Tom, Kevin (2010) Investigation of Near Wake Flow Structure of a Horizontal Axis Wind Turbine Using Particle Image Velocimetry. Masters thesis, Concordia University.
Tom_MASc_S2011.pdf - Accepted Version
An experimental study was conducted to investigate the mean and turbulent flow characteristics in the near wake region of a model horizontal axis wind turbine (HAWT), with the rotor diameter D = 0.15 m. State-of-the-art particle image velocimetry (PIV) technique was utilized to measure two dimensional velocity fields in horizontal planes, which extended between 0.15 D upstream to 0.7 D downstream. Measurements were taken at three vertical positions (z = 0.185 m, 0.135 m, and 0.05 m) to account for wake perturbations from the blades, support tower and blades, and the tower itself. The wind speed was varied to give a tip speed ratio (λ) range of 3.5 - 4.25 and chord Reynolds number between 1900 - 2500.
A phase averaging algorithm was developed according to the rotor’s angular configuration to compute various phase-averaged flow quantities. Results are presented in ensemble-averaged and phase-averaged forms. Results of phase averaged velocity deficit determined regions of accelerated flow adjacent to individual blades, and a localized region of lower momentum due to flow separation. The correlation between blade-trailing vorticity strength, and the increase in turbulence was confirmed through profiles of turbulence intensity. The profiles of Reynolds stress showed significant enhancement immediately downstream of blades and tower indicating the enhanced production of turbulent kinetic energy (TKE). The wavenumber spectra of both streamwise and crosswind velocity components were examined. The result provided the first quantitative estimate of the scales at which energy is injected into the turbulence by the blades and tower. An inertial subrange was observed at all heights, and it was determined that the tower redistributed TKE to a wider range of scales.
|Divisions:||Concordia University > Faculty of Engineering and Computer Science > Mechanical and Industrial Engineering|
|Item Type:||Thesis (Masters)|
|Degree Name:||M.A. Sc.|
|Thesis Supervisor(s):||Siddiqui, Kamran and Ng, Hoi Dick|
|Deposited By:||KEVIN TOM|
|Deposited On:||09 Jun 2011 14:35|
|Last Modified:||04 Nov 2016 23:38|
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