Search Results (72)

To improve collision risk prediction in high-traffic coastal waters and support real-time decision-making in maritime navigation, this study proposes a regional collision risk prediction system integrating the Computed Distance at Collision (CDC) method with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Unlike Distance at Closest Point of Approach (DCPA), which depends on the position of Global Positioning System (GPS) antennas, Computed Distance at Collision (CDC) directly reflects the actual hull shape and potential collision point. This enables a more realistic assessment of collision risk by accounting for the hull geometry and boundary conditions specific to different ship types. The system was designed and validated using ship motion simulations involving bulk and container ships across varying speeds and crossing angles. The CDC method was used to define collision, almost-collision, and near-collision situations based on geometric and hydrodynamic criteria. Subsequently, the FIS–CDC model was constructed using the ANFIS by learning patterns in collision time and distance under each condition. A total of four input variables—ship speed, crossing angle, remaining time, and remaining distance—were used to infer the collision risk index (CRI), allowing for a more nuanced and vessel-specific assessment than traditional CPA-based indicators. Simulation results show that the time to collision decreases with higher speeds and increases with wider crossing angles. The bulk carrier exhibited a wider collision-prone angle range and a greater sensitivity to speed changes than the container ship, highlighting differences in maneuverability and risk response. The proposed system demonstrated real-time applicability and accurate risk differentiation across scenarios. This research contributes to enhancing situational awareness and proactive risk mitigation in Maritime Autonomous Surface Ship (MASS) and Vessel Traffic System (VTS) environments. Future work will focus on real-time CDC optimization and extending the model to accommodate diverse ship types and encounter geometries. Full article

The design process for motor yachts primarily relies on the experience of designers, who draw upon their knowledge gained from working on similar hull forms. However, when a new concept is to be developed, the experience garnered from standard platforms may not suffice for achieving a successful design within a short timeframe. Designing a motor yacht involves considering multiple aspects of ship hydrodynamics, including resistance, propulsion, seakeeping, and maneuverability. While these factors have been extensively discussed for different types of ships, a comprehensive joint investigation of hulls, such as those of motor yachts, is noticeably absent in the available literature. This paper aims to fill that gap by providing guidelines for the design of motor yachts with lengths ranging from 20 to 40 m. As part of a preliminary study, a series of 15 yacht hulls were developed, starting from a reference hull form. The resistance, seakeeping and maneuverability performance of these hulls were assessed under specified environmental conditions and speeds, following the ISO 22834:2022 guidelines for comfort assessment. The calculations produced response surfaces detailing the hydrodynamic properties for this series of yachts as functions of the main dimensions of the hulls. Ultimately, these responses assist in identifying optimal design solutions for the main dimensions of a new motor yacht within the 20 to 40 m length range. Full article

Marine diesel engines face persistent challenges in balancing transient black smoke emissions and maneuverability under low-speed conditions due to inherent limitations of single turbocharger systems, such as high inertia and delayed intake response, compounded by control strategies prioritizing steady-state efficiency. To address this gap, this study proposes a dual -turbocharger dynamic matching framework integrated with a speed–pitch synergistic control strategy—the first mechanical-control co-design solution for transient emission suppression. By establishing a λ-opacity correlation model and a multi-physics ship–engine–propeller simulation platform, we demonstrate that the Type-C dual turbocharger reduces rotational inertia by 80%, shortens intake pressure buildup time to 25.8 s (54.7% faster than single turbochargers), and eliminates high-risk black smoke regions (maintaining λ > 1.5). The optimized system reduces the fuel consumption rate by 12.9 g·(kW·h)⁻¹ under extreme loading conditions and decreases the duration of high-risk zones by 74.4–100%. This study provides theoretical and practical support for resolving the trade-off between transient emissions and maneuverability in marine power systems through synergistic innovations in mechanical design and control strategies. Full article

To ensure safe navigation, ship operators must not only meet the criteria defined in the International Maritime Organization (IMO) maneuverability standards but also understand maneuvering characteristics in restricted waters. This study numerically analyzed the hydrodynamic lateral forces and yaw moments acting on a stern trawler, a container ship, and a very large crude carrier (VLCC) with different hull forms as they navigated near a semi-circular bank wall. The effects of varying bank radius, lateral clearance, and water depth were examined. The results showed that the VLCC experienced the strongest attractive lateral force, while the stern trawler exhibited the most significant yaw moment. The hydrodynamic interaction patterns of the stern trawler and container ship were similar, whereas the VLCC displayed distinct behavior due to its fuller hull and greater inertia. These findings demonstrate that hull geometry significantly influences hydrodynamic interactions near boundaries, and the degree of response varies by ship type. The results provide valuable reference data for improving navigation safety in confined waters and preventing marine accidents such as collisions and groundings. This study contributes to a better understanding of ship–bank interaction and offers a theoretical basis for maneuvering assessments of various ship types in restricted maritime environments. Full article

