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This article emphasises the design, analysis and fabrication of a fighter jet combat UAV featuring a delta wing configuration, renowned for its high manoeuvrability and maximum performance in aerial combat scenarios. The process begins with the design phase, where the UAV is modelled using CAD software. The fabrication involves moulding techniques, utilising foam as the primary material, reinforced with a fiberglass sandwich panel for enhanced strength. Subsequently, static structural analysis and wing aerodynamic simulations at a constant velocity of 15 m/s are conducted using ANSYS FLUENT. This comprehensive approach integrates cutting-edge design tools, innovative fabrication techniques and advanced computational analysis to advance fighter jet combat UAV development.

In this study, we conducted turning tests with rudder angles ± 35 ∘ and ± 20 ∘ / 20 ∘ zig-zag maneuver tests in deep and shallow water using a model of a 3,600 TEU container ship called KCS. Through the comparison of these test results with the free-running test results of three other ships, the shallow-water effect on the maneuverability was investigated. The shallow-water effects obtained during the turning and zig-zag maneuvers are as follows: Turning: The advance ( A D ) decreases slightly when the water depth-to-ship draft ratio ( h / d ) is approximately 2.0 and increases significantly as the water depth decreases. The tactical diameter ( D T ) (up to h / d = 2.0 ) is approximately the same as that in deep water and becomes significantly larger when h / d becomes smaller than 2.0. Thus, there is a slight difference in the appearance of the shallow-water effects in A D and D T . Zig-zag maneuvers: The overshoot angle increases slightly near h / d = 2.0 compared with that in deep water and becomes significantly smaller as the water depth becomes shallower. The forward distance ( l 20 ), until reaching the heading + 20 ∘ / - 20 ∘ after steering, was approximately the same as that in deep water or decreased slightly, until approximately h / d = 2.0 . Furthermore, it increased as the water depth decreased. This is because the course stability of the ship deteriorated at approximately h / d = 2.0 .

The continuous growth in maritime traffic and recent developments towards autonomous navigation have directed increasing attention to navigational safety in which new tools are required to identify real-time risk and complex navigation situations. These tools are of paramount importance to avoid potentially disastrous consequences of accidents and promote safe navigation at sea. In this study, an adaptive ship-safety-domain is proposed with spatial risk functions to identify both collision and grounding risk based on motion and maneuverability conditions for all vessels. The algorithm is designed and validated through extensive amounts of Automatic Identification System (AIS) data for decision support over a large area, while the integration of the algorithm with other navigational systems will increase effectiveness and ensure reliability. Since a successful evacuation of a potential vessel-to-vessel collision, or a vessel grounding situation, is highly dependent on the nearby maneuvering limitations and other possible accident situations, multi-vessel collision and grounding risk is considered in this work to identify real-time risk. The presented algorithm utilizes and exploits dynamic AIS information, vessel registry and high-resolution maps and it is robust to inaccuracies of position, course and speed over ground records. The computation-efficient algorithm allows for real-time situation risk identification at a large-scale monitored map up to country level and up to several years of operation with a very high accuracy.

Marine habitats vary widely in structure, from incredibly complex coral reefs to simpler deep water and open ocean habitats. Hydromechanical models of swimming kinematics and microevolutionary studies suggest that these habitats select for different body shape characteristics. Fishes living in simple habitats are predicted to experience selection for energy-efficient sustained swimming, which can be achieved by fusiform body shapes. In contrast, fishes living in complex habitats are predicted to be under selection for maneuverability, which can be enhanced by deep-bodied and laterally compressed forms. To look for a signature of these processes at a broad macroevolutionary scale, we quantified the body shapes of 3322 species of marine teleostean fishes using a series of linear measurements. We scored each species for whether they were reef-associated or not and tested for morphological differences using a phylogenetic framework. Our results confirmed significant overall shape differences between reef-associated teleosts and those occupying structurally simpler marine habitats. Reef-associated species have, on average, deeper bodies and higher depth-to-width ratios, while non-reef species are more streamlined with narrower and shallower caudal peduncles. Despite the numerous evolutionary forces that may influence body shapes on a broad macroevolutionary scale, our results reveal differences in body shapes between reef-associated and non-reef species that are consistent with hydromechanical models of swimming kinematics as well as with microevolutionary patterns.

Compared with traditional underwater vehicles, bio-inspired fish robots have the advantages of high efficiency, high maneuverability, low noise, and minor fluid disturbance. Therefore, they have gained an increasing research interest, which has led to a great deal of remarkable progress theoretically and practically in recent years. In this review, we first highlight our enhanced scientific understanding of bio-inspired propulsion and sensing underwater and then present the research progress and performance characteristics of different bio-inspired robot fish, classified by the propulsion method. Like the natural fish species they imitate, different types of bionic fish have different morphological structures and distinctive hydrodynamic properties. In addition, we select two pioneering directions about soft robotic control and multi-phase robotics. The hybrid dynamic control of soft robotic systems combines the accuracy of model-based control and the efficiency of model-free control, and is considered the proper way to optimize the classical control model with the intersection of multiple machine learning algorithms. Multi-phase robots provide a broader scope of application compared to ordinary bionic robot fish, with the ability of operating in air or on land outside the fluid. By introducing recent progress in related fields, we summarize the advantages and challenges of soft robotic control and multi-phase robotics, guiding the further development of bionic aquatic robots.

