  In this short note we apply the recently proposed data-driven RANS closure
modelling framework of Schmelzer et al. (2020) to fully three-dimensional, high
Reynolds number flows: namely wall-mounted cubes and cuboids at Re=40,000, and
a cylinder at Re=140,000. For each flow, a new RANS closure is generated using
sparse symbolic regression based on LES or DES reference data. This new model
is implemented in a CFD solver, and subsequently applied to prediction of the
other flows. We see consistent improvements compared to the baseline $k-\omega$
SST model in predictions of mean-velocity in the complete flow domain.