In dynamic environments with continuous variability, such as those affected by typhoons, ship path planning must account for both navigational safety and the maneuvering characteristics of the vessel. However, current methods often struggle to accurately capture the continuous evolution of dynamic obstacles and generally lack adaptive exploration mechanisms. Consequently, the planned routes tend to be suboptimal or incompatible with the ship’s maneuvering constraints. To address this challenge, this study proposes a Space–Time Integrated Q-Learning (STIQ-Learning) algorithm for dynamic path planning under typhoon conditions. The algorithm is built upon the following key innovations: (1) Spatio-Temporal Environment Modeling: The hazardous area affected by the typhoon is decomposed into temporally and spatially dynamic obstacles. A grid-based spatio-temporal environment model is constructed by integrating forecast data on typhoon wind radii and wave heights. This enables a precise representation of the typhoon’s dynamic evolution process and the surrounding maritime risk environment. (2) Optimization of State Space and Reward Mechanism: A time dimension is incorporated to expand the state space, while a composite reward function is designed by combining three sub-reward terms: target proximity, trajectory smoothness, and heading correction. These components jointly guide the learning agent to generate navigation paths that are both safe and consistent with the maneuverability characteristics of the vessel. (3) Priority-Based Adaptive Exploration Strategy: A prioritized action selection mechanism is introduced based on collision feedback, and the exploration factor $ϵ$ is dynamically adjusted throughout the learning process. This strategy enhances the efficiency of early exploration and effectively balances the trade-off between exploration and exploitation. Simulation experiments were conducted using real-world scenarios derived from Typhoons Pulasan and Gamei in 2024. The results demonstrate that in open-sea environments, the proposed STIQ-Learning algorithm achieves reductions in path length of 14.4% and 22.3% compared to the D* and Rapidly exploring Random Trees (RRT) algorithms, respectively. In more complex maritime environments featuring geographic constraints such as islands, STIQ-Learning reductions of 2.1%, 20.7%, and 10.6% relative to the DFQL, D*, and RRT algorithms, respectively. Furthermore, the proposed method consistently avoids the hazardous wind zones associated with typhoons throughout the entire planning process, while maintaining wave heights along the generated routes within the vessel’s safety limits. Full article

As a novel energy-saving and maneuvering device for ships, the gate rudder system (GRS) functions similarly to an accelerating duct. While providing additional thrust, its independently controllable rudder blades on either side of the propeller also enhance ship maneuverability. The GRS was first fully implemented on a container ship in Japan, demonstrating improved propulsion efficiency, fuel savings, and excellent performance in maneuvering, noise, and vibration reduction. In recent years, extensive research has been conducted on the hydrodynamic performance, acoustic characteristics, and energy-saving effects of the GRS. However, certain gaps remain in the research, such as a lack of systematic studies on optimal GRS design in the publicly available literature. Only Ahmet Yusuf Gurkan has investigated the sensitivity of propulsion performance to parameters such as rudder angle, rudder X-shift, rudder tip skewness, and blade tip chord ratio. Therefore, this study employs the JBC benchmark vessel and adopts a coupled CFD-CAESES approach to develop a matching optimization design for the GRS. The influence of geometric parameters—including GRS airfoil camber, maximum camber position, chord length, thickness, distance from the leading edge to the propeller plane, and the gap between the GRS and propeller blades—on ship propulsion performance is investigated. The sensitivity of these design variables to propulsion performance is analyzed, and the optimal GRS design is selected to predict and evaluate its energy-saving effects. This research establishes a rapid and comprehensive CFD-based optimization methodology for GRS matching design. The findings indicate that the gap between the GRS and propeller, the distance from the GRS to the stern, and the airfoil camber of the GRS significantly contribute to various performance responses. After GRS installation, the viscous pressure resistance of the JBC ship decreases, resulting in an 8.05% energy-saving effect at the designated speed. Full article