In this paper, a novel analytical framework for Dynamic Quaternion Ship Domain (DQSD) models has been initially proposed via the Quaternion Ship Domain (QSD) model structure. Unlike previous ship domains, the proposed DQSD model is able to capture essential subjectivity and objectivity of ship domains. To be specific, the significant characteristics are as follows: (1)The proposed DQSD model is integrated by three independent submodels of ship, human and circumstance, which are determined by ship manoeuvrability, navigator's states, and navigation circumstance, respectively.(2)The ship manoeuvrability derived from the MMG-type ship motion model is employed to establish the ship submodel which identifies the DQSD scale.(3)A novel navigator reliability model is proposed to realize the human submodel which defines the ship domain shape with navigator ability, physical and mental states being input variables.(4)In addition, visibility, wind force, wave and traffic congestion are incorporated into the circumstance submodel which is employed to zoom in or out of the DQSD-type ship domain. Finally, the well-known Esso Osaka tanker model is used to conduct simulation studies on various typical stationary and dynamic situations, and comparative investigations with each other have been comprehensively analysed. Simulation results demonstrate that the DQSD model can capture critical dynamics of ship domains and undoubtedly be effective and superior to previous ship domains in terms of performance and accuracy.

The congestion of waterways can easily lead to traffic hazards. Moreover, according to the data, the majority of sea collisions are caused by human error and the failure to comply with the Convention on the International Regulation for the preventing Collision at Sea (COLREGs). To avoid this situation, ship automatic collision avoidance has become one of the most important research issues in the field of marine engineering. In this study, an efficient method is proposed to solve multi-ship collision avoidance problems based on the multi-agent reinforcement learning (MARL) algorithm. Firstly, the COLREGs and ship maneuverability are considered for achieving multi-ship collision avoidance. Subsequently, the Optimal Reciprocal Collision Avoidance (ORCA) algorithm is utilized to detect and reduce the risk of collision. Ships can operate at the safe velocity computed by the ORCA algorithm to avoid collisions. Finally, the Nomoto three-degrees-of-freedom (3-DOF) model is used to simulate the maneuvers of ships. According to the above information and algorithms, this study designs and improves the state space, action space and reward function. For validating the effectiveness of the method, this study designs various simulation scenarios with thorough performance evaluations. The simulation results indicate that the proposed method is flexible and scalable in solving multi-ship collision avoidance, complying with COLREGs in various scenarios.

Precise prediction of unsteady flapping aerodynamics in insect flight is of potential importance in the analysis of maneuverability and flight control. While the quasi-steady model is a cheap while reasonable tool, accurate evaluation of unsteady dynamic effects in complex flight behaviours remains a challenge. Here we develop a computational fluid dynamics (CFD) data-driven aerodynamic model (CDAM), which is informed by high-fidelity CFD simulations using overset meshes to enable the precise and fast prediction of both cycle-averaged and transient aerodynamic force, torque and power with various flying motions and wing kinematics. The CDAM comprises a quasi-steady model for flapping wings and an aerodynamic model for a moving body. The least square method and a surrogate method are employed to achieve aerodynamic coefficient fitting through training using a CFD database. With comparison to CFD test data, the CDAM is validated to be capable of accurately evaluating the aerodynamic force, torque and power of a wing-body bumblebee model in various flight velocities. A genetic optimization algorithm embedded with CDAM is proposed to determine trimmed states for forward flight through adjusting wing kinematics, indicating that bumblebees likely fly in a minimized mass-specific aerodynamic power consumption. The CDAM is further applied to proportional-derivative-based longitudinal flight control of bumblebee hovering, with the control parameters optimized by Laplace transformation and the root locus method, which is implemented consistently in both CDAM and CFD environments. Our results demonstrate that CDAM provides a versatile tool to achieve fast and precise aerodynamical prediction for flying insects in various flight behaviours.

This paper aims to verify a new automatic berthing system using a path following algorithm. Berthing operation is one of the most burdensome tasks for crews among several ship operations. The maneuverability of a ship at low speed during berthing operation deteriorates and becomes more vulnerable to disturbances such as wind. Therefore, it is necessary to support and automate operations that require advanced skills such as berthing operation. Previous studies on automatic berthing have investigated various methods to handle the nonlinearity of ship maneuvering motion and determine the optimal control variable. There is a trade-off between accuracy and real-time performance of berthing control from these studies. The algorithms must have sufficiently real-time performance while maintaining the accuracy of control. For these purposes, we propose the automatic berthing system applied a path following algorithm for a ship with one propeller and one rudder in this paper. We show the mathematical model for numerical simulation of berthing control and carried out system identification of the subject ship. In full-scale experiments, the proposed system performed automatic berthing control in both calm wind conditions around 2 m/s and strong wind conditions around 6 m/s.

The timely and proper rehabilitation of damaged roads is essential for road maintenance, and an effective method to detect road surface distress with high efficiency and low cost is urgently needed. Meanwhile, unmanned aerial vehicles (UAVs), with the advantages of high flexibility, low cost, and easy maneuverability, are a new fascinating choice for road condition monitoring. In this paper, road images from UAV oblique photogrammetry are used to reconstruct road three-dimensional (3D) models, from which road pavement distress is automatically detected and the corresponding dimensions are extracted using the developed algorithm. Compared with a field survey, the detection result presents a high precision with an error of around 1 cm in the height dimension for most cases, demonstrating the potential of the proposed method for future engineering practice.