1 / 8

Predicting Wind Turbine Blade Loads using Vorticity Transport and RANS Methodologies

Predicting Wind Turbine Blade Loads using Vorticity Transport and RANS Methodologies. Vorticity Transport and RANS Models. Vorticity Transport Model. RANS. Reynolds-Averaged Navier-Stokes equations are solved in finite volume form on a hybrid grid.

Download Presentation

Predicting Wind Turbine Blade Loads using Vorticity Transport and RANS Methodologies

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Predicting Wind Turbine Blade Loads usingVorticity Transport and RANS Methodologies

  2. Vorticity Transport and RANS Models Vorticity Transport Model RANS • Reynolds-Averaged Navier-Stokes equations are solved in finite volume form on a hybrid grid • Solves unsteady vorticity transport equation: • Inviscid flux terms are solved by flux-difference splitting; viscous terms by a central-difference method • Flow assumed fully turbulent – Spalart-Allmaras model used • Solved in finite-volume form on a structured Cartesian mesh • Simulations are steady, mostly using one blade with periodic boundary conditions • Lifting-line blade aerodynamic model, trailed and shed vorticity is accounted for using the source term, S • Numerical diffusion of vorticity is limited by using a weighted average flux method – wake structure is preserved European Wind Energy Conference 16-19th March 2009

  3. Blade Aerodynamic Loading Normal Force Coefficient, Cn • Wind Turbine Model: • NREL Phase VI rotor • Rigid • 2 blades • Radius 5.029m • S809 aerofoil • Rotor speed 72rpm (constant) • Blade pitch 3° r/R Wind: 7 m/s Tangential Force Coefficient, Ct r/R European Wind Energy Conference 16-19th March 2009

  4. Blade Aerodynamic Loading Cn Cn r/R r/R Wind: 10 m/s Wind: 25 m/s Ct Ct r/R r/R European Wind Energy Conference 16-19th March 2009

  5. Distribution of Pressure Coefficient Wind: 10 m/s Wind: 25 m/s European Wind Energy Conference 16-19th March 2009

  6. Suction Surface Streamlines European Wind Energy Conference 16-19th March 2009

  7. Wake Structure Radial Location (r/R) VTM Axial Location (z/R) RANS Vortex Age [deg] Rotor European Wind Energy Conference 16-19th March 2009

  8. Conclusion • VTM can be run using coarse aerodynamic discretisation to give efficient performance predictions • VTM simulations using a finer discretisation of the wake have revealed the subtle characteristics of the vortex filaments and the changes in wake structure that result from natural vortex instability • RANS provides accurate predictions of the aerodynamic loading on the blades, and the velocity and pressures fields that surround them. The computational cost is high, though. • In the short term: the VTM and RANS methods can be used to inform the results provided by each other • In the longer term: improvements in computational resources may allow hybrid VTM-RANS schemes to be used European Wind Energy Conference 16-19th March 2009

More Related