Different Types Of Ships Research Articles

Assessing the reliability of a ship energy performance simulation tool through on-board data

To mitigate the environmental impact of shipping on climate change, it is nowadays urgent to explore energy efficiency and cost-effective measures by means of reliable digital tools. These are becoming essential for assisting the design of new ships and the refurbishment of the existing ones, as well as for assessing and optimizing the energy performance of a ship during its entire life-cycle. This paper focuses on the verification of the reliability of a novel ship energy dynamic simulation tool, developed for the calculation of the energy, economic, and environmental performance of large ships, the design and optimization of energy system layouts and operational logics, as well as the definition of design and management guidelines for ships. The reliability of the developed model was verified through the use of data measured onboard an existing sample cruise ship. The verification procedure is conducted for assessing the reliability and for exploiting the potentiality of dynamic analysis for a more precise evaluation of ships energy loads, temperature levels, and necessary sizes of possible saving technologies. The validated tool will enable reaching two different goals: i) to evaluate different energy system layouts and to define the optimal one for achieving the present imposed targets and constraints, ii) to obtain a large amount of data for allowing the implementation of the digital twin approach in the maritime sector. The model validation was successfully achieved and very low or negligible deviations, lower than 4%, of numerical data vs. measurements were observed. Through the validated simulation tool approximately 23.4 GWh of primary energy from polluting fuels over two weeks is computed. In addition, the model provided insights into the flow rate, temperature levels, and energy flows of the ship energy system, necessary for identifying the amount of thermal energy to be recovered as well as potential solutions to enhance the energy efficiency of the entire system.

Air Pollutant Emission Factors of Inland River Ships under Compliance

Inland river ships (IRSs) use diesel with a lower sulfur content and emit relatively low emissions, making it challenging to monitor their emissions. Sniffer monitoring equipment was installed from August 2020 to June 2022 at the Gezhou Dam of the Yangtze River and monitored emissions from 8,238 IRSs passing through the lock. We partnered with the maritime department to select 100 ships passing through the lock to extract fuel oil samples for direct fuel sulfur content (FSC) detection, which determined the actual FSC of the passing ships. The monitoring data from these 100 ships indicated that the relative error of the SO2 emission factors (EFs) and FSC results is significant at the 10-parts-per-million level. The monitoring data from the remaining 8,138 ships showed that the EFs of NO, NO2, PM2.5, and PM10 were 24.02 ± 16.92 g kg−1, 10.30 ± 18.08 g kg−1, 0.72 ± 0.60 g kg−1, and 0.92 ± 0.70 g kg−1, respectively. The NOx EFs of container ships are higher than those of other ship types, while the PM EFs for different ship types do not significantly differ. Based on these EFs, we calculated the average emission rates for different types of ships passing through locks, which is a real-time measurement method for estimating ship emissions. In addition, a comparison of ship EF measurements over the past 20 years revealed that EF values for SO2, NOx, and PM exhibited a downward trend, with the calculated results of the current study determined to be the lowest numerical level.

The effect of ship-induced wave trains on periphytic algal communities in the littoral zone of a large regulated river (River Danube, Austria)

