Recent interest in fly-by-feel approaches for aircraft control has motivated the development of novel sensors for use in aerial systems. Artificial hair sensors are one type of device that promise to fill a unique niche in the sensory suite for aerial systems. In this work, we investigate the capability of an artificial hair sensor based on structural glass fibers to directly identify flow stagnation and separation points on a cylindrical domain in a steady flow. The glass fibers are functionalized with a radially aligned carbon nanotube forest and elicit a piezoresistive response as the carbon nanotube forest impinges on electrodes in a micropore when the hair is deflected due to viscous drag forces. Particle image velocimetry is used to measure the flow field allowing for the resulting moment and force acting on the hair to be correlated with the electrical response. It is demonstrated that the artificial hair sensor provides estimates for the locations of both the stagnation and separation in steady flow. From this, a simulation of a heading estimation is presented to demonstrate a potential application for hair sensors. These results motivate the construction of large arrays of hair sensors for imaging and resolving flow structures in real time. Keywords:hair sensor, carbon nanotube array, piezoresistive transduction, stagnation point, separation point, heading estimation list) for both air and underwater applications. In particular, the work of Dagamseh et al (2012) is interesting for using AHSs for aerodynamic state estimation. In this work, we offer a preliminary investigation of using AHSs based on structural glass fibers coated with a radially aligned forest of carbon nanotubes (CNTs) to identify the location of stagnation and separation on a quasi-2D domain through piezoresistive transduction. Specifically, we generate a steady flow past a cylinder and measure both the sensor electrical response with a source meter and the flow field stimulating the hair using particle image velocimetry (PIV). The results are correlated to investigate the potential of using AHSs for flow feature identification.Engineered flight systems currently utilize sensors for situational awareness and state/parameter estimation, but the number of sensors is limited and the sensors are comparatively expensive. Emphasis is currently placed on point-wise sensor accuracy rather than redundancy. Hot film/wire anemometers are examples of accurate, point-wise technologies that are already used extensively in industry for aerodynamic control and estimation. In contrast to engineered systems, biology generally employs redundancy in both control and estimation systems (Bekey 2005). For many of the same reasons biology depends upon redundancy, there are several reasons to consider redundant, distributed sensory systems for flight control. First and foremost, redundancy provides robustness to sensor failure, which is a systemic problem in systems with very few, high-grade sensors. Redundancy also provides more information regarding ...

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Performance demands of future unmanned air vehicles will require rapid autonomous responses to changes in environment. Towards this goal, we expect that the next generation flight control systems will include advanced sensors beyond the contemporary array. One promising scenario correlates measurements of flow footprints over aircraft surfaces with aerodynamic data to aid navigation and feedback control algorithms. As a sensor for this concept, we construct artificial hair sensors (AHSs) based on glass microfibers enveloped in an annular, radially-aligned piezoresistive carbon nanotube (CNT) forest to measure air flow in boundary layers. This study includes an analysis of the sensitivity based on laboratory scale electromechanical testing. The sensors in this work utilize nine micron diameter S2 glass fibers as the sensing mechanism for coupling to boundary layer air flows. The annular CNT forest resides in a fused silica microcapillary with electrodes at the entrance. The sensor electrical transduction mechanism relies on the resistance change of the CNT forest due to changes in both the bulk and contact resistance as a function of mechanical loading on the fiber. For the electromechanical analysis, the sensors are controllably loaded to measure both the force and moment acting at the base of the hair and the resulting deflection of the CNT forest inside of the microcapillary is measured to estimate the stress on the forest and the pressure between the forest and the electrode. The electrical responses of the sensors are compared to the mechanical state of the CNT forest. This work represents the development of a characterization tool to better understand and control the response of CNT based AHSs.

Measurements and calculations of the phase speed of disturbances observed in a small shock tube are made, via cross-correlation of successive frames from focusing schlieren videography and double focused laser differential interferometry. The efficacy of the latter technique for measuring slender-body hypersonic boundary-layer instability wave-packets is also demonstrated. Shock tube experiments are performed to provide a known velocity input to both sensors for comparison, and measurements of phase velocity are made behind the reflected shock. Power spectral density curves from the FLDI and focusing schlieren from shock tube experiments at similar conditions are compared with each other and with pitot tube results, and reasonable agreement is found to the frequency limits of the sensors.

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