  The predictive accuracy of wall-modelled LES is influenced by a combination
of the subgrid model, the wall model, the numerical dissipation induced
primarily by the convective numerical scheme, and also by the density and
topology of the computational grid. The latter factor is of particular
importance for industrial flow problems, where unstructured grids are typically
employed due to the necessity to handle complex geometries. Here, a systematic
simulation-based study is presented, investigating the effect of grid-cell type
on the predictive accuracy of wall-modelled LES in the framework of a
general-purpose finite-volume solver. Following standard practice for meshing
near-wall regions, it is proposed to use prismatic cells. Three candidate
shapes for the base of the prisms are considered: a triangle, a quadrilateral,
and an arbitrary polygon. The cell-centre distance is proposed as a metric to
determine the spatial resolution of grids with different cell types. The
simulation campaign covers two test cases with attached boundary layers:
fully-developed turbulent channel flow, and a zero-pressure-gradient flat-plate
turbulent boundary layer. A grid construction strategy is employed, which
adapts the grid metric to the outer length scale of the boundary layer. The
results are compared with DNS data concerning mean wall shear stress and
profiles of flow statistics. The principle outcome is that unstructured
simulations may provide the same accuracy as simulations on structured
orthogonal hexahedral grids. The choice of base shape of the near-wall cells
has a significant impact on the computational cost, but in terms of accuracy
appears to be a factor of secondary importance.