Riverine ecosystems are profoundly influenced by hydrological dynamics and natural flow regimes, which dictate the temporal variability of water levels and the amplitude of fluctuations. Human activities, particularly navigation and hydropower generation, have significantly altered these natural patterns, leading to detrimental impacts on the physical, chemical, and biological integrity of river ecosystems. The littoral zone, in particular, is highly susceptible to anthropogenic disturbances, experiencing disruptions in biological activity and biogeochemical processes. This study evaluates the effects of ship-induced wave trains on the structural and functional properties of periphytic algal communities in a regulated river environment. Using data from the Austrian Danube River, periphytic algae's immediate and long-term responses to wave events generated by different types of ships were investigated. Immediate reactions of periphytic algae to wave trains were characterized by reductions in the effective quantum yield of PS II, indicating stress-induced down-regulation of photosystem II photochemistry. Abrasion and remobilization of periphytic algae due to wave action led to increased resuspension of chlorophyll-a into the water column. Furthermore, ship-induced wave trains influenced the pigment composition of periphyton, with photoprotective mechanisms being activated in response to fluctuating light conditions. Long-term effects of wave impact on periphytic algae biomass varied depending on water depth and exposure to aerial stress. While wave action mitigated desiccation stress in shallow areas, it resulted in biomass reduction and alterations in community composition in deeper zones. Notably, the occurrence of diatoms decreased in wave-impacted areas, potentially shifting the community towards Chlorophyceae dominance. Overall, this study underscores the complexity of ship-induced wave impacts on riverine ecosystems and highlights the importance of considering both immediate and long-term responses of periphytic algal communities. Understanding these dynamics is crucial for informing sustainable management strategies aimed at mitigating the adverse effects of navigation activities on riverine biodiversity and ecosystem functioning.

Refinement of Norrbin Model via Correlations between Dimensionless Cross-Flow Coefficient and Hydrodynamic Derivatives

To develop a simplified and highly accurate ship motion model, this study thoroughly investigated the relationship between the dimensionless cross-flow coefficient and the four hydrodynamic derivatives of the Norrbin model. Eight different types of ships were simulated to explore the impact of dimensionless cross-flow coefficients and individual hydrodynamic derivatives on the ship’s turning circle. A set of precise formulas is proposed to depict the interplay between these variables. The simulation outcomes indicate that the average deviation in the agreement between the turning circles produced by adjusting the dimensionless cross-flow coefficient and those predicted by modifying the four hydrodynamic derivatives was only 2.70%. Furthermore, the similarities between the two circles and the sea trail were significantly higher at 91.45% and 92.87% compared with the original Norrbin model’s accuracy of 78.12%. Adjusting the dimensionless cross-flow coefficients enabled the rapid identification of a curve that closely mirrored the sea trail. This research aimed to improve the accuracy of the Norrbin model and resolve issues related to determining the magnification of the hydrodynamic derivatives, laying a robust foundation for subsequent studies and applications in relevant domains.

Discrete Distribution Model of Ship Noise Source in Shipping Channel

Ship noise plays an important role in low-frequency ocean ambient noise. With the increasingly busy sea traffic, the randomness of the spatiotemporal distribution characteristics of ship noise is also increasing. However, most ships sail in a relatively fixed range in different sea areas. Most of the previous studies assumed that the ship noise sources in shipping channel satisfy a uniformly distribution, actually all kinds of large ships are not uniformly distributed in the shipping channel, and there are also many small boats distributed on the channel that contribute significantly to low-frequency ocean ambient noise. The channel within a certain sea area will be divided into different regions, and ship information (AIS) in different regions will be analyzed statistically in this paper. It is assumed that the ship noise sources in different channel regions are discrete point noise sources that obey a certain spatiotemporal statistical distribution, combined with the noise source level models of different types of ships to form a discrete source model of ship noise in shipping channel. Using the ray propagation theory considering the horizontal refraction of sound energy, the vertical distribution of the ship noise level in this sea area is calculated, and compared with the vertical noise level distribution of ship noise source uniform distribution model, the variation range of noise level vertical distribution of two models is close calculated noise level (such as maximum and minimum values) is consistent with the measured data. The discrete source model of ship noise established in this paper may provide a technical support for predicting low-frequency ambient noise characteristics near the channel.

