LES Scale Enrichment in spatially-decaying isotropic turbulence
ORAL
Abstract
High Reynolds number flows, common in engineering applications, limit the bandwidth of scales available to modern computers when solving the full nonlinear governing equations. We have shown that second-order subgrid scale statistics are accurately reconstructed using spatially- and spectrally- local Gabor modes. The method relies on a quasi-homogeneous assumption and expands the sub-grid velocity field as a local sum over Gabor modes which evolve dynamically with the large-scale field.
We have applied the method to spatially decaying isotropic turbulence. Our investigation is two-fold. First, we are interested in exploring the limit of infinite turbulence intensity at the inlet. This is difficult to achieve in the laboratory and, to our knowledge, no numerical investigation has been conducted. Initial results indicate that scaling exponents for the integral length scale and turbulence intensity are strong functions of inlet intensity due to the increased role of turbulent transport to balance energy dissipation. Second, we will evaluate the ability of the enrichment method to handle the high-turbulence intensity regime and represent the subgrid field consistently; we have seen good results for moderate intensities.
We have applied the method to spatially decaying isotropic turbulence. Our investigation is two-fold. First, we are interested in exploring the limit of infinite turbulence intensity at the inlet. This is difficult to achieve in the laboratory and, to our knowledge, no numerical investigation has been conducted. Initial results indicate that scaling exponents for the integral length scale and turbulence intensity are strong functions of inlet intensity due to the increased role of turbulent transport to balance energy dissipation. Second, we will evaluate the ability of the enrichment method to handle the high-turbulence intensity regime and represent the subgrid field consistently; we have seen good results for moderate intensities.
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Presenters
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Ryan Hass
Stanford University
Authors
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Ryan Hass
Stanford University
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Aditya S Ghate
Stanford Univ, Stanford University
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Sanjiva K Lele
Stanford Univ, Stanford University