This study aims to improve control accuracy across various ship types, speeds, and external interference scenarios using conventional control methods. The ship’s maneuvering model is identified online and the identified parameters are applied for self-adaptive course and track control, laying the groundwork for intelligent ship control. A response-type ship maneuvering model is used, with a forgetting factor incorporated into the recursive least squares (RLS) algorithm based on the iterative least squares (ILS) method. This addresses the limitations of the ordinary least squares (OLS) method and the RLS algorithm’s reduced update speed with data accumulation. The forgetting factor recursive least squares (FFRLS) algorithm is employed to identify the maneuverability index parameters (K and T). Data for identification are obtained via a maneuvering simulator and the impact of different forgetting factors on the identification process is evaluated. The identified results are then used to calculate real-time optimal PID (OP-PID) parameters, leading to the development of a Self-adaptive OP-PID course control method. Simulations of course and track control are conducted with various ship types and environments, comparing the Self-adaptive OP-PID with existing OP-PID methods. Results show that the Self-adaptive OP-PID outperforms the OP-PID in course stability, convergence time, and track deviation under the same conditions. Full article

Considering that slow steaming requires low engine power, which impedes maneuverability under severe sea conditions, the International Maritime Organization (IMO) provides guidelines for the minimum propulsion power (MPP) required to maintain ship maneuverability in adverse conditions. This study focused on the characteristics of self-propulsion factors in the context of MPP assessment to enhance MPP prediction accuracy. Overload tests were conducted at low speeds of advance, considering added resistance in adverse conditions. Moreover, propeller open-water tests were conducted corresponding to propeller flow with low Reynolds numbers to investigate their effect on self-propulsion factors. In addition, computational fluid dynamics (CFD) simulations were conducted to analyze physical phenomena such as the flow field and pressure distribution under model test conditions. The results indicated that the thrust deduction factor was lower than that given in the guidelines, whereas the wake fraction was higher at the required forward speed of 2 knots. The MPP assessment in this study revealed that the required brake power was 4–5% lower than that given in the guidelines, indicating that the guidelines need reviewing for a more reliable assessment. Full article

As the windage area of containerships increases, wind loads are becoming a more significant factor in navigating ships at open sea. This can lead to increased resistance and affect ship stability, maneuverability, and fuel efficiency. In this study, machine learning models based on the multilayer perceptron and gradient-boosted tree methods were employed to predict wind load coefficients for containerships with various container configurations. Six models were developed to estimate longitudinal and transverse wind loads and moment coefficients using a comprehensive dataset generated by numerical simulations. Numerical simulations were conducted for two containerships with various container configurations at angles of attack ranging from 0° to 180°. The models showed satisfactory performance on an evaluation set, with high coefficients of determination. The models based on the gradient-boosted tree method slightly outperformed those based on the multilayer perceptron method, particularly in terms of mean absolute error. The study demonstrates that accurate prediction of wind load coefficients is feasible, making these models a reliable tool for practical engineering applications. Full article

Currently, research on the rotational modulation of dual-axis inertial navigation for isolated carrier motion does not provide sufficient solutions for the compensation of the gyroscope scale factor error caused by the Earth’s rotation. Moreover, it is primarily applied to ships with low maneuverability and has not yet been implemented in the field of pure inertial guidance weapons. A dual-axis inertial isolation rotation modulation method is proposed to address this issue, taking into account the application characteristics of long-endurance guided weapons. An analysis of the system error characteristics under the coupling of multiple error sources acting on IMU was conducted, and it was found that the angular velocity of the inertial isolation carrier can significantly reduce the output error of the IMU. A dual-axis inertial isolation shaft system installation error compensation algorithm was designed, and an improvement was made based on the traditional sixteen-sequence rotation scheme to compensate for the projection components of the Earth’s rotation and carrier motion on the inner and outer frame rotation axes, achieving the inertial isolation rotation modulation function of dual-axis inertial navigation. Based on the attitude changes in long-range guided weapons, Monte Carlo simulation verification was conducted, and the results showed that this scheme can improve inertial navigation accuracy by 10% to 20%. Full article

The poor maneuverability inherent to large ships is a non-negligible problem that restricts the development of the shipping industry, as large ships can only cruise at an excessively conservative speed when they encounter complicated traffic conditions; nevertheless, ship collision accidents still occasionally occur. In the present study, the novel concept of spoiler fins for modern large ships is proposed. In order to assess their effectiveness in enhancing ship maneuverability, a KRISO container ship (KCS) was selected to carry a pair of spoiler fins, after which a simplified simulation approach for saving the calculation resource was designed for ship collision avoidance conditions, and a full-scale numerical model, including the ship hull, fin, and fluid field domain, was established. Transient-state hydrodynamic forces were calculated during collision avoidance maneuvers using the CFD method; the pressure and velocity contours around the ship were demonstrated; and the ship motion trajectories under different initial ship speeds were simulated and predicted through the adoption of overset mesh and 6-DOF dynamic mesh techniques. Eventually, the improved course-changing performance, dependent on the spoiler fins, was validated. Full article

