Flow Structure around a Multicopter Drone: A Computational Fluid Dynamics Analysis for Sensor Placement Considerations

Author:

Ghirardelli Mauro1ORCID,Kral Stephan T.2ORCID,Müller Nicolas Carlo34ORCID,Hann Richard34ORCID,Cheynet Etienne1ORCID,Reuder Joachim2ORCID

Affiliation:

1. Geophysical Institute, Bergen Offshore Wind Centre, University of Bergen, 5020 Bergen, Norway

2. Geophysical Institute, Bergen Offshore Wind Centre, Bjerknes Center for Climate Research, University of Bergen, 5020 Bergen, Norway

3. Department of Engineering Cybernetics, Norwegian University of Science and Technology, 7491 Trondheim, Norway

4. UBIQ Aerospace, 7011 Trondheim, Norway

Abstract

This study presents a computational fluid dynamics (CFD) based approach to determine the optimal positioning for an atmospheric turbulence sensor on a rotary-wing uncrewed aerial vehicle (UAV) with X8 configuration. The vertical (zBF) and horizontal (xBF) distances of the sensor to the UAV center to reduce the effect of the propeller-induced flow are investigated by CFD simulations based on the k−ϵ turbulence model and the actuator disc theory. To ensure a realistic geometric design of the simulations, the tilt angles of a test UAV in flight were measured by flying the drone along a fixed pattern at different constant ground speeds. Based on those measurement results, a corresponding geometry domain was generated for the CFD simulations. Specific emphasis was given to the mesh construction followed by a sensitivity study on the mesh resolution to find a compromise between acceptable simulation accuracy and available computational resources. The final CFD simulations (twelve in total) were performed for four inflow conditions (2.5 m s−1, 5 m s−1, 7.5 m s−1 and 10 m s−1) and three payload configurations (15 kg, 20 kg and 25 kg) of the UAV. The results depend on the inflows and show that the most efficient way to reduce the influence of the propeller-induced flow is mounting the sensor upwind, pointing along the incoming flow direction at xBF varying between 0.46 and 1.66 D, and under the mean plane of the rotors at zBF between 0.01 and 0.7 D. Finally, results are then applied to the possible real-case scenario of a Foxtech D130 carrying a CSAT3B ultrasonic anemometer, that aims to sample wind with mean flows higher than 5 m s−1. The authors propose xBF=1.7 m and zBF=20 cm below the mean rotor plane as a feasible compromise between propeller-induced flow reduction and safety. These results will be used to improve the design of a novel drone-based atmospheric turbulence measurement system, which aims to combine accurate wind and turbulence measurements by a research-grade ultrasonic anemometer with the high mobility and flexibility of UAVs as sensor carriers.

Funder

European Union Horizon 2020 research and innovation program

Research Council of Norway

Publisher

MDPI AG

Subject

Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering

Reference51 articles.

1. Stull, R.B. (1988). An Introduction to Boundary Layer Meteorology, Springer.

2. Wyngaard, J.C. (2010). Turbulence in the Atmosphere, Cambridge University Press.

3. Jensen, N., and Hjort-Hansen, E. (1978). Dynamic Excitation of Structures by Wind—Turbulence and Response Measurements at the Sotra Bridge, SINTEF.

4. Lateral coherence in isotropic turbulence and in the natural wind;Kristensen;Bound.-Layer Meteorol.,1979

5. Spectral characteristics of surface-layer turbulence;Kaimal;Q. J. R. Meteorol. Soc.,1972

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