Search Results (39)

When ships conduct offshore operations in the ocean, they are subject to disturbances from natural factors such as sea breezes and waves. These disturbances lead to movements detrimental to the ship’s stability, especially heave movement in the vertical direction, which profoundly impacts the safety of shipboard facilities and staff. To counter this, the active wave compensation device is widely used on ships to maintain the stability of the working environment. However, the system’s efficiency and accuracy are compromised by the significant delay incurred while obtaining real-time motion signals and driving the actuator for motion compensation. To solve the time delay problem of shipborne wave compensation equipment in motion compensation under complex sea conditions, it is necessary to improve the ship heave motion prediction accuracy in an active wave compensation system. This paper presents a prediction method of ship heave motion based on the particle swarm optimization (PSO) and convolutional neural network–long short-term memory (CNN-LSTM) hybrid prediction model. The paper begins by establishing the ship heave motion model based on the P–M spectrum and slice theory, simulating the ship heave motion curve under different sea conditions on MATLAB. This simulation provides crucial data for the subsequent prediction model. The paper then delves into the realization method of ship heave motion based on PSO-CNN-LSTM, where the convolutional neural network (CNN) is used to extract the features of the input signal, thereby enhancing the multi-source feature fusion ability of the LSTM neural network model. The PSO algorithm is then employed to optimize the network structure and hyperparameters of the convolutional neural network. The experiments demonstrate that the proposed PSO-CNN-LSTM hybrid model effectively addresses the problem of predicting drift and boasts significantly higher prediction accuracy, making it suitable for predicting the short-term heave motion of ships. The data show that the optimized root mean square error (RMSE) value under level 5 sea conditions is 0.01265 compared to 0.01673 before optimization, and the optimized RMSE value under level 6 sea conditions is 0.01140 compared to 0.01479 before optimization, which demonstrates that the error between the predicted value and the actual value of the model decreases. This improved accuracy provides reassurance in the model’s predictive capabilities and lays the foundation for improving the accuracy of the motion compensation system in the future. Full article

The amendment to MARPOL Annex VI, which limits the sulfur content in marine fuels to a maximum of 0.5 wt.%, came into effect in January 2020. This includes reducing sulfur oxide (SO_X) emissions and establishing nitrogen oxide (NO_X) emission standards (Tiers I, II, and III) based on the ship’s engine type and construction date. Furthermore, the regulations require oil tankers to control volatile organic compound (VOC) emissions and prohibit the installation of new equipment containing ozone-depleting substances. After a four-year exploration phase, global shipping companies still lack consistent evaluation criteria for the selection and use of alternative fuels, resulting in divergence across the industry. According to the latest data, methanol can reduce NO_X, SO_X, and particulate matter (PM) emissions by approximately 80%, 99%, and 95%, respectively, compared to traditional heavy fuel oil. Furthermore, green methanol has the potential for near-zero greenhouse gas emissions and can meet the stringent standards of Emission Control Areas. Therefore, this study adopts a cost-benefit analysis method to evaluate the feasibility and implementation benefits of two promising strategies: methanol dual fuel and very low-sulfur fuel oil (VLSFO). A 6600-TEU container ship was selected as a representative case, and the evaluation was conducted by replacing an older ship with a newly built one. The reductions in total pollutants and CO₂-equivalent emissions of the container ship, as well as the cost-effectiveness of each specific strategy, were calculated. This study found that, in the first five years of operation, the total incremental cost of Vessel A, which uses 100% VLSFO, will be significantly lower than that of Vessel B, which uses a blend of 30% e-methanol + 70% VLSFO as fuel. Furthermore, compared to a scenario without any improvement strategies, the total incremental cost for Vessels A and B will increase by 69.90% and 178.15%, respectively, over five years. Vessel B effectively reduced the total greenhouse gas emission equivalent (CO₂e) of CO₂, CH_4, and N₂O by 24.72% over five years, while Vessel A reduced the CO₂e amount by 12.18%. Furthermore, the cost-benefit ratio (CBR) based on total pollutant emission reduction is higher for Vessel A than for Vessel B within five years of operation. However, in terms of the cost-effectiveness of CO₂e emission reduction, the CBR of Vessel A becomes lower than Vessel B after 4.7 years of operation. Therefore, Vessel A’s strategy should be considered a short-term option for reducing CO₂e within 4.7 years, whereas the strategy of Vessel B is more suitable as a long-term solution for more than 4.7 years. Full article

