Search Results (47)

To overcome the limitations of existing maritime radar identification analysis methods, which are only applicable to sea-skimming aircraft and fail to quantitatively calculate the probability of radar correctly identifying the target under electromagnetic influence from marine geographical features (MGFs), an advanced method is proposed for calculating the radar identification probability in marine areas using 3D MGF models. The method first established the radar identification criteria in 3D space, considering radar line of sight (LOS), radar target adhesion (RTA), and radar resolutions in range, azimuth angle, and elevation angle. It then comprehensively analyzed errors from both the aircraft and MGFs. Finally, the probability of a target at a specific marine location being correctly identified by radar was calculated using the Monte Carlo method. Theoretical derivations and simulation results demonstrated that: (1) Unlike existing methods limited to sea-skimming aircraft, the proposed method is applicable to aircraft at any altitude, better aligning with current aircraft performance and requirements; (2) While existing methods provide only a binary result of “identified” or “unidentified,” the proposed method offers a probability value. For the same marine location point T_a, the proposed method yields radar identification probabilities of 0.0877 for sea-skimming aircraft and 0.5887 for high-altitude aircraft, providing more precise and intuitive decision-making support for mission planners. Full article

Drone swarms often need to fly cooperatively in complex spaces filled with multiple obstacles. In such scenarios, they must meet the requirements of both external obstacle avoidance and internal collision avoidance while maintaining a certain topological configuration among individuals. This easily leads to problems such as congestion, oscillation, and poor stability, including being out of control. Thus, it is essential to measure system-wide stability, regulate the autonomous cooperative evolution of swarms, and enhance their adaptation to environmental changes. To solve this problem, using the symmetric unmanned aerial vehicle (UAV) swarm as the research object, a group entropy measurement theory for the stability of drone swarms is proposed. We introduce an entropy-based metric for group motion consistency. This metric serves as a fitness index for individual collaboration, enabling adaptive adjustment of drone swarm coherence under multi-obstacle conditions. Finally, simulation experiments are conducted to verify the effectiveness of the established theory and algorithm. Full article

Resin matrix composites are commonly utilized in water-lubricated stern tube bearings for warship propulsion systems. Low-speed and high-load conditions are significant factors influencing the tribological properties of stern tube bearings. The wear characteristics of resin-based laminated composites (RLCs), resin-based winding composites (RWCs), and resin-based homogeneous polymer (RHP) blocks were investigated under simulated environmental conditions using a ring-on-block wear tester. Simulated seawater was prepared by combining sodium chloride with distilled water. The wetting angle, coefficient of friction (COF), and mass loss were measured and compared. Additionally, their surface morphologies were examined. The results indicate a significant increase in the COFs for the three materials with an increased speed or load under dry conditions. The COF of the RLCs is the lowest, indicating that it has superior self-lubricating properties. In wet conditions, the COFs of the three materials decrease with an increasing speed or load, exhibiting a pronounced hydrodynamic effect. The COF and mass loss of RWCs are the highest, while RLCs and RHP exhibit lower COFs and mass loss values. The reticulated texture and flocculent fibers on the surface of RLC enhance the heat diffusion and improve the material wettability and water storage capacity. The surface of RWC is dense, and the friction area under dry conditions is melted and brightened. The surface of RHP is smooth, while the worn material forms an agglomerate and exhibits susceptibility to burning and blackening under dry conditions. The laminated formation method demonstrates superior tribological performance throughout the wear evolution process. Full article

Maritime transport is crucial for global trade, as over 80% of goods are transported by sea. Recent conflicts have exposed the vulnerability of shipping routes to disruptions. Therefore, devising an optimal plan for naval escort operations is critical to ensure that ships are safely escorted. This study addresses the naval escort operation problem by constructing a mixed-integer programming model that integrates escort scheduling of the warship with the speed optimization of liner ships, aiming to minimize overall cargo delay and fuel consumption costs while ensuring the protection of all ships. The results indicate that as the number of container ships increases, ships wait longer before departure with the warship, leading to a higher average delay cost per ship. For instances with a single ship type, ships have similar sailing speeds on different legs. The proposed model balances cargo delivery timeliness with carbon emission reduction, enhancing economic viability and environmental sustainability in crisis-prone maritime scenarios. Future research should explore real-time data integration and adaptive strategies to improve naval escort operations’ robustness and responsiveness. Full article

