN model, the accuracy results are 99.78% and 99.24%, respectively.

A study on analysis of green house gaseous emitted from ships through operation information

ABSTRACT In line with the global trend for environmental protection, the shipping industry is also making significant efforts. The International Maritime Organization introduced carbon intensity indicator and energy efficiency existing ship index to reduce greenhouse gases and presented “Initial IMO Strategy on reduction of GHG emissions from ships”. In contrast to previous environmental indices, carbon intensity indicator is calculated based on the operation information of ship. In this study, the annual fuel consumption was calculated based on the operation information of 4,151 ships and CO2, N2O, and CH4 emissions among greenhouse gases were estimated. The results of the study showed that CO2 accounted for 98% of the greenhouse gases emitted from ships, the highest, and N2O and CH4 were found to be insignificant at 1.5% and 0.5%. The major types of ships that emitted greenhouse gases were cargo ships, chemical tankers, oil tankers, and gas carriers. Ships subject to data collection system and carbon intensity indicator regulations include only 69% of the fuel consumed by all ships. This proportion increases to 87% of the total fuel consumption if it is expanded to include ships over 400 GT that are regulated by energy efficiency existing ship index.

Study on simplified estimation formula for long-term predictions of ship response in waves – Application to vertical bending moment

This paper proposed a simplified formula for the long-term maximum wave-induced vertical bending moment (VBM) of ships. First, as a general theory independent of the type of ship response, the relationship between the long-term response and the peak value of the response amplitude operation (RAO) was discussed and its governing factors were clarified, and the methodology of the simplified formula development approach was presented. In particular, if the RAO has two properties, “band parameter-invariance” and “peak value-wavelength correspondence,” the long-term response can be expressed by only the peak value of RAO. Based on this approach, a simplified formula for the long-term maximum VBM was presented. First, focusing on the characteristics of the VBM-RAO in the case of zero speed, a formula with zero speed was derived, and based on this, a formula with a speed of 5 knots was derived. These formulae were validated by comparison with the results of a numerical analysis using 154 actual merchant ship models. The proposed method for developing the simplified formula is physically clear and is valid for all types of ships and responses.

Analysis Of River Cleaning Ship Design With The Trasher Boat Concept By Using MAXSURF

Ships are a means of transportation for moving materials and goods from one place to another. Along with this increase, it was also followed by the development of other industries so that it had an impact. However, in increasing these activities, in addition to generating benefits, it also creates new impacts through the waste produced. Several work boats are made to solve problems related to the type of work according to needs. The solution that can be used to overcome the accumulation of garbage in the river is to use the help of a Trash Skimmer Boat. This work boat is a type of special ship that is used to carry out waste collection in rivers, lakes, seas and canals. By using the help of Maxsurf Software, the main size is L = 100 cm, B = 30 cm H = 15 cm, T = 3.54 cm with a payload capacity of 3 kg. It has the following data: Displacement = 6,968 kg ; block coefficient (Cb) = 0.387; Prismatic Coef (Cp) = 0.832.
 Keyword : Ship, Workboat, Trasher boat, Trash Skimmer Boat

MANAJEMEN PROYEK SISTEM INFORMASI PERANCANGAN APLIKASI GOSHIP BERBASIS MOBILE ANDROID

Sea crossing transportation is a link for community activities in Balikpapan Bay by ordering speedboats and klotok boats. The Goship application is an information system in the form of an android-based application that is used to facilitate sea crossing transportation services to run effectively and efficiently. The Goship application offers direct booking services between drivers and passengers only via smartphones in the application. . Passengers who are going to cross can be made easier by simply using the application on their smart phone by clicking GO and can order the type of ship and the desired destination. The estimated time for designing and making this program is about four months. It is estimated that the costs incurred in the process of this program are around Rp. 2,600,000, -. the energy needed in making this program is two people and one programmer.

