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Full Length Article | Open Access

Improving flight performance of UAVs by ice shape modulation

Jiajun ZHANGaXuecheng LIUaHua LIANGa,b,( )Like XIEaBiao WEIa( )Haohua ZONGbYun WUa,bYinghong Lia,b
National Key Lab of Aerospace Power System and Plasma Technology, Air Force Engineering University, Xi’an 710038, China
Institute of Aero-Engine, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China

Peer review under responsibility of Editorial Committee of CJA.

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Abstract

Aircraft icing poses a great threat to flight safety. In response to the characteristics of high-power consumption, large volume, and heavy weight of traditional anti-/de-icing technologies, the concept of ice shape modulation is proposed, which is called ice tolerant flight. Firstly, the flight performance of Unmanned Aerial Vehicle (UAV) was compared in three states: no ice, full ice, and modulated ice through flight tests. It was found that ice shape modulation has a significant improvement effect on the aerodynamic performance of aircraft under icing conditions. Under the three modulated ice shape conditions in this experiment, the lift coefficient of the UAV under different ice shape modulation conditions increased by 18%–33%, and the stalling angle was delayed by 3°-5°. Subsequently, the pressure distribution, streamlines in the flow field, and detached vortex distribution of the UAV model in these three states were obtained through numerical simulation, to study the mechanism of ice shape modulation on the aerodynamic performance of aircraft. The simulation found that the reason for the improvement of the wings effect after ice shape modulation is that the modulated area forms a leading-edge protrusion structure similar to a vortex generator. This structure prolongs the mixed flow region on the wings surface and reduces the trend of flow separation, which plays a role in increasing lift and reducing drag for UAVs under icing conditions. Finally, a reverse reachable set that can be used for unexpected state recovery is used as the definition of flight safety boundaries, and an aircraft dynamics model is established to obtain flight safety boundaries for different states. Research has found that the flight safety boundary of the UAV in a no ice state is greater than that in a modulated ice state, and the safety boundary in a modulated ice state is greater than that in a full ice state. Compared with the full ice state, the flight safety boundary after modulation has expanded by 27.0%. The scheme of ice shape modulation can provide a basis for the flight safety of aircraft under icing conditions.

References

1

Levin IA. USSR electric impulse de-icing design. Aircr Eng 1972;44:7–10.

2

Dai J, Li H, Zhang Y, et al. Optimization of multi-element airfoil settings considering ice accretion effect. Chin J Aeronaut 2023;36(1):41–57.

3

Liu X, Zhu Y, Wang Z, et al. Current status and trends of biomimetic anti icing coating technology for aircraft. J Aerodyn 2022;43(10):587–604 [Chinese].

4

Li H, Zhang Y, Chen H. Optimization design of airfoils under atmospheric icing conditions for UAV. Chin J Aeronaut 2022;35(1):118–33.

5

Wu Q, Xu H, Pei B, et al. Conceptual design and preliminary experiment of icing risk management and protection system. Chin J Aeronaut 2022;35(1):101–15.

6

Zhang X, Zhao Y, Yang C. Recent developments in thermal characteristics of surface dielectric barrier discharge plasma actuators driven by sinusoidal high-voltage power. Chin J Aeronaut 2023;36(1):1–21.

7
Planquart P, Vanden Borre G, Buchlin J M. Experimental and numerical optimization of a wing leading edge hot air anti-icing system. In: AIAA atmospheric space environments conference; 2005.
8

Jing J, Cheng P, Luo Z, et al. Characteristics of ice breaking and crack propagation of arc discharge exciters. J Aerodyn 2022;43(2):207–16 [Chinese].

9

Gao T, Luo Z, Zhou Y, et al. Experimental investigation on ice-breaking performance of a novel plasma striker. Chin J Aeronaut 2022;35(1):307–17.

10
Reehorst AL, Addy J, Harold E, et al. Examination of icing induced loss of control and its mitigations. In: AIAA guidance, navigation, and control conference; 2010.
11

Safety A. Preliminary information on aircraft icing and winter operations. Aviat Saf 2010.

12
Bragg M, Hutchison T, Merret J. Effect of ice accretion on aircraft flight dynamics. In: Aerospace sciences meeting and exhibit; 2000.
13
Bragg M, Perkins W, Sarter N, et al. An interdisciplinary approach to inflight aircraft icing safety. In: AIAA aerospace sciences meeting and exhibit; 1998.
14

Xie L, Liang H, Zong H, et al. Improving aircraft aerodynamic performance with bionic wing obtained by ice shape modulation. Chin J Aeronaut 2023;36(1):76–86.

15

Su Z, Liang H, Zong H, et al. Geometrical and electrical optimization of NS-SDBD streamwise plasma heat knife for aircraft anti-icing. Chin J Aeronaut 2023;36(1):87–99.