The selection of a navy ship is essential to guarantee a country’s sovereignty, deterrence capabilities, and national security, especially in the face of possible conflicts and diplomatic instability. This paper proposes the integration of concepts related to multi-criteria decision making (MCDM) methodology and machine learning, creating the Simple Aggregation of Preferences Expressed by Ordinal Vectors—Principal Components (SAPEVO-PC) method. The proposed method proposes an evolution of the SAPEVO family, allowing the inclusion of qualitative preferences, and adds concepts from Principal Component Analysis (PCA), aiming to simplify the decision-making process, maintaining precision and reliability. We carried out a case study analyzing 32 warships and ten quantitative criteria, demonstrating the practical application and effectiveness of the method. The generated rankings reflected both subjective perceptions and the quantitative performance data of each ship. This innovative integration of qualitative data with a quantitative machine learning algorithm ensures comprehensive and robust analyses, facilitating informed and strategic decisions. The results showed a high degree of consistency and reliability, with the top and bottom rankings remaining stable across different decision-makers’ perspectives. This study highlights the potential of SAPEVO-PC to improve decision-making efficiency in complex, multi-criteria environments, contributing to the field of marine science. Full article

This paper examines the response characteristics of a warship’s double-layer plates under a secondary near-field explosion after the ship’s outer plate has been perforated by shaped metal jets. First, the effectiveness of the Coupled Eulerian–Lagrangian (CEL) method was validated, showing numerical simulations to be well aligned with experimental results. Subsequently, the damage inflicted on the outer plate by metal jets was simplified to a prefabricated orifice, further studying the explosive impact response of double-layer plates under different inter-compartmental water levels and charge distances. Our findings indicated the following: (1) shockwave and bubble pulsation loads are the main causes of deformation in the outer plate; (2) the driving of the outer plate and the flooding water between compartments are the main causes of deformation in the inner plate; and (3) deformation in the outer plate will decrease as the water level in the compartment increases, while deformation in the inner plate will increase with the increasing water level. Consequently, under certain specific damage, the ingress of water into a compartment effectively enhances the explosion resistance of the double-layer plates. Full article

The intensive integration of technology and the demand for high-level performance are specific features of warships, which are at present one of the most complex systems. An appropriate design process, able to foresee in a life cycle perspective, is necessary to properly implement the emergent properties and the capabilities required for the warship in the different operational profiles. This paper will delve into the integration of the Systems Engineering (SE) approach into the realm of naval ship design, fostering an innovative perspective. An integration of the design spiral method with the SE approach will be described, making possible the definition of a hinge between the two realms and depicting a novel comprehensive approach where the ship platform and the so-called payload are finally interconnected with each other. Full article

Ship recognition with optical remote sensing images is currently widely used in fishery management, ship traffic surveillance, and maritime warfare. However, it currently faces two major challenges: recognizing rotated targets and achieving fine-grained recognition. To address these challenges, this paper presents a new model called Related-YOLO. This model utilizes the mechanisms of relational attention to stress positional relationships between the components of a ship, extracting key features more accurately. Furthermore, it introduces a hierarchical clustering algorithm to implement adaptive anchor boxes. To tackle the issue of detecting multiple targets at different scales, a small target detection head is added. Additionally, the model employs deformable convolution to extract the features of targets with diverse shapes. To evaluate the performance of the proposed model, a new dataset named FGWC-18 is established, specifically designed for fine-grained warship recognition. Experimental results demonstrate the excellent performance of the model on this dataset and two other public datasets, namely FGSC-23 and FGSCR-42. In summary, our model offers a new route to solve the challenging issues of detecting rotating targets and fine-grained recognition with remote sensing images, which provides a reliable foundation for the application of remote sensing images in a wide range of fields. Full article

In recent years, trimarans have been used in high-speed transport and in warships, but studies of them have made little progress. We designed a trimaran model and used it to perform a water-entry experiment to find a way to reduce the slamming pressure. The process of the model entering the water was divided into several steps, and different theoretical models were designed for each step, together with their force analysis. Relying on our experimental platform, we designed three flexible coating thicknesses and six drop heights as the different working conditions. With an analysis of the results under these experimental conditions, the experiment clearly indicates that the flexible cladding on the model can decrease the impact force when the model slams into water. Furthermore, the theoretical models and their corresponding force analyses are validated by the experimental results. Full article

Humans’ performance varies due to the mental resources that are available to successfully pursue a task. To monitor users’ current cognitive resources in naturalistic scenarios, it is essential to not only measure demands induced by the task itself but also consider situational and environmental influences. We conducted a multimodal study with 18 participants (nine female, M = 25.9 with SD = 3.8 years). In this study, we recorded respiratory, ocular, cardiac, and brain activity using functional near-infrared spectroscopy (fNIRS) while participants performed an adapted version of the warship commander task with concurrent emotional speech distraction. We tested the feasibility of decoding the experienced mental effort with a multimodal machine learning architecture. The architecture comprised feature engineering, model optimisation, and model selection to combine multimodal measurements in a cross-subject classification. Our approach reduces possible overfitting and reliably distinguishes two different levels of mental effort. These findings contribute to the prediction of different states of mental effort and pave the way toward generalised state monitoring across individuals in realistic applications. Full article

