Escaping the lab: advances in large-scale particle tracking using natural light and uncrewed aerial vehicles

Abstract Here we explore the potential of the glare-point particle tracking (GPPT) technique for realistic field-scale measurements. We make use of a commercially available, drone-based camera to extract three-dimensional information under natural light conditions. Air-filled soap bubbles on the order of centimeters are used as seeding tracers. In the current tests, the suitability of the portable setup has been demonstrated for volumes up to $$163\,$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>163</mml:mn> <mml:mspace/> </mml:mrow> </mml:math> m $$^3$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mmultiscripts> <mml:mrow/> <mml:mrow/> <mml:mn>3</mml:mn> </mml:mmultiscripts> </mml:math> . The frame-to-frame camera movement, caused by slight adjustments of the drone flying outdoors, could be quantified and corrected via an image-based approach. Both limits introduced through the larger tracer size and uncertainty caused by the glare-point approach are discussed accordingly. Furthermore, based on the fixed magnification of the drone camera, the limit in drone operation can be determined when the two most dominant, bubble-based glare points collapse onto one, which was observed well above a height of $$10\,$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>10</mml:mn> <mml:mspace/> </mml:mrow> </mml:math> m. Finally, a turbulent free jet, exiting from a square-shaped nozzle with edge length $$0.3\,$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>0.3</mml:mn> <mml:mspace/> </mml:mrow> </mml:math> m, served as an exemplary test case. Tracks emerging at the jet exit all the way to $$10\,$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>10</mml:mn> <mml:mspace/> </mml:mrow> </mml:math> m downstream of the nozzle were successfully reconstructed in three dimensions. Lagrangian properties, such as flow acceleration, as well as pathline curvature at the integral length scale, were resolved in the large turbulent jet. This sparse yet accurate Lagrangian data over a large physical volume demonstrates insights into turbulent mixing processes at the integral length well beyond current Eulerian-based descriptions.