Predictive accuracy of wall-modelled large-eddy simulation on unstructured grids
Journal article, 2021

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.


Channel flow

Large-eddy simulation

Unstructured grids

Wall modelling

Turbulent boundary layer


Timofey Mukha

Chalmers, Mechanics and Maritime Sciences, Marine Technology

Rickard Bensow

Chalmers, Mechanics and Maritime Sciences, Marine Technology

M. Liefvendahl

Swedish Defence Research Agency (FOI)

Computers and Fluids

00457930 (ISSN)

Vol. 221 104885

Subject Categories

Applied Mechanics

Computational Mathematics

Fluid Mechanics and Acoustics



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4/1/2021 8