Financial Implications of the COVID-19 Pandemic on the Container Ship Time Charter Business

This study examines the financial implications of the COVID-19 pandemic on the container ship time charter business. In this context, the container charter transactions were derived from the Clarksons Research Database, which included the ship types, daily charter fees, ship ages, and total charter days. The empirical analysis employed the K-Means Algorithm to cluster the observations in which the elbow curves revealed three cluster centers in the pre-COVID period and four in the post-COVID era, respectively. Based on the industry-wide used threshold definitions, the clusters were then named according to the mean value of given features. In addition, the relative weight of each cluster was disclosed based on the number of transactions falling into the respective cluster. Accordingly, the pre-COVID period clusters were described as intermediate-rated middle-termed young-aged intermediate-TEU container ships; low-rated middle-termed middle-aged feeders; and intermediate-rated long-termed middle-aged upper intermediate-TEU container ships. As for the post-COVID era, the cluster definitions were determined as intermediate-rated middle-termed young-aged feeders; intermediate-rated middle-termed old-aged feeders; high-rated long-termed middle-aged intermediate-TEU container ships; and high-rated short-termed middle-aged intermediate-TEU container ships. The findings suggested that the pandemic boosted the demand for relatively lower TEU container ships such as the feeders in which the criterium of ship age lost its importance due to availability reasons in the market. In addition, the pandemic led to higher charter rates which was a prioritized factor over the charter period.

ANALISA KEKUATAN KONSTRUKSI PADA DESAIN RAMP DOOR KAPAL JENIS MULTIPURPOSE

Ferry ships generally have various kinds of cargo such as passengers, motorbikes, livestock, or goods carried by passengers. The process of transferring the load requires a special path or path in its transfer which is called a Ramp door. One of the important factors in making Ramp doors is their strength, so there is a need for strength analysis in rampdoor design on certain types of ships, one of which is multipurpose ships, strength analysis on ramp doors for certain loads can be visualized using solidwork software.In a comparison of the strength analysis between using the software and calculating the stress, the difference is not that significant and the biggest difference is the calculation of the stress on the load of passengers riding motorbikes when going through the Ramp door. From the results obtained in the calculations and the software, there is a difference of 4.29 % with the safety factor in accordance with the rules of safety factor, which exceeds the number 1.

Analysis Of The Influence Of Ship Speed On Seakeeping Motion On The Ship

Ship motion (Seakeeping) is the ability of a ship to survive under any conditions. Therefore this capability is clearly an important aspect in terms of ship design (Ship Design). The shape of the hull greatly influences the characteristics of the movement and operability of the ship itself. Vessel operability is the amount of time at sea during which the structure can still operate according to established criteria and its correlation to the height at which the weather will occur. In this study, an analysis of 3 degrees of freedom of translational movement and heave roll and pitch rotation was carried out on the model of a fast ship type planing hull at regular waves with parameters of body mass, radius of gyration, damping and others presented in the form of Response Amplitude Operator (RAO) images.

Towards the Testing and Validation of Autonomous Ships: Design of a Variable Stability Ship Control System

Maritime autonomous surface ships (MASSs) have received increased attention in both academic research and industrial applications in the global shipping and shipbuilding industry in recent years. According to its definition, a MASS can independently operate without human interaction. This brings the problem of how to test and evaluate the capabilities of the autonomous navigation control system developed for MASS. This paper proposes the novel concept of a variable stability ship and the design of its control system. A variable stability ship consists of a model-scaled ship, a model-following controller, and a hardware and software platform to implement its functions. The variable stability ship can replicate the dynamic responses of different reference ships despite their dissimilarities in physical parameters and hydrodynamic characteristics with the design of the model-following controller. Therefore, it can be used to test the performance of different control strategies on various ship types such that the R&D costs of physical model-based tests can be reduced, as well as shortening the time spent in developing physical ship models. Preliminary simulations are carried out to show its effectiveness and applicability.