Unmanned aerial vehicles (UAVs) with cameras offer extensive monitoring capabilities and exceptional maneuverability, making them ideal for real-time ship detection and effective ship management. However, ship detection by camera-equipped UAVs faces challenges when it comes to multi-viewpoints, multi-scales, environmental variability, and dataset scarcity. To overcome these challenges, we proposed a data augmentation method based on stable diffusion to generate new images for expanding the dataset. Additionally, we improve the YOLOv8n OBB model by incorporating the BiFPN structure and EMA module, enhancing its ability to detect multi-viewpoint and multi-scale ship instances. Through multiple comparative experiments, we evaluated the effectiveness of our proposed data augmentation method and the improved model. The results indicated that our proposed data augmentation method is effective for low-volume datasets with complex object features. The YOLOv8n-BiFPN-EMA OBB model we proposed performed well in detecting multi-viewpoint and multi-scale ship instances, achieving the mAP (@0.5) of 92.3%, the mAP (@0.5:0.95) of 77.5%, a reduction of 0.8 million in model parameters, and a detection speed that satisfies real-time ship detection requirements. Full article

The maneuverability of ships is influenced by several factors, including ship design, size, propulsion system, hull shape, and external conditions such as wind, waves, and currents. The size, shape, and arrangement of the hull, rudder, and propeller are decisive for maneuverability. Hydrodynamic forces such as bank effect and squat significantly impact the maneuverability of large ships in narrow channels. With the increasing trend of building ever-larger ships, the demand to evaluate the maneuvering performance of the ship at the design stage has become more critical than ever. Both experimental and computational methods are used to obtain accurate maneuvering characteristics of vessels. In this study, the methods for predicting ship maneuvering characteristics are analyzed using a systematic review based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA). This article contributes to a deeper understanding of the hydrodynamic capabilities of ships and identifies possible future challenges in the field of ship hydrodynamics. The findings inform educators and the shipping industry about the importance of predicting the maneuvering performance of ships, with an emphasis on the education and training of seafarers needed to make timely decisions in critical situations. Full article

Enhancing the path planning capabilities of ships is crucial for ensuring navigation safety, saving time, and reducing energy consumption in complex maritime environments. Traditional methods, reliant on static algorithms and singular models, are frequently limited by the physical constraints of ships, such as turning radius, and struggle to adapt to the maritime environment’s variability and emergencies. The development of reinforcement learning has introduced new methods and perspectives to path planning by addressing complex environments, achieving multi-objective optimization, and enhancing autonomous learning and adaptability, significantly improving the performance and application scope. In this study, we introduce a two-stage path planning approach for large ships named MAPF–DQN, combining Manipulation-Compliant Artificial Potential Field (MAPF) with Deep Q-Network (DQN). In the first stage, we improve the reward function in DQN by integrating the artificial potential field method and use a time-varying greedy algorithm to search for paths. In the second stage, we use the nonlinear Nomoto model for path smoothing to enhance maneuverability. To validate the performance and effectiveness of the algorithm, we conducted extensive experiments using the model of “Yupeng” ship. Case studies and experimental results demonstrate that the MAPF–DQN algorithm can find paths that closely match the actual trajectory under normal environmental conditions and U-shaped obstacles. In summary, the MAPF–DQN algorithm not only enhances the efficiency of path planning for large ships, but also finds relatively safe and maneuverable routes, which are of great significance for maritime activities. Full article

It is necessary to maintain maneuverability for ship navigation in shallow water, such as channels, ports and other confined waters. In this study, a turning circle maneuver with 35° rudder deflection and a 20/5 zigzag maneuver for KVLCC2 in shallow waters are tested numerically to directly predict the maneuverability of the ship in shallow water. A viscous in-house CFD solver is applied with the dynamic overset grid approach. The impacts of the water depth on the ship’s maneuverability in terms of turning and zigzag competence are evaluated, and the underlying mechanism is analyzed. The numerical method is validated by comparing it with experimental data on the turning indices, which shows good agreement. It is demonstrated that the turning capability become worse with a smaller depth–draft ratio, thus resulting in a lower yaw rate and a greater steady turning diameter. However, the drift angle and lateral speed are reduced with a smaller depth–draft ratio for zigzag maneuvers, but the overshoot angle and turn lag vary with the water depth non-monotonically. Full article