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Unmanned aerial vehicle (UAV) design aspects are as broad as the missions they are used to support. In some cases, the UAV mission scope can impose design constraints that can be difficult to achieve. This paper describes recent work performed at West Virginia University (WVU) to support repeated flight testing of a single-use UAV platform with emphasis on the highly specialized wings required to help meet the overall airframe mass properties constrained by the project sponsor. The wings were fabricated using a molded polyurethane (PU) foam as the base material which was supported by several different types of rigid and flexible substructures, skins, and matrix-infused fiber elements. Different ratios of infused fiber mass to PU foam were tested and additional tungsten masses were added to the wings to achieve the correct total mass and mass distribution of the wings.

As unmanned aerial vehicle applications continue their rise in popularity in the public and private sectors, there is an increasing demand in many cases for smaller, more efficient low speed unmanned aerial vehicles (UAVs). Although the primary drivers for the continued performance improvement of smaller UAV platforms tend to be in the areas of electronics miniaturization and improved energy storage, aerodynamics, particularly in the low Reynolds number regime, still have a significant role in the overall performance enhancement of small UAVs. This paper focuses on the study of the nearfield aerodynamic effects of a low-power active flow enhancement technique known as dielectric barrier discharge (DBD) in very low speed/low Reynolds number flows most closely associated with small and micro unmanned aerial vehicles.

In this research, the magnetoplasmadynamic (MPD) effects of applying a toroidal magnetic field around an ionized exhaust plume were investigated to manipulate the exhaust profile of the plasma jet under near vacuum conditions. Tests for this experiment were conducted using the West Virginia University (WVU) Hypersonic Arc Jet Wind Tunnel. A series of twelve N52 grade neodymium magnets were placed in different orientations around a steel toroid mounted around the arc jet’s exhaust plume. Four different magnet orientations were tested in this experiment. Two additional configurations were run as control tests without any imposed magnetic fields surrounding the plume. Each test was documented using a set of 12 photographs taken from a fixed position with respect to the flow. The photographic data was analyzed by comparing images of the exhaust plume taken 10, 20, and 30 seconds after the plasma jet was activated.

Scale-resolving turbulence modeling for engine flow simulation has constantly increased its popularity in the last decade. In contrast to classical RANS modeling, LES-like approaches are able to resolve a larger number of unsteady flow features. In principle, this capability allows to accurately predict some of the key parameters involved in the development and optimization of modern engines such as cycle-to-cycle variations in a DI engine. However, since multiple simulated engine cycles are required to extract reliable flow statistics, the spatial and temporal resolution requirements of pure LES still represent a severe limit for its wider application on realistic engine geometries. In this context, Hybrid URANS-LES methodologies can therefore become a potentially attractive option. In fact, their task is to preserve the turbulence scale-resolving in the flow core regions but at a significantly lower computational cost compared to standard LES.

Recent catastrophic air crashes have shown that physical redundancy is not a foolproof option for failures on Air Data Systems (ADS) on an aircraft providing airspeed measurements. Since all the redundant sensors are subjected to the same environmental conditions in flight, a failure on one sensor could occur on the other sensors under certain conditions such as extreme weather; this class of failure is known in the literature as “common mode” failure. In this paper, different approaches to the problem of detection, identification and accommodation of failures on the Air Data System (ADS) of an aircraft are evaluated. This task can be divided into component tasks of equal criticality as Sensor Failure Detection and Identification (SFDI) and Sensor Failure Accommodation (SFA). Data from flight test experiments conducted using the WVU YF-22 unmanned research aircraft are used.

Tube Launched-Unmanned Air Vehicles (TL-UAV) are munitions that alter their trajectories during flight to enhance the capabilities by possibly extending range, increasing loiter time through gliding, and/or having guided targeting capabilities. Traditional munition systems, specifically the tube-launched mortar rounds, are not guided. Performance of these "dumb" munitions could be enhanced by updating to TL-UAV and still utilize existing launch platforms with standard propellant detonation firing methods. The ability to actively control the flight path and extend range of a TL-UAV requires multiple onboard systems which need to be identified, integrated, assembled, and tested to meet cooperative function requirements. The main systems, for a mortar-based TL-UAV being developed at West Virginia University (WVU), are considered to be a central hub to process information, aerodynamic control devices, flight sensors, a video camera system, power management, and a wireless transceiver.