An experimental study of stabilizing ordinary fishing nets (SOFNets) on a stationary SWATH ship seakeeping behavior under irregular waves

The present research aims to experimentally demonstrate the effectiveness of an innovative method for reducing the ship motions using Stabilizing Ordinary Fishing Nets that we call it SOFNets from now on. To this end, the influence of a range of SOFNets on the seakeeping behavior of a Small-Waterplane-Area Twin Hull (SWATH) ship in irregular waves is investigated physically in a towing tank laboratory. Understanding, controlling, and improving the seakeeping behavior of ships has always been a major concern of ship designers. As a result, various techniques have been utilized to stabilize ships, including the use of anti-rolling tanks, gyrostabilizers, and stabilizer fins, all three of which are bulky, heavy, and costly. These disadvantages have prevented many ships from using conventional rolling reduction methods. In contrast, the present idea, SOFNets, does not suffer from these shortcomings and can be used in any type of ship with any tonnage. The prepared model is tested in the towing tank of the National Iranian Marine Laboratory (NIMALA) using three different net samples in order to compare the behavior of those nets. This research has introduced for the first time the concept of using a SOFNets to reduce motion amplitude in waves. The length of the SWATH model was 2.1 m, and the tests were carried out according to the International Towing Tank Conference (ITTC) guidelines. The research findings for the SWATH ship indicate that the heave and pitch amplitudes in the head sea state were reduced by up to 21%, and the roll amplitude in the beam sea state was reduced by up to 36%.

Effects of ship domain shapes on ship collision risk estimates considering collision frequency and severity

This study aims to estimate ship collision risk considering the occurrence frequency and severity simultaneously, as well as to explore the influence of ship domain shapes on estimation results in the Yangtze River estuary waterway. In contrast to the circular ship domain, the elliptical domain may result in an overestimate for head-on collisions and overtaking collisions, while it may underestimate the small-angle and large-angle crossing collision frequency. Conversely, the sector domain may underestimate the occurrence frequency of all collision types. Results also reveal that overtaking encounters are the most common type with a relatively low severity degree, while large-angle crossing collisions are associated with a lower frequency but a higher potential for causing serious consequences. The collision occurrence likelihood and severity are a little higher for the passenger ship type. Furthermore, two high-risk areas are found to be located between longitudes of 121°33′E and 121°46′E, 121°50′E and 121°58′E, respectively. The results of this study are beneficial for a better understanding of the overall collision risk in the Yangtze River estuary waterway.

Role of Port Tugs in Ship-Borne Emissions: An Analysis in Turkey's Izmit Bay

Thanks to the awareness created by the concrete effects of global warming and climatic irregularities, concepts such as carbon emissions, polluting gases, internal combustion engines, energy efficiency are gaining more and more importance in our lives globally. In this context, the maritime sector, which provides the transfer of 90% of global trade, has become the center of attention with its ships boasting huge machinery and has also been a subject of exhaust emission studies. The fact that approximately 70% of ship emissions occur in coastal areas requires more scrutiny of ships operating in these areas. Providing docking and departing services for ports, having small hull sizes compared to other ships but featuring big machinery in terms of power output (kW), port tugboats are a serious source of emissions. As a first in this literature, the present study aimed to make a 3-month emission inventory of port tugs in Izmit Bay, where Turkey’s largest shipping activities take place, and to compare it with emission studies for other ships. In the study period, port tugs’ emissions of CO2, NOX, SOX, VOC, PM, CO were calculated to be 7,398.88 tonnes, 121.09 tonnes, 66.43 tonnes, 2.13 tonnes, 4.27 tonnes, and 5.77 tonnes, respectively. This suggests that port tugs have a significant place among ship types in terms of producing exhaust emissions.