Shipping in the EU emissions trading system: implications for mitigation, costs and modal split

ABSTRACT EU recently decided to include shipping, meaning all intra-European shipping and 50% of extra-European voyages, in the EU Emissions Trading System (ETS) beginning in 2024. This article provides an early assessment of the impacts of the EU ETS on the shipping sector’s potential reductions in greenhouse gas emissions for different types of ships. It further examines selected mitigation measures and the impact on modals split and costs. The study employs a mixed-methods approach combining quantitative estimates (based on data from the EU monitoring, reporting and verification system) with qualitative data and information from interviews with key actors and from previous literature. This approach aims to provide a comprehensive understanding of the impacts of the EU ETS. The inclusion of shipping in the EU ETS is expected to introduce significant incentives to reduce emissions. We estimate that switching to bio-methanol at an emissions allowance price of €90–100/tCO2 will be cost-effective for a minor share of shipping segments (representing about 0.5-5% of all ships), whereas at a price above €150/tCO2 it could be cost-effective for a considerable share (potentially 75%) of ships. In the short term, the costs incurred by the EU ETS will be passed on to transport customers as a surcharge. The increased cost may, unless properly addressed, drive carbon leakage. Meanwhile, a modal shift away from shipping may occur in the roll-on, roll-off (RoRo) and roll-on passenger (RoPax) segments due to direct competition with road and rail transport and the relative ease of shifting to other modes of transport.

SAR Image Ship Target Detection Based on Receptive Field Enhancement Module and Cross-Layer Feature Fusion

The interference of natural factors on the sea surface often results in a blurred background in Synthetic Aperture Radar (SAR) ship images, and the detection difficulty is further increased when different types of ships are densely docked together in nearshore scenes. To tackle these hurdles, this paper proposes a target detection model based on YOLOv5s, named YOLO-CLF. Initially, we constructed a Receptive Field Enhancement Module (RFEM) to improve the model’s performance in handling blurred background images. Subsequently, considering the situation of dense multi-size ship images, we designed a Cross-Layer Fusion Feature Pyramid Network (CLF-FPN) to aggregate multi-scale features, thereby enhancing detection accuracy. Finally, we introduce a Normalized Wasserstein Distance (NWD) metric to replace the commonly used Intersection over Union (IoU) metric, aiming to improve the detection capability of small targets. Experimental findings show that the enhanced algorithm attains an Average Precision (AP50) of 98.2% and 90.4% on the SSDD and HRSID datasets, respectively, which is an increase of 1.3% and 2.2% compared to the baseline model YOLOv5s. Simultaneously, it has also achieved a significant performance advantage in comparison to some other models.

Assessment of Selected Alternative Fuels for Spanish Navy Ships According to Multi-Criteria Decision Analysis

Climate change and environmental degradation are growing concerns in today’s society, which has led to greater awareness and responsibility regarding the need to adopt sustainable practices. The European Union has established the goal of achieving climate neutrality by 2050, which implies a significant reduction in greenhouse gas emissions in all sectors. To achieve this goal, renewable energies, the circular economy, and energy efficiency are being promoted. A major source of emissions is the use of fossil fuels in different types of ships (from transport ships to those used by national navies). Among these, it highlights the growing interest of the defense sector in trying to reduce these emissions. The Spanish Ministry of Defense is also involved in this effort and is taking steps to reduce the carbon footprint in military operations and improve sustainability in equipment acquisition and maintenance. The objective of this study is to identify the most promising alternative fuel among those under development for possible implementation on Spanish Navy ships in order to reduce greenhouse gas emissions and improve its capabilities. To achieve this, a multi-criteria decision-making method will be used to determine the most viable fuel option. The data provided by the officers of the Spanish Navy is of great importance, thanks to their long careers in front of the ships. The analysis revealed that hydrogen was the most suitable fuel with the highest priority, ahead of LNG, and scored the highest in most of the sections of the officials’ ratings. These fuels are less polluting and would allow a significant reduction in emissions during the navigation of ships. However, a further study would also have to be carried out on the costs of adapting to their use and the safety of their use.

