Artificial hair sensors have been developed in the Air Force Research Laboratory for use in prediction of local flow
around airfoils and subsequent use in gust rejection applications. The on-going sensor development is based on a micro-sized
unmanned vehicle, resulting in a sensor design that is sensitive in that aircraft’s nominal flight condition (speed).
However, the active, or operating, region of the artificial hair sensor concept is highly dependent on the geometry and
properties of the hair, capillary, and carbon nanotubes that make up the sensor design. This paper aims at expanding the
flow measurement concept using artificial hair sensors to UAVs with different dimensions by properly sizing the
parameters of the sensors, according to the nominal flight conditions of the UAVs. In this work, the hair, made of glass
fiber, will be modeled as a cantilever beam with an elastic foundation, subject to external distributed aerodynamic drag.
Hair length, diameter, capillary depth, and carbon nanotube length will be scaled by keeping the maximum strain of the
carbon nanotubes constant for different sensors under different working conditions. Numerical studies will demonstrate
the feasibility of the scaling methodology by designing artificial hair sensors for UAVs with different dimensions and
flight conditions, starting from a baseline sensor design.