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TURBULENCE MODELING FOR HORIZONTAL AXIS WIND TURBINE ROTOR BLADES

Abdulqadir, Sherwan Ahmed

[Thesis]. Manchester, UK: The University of Manchester; 2017.

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Abstract

This Thesis aims to assess the reliability of turbulence models in predicting the flow fields around the horizontal axis wind turbine (HAWT) rotor blades and also to improve our understanding of the aerodynamics of the flow field around the blades. The simulations are validated against data from the NREL/NASA Phase VI wind turbine experiments. The simulations encompass the use of fourteen turbulence models including low-and high-Reynolds-number, linear and non-linear eddy-viscosity models and Reynolds stress models. The numerical procedure is based on the finite-volume discretization of the 3D unsteady Reynolds-Averaged Navier-Stokes equations in an inertial reference frame with the sliding mesh technique to follow the motion of the rotor blades. Comparisons of power coefficient, normalised thrust, local surface pressure coefficients (CP) and the radial variation of the section average of normal force coefficients with published experimental data over a range of tip-speed ratios, lead to the identification of the turbulence models that can reliably reproduce the values of the key performance indicators. The main contributions of this study are in establishing which RANS models can produce quantitatively reliable simulations of wind turbine flows and in presenting the flow evolution over a range of operating conditions. At low (relative to the blade tip speed) wind speeds the flow over the blade surfaces remains attached and all RANS models return the correct values of key performance coefficients. At higher wind speeds there is circumferential flow separation over the downwind surface of the blade, which eventually spreads over the entire surface, Moreover, within the separation bubble the centrifugal force pumps the flow outwards, which at the higher wind speeds suppresses the formation of the classical tip vortices. More refined RANS models which do not rely on the linear effective viscosity approximation generally lead to more reliable predictions over this range of higher wind speeds. In particular the Gibson-Launder version of the Reynolds stress transport model and the high-Re versions of the Lien et al non-linear ðÂ‘˜Ã¢ÂˆÃ‚’ðÂœÃ‚€ produce consistently reliable simulations over the entire range of wind speeds. By contrast some popular linear effective viscosity models, like the SST (ðÂ‘˜Ã¢ÂˆÃ‚’ðÂœÃ‚”) and the v2âˆÂ’ðÂ‘“, perform the poorest over this complex flow range. Finally all RANS models are also able to predict the dominant (lowest) frequency of the pressure fluctuations and the non-linear effective viscosity models, the Launder and Shima version of RSM and the SST are also able to return some of the higher frequencies measured.

Keyword(s)

Computational fl uid dynamics Wind turbine aerodynamics Unsteady RANS Turbulence modelling

Bibliographic metadata

Type of resource:
Content type:
Form of thesis:
Type of submission:
Degree type:
Doctor of Philosophy
Degree programme:
PhD Mechanical Engineering
Publication date:
Location:
Manchester, UK
Total pages:
434
Abstract:
This Thesis aims to assess the reliability of turbulence models in predicting the flow fields around the horizontal axis wind turbine (HAWT) rotor blades and also to improve our understanding of the aerodynamics of the flow field around the blades. The simulations are validated against data from the NREL/NASA Phase VI wind turbine experiments. The simulations encompass the use of fourteen turbulence models including low-and high-Reynolds-number, linear and non-linear eddy-viscosity models and Reynolds stress models. The numerical procedure is based on the finite-volume discretization of the 3D unsteady Reynolds-Averaged Navier-Stokes equations in an inertial reference frame with the sliding mesh technique to follow the motion of the rotor blades. Comparisons of power coefficient, normalised thrust, local surface pressure coefficients (CP) and the radial variation of the section average of normal force coefficients with published experimental data over a range of tip-speed ratios, lead to the identification of the turbulence models that can reliably reproduce the values of the key performance indicators. The main contributions of this study are in establishing which RANS models can produce quantitatively reliable simulations of wind turbine flows and in presenting the flow evolution over a range of operating conditions. At low (relative to the blade tip speed) wind speeds the flow over the blade surfaces remains attached and all RANS models return the correct values of key performance coefficients. At higher wind speeds there is circumferential flow separation over the downwind surface of the blade, which eventually spreads over the entire surface, Moreover, within the separation bubble the centrifugal force pumps the flow outwards, which at the higher wind speeds suppresses the formation of the classical tip vortices. More refined RANS models which do not rely on the linear effective viscosity approximation generally lead to more reliable predictions over this range of higher wind speeds. In particular the Gibson-Launder version of the Reynolds stress transport model and the high-Re versions of the Lien et al non-linear ðÂ‘˜Ã¢ÂˆÃ‚’ðÂœÃ‚€ produce consistently reliable simulations over the entire range of wind speeds. By contrast some popular linear effective viscosity models, like the SST (ðÂ‘˜Ã¢ÂˆÃ‚’ðÂœÃ‚”) and the v2âˆÂ’ðÂ‘“, perform the poorest over this complex flow range. Finally all RANS models are also able to predict the dominant (lowest) frequency of the pressure fluctuations and the non-linear effective viscosity models, the Launder and Shima version of RSM and the SST are also able to return some of the higher frequencies measured.
Thesis main supervisor(s):
Thesis co-supervisor(s):
Language:
en

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:311813
Created by:
Abdulqadir, Sherwan
Created:
6th October, 2017, 09:28:05
Last modified by:
Abdulqadir, Sherwan
Last modified:
3rd January, 2019, 13:49:11

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