Methodology for Assessing Power Needs for Onshore Power Supply in Maritime Ports

Maritime ports represent an important ecosystem for pollutant emissions and, considering the ongoing energy transition, need to adopt new solutions to mitigate current emission levels. These emissions are partially avoidable if ships and vessels docked at the port use electric energy to feed their power needs instead of using their internal combustion engines. In Europe, there is an ongoing discussion on including such emissions in the European Union Emissions Trading System, which will represent added costs for maritime operators. Onshore power supply systems can contribute to the ongoing energy transition by allowing the use of electric power to feed docked ships. As a first step to contribute to the development of onshore power supply solutions, it is necessary to evaluate the added power needs that these systems would represent for the port. This paper presents a methodology that allows port operators to verify, straightforwardly and transparently, their power needs for onshore power supply applications. The methodology is based on the historical data of docked ships at the port or quay level and provides an energy analysis of each type of vessel to determine the power to be installed at the port so that it is possible to supply energy to different types of ships and vessels simultaneously. Additionally, the implemented methodology provides economic and technical decision support factors by comparing the fuel costs with electric power costs, assessing the potential for this transition to onshore power supply. The methodology is validated using a real case study for the Port of Lisbon, and obtained results demonstrate the potential for the installation of an onshore power supply in medium- to large-dimension maritime ports.

A probabilistic bottom-up modelling approach for synthetic load profiles within the energy efficiency management of cruise ship cabins

A reliable estimate of the electrical demand is a decisive factor in the design of electric board systems on cruise ships. This applies to all areas of the ship, including the hotel area with its up to several thousand cabins, which account for a non-negligible share of the total energy demand. In this paper, a simplified bottom-up model that can depict the electrical demand cabins with high temporal resolution and thus support marine and electrical engineers in developing future on-board power grids is presented. Key-card data will be used as a basis to easily access the behaviour of passengers on board. Another benefit is that the key data of the electrical consumers can be easily adapted to different types of ships and cabins. By including the ships route it is possible to precisely calculate the heat input through the glazing at any time of day and to determine its effect on the air-conditioning requirement. The model presented here is therefore not limited to certain regions but can be used globally. The functionality of the model is demonstrated on the example of a Caribbean cruise where the average electrical demand of a cabin is determined to 1.6 kWh per day.

A transfer learning-based approach to maritime warships re-identification

Marine vessel re-identification technology is an important component of intelligent shipping systems and an important part of the visual perception tasks required for marine surveillance. However, unlike the situation on land, the maritime environment is complex and volatile, and ships are prone to different degrees of swaying. Warships, as a class of ships, are characterized by fewer image samples and high similarity, and it is more difficult to re-identify warships at sea. Therefore, this paper proposes a dynamic alignment re-identification network model incorporating transfer learning methods. Various types of ships are used as source domain data to assist the network in learning the target domain warships so as to improve the recognition accuracy of warships. At the same time, the swaying situation of warships at sea is simulated and tested to improve the recognition difficulty so as to cope with the impact caused by complex sea conditions. The effect of different types of ships as transfer objects is also discussed. The experimental results show that the improved algorithm improves the mean average accuracy (mAP) by 10.2% and the first hit rate (Rank1) by 4.9% on average.

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.

A New Method of Ship Type Identification Based on Underwater Radiated Noise Signals

Ship type identification is an important basis for ship management and monitoring. The paper proposed a new method of ship type identification by combining characteristic parameters from the energy difference between high and low frequencies and the sensitive IMF variance mean value based on the modal decomposition of the underwater radiated noise signals using the Ensemble Empirical Mode Decomposition (EEMD) method. The comparison shows that the characteristic parameters of different types of ship, underwater radiated noises are different, whereas those of the same types of ship, underwater radiated noises fall in close range. Validation experiments based on randomly selected ship underwater radiated noise samples manifest that the method is of good separability for the four types of ship underwater radiated noises in the Deepship dataset. It has a higher identification rate than other methods within the distance range of ship underwater radiated noise detection in the dataset. The accuracy of this method tends to decrease with distance in the classification experiments of the ship underwater radiated noises at different distances.

