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Some small UAVs have been designed to resemble birds so that they can blend in with nature when seen from a distance. Wings with various tip configurations were compared to a control wing to observe the variations in aerodynamic performance. Computer simulations were performed to determine expected results and then wings were designed and constructed for wind-tunnel tests to obtain experimental performance data. The wing was built in a standard rectangular configuration and featured an interchangeable plate on the tip to test the effect of the wing slots (feathers that project from the tips) and to see if changing the shape and length of the slots increases the effective aspect ratio (and therefore efficiency). Particle image velocimetry tests in a wind tunnel were performed to observe the vortex created by the wing and how the flow around the wingtips was affected by the changes in the wing slots. Circulation was then calculated and used to find coefficient of lift using the Kutta-Joukowski Theorem. The results were then compared to determine the most effective combination of performance and realistic look to create a bird-mimicking MAV. Nomenclature MAV= Micro Air Vehicle PIV = Particle Image Velocimetry AoA = Angle of Attack α = Alpha (Angle of Attack) V = Velocity V ∞ = Freestream Velocity Re = Reynolds Number Γ = Circulation µ = Dynamic Viscosity ρ = Density ρ ∞ = Freestream Density c = Wing Chord Length b = Wing Span s = Area

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When operating under Visual Flight Rules, pilots primarily rely on visual scanning to avoid other aircraft and airborne collision threats. Records from the Federal Aviation Administration indicate that near encounters with unmanned aircraft are on the rise, reaching 1,761 reported unmanned aircraft system (UAS) sightings or near-misses in 2016. This study sought to assess the effectiveness of pilot visual detection of UAS platforms that were equipped with strobe lighting. A sample of 10 pilots flew a general aviation aircraft on a scripted series of five intercepts with a small UAS (sUAS) that was equipped with strobe lighting. Participants were asked to indicate when they visually detected the unmanned aircraft. Geolocation information for both the aircraft and sUAS platform was compared to assess visibility distance. Findings were used to evaluate the efficacy of daytime strobe lighting as a method to enhance pilot sUAS detection, visibility, and collision avoidance. Participants detected the unmanned aircraft during 7.7% of the intercepts. Due to a lack of data points, the authors were unable to conclusively determine if strobe lighting improved UAS visual detection. The authors recommend further research to explore the effectiveness of using sUAS-mounted strobe lights for nighttime visual detection.

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