Variable deflection response of sensitive CNT-on-fiber artificial hair sensors from CNT synthesis in high aspect ratio microcavities

Slinker, Keith; Maschmann, Matthew R.; Kondash, Corey; Severin, Benjamin; Phillips, David M.; Dickinson, Benjamin T.; Reich, Gregory W.; Baur, Jeff

doi:10.1117/12.2085568

Cited by 6 publications

(8 citation statements)

References 23 publications

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“…The AEROLAB Educational Wind Tunnel was used for the wind tunnel experiment. It is an open circuit wind tunnel having a  ´ ´ 12 12 24 test section and operating wind speed range of 10 mph-145 mph. This wind tunnel setup allowed measurements of force, moment, angle of attack, and free-stream velocity to be recorded at discrete points.…”

Section: Data Acquisition and Wind Tunnel Testmentioning

confidence: 99%

“…During this study we kept pitch angle constant and increased the wind velocity gradually from 5 to 45 mph; therefore, the sensor measurement was quasistatic. However, the sensors exhibit a wide bandwidth [12] and is able to preserve the temporal information. For this initial phase of test, temporal information does not have huge contribution because our main concern is to predict the steady aerodynamic parameters.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

“…The Air Force Research Laboratory (AFRL) has developed an artificial hair sensor (AHS) mimicking those used by natural fliers to detect surface flow features [10][11][12][13]. The AHS consists of a S-2 glass fiber with radially grown carbon nanotube (CNT) forests on it (figure 1).…”

Section: Introductionmentioning

confidence: 99%

“…Compared to typical MEMs sensors, these sensors are more sensitive [10] and can be fabricated with much longer hairs to extend farther out of the boundary layer. Not only is longer-hair fabrication possible, it can be done without sacrificing bandwidth [12,13]. Their sensitivity to detect small flow changes (∼0.1m/s) and high bandwidth (>1kHz) are also ideal characteristics for an effective fly-by-feel implementation.…”

Section: Introductionmentioning

confidence: 99%

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Aerodynamic parameters from distributed heterogeneous CNT hair sensors with a feedforward neural network

Magar¹,

Reich²,

Kondash³

et al. 2016

Bioinspir. Biomim.

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Distributed arrays of artificial hair sensors have bio-like sensing capabilities to obtain spatial and temporal surface flow information which is an important aspect of an effective fly-by-feel system. The spatiotemporal surface flow measurement enables further exploration of additional flow features such as flow stagnation, separation, and reattachment points. Due to their inherent robustness and fault tolerant capability, distributed arrays of hair sensors are well equipped to assess the aerodynamic and flow states in adverse conditions. In this paper, a local flow measurement from an array of artificial hair sensors in a wind tunnel experiment is used with a feedforward artificial neural network to predict aerodynamic parameters such as lift coefficient, moment coefficient, free-stream velocity, and angle of attack on an airfoil. We find the prediction error within 6% and 10% for lift and moment coefficients. The error for free-stream velocity and angle of attack were within 0.12 mph and 0.37 degrees. Knowledge of these parameters are key to finding the real time forces and moments which paves the way for effective control design to increase flight agility, stability, and maneuverability.

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Section: Data Acquisition and Wind Tunnel Testmentioning

confidence: 99%

Section: Conclusion and Future Researchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Aerodynamic parameters from distributed heterogeneous CNT hair sensors with a feedforward neural network

Magar¹,

Reich²,

Kondash³

et al. 2016

Bioinspir. Biomim.

View full text Add to dashboard Cite

show abstract

“…The cantilever beam, the most widely used mechanical sensing structure of external sensors, greatly improves the sensing performance for detecting out‐of‐plane forces. [ 6,18,19 ] However, in contrast to the abundant research on the cantilever‐based sensing structure of external sensors, appropriate strategies for the development of sensing structures used by internal mechanosensors are scarce, which has become an obstacle for improving the performance of internal sensors to further optimize proprioceptive capability. In this regard, finding a sophisticated and widely used sensing structure to overcome the performance limit of conventional internal mechanosensors is highly desirable.…”

Section: Introductionmentioning

confidence: 99%

Mechano‐Sensor for Proprioception Inspired by Ultrasensitive Slit‐Based Mechanosensilla

Wang

Zhang

Gui

et al. 2022

Adv Materials Technologies

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Internal mechanosensors, as the core component of a proprioceptive system, provide vital mechanical information from intelligent devices for adaptive motor control, mechanical fault diagnosis, and machining condition monitoring. However, developing a sophisticated mechanosensory structure that can be widely used is highly desirable to significantly improve the detection performance of internal mechanosensors. Coincidentally, in nature, optimized microscale slits of arachnids (e.g., scorpions and spiders) are ingeniously used as a mechanosensory structure for internal mechanosensilla to efficiently detect the inevitable internal mechanical feedbacks caused by self‐motion and external mechanical stimuli. Biological slit‐based mechano‐sensilla provide an attractive bio‐inspired strategy to use the controllable slit as the sensory structure to improve the perceptual performance of internal mechanosensors. In this study, the structure‐deformation‐performance coupling relationship of slit‐based mechano‐sensilla is explored through experiment and theoretical analysis. An artificial slit‐based mechanosensor is developed by mimicking the combined deformation properties of the slit and the ultrathin cuticular membrane covering the slit tail. This bio‐inspired mechanosensor shows excellent performance in terms of mechanical stability, response time, and sensitivity to mechanical signals. The research on a practical application highlights the importance of the unique basic “design” principles of the slit‐based mechano‐sensilla in improving the proprioceptive capability of smart engineering devices.

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3D‐Structured Stretchable Strain Sensors for Out‐of‐Plane Force Detection

Liu

Leow

et al. 2018

Advanced Materials

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Stretchable strain sensors, as the soft mechanical interface, provide the key mechanical information of the systems for healthcare monitoring, rehabilitation assistance, soft exoskeletal devices, and soft robotics. Stretchable strain sensors based on 2D flat film have been widely developed to monitor the in-plane force applied within the plane where the sensor is placed. However, to comprehensively obtain the mechanical feedback, the capability to detect the out-of-plane force, caused by the interaction outside of the plane where the senor is located, is needed. Herein, a 3D-structured stretchable strain sensor is reported to monitor the out-of-plane force by employing 3D printing in conjunction with out-of-plane capillary force-assisted self-pinning of carbon nanotubes. The 3D-structured sensor possesses large stretchability, multistrain detection, and strain-direction recognition by one single sensor. It is demonstrated that out-of-plane forces induced by the air/fluid flow are reliably monitored and intricate flow details are clearly recorded. The development opens up for the exploration of next-generation 3D stretchable sensors for electronic skin and soft robotics.

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Variable deflection response of sensitive CNT-on-fiber artificial hair sensors from CNT synthesis in high aspect ratio microcavities

Cited by 6 publications

References 23 publications

Aerodynamic parameters from distributed heterogeneous CNT hair sensors with a feedforward neural network

Aerodynamic parameters from distributed heterogeneous CNT hair sensors with a feedforward neural network

Mechano‐Sensor for Proprioception Inspired by Ultrasensitive Slit‐Based Mechanosensilla

3D‐Structured Stretchable Strain Sensors for Out‐of‐Plane Force Detection

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