100 likes | 222 Views
Thomas Hahm Steffen Wussow F2E Fluid & Energy Engineering GmbH & Co. KG Hamburg, Germany. LES-simulation of a turbulent and meandering wake. Note to the reader of this draft: The presentation was created with OpenOffice.org Impress and exported to PowerPoint-format.
E N D
F2E - fluid & energy engineering 1 Thomas Hahm Steffen Wussow F2E Fluid & Energy Engineering GmbH & Co. KG Hamburg, Germany LES-simulation of a turbulent and meandering wake
F2E - fluid & energy engineering 2 Note to the reader of this draft: The presentation was created with OpenOffice.org Impress and exported to PowerPoint-format. This does work of course not 100 percent perfectly and we have no chance to check the powerpoint-output from OpenOffice.org, if it really works correctly. Sadly the native OpenOffice-format will not be supported at EWEC. We will try to keep the presentation as simple as possible to avoid conflicts when converting to PowerPoint. We will therefore keep the movies in extra files and prepare a second backup as pdf-presentation just to be sure.
F2E - fluid & energy engineering 3 Content • Introduction • Short description of the model • Animations • Comparison to measured data • Analysis of turbulence at different time scales • Conclusions and outlook
F2E - fluid & energy engineering 4 Introduction • Motivation: inside a wind farm WTs are subject to turbulent wakes. A detailed knowledge of these wind fields is necessary to better understand the wind loads and the power performance in (closely spaced) wind farms. • CFD: can provide 3-dimensional wind fields for e.g. BEM-based models • History: • 2000: RANS, k-e-turbulence-model • 2003: DES (DIBt research project) • 2007: LES • 2009: LES (improved)
F2E - fluid & energy engineering 5 Short description of the model • Software: ANSYS FLUENT 6.3 • WT modelled: 2 WT ENERCON E66, hub height 65m, spacing: 4.25D • Turbulence Model: LES with Smagorinsky-Lilly Subgrid-scale-modell • Grid: Domain extent 1.5 RD upstream and 3D downstream of the second WT. Pure Hexader grid (7.8 million cells). Full WT geometry, rotating hub, blades can be pitched individually • Wind input: 3 component von-Karman-Model • Data: 50.000 measuring points, monitoring rate 10Hz. Located at 2.0, 2.5, 3.0 and 3.5D behind the first WT
F2E - fluid & energy engineering 6 Animationshere 3 movies of the CFD-calculations will be presented
F2E - fluid & energy engineering 7 Comparison – velocity profile
F2E - fluid & energy engineering 8 Comparison – turbulence intensity
F2E - fluid & energy engineering 9 TI at different time scales • Values of turbulence intensity will be generated for different time scales, i.e. based on averaging times ranging from several minutes to a couple of seconds. Based on this an estimate will be given of the contribution of meandering to local turbulence intensity in the wake. • Approximately 4 slides
F2E - fluid & energy engineering 10 Conclusions and Outlook • ...