CSP: A Cost-Aware Ship Proportioning Algorithm Based on Operation Process Simulation

Inland waterway dredging is daily maintenance which is undertaken to ensure the safe navigation of ships. Due to the limitations of river width, bridge height, and other conditions, dredging projects usually require different types of ships, namely dredgers, mud-carrying ships, and mud-blowing ships which work in cooperation with each other. The proportion of these three types of ships affects dredging cost and operation efficiency. Most existing algorithms calculate ship proportion according to the operating speeds of ships without considering the influence of navigation locks on waterways. In this paper, we propose a cost-aware ship proportioning (CSP) algorithm based on operation process simulation. The premise is to save dredging cost by making full use of the three types of ships. First, we establish a model to simulate the operation process of the three types of ships considering navigation locks. Furthermore, we utilize the simulation model to obtain the optimal ship proportion that has the lowest cost through loop iterations. In addition, we quantify the relationship between the opening time of navigation locks and the project cost. We evaluate the effectiveness of CSP in terms of the project cost based on real engineering data. The experiment results show that CSP significantly outperforms the baseline.

Scattering-Point-Guided RPN for Oriented Ship Detection in SAR Images

Ship detection in synthetic aperture radar (SAR) images has attracted widespread attention due to its significance and challenges. In recent years, numerous detectors based on deep learning have achieved good performance in the field of SAR ship detection. However, ship targets of the same type always have various representations in SAR images under different imaging conditions, while different types of ships may have a high degree of similarity, which considerably complicates SAR target recognition. Meanwhile, the ship target in the SAR image is also obscured by background and noise. To address these issues, this paper proposes a novel oriented ship detection method in SAR images named SPG-OSD. First, we propose an oriented two-stage detection module based on the scattering characteristics. Second, to reduce false alarms and missing ships, we improve the performance of the network by incorporating SAR scattering characteristics in the first stage of the detector. A scattering-point-guided region proposal network (RPN) is designed to predict possible key scattering points and make the regression and classification stages of RPN increase attention to the vicinity of key scattering points and reduce attention to background and noise. Third, supervised contrastive learning is introduced to alleviate the problem of minute discrepancies among SAR object classes. Region-of-Interest (RoI) contrastive loss is proposed to enhance inter-class distinction and diminish intra-class variance. Extensive experiments are conducted on the SAR ship detection dataset from the Gaofen-3 satellite, and the experimental results demonstrate the effectiveness of SPG-OSD and show that our method achieves state-of-the-art performance.

A Multipurpose and Power Quality Improved Electric Vessels Charging Station for the Seaports

To avoid air and noise pollution on seaports, the use of electric vessels and shore-to-ship power supply based charging station on seaports are in trend, which is also known as cold ironing (CI) infrastructure. In the starting stage, electric vessels charging stations are being implemented on the most busiest commercial ports, where modern electronic devices are used to serve different types of vessels. These devices only take care of the quality of output power. However, on the input side, it creates a serious harmonic issue. During CI, megawatt range of power is supplied to the ships, so generated harmonics and interharmonics in the high-power supply based charging system become more dangerous for the grid. In this article, we propose a novel power quality improved cold ironing (PQICI) system (charging mechanism) to overcome this issue. Moreover, due to inherent multipurpose useability, this novel PQICI is able to supply different types of power to various types of vessels, such as ac power, dc power, 50 Hz frequency, 60 Hz frequency, single phase, three phases, three-wire network, four-wire network, five-wire network, and different ac and dc voltages. Furthermore, this PQICI supply system is capable of serving four vessels at a time. In every type of loading condition with different kinds of power supply mode, the PQICI maintains the power quality on the input side, with fulfilling the varieties of the power demand of vessels. The capability of the developed “PQICI” system is tested for different types of ships and vessels on the simulation platform as well as through real-time hardware-in-the-loop experimentation. On IEEE standard 519, satisfactory test results on both platforms show the efficiency of the developed system and its control mechanism.

