Scanning Lagrangian Particle Tracking to measure 3D large scale aerodynamics of quadcopter flight

Kurzfassung

We present large-scale time-resolved and volumetric measurements of the flow surrounding a quadcopter drone. Cases with hovering flight, forward flight - with and without ground-effect - as well as lift-off scenarios have been realized. Five high-speed cameras were used to capture images of hundreds of thousands helium-filled soap bubbles being illuminated by pulsed LED arrays. The arrays were operated in a dual-scanning mode, where the front and the back part of the volume are illuminated intermittently, each with a frequency of 3 kHz. The cameras were recording at 6 kHz, thereby capturing both sub-time-series in a single measurement run. Compared to a full illumination of the volume, we can either reduce the number of particles imaged on the cameras given a fixed tracer concentration - facilitating the reconstruction - or operate at a higher tracer concentration while keeping the number of imaged particles fixed. The dual time-series were evaluated by Lagrangian Particle Tracking, using the Shake-The-Box method, yielding dense fields of particle tracks. For the current results, the time series for both sub-volumes were evaluated independently. For the final contribution, an integrated evaluation scheme, alternatingly operating on both time-series is foreseen. After the tracking step, flow structures were identified using the data assimilation method FlowFit. The temporally and spatially highly resolved results document the strong interaction of the wakes induced by several rotors, as well as the interaction of wing tip vortices stemming from a single rotor. Brown-out effects are documented in forward flight. Averaged results of hovering flight enable an evaluation of the azimuthal distribution of the downwash- and outwash-velocities resulting from the geometric layout of the four rotors. By having highly resolved data encompassing the whole flight vehicle, the forces conveyed by the drone to the liquid can be determined via surface- or volume-integration.