A LoRaWAN application architecture comprises three functional components: (i) nodes, which convert and wirelessly transmit data as LoRaWAN messages; (ii) gateways, which receive and forward these transmissions; and (iii) network servers, which process the received data for application delivery. The nodes convert data into LoRaWAN messages and transmit them wirelessly with the hope that one or more LoRaWAN gateway will receive the messages successfully. Then, the gateways pass on the received messages to a distant network server, where various processing steps occur before the messages are forwarded to the end application. If none of the gateways can receive the messages, then they will be lost. Although this default behaviour is suitable for some applications, there are others where ensuring messages are successfully delivered at a higher rate would be helpful. One such scenario is the application in this paper: monitoring maritime vessels and fishing equipment in offshore environments characterised by intermittent or absent shore connectivity. To address this challenge, the Custodian project was initiated to develop a maritime monitoring solution with enhanced connectivity capabilities. Two additional features are especially welcome in this scenario. The most important feature is the transmission of messages created in offshore areas to end users who are offshore, regardless of the unavailability of the ground network server. An example would be fishermen who are offshore and wish to position their fishing equipment, also offshore, based on location data transmitted from nodes via LoRaWAN, even when both entities are far away from the mainland. The second aspect concerns the potential use of gateway-to-gateway communications, through gateways on various ships, to transmit messages to the coast. This setup enables fishing gear and fishing vessels to be monitored from the coast, even in the absence of a direct connection. The functional constraints of conventional commercial gateways necessitated the conceptualisation and implementation of C-Mesh, a novel relay architecture that extends LoRaWAN functionality beyond standard protocol implementations. The C-Mesh integrates with the Custodian ecosystem, alongside C-Beacon and C-Point devices, while maintaining transparent compatibility with standard LoRaWAN infrastructure components through protocol-compliant gateway emulation. Thus, compatibility with both commercially available nodes and gateways and those already in deployment is guaranteed. We provide a comprehensive description of C-Mesh, describing its hardware architecture (communications, power, and self-monitoring abilities) and data processing ability (filtering duplicate messages, security, and encryption). Sea trials carried out on board a commercial fishing vessel in Sesimbra, Portugal, proved C-Mesh to be effective. Location messages derived from fishing gear left at sea were received by an end user aboard the fishing vessel, independently of the network server on land. Additionally, field tests demonstrated that a single C-Mesh deployment functioning as a signal repeater on a vessel with an antenna elevation of $15m$ above sea level achieved a quantifiable coverage extension of 13 km (representing a 20% increase in effective transmission range), demonstrating the capacity of C-Mesh to increase LoRaWAN’s coverage. Full article

Ship detection technology represents a significant research focus within the application domain of synthetic aperture radar. Among all the detection methods, the deep learning method stands out for its high accuracy and high efficiency. However, large-scale deep learning algorithm training requires huge computing power support and large equipment to process, which is not suitable for real-time detection on edge platforms. Therefore, to achieve fast data transmission and little computation complexity, the design of lightweight computing models becomes a research hot point. In order to conquer the difficulties of the high complexity of the existing deep learning model and the balance between efficiency and high accuracy, this paper proposes a lightweight dual-domain feature fusion detection model (LD-Det) for ship target detection. This model designs three effective modules, including the following: (1) a wavelet transform method for image compression and the frequency domain feature extraction; (2) a lightweight partial convolutional module for channel feature extraction; and (3) an improved multidimensional attention module to realize the weight assignment of different dimensional features. Additionally, we propose a hybrid IoU loss function specifically designed to enhance the detection of small objects, improving localization accuracy and robustness. Then, we introduce these modules into the Yolov8 detection algorithm for implementation. The experiments are designed to verify LD-Det’s effectiveness. Compared with other algorithm models, LD-Det can not only achieve lighter weight but also take into account the precision of ship target detection. The experimental results from the SSDD dataset demonstrate that the proposed LD-Det model improves precision (P) by 1.4 percentage points while reducing the number of model parameters by 20% compared to the baseline. LD-Det effectively balances lightweight efficiency and detection accuracy, making it highly advantageous for deployment on edge platforms compared to other models. Full article