16
Bragg M, Basar T, Perkins W, et al. Smart icing systems for aircraft icing safety. In: AIAA aerospace sciences meeting & exhibit; 2002.
17

Caliskan F, Aykan R, Hajiyev C. Aircraft icing detection, identification, and reconfigurable control based on Kalman filtering and neural networks. J Aerosp Eng 2008;21:51–60.

18
Aykan R, Hadjiyev C, Caliskan F. Aircraft icing detection, identification and reconfigurable control based on Kalman filtering and neural networks. In: AIAA atmospheric flight mechanics conference and exhibit; 2005.
19
Gingras D, Ranaudo R, Barnhart B, et al. Envelope protection for in-flight ice contamination. In: AIAA aerospace sciences meeting including the new horizons forum and aerospace exposition; 2009.
20
Gingras DR, Barnhart B, Ranaudo R, et al. Development and implementation of a model-driven envelope protection system for in-flight ice contamination. In: AIAA guidance, navigation, and control conference; 2009.
21
Ranaudo R, Martos B, Norton B, et al. Piloted simulation to evaluate a real-time envelope protection system for mitigating in-flight icing hazards. In: AIAA atmospheric and space environments conference; 2010.
22
Alam MF, Walters DK, Thompson DS. Simulations of separated flow around an airfoil with ice shape using hybrid RANS/LES models. In: AIAA applied aerodynamics conference; 2011.
23

Wu Q, Xu H, Wei Y, et al. Aerodynamic/kinematic characteristics of aircraft under icing conditions. J Aerodyn 2022;43(2):368–81 [Chinese].

24

Xie L, Liang H, Wu Y, et al. Comparison of anti icing performance between plasma excitation and electric heating. J Aerodyn 2023;44(1):137–47 [Chinese].

25

Alam MF, Thompson DS, Walters DK. Hybrid Reynolds-averaged Navier–Stokes/large-eddy simulation models for flow around an iced wing. J Aircr 2015;52(1):244–56.

26
Hossain KN, Sharma V, Bragg MB, et al. Envelope protection and control adaptation in icing encounters. In: Aerospace sciences meeting and exhibit; 2003.
27

Sharma V, Voulgaris PG, Frazzoli E. Aircraft autopilot analysis and envelope protection for operation under icing conditions. J Guid Control Dynam 2004;27:454–65.

28
Mitchell IM. Comparing forward and backward reachability as tools for safety analysis. In: International workshop on hybrid systems: computation and control; 2007.
29

Bayen AM, Mitchell IM, Osihi MK, et al. Aircraft autoloader safety analysis through optimal control-based reach set computation. J Guid Control Dynam 2007;30:68–77.

30

Mitchell I, Bayen A, Tomlin C. A time-dependent hamilton-jacobi formulation of reachable sets for continuous dynamic games. IEEE Trans Autom Control 2005;50:947–57.

31

Mitchell IM. The flexible, extensible and efficient toolbox of level set methods. J Sci Comput 2008;35:300–29.

32

Helsen R, Van Kampen EJ, De Visser CC, et al. Distance-fields-over-grids method for aircraft envelope determination. J Guid Control Dynam 2016;39:1470–80.

33

Bayen AM, Mitchell IM, Osihi MK, et al. Aircraft autolander safety analysis through optimal control-based reach set computation. J Guid Control Dynam 2007;30:68–77.

34
Allen RC. Safe set maneuverability, restoration, and protection for aircraft [dissertation]. Drexel: Drexel University; 2014.
35
Lv T. Aerodynamic characteristics of wings under icing conditions [dissertation]. Harbin: Harbin Engineering University; 2015 [Chinese].
36

Fish FE, Battle JM. Hydrodynamic design of the humpback whale flipper. J Morphol 2010;225:51–60.

37

Liu X, Liang H, Zong H, et al. NACA0012 airfoil plasma ice shape control experiment. J Aerodyn 2022;43(2):398–409 [Chinese].

38

Xu W, Li Y, Yu Z, et al. Envelope protection and control margin of icing aircraft. Control Decis-Mak 2021;36:1415–24.

39

Rodrigues F, Pascoa J, Trancossi M. Heat generation mechanisms of DBD plasma actuators. Exp Therm Fluid Sci 2018;90:55–65.

Chinese Journal of Aeronautics
Pages 49-62
Cite this article:
ZHANG J, LIU X, LIANG H, et al. Improving flight performance of UAVs by ice shape modulation. Chinese Journal of Aeronautics, 2024, 37(8): 49-62. https://doi.org/10.1016/j.cja.2024.04.005

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Received: 01 August 2023
Revised: 06 October 2023
Accepted: 29 October 2023
Published: 10 April 2024
© 2024 Chinese Society of Aeronautics and Astronautics.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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