Emission and optical characteristics of brown carbon in size-segregated particles from three types of Chinese ships

Brown carbon (BrC) is one of the important light absorption substances that have high light absorption ability under short wavelength light. However, limit studies have focused on the BrC emission from ships. In this study, size-segregated particulate matters (PM) were collected from three different types of ships, light absorption characteristics and size distribution of methanol-soluble BrC and water-soluble BrC in PM from ship exhausts were investigated. Results showed that four-stroke low-power diesel fishing boat (4-LDF) had the highest mass concentrations of methanol-soluble organic carbon (MSOC) and water-soluble organic carbon (WSOC), followed by 2-stroke high-power heavy-fuel-oil vessel (2-HHV), and four-stroke high-power marine-diesel vessel (4-HMV). While 2-HHV had obviously higher light absorption coefficients of methanol-soluble BrC (Abs365,M) and water-soluble BrC (Abs365,W) in unit weight of PM than the other two types of ships. The tested ships presented comparable or higher absorption efficiency of BrC in water extracts (MAE365,W) compared with other BrC emission sources. Majority of BrC was concentrated in fine particles, and the particle size distributions of both Abs365,M and Abs365,W showed bimodal patterns, peaking at 0.43–0.65 µm and 4.7–5.8 µm, respectively. However, different particle size distributions were found for MAE365,M between diesel and heavy fuel oil ships. Besides, different wavelength dependence in particles with different size were also detected. Ship exhaust could be confirmed as a non-ignorable BrC emission source, and complex influencing factor could affect the light absorption characteristics of ship emissions. Particle size should also be considered when light absorption ability of BrC was evaluated.

SwinSeg: Swin transformer and MLP hybrid network for ship segmentation in maritime surveillance system

Accurate identification and segmentation of moving ships to ensure maritime traffic safety has become an important task in maritime intelligent transportation system. With the development of artificial intelligence, maritime surveillance system based on computer vision has been widely studied. However, there are still some problems when applied to the actual maritime scene. For example, the degradation of visible image quality caused by rain, haze, and low illumination leads to a significant reduction in segmentation performance. To improve the performance of ship identification and segmentation under adverse weather conditions, we propose SwinSeg, a hybrid network combining Swin Transformer and lightweight multi-layer perceptron (MLP). To address the lack of suitable open-source datasets in the community, we have collected and labeled a semantic segmentation dataset of marine ships, named SeaShipsSeg. It consists of 1200 visible marine ship images and covers six common ship types (bulk cargo carrier, container ship, fishing boat, general cargo ship, ore carrier, and passenger ship). In addition, synthetic degraded images are added to the dataset to increase its diversity and improve the generalization ability of the network. The experimental results show that the performance of our method is significantly better than the state-of-the-art (SOTA) methods in terms of segmentation accuracy, robustness, and efficiency under different weather conditions. The dataset is available at https://github.com/GrimreaperZ-creator/SeaShipsSeg.

A Marine Small-Targets Classification Algorithm Based on Improved Convolutional Neural Networks

Deep learning, especially convolutional neural network (CNN) techniques, has been shown to have superior performance in ship classification, as have small-target recognition studies in safety inspections of hydraulic structures such as ports and dams. High-resolution synthetic aperture radar (SAR)-based maritime ship classification plays an increasingly important role in marine surveillance, marine rescue, and maritime ship management. To improve ship classification accuracy and training efficiency, we proposed a CNN-based ship classification method. Firstly, the image characteristics of different ship structures and the materials of ship SAR images were analyzed. We then constructed a ship SAR image dataset and performed preprocessing operations such as averaging. Combined with a classic neural network structure, we created a new convolutional module, namely, the Inception-Residual Controller (IRC) module. A convolutional neural network was built based on the IRC module to extract image features and establish a ship classification model. Finally, we conducted simulation experiments for ship classification and analyzed the experimental results for comparison. The experimental results showed that the average accuracy of ship classification of the model in this paper reached 98.71%, which was approximately 3% more accurate than the traditional network model and approximately 1% more accurate compared with other recently improved models. The new module also performed well in evaluation metrics, such as the recall rate, with accurate classifications. The model could satisfactorily describe different ship types. Therefore, it could be applied to marine ship classification management with the possibility of being extended to hydraulic building target recognition tasks.