The optimal dispatching of integrated energy systems can effectively reduce energy costs and decrease carbon emissions. The accuracy of the load forecasting method directly determines the dispatching outcomes, yet considering the stochastic and non-periodic characteristics of port electricity load, traditional load forecasting methods may not be suitable due to the weak historical regularity of the load data themselves. Therefore, this paper proposes a method for forecasting the electricity load of container ports based on ship arrival and departure schedules as well as port handling tasks. By finely modeling the electricity consumption behavior of port machinery, effective prediction of the main electricity load of ports is achieved. On this basis, the overall structure of an integrated port energy system (IPES) including renewable energy systems, electricity/thermal/cooling/hydrogen energy storage systems, integrated energy dispatching equipment, and integrated loads is studied. Furthermore, a dispatching model considering demand response for the optimal operation of the IPES is established, and the day-ahead optimal dispatching of the IPES is achieved based on the forecasted load. The experimental results indicate that the developed method can ensure the operational efficiency of IPES, reduce port energy costs, and decrease carbon emissions. Full article

This study evaluates the hydrodynamic performance of a movable fish cage equipped with a spread mooring system in offshore condition. It investigates the global behavior and safety of a mooring system under environmental influences such as waves, currents, and biofouling. A numerical model was developed using the Cummins equation and a lumped-mass line model to capture the coupling effects between the floating structure and mooring lines. The steel frame was modeled using Morison members, whereas fishing nets were represented by a screen model incorporating drag forces. Parametric studies were performed to assess the effects of varying mooring line lengths, current speeds, and biofouling on cage behavior. Evidently, heavier chains reduced excursions but increased tension, whereas high current speeds increased the line tension (owing to increased drift) and mooring line stiffness by up to 66%. Biofouling increased the maximum excursion by 6% and line tension by up to 17%. Safety evaluations based on the American Bureau of Shipping rules examined intact and damaged conditions, comparing estimated line tensions with allowable values. The findings confirm that the mooring system ensures reliable station-keeping performance even under challenging conditions, validating its suitability for offshore deployment and ensuring the safety and stability of floating fish cage systems. Full article

In response to problems such as insufficient adhesion, difficulty in adjustment, and weak obstacle-crossing capabilities in traditional robots, an innovative design has been developed for a five-wheeled climbing robot equipped with a pendulum-style magnetic control adsorption module. This design effectively reduces the weight of the robot, and sensors on the magnetic adsorption module enable real-time monitoring of magnetic force. Intelligent control adjusts the pendulum angle to modify the magnetic force according to different wall conditions. The magnetic adsorption module, using a Halbach array, enhances the concentration effect of the magnetic field, ensuring excellent performance in high-load tasks such as building maintenance, bridge inspection, and ship cleaning. The five-wheel structural design enhances the stability and obstacle-crossing capability, making it suitable for all-terrain environments. Simulation experiments using Maxwell analyzed the effects of the magnetic gap and the angle between the adsorption module and the wall, and mechanical performance analysis confirmed the robot’s ability to adhere safely and operate stably. Full article

NAVTEX is a key component in the Global Maritime Distress and Safety System (GMDSS) that automatically transmits urgent maritime safety information such as navigational and meteorological warnings and forecasts to vessels. For the safe navigation of smart ships, this information from different systems should be shared harmoniously in the Common Maritime Data Structure (CMDS). To share NAVTEX messages as CMDS, words in NAVTEX messages must be semantically classified and placed within the CMDS structure. While traditional parsing methods are typically used to understand message semantics, NAVTEX requires natural language processing methods with deep learning due to its unstructured messages. This paper applies six types of Bi-LSTM CRF-based deep learning models to NAVTEX navigational safety messages and analyzes the results to find the most suitable model for understanding the semantics of each word in NAVTEX messages. This technique can be applied to accurately convey the meaning of NAVTEX navigational safety messages to equipment that requires navigational safety information on smart ships without human intervention. Full article

