  The widespread adoption of quadrotors for diverse applications, from
agriculture to public safety, necessitates an understanding of the aerodynamic
disturbances they create. This paper introduces a computationally lightweight
model for estimating the time-averaged magnitude of the induced flow below
quadrotors in hover. Unlike related approaches that rely on expensive
computational fluid dynamics (CFD) simulations or time-consuming empirical
measurements, our method leverages classical theory from turbulent flows. By
analyzing over 9 hours of flight data from drones of varying sizes within a
large motion capture system, we show that the combined flow from all propellers
of the drone is well-approximated by a turbulent jet. Through the use of a
novel normalization and scaling, we have developed and experimentally validated
a unified model that describes the mean velocity field of the induced flow for
different drone sizes. The model accurately describes the far-field airflow in
a very large volume below the drone which is difficult to simulate in CFD. Our
model, which requires only the drone's mass, propeller size, and drone size for
calculations, offers a practical tool for dynamic planning in multi-agent
scenarios, ensuring safer operations near humans and optimizing sensor
placements.