A numerical method for analysing the responses of cargo containment system of an LNGC under iceberg collision

ABSTRACT With the rapid development of Arctic route and increasing requirement of LNG resource, the ice-breaking LNGC becomes potential due to short transportation period and low cost. The new ship type brings a demand for the comprehensive safety assessment of cargo containment system (CCS), where the ice load should be further considered. In this study, a numerical method is proposed to investigate the responses of LNGC’s CCS under iceberg collision. Firstly, an LNGC model considering the stiffness contribution of CCS is used to study the iceberg collision scenarios. Subsequently, a refined CCS model coupled with the inner hull structure is proposed. The mechanical connection forms between CCS and inner hull structure are considered. Then the responses of insulation box, coupler and mastic ropes are analysed. The results show that this numerical method can accurately simulate the iceberg-ship collision process and efficiently analyse the responses of each CCS component.

Ship Classification Based on Density Features in SAR Images

Ship classification in SAR images has attracted much attention by researchers. In this paper, a SAR target classification method for three commercial ships (container ships, bulk carriers and oil tanker) is proposed by analyzing their scattering features. Firstly, the ship slice is preprocessed to obtain the binary image, from which the density features can be extracted, which describing the ship scattering point distribution. Finally, the support vector machine (SVM) classifier is applied to classify these three types of commercial ships. The experimental results show that the classification accuracy of structure feature and strength feature is low, while the proposed density feature can reach 80% for three types of ships. The combination of structure features and strength features with density features can improve the classification accuracy. Combining the three features has the best classification performance.

Using Artificial Neural Networks for Predicting Ship Fuel Consumption

Abstract In marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types of ships. Most traditional statistical methods do not consider these factors when predicting marine vessel fuel consumption. With technological development, different statistical models have been developed for estimating fuel consumption patterns based on ship data. Artificial Neural Networks (ANN) are some of the most effective artificial methods for modelling and validating marine vessel fuel consumption. The application of ANN in maritime transport improves the accuracy of the regression models developed for analysing interactive relationships between various factors. The present review sheds light on consolidating the works carried out in predicting ship fuel consumption using ANN, with an emphasis on topics such as ANN structure, application and prediction algorithms. Future research directions are also proposed and the present review can be a benchmark for mathematical modelling of ship fuel consumption using ANN.

Ballast Water Treatment with Heat Exchanger Modeling Simulation

Pollution of the marine environment has become a global issue, including marine pollution from ballast water. The impact is it can damage ecosystems and even affect humans. Therefore, pollution from ballast water is something that must be prevented by ballast water treatment. In this research, the author carried out a modeling simulation on a heat exchanger with a mechanical-type ballast water treatment method by utilizing the heat generated by the ship’s engine. Heat is used to kill microorganisms. So that the ballast water becomes cleaner than without treatment. In this research, the calculation of the need for heat exchangers on certain types of ships with certain sizes is carried out. In this calculation, the ship used is a container type with 3 categories based on cargo capacity and ballast tank capacity. Then the heat from the exhaust gases is used to heat the ballast water of the ship. The simulation results show that the maximum ballast water temperature of each ship category is in the range of 68-75 C. With this temperature, it is sufficient to kill and reduce microorganisms in the ballast water.

Powering Maritime: Challenges and prospects in ship electrification

The exponential increase in Global greenhouse gas (GHG) emissions and the rapid depletion of fossil fuels over the past few decades have swayed the transportation sector toward becoming more electric. In the last decade, with continuous improvements in battery technology and interfacing power electronics, there has been immense progress in the electrification of land-based transport. As their electrification gains pace, the focus is shifting toward greening other forms of transport, such as maritime and aviation sectors, since they contribute substantially to the total carbon footprint. The marine sector has witnessed huge growth in recent years because of the development of international trade, wherein it plays an essential role in the transportation of goods across the globe. The variation in ship sizes, types, and routes—along with their grid-distant nature and water-borne operation—distinguishes them from terrestrial electric vehicles. This gives rise to a multitude of unique challenges on board as well as at the ports that they operate around. Power electronics is one of the key enabling technologies in tackling these challenges and thereby creating safe, reliable, and emission-free maritime transport.