The current research investigates the effects of materials and riblets on cavitation-induced erosion morphology, depth, and cross-sectional area through experimental approaches. To achieve these aims, the erosion of pure aluminum (1xxxAl or Al) and alpha brass (CuZn37 or CZ108), in the presence and absence of bio-inspired sawtooth riblets, was examined after exposure to multiple collapses of single cavitation bubbles with a wall distance of 1.8 (dimensionless). The results indicate that the erosion morphology resembles a rounded cone with a circular cross-section. Brass provides 21.6% more erosion resistance compared to that of Al in terms of material properties. Furthermore, the erosion for both Al (depth by 3.8% and width by 18.3%) and brass (depth by 7.9% and width by 27.4%) decreases in the presence of riblets compared to the results for flat surfaces. The greater erosion resistance of brass compared to Al is attributed to the superior mechanical stability of brass, making it a potentially suitable alloy for use in propellers and hulls in the shipping industry. In summary, the results reveal that riblet-equipped materials with high mechanical durability are promising erosion-resistant materials for the shipping industry. However, the potential for chemical reactions in a cathodic environment should be addressed to provide a comprehensive perspective in regards to reducing corrosion intensity. Full article

The engine room is the core area of a ship, critical to its operation, safety, and efficiency. Currently, many researchers merely address the ship engine room layout design (SERLD) problem using optimization algorithms and independent layout strategies. However, the engine room environment is complex, involving two significantly different challenges: equipment layout and pipe layout. Traditional methods fail to achieve optimal collaborative layout objectives. To address this research gap, this paper proposes a collaborative layout method that combines improved reinforcement learning and heuristic algorithms. For equipment layout, the engine room space is first discretized into a grid, and a Markov decision process (MDP) framework suitable for equipment layout is proposed, including state space, action space, and reward mechanisms suitable for equipment layout. An improved adaptive guided multi-agent Q-learning (AGMAQL) algorithm is employed to train the layout model in a centralized manner, with enhancements made to the agent’s exploration state, exploration action, and learning strategy. For pipe layout, this paper proposes an improved adaptive trajectory artificial fish swarm algorithm (ATAFSA). This algorithm incorporates a hybrid encoding method, adaptive strategy, scouting strategy, and parallel optimization strategy, resulting in enhanced stability, accuracy, and problem adaptability. Subsequently, by comprehensively considering layout objectives and engine room attributes, a collaborative layout method incorporating hierarchical and adaptive weight strategies is proposed. This method optimizes in phases according to the layout objectives and priorities of different stages, achieving multi-level optimal layouts and providing designers with various reference schemes with different focuses. Finally, based on a typical real-world engine room engineering case, various leading algorithms and strategies are tested and compared. The results show that the proposed AGMAQL-ATAFSA (AGMAQL-ATA) exhibits robustness, efficiency, and engineering practicality. Compared to previous research methods and algorithms, the final layout quality improved overall: equipment layout effectiveness increased by over 4.0%, pipe optimization efficiency improved by over 40.4%, and collaborative layout effectiveness enhanced by over 2.2%. Full article

Despite being stored at 113 K and at atmospheric pressure, LNG cold potential is not exploited to reduce green ships’ energy needs. An innovative system based on three organic Rankine cycles integrated into the regasification equipment is proposed to produce additional power and recover cooling energy from condensers. A first-law analysis identified ethylene and ethane as suitable working fluids for the first and the second ORC, making freshwater and ice available. Propane, ammonia and propylene could be arbitrarily employed in the third ORC for air conditioning. An environmental analysis that combines exergy efficiency, ecological indices and hazard aspects for the marine environment and ship passengers indicated propylene as safer and more environmentally friendly. Exergy analysis confirmed that more than 20% of the LNG potential can be recovered from every cycle to produce a net clean power of 76 kW, whereas 270 kW can be saved by recovering condensers’ cooling power to satisfy some ship needs. Assuming the sailing mode, a limitation of 162 kg in LNG consumptions was determined, avoiding the emission of 1584 kg of CO₂ per day. Marine thermal pollution is reduced by 3.5 times by recovering the working fluids’ condensation heat for the LNG pre-heating. Full article