A water-lubricated rubber bearing (WLRB) is prone to generate frictional vibration noise under special operating conditions, which seriously affects the acoustic stealth performance of warships and threatens their navigation safety. Meanwhile, the main factor affecting the frictional vibration behavior of a WLRB is the materials of the friction pair. Therefore, this work selects a friction pair composed of a copper ring and a rubber block as the research object and studies the frictional vibration behavior of the ring–block friction pair under low-speed and starting conditions. The real friction coefficient curve is used to establish a transient dynamic finite element analysis model for the ring–block friction pair. The effects of the load, friction coefficient, and Young’s modulus on the frictional vibration behavior under special operating conditions are studied. The analysis’s results show that the frequency of the medium-high frequency friction-induced vibration disappears under low-speed operating conditions when the friction coefficient is below 0.1. During the startup process, even if the friction coefficient is very low, the medium-high frequency friction-induced vibration still exists. The research results provide ideas for future theoretical research and guidance suggestions for engineering practice. Full article

This article discusses the Brazilian maritime authority’s efforts to monitor and control vessels in specific maritime areas using data from the naval traffic control system. Anomalies in vessel locations can signal security threats or illegal activities, such as drug trafficking and illegal fishing. A reliable Maritime Domain Awareness (MDA) is necessary to reduce such occurrences. This study proposes a data-driven framework, CV-MDA, which uses computer vision to enhance MDA. The approach integrates vessel records and camera images to create an annotated dataset for a Convolutional Neural Network (CNN) model. This solution supports detecting, classifying, and identifying small vessels without trackers or that have deliberately shut down their tracking systems in order to engage in illegal activities. Improving MDA could enhance maritime security, including identifying warships invading territorial waters and preventing illegal activities. Full article

This study examines the legal challenges related to preserving sunken military vessels as Underwater Cultural Heritage (UCH) in Colombia. These challenges include Spanish galleon shipwrecks, limited international cooperation, and the lack of legal recognition for sunken military vessels under domestic law (Law 1675 of 2013). To address these issues, this article reviews the concepts of warship and sovereign immunity as they relate to the status of sunken military vessels. The study places a particular focus on the USS Kearsarge, a military shipwreck in Colombian territorial waters protected by the Sunken Military Craft Act of 2004 (SMCA) of the United States. Additionally, it analyzes the legal frameworks and management of UCH in both Colombia and the United States, as well as providing two lists of Colombia’s sunken military vessels and foreign sunken military vessels in its waters. The research concludes by highlighting the complexities of managing UCH in Colombia and offering a prospectus on the future of the USS Kearsarge wreck site as shared heritage. Ultimately, this study underscores the need for a more comprehensive legal framework and greater international cooperation to ensure the preservation and protection of sunken military vessels in Colombia. Full article

The studies of bone tissue have mainly highlighted the morphometrical characteristics of the osteons, rather than their spatial distribution. This work aimed to verify if the topographical distribution of the osteons responds to geometrical order. From an analysis of hundreds of bone sections of domestic and wild mammals collected over 60 years, it is evident that the spatial distribution of osteons varies from a random arrangement in the irregular Haversian tissue to an ordered geometric arrangement in the dense Haversian tissue. In this work, a new method of classification of Haversian bone tissue was introduced based on the number of points of contact that the perimeter of an osteon has with neighboring osteons. When the functional commitment of the bone is maximum to resist biomechanical stresses, the osteons are smaller and crammed adjacent to each other as if to occupy less space. Their spatial arrangement, in this case, reminds us of Kepler’s conjecture, which predicts the ideal arrangement that spheres must have to occupy as little space as possible. The conjecture was elaborated by Kepler in the Seventeenth Century to solve the practical problem linked to the need to transport the largest number of cannonballs in warships. Full article

Changeability analysis methods primarily assist with formulating a response to uncertain and new requirements from various system stakeholders and include asset management issues such as modelling lifecycle path dependency. Epoch-era networks proved to be an effective tool for managing the evolving requirements of a capability system, ensuring sustained value through life. Over the life of a system, stakeholders are faced with countless options to change their capability systems to sustain value, which is path dependent and can greatly impact the scope of decisions available later in life. This paper introduces and demonstrates the application of a revised epoch-era network approach to explore many potential lifecycle paths, along with utility vs. expense strategies, demonstrated through an example of a military frigate subject to evolving requirements. Results indicated the future limitations to sustaining value if the largest and most capable technology upgrades are selected too early in life. The two best lifecycle paths from different strategies were compared to understand the utility/expense trade-offs for the most optimal frigate upgrade trajectory. Full article