Wind-tunnel study of surface boundary conditions for large-eddy simulation of turbulent flow past a rough-to-smooth surface transition

Abstract

A wind-tunnel experiment was performed to test surface boundary condition formulations for large-eddy simulation downwind of a rough-to-smooth surface transition in a turbulent boundary layer for (Re_τ ≈ 1.5 × 10⁴). Single and x-wire anemometers were used to obtain simultaneous high-resolution measurements of surface shear stress and wind velocity at different heights and positions downwind of the transition. One-dimensional filtering, using Taylor's hypothesis, was used to obtain filtered signals of both velocity and surface shear stress. Experimental results show substantial differences between measured and modelled shear stress using standard boundary conditions based on the direct application of the similarity theory (the log law under neutral conditions) with local fluctuating filtered velocities. Those errors affect both the average value as well as higher order statistics of the predicted surface shear stress. The best performance is obtained with a model that calculates the average surface shear stress using a modified log law that accounts for the adjustment of the mean velocity and surface shear stress downwind of the transition. The surface shear stress fluctuations are modelled proportional to the velocity fluctuations, which improves the prediction of the variance and spectrum of the fluctuating shear stress with respect to standard boundary conditions. The optimum value of the proportionality coefficient in that model is found to be slightly larger than the one reported for homogeneous boundary layers, and it has only a small dependence on distance from the transition.

Keywords:

• atmospheric boundary layer
• large-eddy simulation
• roughness transition
• surface shear stress model

Acknowledgments

This research was supported by the National Science Foundation (grants EAR- 0537856 and ATM-0854766) and NASA (grant NNG06GE256). Computing resources were provided by the Minnesota Supercomputing Institute.