This paper presents a framework for structural analysis of icebreakers during ramming of first-year ice ridges. The framework links the ice-ridge load and the structural analysis based on the physical characteristics of ship–ice-ridge interactions. A ship–ice-ridge interaction study was conducted to demonstrate the feasibility of the proposed framework. A PC-2 icebreaker was chosen for the ship–ice interaction study, and the geometrical and physical properties of the ice ridge were determined based on empirical data. The ice ridge was modeled by solid elements equipped with the continuous surface cap model (CSCM). To validate the approach, the simulated ice resistance was computed using the Lindqvist solution and in situ tests of R/V Xuelong 2. First, the local ice-induced pressure on the hull shell was determined based on numerical simulations. Subsequently, the local ice pressure was applied to local deformable sub-structural models of the PC-2 icebreaker hull by means of triangular impulse loads. Finally, the structural response of sub-structural models with refined meshes was computed. This case study demonstrates that the proposed framework is suitable for structural analysis of ice-induced stresses in local hull components. The results show that the ice load and the structural response obtained based on the four first-year ice-ridge models show obvious differences. Furthermore, the ice load and corresponding structural response increases with the width of the ridge and with increasing ship speed. Full article

As most of the current dynamic positioning systems are based on model ships, they cannot accurately reflect the motion state, position changes, and mutual influence of each part of the dynamic positioning system of actual ships in complex environments. Other actual ships such as cargo ships cannot add various sensors and auxiliary equipment to verify and analyze the positioning system. This article takes the intelligent research and training dual-use ship of Dalian Maritime University, which integrates scientific research and training, as the object of study. This ship will not be affected by the voyage period and route and can choose a suitable sea area for research. Therefore, in order to improve the accuracy and reliability of the dynamic positioning system, research on the ship’s dynamic positioning system was carried out. Firstly, an accurate mathematical model was developed to simulate ship motion, focusing on the use of the Dalian Maritime University’s intelligent and practical training dual-purpose vessel as the modeling object. Through this approach, a more detailed understanding of the effects of actual environmental perturbations on ship control and positioning can be obtained, as well as more realistic ship control and positioning results. The hydrodynamic derivatives of ship model motion were obtained by numerical calculation and applied to the three-degree-of-freedom model of the intelligent research and training dual-use ship. Then, the model was used as part of the closed-loop simulation model of the ship’s dynamic positioning system, and the terminal sliding mode controller was used for simulation and emulation, thereby obtaining ideal simulation test results. Our results deepen the understanding of DPS accuracy and are consistent with the theory of terminal slip modes for ship power positioning control systems. This has implications for improving the accuracy of ship power positioning systems, as previously discussed in previous authors. In conclusion, this study not only improves the accuracy and reliability of the DPS but also proposes the use of the terminal slip film for a ship power positioning control system modeled on the Dalian Maritime University intelligent and practical dual-purpose vessel. These contributions are significant in improving the efficiency, safety, and environmental sustainability of ship operations. Full article

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. Full article

Urban forests by the riverside are important habitats for various animals and contribute various soundscapes for citizens. Unfortunately, urban forests are exposed to the influence of riverside traffic noises from freeways. This study aims to explore the spatial and temporal variation of soundscape, conduct soundscape optimization for multiple parameters, and find a balance and its interval of soundscape elements through optimizing a soundscape map. Questionnaires and measuring equipment were used to gather soundscape information in an urban forested area in Fuzhou, China. Diurnal variations and soundscape mapping were used to analyze spatial and psychophysical relationships between soundscape drivers. We then conducted optimization for a soundscape map, which included normalization, critical value determination, target interval of optimal SPL determination, and modification of SPL and mapping. Our findings suggest that biological activities and natural phenomena are potential drivers for diurnal variation of soundscapes, especially tidal phenomena contributing water and shipping soundscapes. Our results also suggest that all the high values of perceived soundscapes were found at the southwest corner of the study area, which includes both riverside and urban forest elements. Furthermore, we suggest combining both optimal soundscape and SPL correction maps to aid in sustainable design in urban forests. This can contribute to the understanding and methodology of soundscape map optimization in urban forests when proposing suitable design plans and conservation of territorial sound. Full article