Morphing structures and fatigue: The case of an unmanned aerial vehicle wing leading edge

2017 ◽  
Vol 40 (10) ◽  
pp. 1601-1611 ◽  
Author(s):  
S.J. Moreira ◽  
S.M.O. Tavares ◽  
P.M.S.T. de Castro
Aerospace ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 23 ◽  
Author(s):  
David Communier ◽  
Ruxandra Mihaela Botez ◽  
Tony Wong

This paper presents the design and wind tunnel testing of a morphing camber system and an estimation of performances on an unmanned aerial vehicle. The morphing camber system is a combination of two subsystems: the morphing trailing edge and the morphing leading edge. Results of the present study show that the aerodynamics effects of the two subsystems are combined, without interfering with each other on the wing. The morphing camber system acts only on the lift coefficient at a 0° angle of attack when morphing the trailing edge, and only on the stall angle when morphing the leading edge. The behavior of the aerodynamics performances from the MTE and the MLE should allow individual control of the morphing camber trailing and leading edges. The estimation of the performances of the morphing camber on an unmanned aerial vehicle indicates that the morphing of the camber allows a drag reduction. This result is due to the smaller angle of attack needed for an unmanned aerial vehicle equipped with the morphing camber system than an unmanned aerial vehicle equipped with classical aileron. In the case study, the morphing camber system was found to allow a reduction of the drag when the lift coefficient was higher than 0.48.


2019 ◽  
Vol 8 (5) ◽  
pp. 4374-4386
Author(s):  
Ernnie Illyani Basri ◽  
Faizal Mustapha ◽  
Mohamed Thariq Hameed Sultan ◽  
Adi Azriff Basri ◽  
Mohd Firdaus Abas ◽  
...  

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3233 ◽  
Author(s):  
Zijun Ren ◽  
Wenxing Fu ◽  
Supeng Zhu ◽  
Binbin Yan ◽  
Jie Yan

Inspired by the exceptional flight ability of birds and insects, a bio-inspired neural adaptive flight control structure of a small unmanned aerial vehicle was presented. Eight pressure sensors were elaborately installed in the leading-edge area of the forward wing. A back propagation neural network was trained to predict the aerodynamic moment based on pressure measurements. The network model was trained, validated, and tested. An adaptive controller was designed based on a radial basis function neural network. The new adaptive laws guaranteed the boundedness of the adaptive parameters. The closed-loop stability was analyzed via Lyapunov theory. The simulation results demonstrated the robustness of the bio-inspired flight control system when subjected to measurement noise, parametric uncertainties, and external disturbance.


2018 ◽  
Vol 154 ◽  
pp. 01115
Author(s):  
Rahmat Riza ◽  
Dicky Kurniawan ◽  
Arif Budi Wicaksono

NACA0012H is an airfoil type that could be used for Unmanned Aerial Vehicle Medium Altitude Long Endurance. This experiment was used to analyze stress in the surface of Tail of UAV MALE that was caused by air flow. The experiment was conducted using Computational Fluid Dynamics Software. Two designs of tail, horizontal and V-tail, were considered to simulate pressure occurred on the surface of leading edge, chamber and trailing edge. The simulation was developed varying the speed of the UAV MALE. The results showed that pressure occurred on the surface of horizontal tail higher than pressure on the V-tail.


2020 ◽  
Vol 20 (4) ◽  
pp. 332-342
Author(s):  
Hyung Jun Park ◽  
Seong Hee Cho ◽  
Kyung-Hwan Jang ◽  
Jin-Woon Seol ◽  
Byung-Gi Kwon ◽  
...  

2018 ◽  
pp. 7-13
Author(s):  
Anton M. Mishchenko ◽  
Sergei S. Rachkovsky ◽  
Vladimir A. Smolin ◽  
Igor V . Yakimenko

Results of experimental studying radiation spatial structure of atmosphere background nonuniformities and of an unmanned aerial vehicle being the detection object are presented. The question on a possibility of its detection using optoelectronic systems against the background of a cloudy field in the near IR wavelength range is also considered.


Author(s):  
Amir Birjandi ◽  
◽  
Valentin Guerry ◽  
Eric Bibeau ◽  
Hamidreza Bolandhemmat ◽  
...  

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