Smart High Power Charging Networks and Optimal Control Mechanism for Electric Ships

On commercial ports, during loading/unloading on cruise, carrier, container, or tanker, its diesel engine creates pollution. Therefore, in ports, shore-to-ship power (Cold Ironing) supply is an alternative way to overcome the pollution issue at shipyards. However, different ships of different countries and different companies require different types of power with different electrical connections, such as ac power with 50 Hz and 3-phase 3-wire connection, ac power with 60 Hz and 3-phase 4-wire connection, ac power with 50 Hz and 1-phase 2-wire connection, dc power, etc. The ship's power requirements are always in the megawatt range and its required potentials are in the kilovolt range. Therefore, in this article, a smart high power charging network and its control mechanism are developed for cold ironing on the ports, which is capable of serving almost all types of power with different types of power supply network. This developed supply system is capable of providing ac power, dc power, 50 Hz frequency, 60 Hz frequency, single phase, three phases, 3 wire, 4 wire, and 5 wire networks, different ac, dc voltages, etc. The capability of the developed smart power network is validated for different types of ships and vessels, on the simulation platform as well as through experimentation on real-time hardware-in-the-loop. The test results on both the platforms satisfactorily demonstrate the proposed power network and control scheme.

Analytical modelling of ship bottom grounding considering combined surge and heave motions

This paper provides a new contribution to the analytical treatment of ship grounding accidents. New formulations are proposed to assess the resisting force of outer/inner bottom plating and transverse floors when the vessel undergoes combined surge and heave motions during the grounding event. Considering shallow and sharp rocks described by parabolic functions, analytical solutions are derived from plastic limit analysis and validated by comparison to non-linear finite element simulations. A failure criterion is also proposed to trigger the rupture of the bottom plating and all the derived closed-form expressions are implemented into an in-house solver. The solver is then coupled to a 6-DOFs external dynamics program, which allows to account for the action of the surrounding water. Resulting tool is first validated on a full scale cruise ship by comparison to finite element results. It appears than although some discrepancies arise, especially in the response of transverse floors after rupture, the bottom damage distribution seems to be well predicted. Finally, the developed tool is used to quickly predict the grounding response of different types of ships and the influence of their mass and hydrodynamic properties on the damage extent is investigated.

Ship Classification and Anomaly Detection Based on Spaceborne AIS Data Considering Behavior Characteristics.

With the establishment of satellite constellations equipped with ship automatic identification system (AIS) receivers, the amount of AIS data is continuously increasing, and AIS data have become an important part of ocean big data. To further improve the ability to use AIS data for maritime surveillance, it is necessary to explore a ship classification and anomaly detection method suitable for spaceborne AIS data. Therefore, this paper proposes a ship classification and anomaly detection method based on machine learning that considers ship behavior characteristics for spaceborne AIS data. In view of the characteristics of different types of ships, this paper introduces the extraction and analysis of ship behavior characteristics in addition to traditional geometric features and discusses the ability of the proposed method for ship classification and anomaly detection. The experimental results show that the classification accuracy of the five types of ships can reach 92.70%, and the system can achieve better results in the other classification evaluation metrics by considering the ship behavior characteristics. In addition, this method can accurately detect anomalous ships, which further proves the effectiveness and feasibility of the proposed method.

Considerations on the Effect of Slow-Steaming to Reduce Carbon Dioxide Emissions from Ships

Carbon dioxide emissions have become a growing problem worldwide. Global institutions are addressing this problem and developing solutions. Countries that are aware of this problem are implementing regulations that affect global industry and, in particular, maritime transport. Considering that the combustion process, namely, diesel, remains the main energy conversion process on board ships, the question arises: what is the best solution to reduce pollutant emissions? Coastal countries have taken various measures to reduce the emission of harmful gases into the marine environment. The problem with these measures is that it is difficult to accurately predict their impact. This paper looks at one of these measures (slow-steaming) to determine how it affects carbon dioxide emissions from different types of ships and their modes of operation. Engine room simulators were used to study two marine power plants under different operating conditions. Fuel consumption was measured, i.e., flows from heavy fuel oil and diesel oil service tanks to all consumers, and carbon emissions were calculated accordingly. The study showed a large reduction in carbon dioxide emissions in the case of a modern power plant ship, and large deviations when all operating modes were compared.