Aerodynamics of Landing Maneuvering of an Unmanned Aerial Vehicle in Close Proximity to a Ground Vehicle

Abstract

<div class="section abstract"><div class="htmlview paragraph">Autonomous takeoff and landing maneuvers of an unmanned aerial vehicle (UAV) from/on a moving ground vehicle (GV) have been an area of active research for the past several years. For military missions requiring repeated flight operations of the UAV, precise landing ability is important for autonomous docking into a recharging station, since such stations are often mounted on a ground vehicle. The development of precise and efficient control algorithms for this autonomous maneuvering has two key challenges; one is related to flight aerodynamics and the other is related to a precise detection of the landing zone. The aerodynamic challenges include understanding the complex interaction of the flows over the UAV and GV, potential ground effects at the proximity of the landing surface, and the impact of the variations in the surrounding wind flow and ambient conditions. While a large body of work in this area can be found on the control aspect of the UAV landing and takeoff maneuvers, research on the aerodynamic aspects of such maneuvers is non-existent. This paper presents an in-depth computational fluid dynamics (CFD) based aerodynamic characterization of the transient flow fields associated with the landing of a hobby-model quadcopter (the UAV) on an idealized road vehicle (the GV), the 35-degree slant angle Ahmed body. Transient improved delayed detached eddy simulations (IDDES) are carried out using the commercial CFD code STAR-CCM+. Our study indicates that the pressure field is the first flow property that gets impacted by the proximity of the UAV to the GV.</div></div>

Application of the DMD Approach to High Reynolds Number Flow Over an Idealized Ground Vehicle

“…The computational resources required by the mfDMD algorithm look feasible for the implementation alongside a DMD with control modification to effect real-time control of a moving vehicle by an on-board controller. Applications of the modified DMD algorithm to aerodynamic interactions between vehicles in close proximity, such as dynamic platooning conditions [45], and NASCAR race cars subject to ride height and crosswind changes [21,51] are the subjects of future research.…”

“…In Figure 5c, we observed that the result differences are mostly toward the rear of the GV and around the edges of the front face. From Figure 5d, we observed that the discrepancies are most pronounced on the rear slant, rear fascia, and around the two downstream stilts, which are regions with recirculation and where smaller vortical structures can exist; see [20,45]. We will revisit this when analyzing Figure 6.…”

“…This choice is driven by the fact that extensive experimental and CFD data are available for correlation and validation of this idealized GV model. Among many variants of the Ahmed Body model, we, however, chose to proceed with the 35 • slant-angle Ahmed body model, as the flow over this model shows all the salient features of the flow over a Sport Utility Vehicle (SUV)-type of vehicle, which is the subject of the next phase of our work [45].…”