  Fireball networks are used to recover meteorites, with the context of orbits.
Observations from these networks cover the bright flight, where the meteoroid
is luminescent, but to recover a fallen meteorite, these observations must
often be predicted forward in time to the ground to estimate an impact
position. This darkflight modelling is deceptively simple, but there is hidden
complexity covering the precise interactions between the meteorite and the
(usually active) atmosphere. We describe the method and approach used by the
Desert Fireball Network, detailing the issues we have addressed, and the impact
that factors such as shape, mass and density have on the predicted fall
position. We illustrate this with a case study of Murrili meteorite fall that
occurred into Lake Eyre-Kati Thanda in 2015. The fall was very well observed
from multiple viewpoints, and the trajectory was steep, with a low altitude
endpoint, such that the darkflight was relatively short. Murrili is 1.68 kg
with a typical ordinary chondrite density, but with a somewhat flattened shape
compared to a sphere, such that there are discrepancies between sphere-based
predictions and the actual recovery location. It is notable that even in this
relatively idealised darkflight scenario, modelling using spherical shaped
projectiles resulted in a significant distance between predicted fall position
and recovered meteorite.
