The development of a maneuverable underwater high-speed vehicle is worthy of attention and study using supercavitation drag reduction theory and technology. The supercavity shape determines the hydrodynamics of the vehicle, and especially during a maneuver, its unsteady characteristics have a significant impact on the motion stability of the vehicle. The three-dimensional dynamic model of a ventilated supercavitating vehicle is established using the unsteady supercavity dynamic model based on the rigid body dynamics theory as an extension of the vehicle's longitudinal dynamic model in our recent work. The vehicle's accelerating and decelerating motions are simulated in the straight flight state using a self-developed numerical method based on the vehicle's dynamic model with the designed control law. Motion characteristics are analyzed on the evolution laws of the vehicle's motion state variables and control variables and the supercavity's characteristic parameters (i.e., ventilation cavitation number, supercavity maximum diameter and supercavity length) in the acceleration motions. The evolution laws in the accelerating and decelerating motions are compared, and the effects of the acceleration on the laws are further analyzed. This study lays the foundation for the in-depth study of the hydrodynamic characteristics and motion stability of ventilated supercavitating vehicles in maneuvering states.

In order to solve the cooperative search problem of multiple unmanned aerial vehicles (multi-UAVs) in a large-scale area, we propose a genetic algorithm (GA) incorporating simulated annealing (SA) for solving the task region allocation problem among multi-UAVs on the premise that the large area is divided into several small areas. Firstly, we describe the problem to be solved, and regard the task areas allocation problem of multi-UAVs as a multiple traveling salesman problem (MTSP). And the objective function is established under the premise that the number of task areas to be searched by each UAV is balanced. Then, we improve the GA, using the advantages of the SA can jump out of the local optimal solution to optimize the new population of offspring generated by GA. Finally, the validity of the algorithm is verified by using the TSPLIB database, and the set MTSP problem is solved. Through a series of comparative experiments, the validity of GAISA and the superiority of solving the MTSP problem can be demonstrated.

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The shear flow on the large-scale gas-water wall inside a ventilated supercavity exhibits gas entrainment mode and determines the change law of the supercavity's gas loss, significantly impacting the shape and dynamics of the supercavity. Therefore, to develop an accurate prediction model and a ventilation control method for a supercavity under complex motion conditions, it is required to systematically and quantitatively study the shear flow characteristics and rules. This study calculates and comparatively analyzes the shear layers on either side of the supercavity wall based on numerical simulations of ventilated supercavitating flows in an unbounded field using the gas-vapor-water multi-fluid model. It is shown that the external shear layer with a very irregular outer boundary is considerably thinner than the internal shear layer. We further analyze the flow and distribution characteristics of all the phases in the shear layers with and without the influence of gravity. Our analysis confirms that all the phases exhibit a similar velocity change rule along the supercavity radial direction in the shear layer, whereas gas and water phases exhibit opposite radial phase distribution trends. It was also seen when natural cavitation occurs that the vapor phase is mainly distributed in the head of the supercavity. Moreover, at the same radial position, it was seen that the vapor velocity was higher than the gas velocity and slightly lower than the water velocity. Using the shear flow and phase distribution characteristics, a shear-layer gas loss model is established and validated for ventilated supercavitating flows.

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