A Quadmaran vessel is a maritime navigation vessel with four hulls, and is expected to be utilized for high-density water quality observation in aquaculture farms. The performance of the vessel during dynamic positioning (DP) is integral to the accuracy of collected data. However, there are no models available to understand the motion characteristics of the multi-hull vessels in DP mode. Therefore, a computational model was developed to predict the DP motion of the Quadmaran vessel based on quasi-static assumptions. The fluid forces on the hulls, the thrust force of the propellers, and the external wind forces are modelled systematically, assuming the average speed while in DP does not exceed 0.25 m/s. A series of oblique towing tests and static turning tests were conducted on a 1/3 scale model to determine the hydrodynamic coefficients, while the Propeller Open Test was conducted to survey the propeller performance. The wind load was also incorporated into the computational model. Experimental validation tests were conducted in calm water and actual sea areas, and the correlation between experiment and simulation results was good. We concluded that the computational model can predict the DP motion of the Quadmaran vessel with an accuracy of roughly 2 m.

This study will discuss the influence of descent flow from small unmanned aerial vehicle (quadcopter) on a small floating body. At present, unmanned aerial vehicles, especially industrial unmanned aerial vehicles, are playing an active role in various applications such as agriculture, aerial photography and disaster support. Among them, quadcopter drone, which is a convenient

Rapid advances in deep-space exploration are drawing increasing attention from geode-sists and creating an urgent demand for effective management and visualization of deep-space object information. This paper presents a comprehensive study on methods for managing and visualizing small celestial bodies’ “orbit–shape–field” spatial information, including geometric shape, orbital simulation and gravitational fields. We develop an in-tegrated solution that combines a backend spatial database, a web frontend and a virtual reality (VR) frontend. On the backend, we design and implement a database to catalog heterogeneous small-body information efficiently, where partitioned tables are adopted to support scalable storage, fast querying and convenient updates. On the web frontend, Spacekit.js and Cesium.js are integrated to simulate coordinated solar-system motion of planets, comets and asteroids (both rotation and revolution) while enabling rapid loading and rendering of gravitational vector fields. On the VR frontend, we build a standalone Unreal Engine 5 application that renders orbits with spline curves consistent with the web results and supports cooperative multi-body motion in immersive exploration. Finally, performance tests are conducted to recommend VR hardware configurations and practical data-loading scales for smooth gravitational-vector rendering and interaction. These methods support analysis workflows and have potential value for deep-space science.