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

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.

Rotary-wing drone-induced flow – comparison of simulations with lidar measurements

“…A total of seven CFD simulations were performed using Ansys Fluent 2022 R1. The simulation design relies on the study by Ghirardelli et al (2023), where it is extensively described. The inflow wind speeds for this comparison were carefully adjusted to match the field experiment.…”

“…Since the beginning of the 21st century, uncrewed aerial vehicles (UAVs) with rotary wings have become more popular for conducting atmospheric measurements (Hemingway et al, 2017;Leuenberger et al, 2020;Tikhomirov et al, 2021) due to their flexibility in orienting, precise hovering capabilities, and ease of deployment. Wind velocity and direction can be reconstructed either from the avionic information of UAVs alone (Neumann and Bartholmai, 2015;Palomaki et al, 2017;Segales et al, 2020;Wetz et al, 2021;González-Rocha et al, 2023) or from the wind sensors mounted on the UAVs. Even though the former indirect approach is well-established and has the advantage of not requiring external measurement devices, it has limitations in resolving three-dimensional wind fields and fine-scale turbulent fluctuations.…”

“…Furthermore, increasing the battery capacity extends the flight time and shifts the battery position closer to the fuselage center. CFD simulations of this design were presented in Ghirardelli et al (2023), which were computed efficiently by simplifying the drone's geometry and by setting up ideal flow conditions. However, this simulation model must be experimentally validated before its results can be used as a reference for sensor placement.…”

“…Being aware of the capability of lidar measurements, we conducted a field measurement campaign using three synchronized CW Doppler lidars to reconstruct the threedimensional flow field around and below a drone. The goal was to validate CFD simulations based on the setup presented by Ghirardelli et al (2023). Such a CFD setup can be further used to determine the optimal placement location for a sonic anemometer on a large multi-copter drone (diameter of 1.88 m).…”

Aeroelasticity Model for Highly Flexible Aircraft Based on the Vortex Lattice Method

“…Some authors use aeroelasticity models based on computational fluid dynamics (CFD) [4,7]. Because of its accuracy and versatility, CFD is a commonly used tool in both aerospace and other disciplines [10][11][12][13][14]. However, because CFD is very computationally expensive, for aeroelastic analysis most authors use either an analytical aerodynamic model [8] or a vortex lattice method (VLM) or doublet lattice method (DLM)-based model [5].…”