Large Eddy Simulation of Vertical Axis Wind Turbine Wakes

By Sina Shamsoddin, Fernando Port'e-Agel. 2014

150 citations recorded by the source corpus.

In this study, large eddy simulation (LES) is combined with a turbine model to investigate the wake behind a vertical-axis wind turbine (VAWT) in a three-dimensional turbulent flow. Two methods are used to model the subgrid-scale (SGS) stresses: (a) the Smagorinsky model; and (b) the modulated gradient model. To parameterize the effects of the VAWT on the flow, two VAWT models are developed: (a) the actuator swept-surface model (ASSM), in which the time-averaged turbine-induced forces are distributed on a surface swept by the turbine blades, i.e., the actuator swept surface; and (b) the actuator line model (ALM), in which the instantaneous blade forces are only spatially distributed on lines representing the blades, i.e., the actuator lines. This is the first time that LES has been applied and validated for the simulation of VAWT wakes by using either the ASSM or the ALM techniques. In both models, blade-element theory is used to calculate the lift and drag forces on the blades. The results are compared with flow measurements in the wake of a model straight-bladed VAWT, carried out in the Institute de Mechanique et Statistique de la Turbulence (IMST) water channel. Different combinations of SGS models with VAWT models are studied, and a fairly good overall agreement between simulation results and measurement data is observed. In general, the ALM is found to better capture the unsteady-periodic nature of the wake and shows a better agreement with the experimental data compared with the ASSM. The modulated gradient model is also found to be a more reliable SGS stress modeling technique, compared with the Smagorinsky model, and it yields reasonable predictions of the mean flow and turbulence characteristics of a VAWT wake using its theoretically-determined model coefficient.

Subfields: Aerospace Engineering, Computational Mechanics, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/8f6f18fe512b7e430f1ed829b17e61dc3ece9c32

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

  1. M. Bastankhah
  2. Sina Shamsoddin
  3. Fernando Port'e-Agel
  4. P. Bachant
  5. M. Wosnik
  6. Haohua Zong
  7. Charles Meneveau
  8. A. Niayifar

In Computational Mechanics

  1. M. Bastankhah
  2. Fernando Port'e-Agel
  3. Sina Shamsoddin
  4. P. Bachant
  5. M. Wosnik
  6. Haohua Zong
  7. Charles Meneveau
  8. A. Niayifar

In Environmental Engineering

  1. M. Bastankhah
  2. Sina Shamsoddin
  3. Fernando Port'e-Agel
  4. P. Bachant
  5. M. Wosnik
  6. Haohua Zong
  7. Charles Meneveau
  8. Yu‐Ting Wu

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