Three-dimensional large-eddy simulations (LES) of single and multiple jets in cross-flow (JICF) were conducted using the 19-bit Lattice Boltzmann Equation (LBE) method coupled with a conventional Navier-Stokes (NS) finite-volume scheme. In this coupled LBE-NS approach, the LBE-LES was employed to simulate the flow inside jet nozzles, while the NS-LES was used to simulate the cross-flow. The key application area was to study the micro-blowing technique (MBT) for drag control similar to recent experiments at NASA/GRC.
A single jet in the cross-flow case was used for validation purposes, and results were compared with experimental data and full LBE-LES simulation. Good agreement with data was obtained. Transient analysis of flow structures was performed to investigate the contribution of flow structures to the counter-rotating vortex pair (CRVP) formation. It was found that both spanwise roller (at the lee side of the jet) and streamwise vortices (at the jet-side) contribute to the generation of the CRVP. Span-wise roller at the corner of the jet experiences high spanwise vortex compression as well as high streamwise vortex stretch. As a result, they get realigned, mix with the jet-side streamwise vortices, and eventually generate the CRVP.
Furthermore, acoustic pulses were used to test the proper information exchange from the LBE domain to the NS domain, and vice-versa. Subsequently, MBT over a flat plate with porosity of 25 percent was simulated using nine jets in a compressible cross-flow at a Mach number of 0.4. Three cases with injection ratios of 0.003, 0.02 and 0.07 were conducted to investigate how the blowing rate impacts skin friction. It is shown that MBT suppressed the near-wall vortices and reduced the skin friction by up to 50 percent. This is in good agreement with experimental data.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/14040 |
Date | 14 November 2006 |
Creators | Feiz, Homayoon |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Language | en_US |
Detected Language | English |
Type | Dissertation |
Format | 45204550 bytes, application/pdf |
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