Optimal Control Framework for Gust Load Alleviation using Real time Aerodynamic Force Prediction from Artificial Hair Sensor Array

Author(s):  
Kaman S. Thapa Magar ◽  
Alexander M. Pankonien ◽  
Gregory W. Reich ◽  
Richard Beblo
2021 ◽  
Vol 92 (3) ◽  
pp. 035113
Author(s):  
Huan Liu ◽  
Changfeng Zhao ◽  
Xiaobin Wang ◽  
Zehua Wang ◽  
Jian Ge ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1922
Author(s):  
Gwang Su Kim ◽  
Yumin Park ◽  
Joonchul Shin ◽  
Young Geun Song ◽  
Chong-Yun Kang

The breath gas analysis through gas phase chemical analysis draws attention in terms of non-invasive and real time monitoring. The array-type sensors are one of the diagnostic methods with high sensitivity and selectivity towards the target gases. Herein, we presented a 2 × 4 sensor array with a micro-heater and ceramic chip. The device is designed in a small size for portability, including the internal eight-channel sensor array. In2O3 NRs and WO3 NRs manufactured through the E-beam evaporator’s glancing angle method were used as sensing materials. Pt, Pd, and Au metal catalysts were decorated for each channel to enhance functionality. The sensor array was measured for the exhaled gas biomarkers CH3COCH3, NO2, and H2S to confirm the respiratory diagnostic performance. Through this operation, the theoretical detection limit was calculated as 1.48 ppb for CH3COCH3, 1.9 ppt for NO2, and 2.47 ppb for H2S. This excellent detection performance indicates that our sensor array detected the CH3COCH3, NO2, and H2S as biomarkers, applying to the breath gas analysis. Our results showed the high potential of the gas sensor array as a non-invasive diagnostic tool that enables real-time monitoring.


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