
Hybrid RANS/LES method for wind flow over complex terrain
Author(s) -
Bechmann A.,
Sørensen N. N.
Publication year - 2010
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.346
Subject(s) - reynolds averaged navier–stokes equations , turbulence , mechanics , turbulence kinetic energy , large eddy simulation , reynolds number , flow (mathematics) , reynolds stress , wake , reynolds stress equation model , physics , statistical physics , mathematics , geometry , k omega turbulence model
The use of Large Eddy Simulation (LES) to predict wall‐bounded flows has presently been limited to low Reynolds number flows. Since the number of computational grid points required to resolve the near‐wall turbulent structures increase rapidly with Reynolds number, LES has been unattainable for flows at high Reynolds numbers. To reduce the computational cost of traditional LES, a hybrid method is proposed in which the near‐wall eddies are modelled in a Reynolds‐averaged sense. Close to walls, the flow is treated with the Reynolds‐averaged Navier–Stokes (RANS) equations (unsteady RANS), and this layer acts as wall model for the outer flow handled by LES. The well‐known high Reynolds number two‐equation k − ϵ turbulence model is used in the RANS layer and the model automatically switches to a two‐equation k − ϵ subgrid scale stress model in the LES region. The approach can be used for flow over rough walls. Previous attempts of combining RANS and LES has resulted in unphysical transition regions between the two layers, but the present work improves this region by using a stochastic backscatter model. To demonstrate the ability of the proposed hybrid method, simulations are presented for wind flow over the Askervein hill. Comparisons show that both RANS and the new hybrid model are able to capture the simple flow windward of the hill. In the complex wake region, however, the RANS and the hybrid model give different results. The RANS model predicts the mean velocity well but underestimates the turbulent kinetic energy, whereas the new method captures the high turbulence levels well but underestimates the mean velocity. The presented results are for a relative mild configuration of complex terrain, but the proposed method can also be used for highly complex terrain where the benefits of the new method is expected to be larger. Copyright © 2009 John Wiley & Sons, Ltd.