Turbulent flow over transitionally rough surfaces with varying roughness densities

Abstract

We investigate rough-wall turbulent flows through direct numerical simulations of flow over three-dimensional transitionally rough sinusoidal surfaces. The roughness Reynolds number is fixed at $k^{+}=10$, where $k$ is the sinusoidal semi-amplitude, and the sinusoidal wavelength is varied, resulting in the roughness solidity, $\Lambda$ (frontal area divided by plan area) ranging from 0.05 to 0.54. The high cost of resolving both the flow around the dense roughness elements and the bulk flow is circumvented by the use of the minimal-span channel technique, recently demonstrated by Chung et al. (J. Fluid Mech., vol. 773, 2015, pp. 418-431) to accurately determine the Hama roughness function, $\Delta U^{+}$. Good agreement of the second-order statistics in the near-wall roughness-affected region between minimal- and full-span rough-wall channels is observed. In the sparse regime of roughness ($\Lambda \lesssim 0.15$) the roughness function increases with increasing solidity, while in the dense regime the roughness function decreases with increasing solidity. It was found that the dense regime begins when $\Lambda \gtrsim 0.15-$0.18, in agreement with the literature. A model is proposed for the limit of $\Lambda \to \infty$, which is a smooth wall located at the crest of the roughness elements. This model assists with interpreting the asymptotic behaviour of the roughness, and the rough-wall data presented in this paper show that the near-wall flow is tending towards this modelled limit. The peak streamwise turbulence intensity, which is associated with the turbulent near-wall cycle, is seen to move increasingly further away from the wall with increasing solidity. In the sparse regime, increasing $\Lambda$ reduces streamwise turbulent energy associated with the near-wall cycle, while increasing $\Lambda$ in the dense regime increases turbulent energy [continued]$\dots$

Accepted in the Journal of Fluid Mechanics

References in corpus (1)

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