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Published May 2013 | Published
Journal Article Open

On filtering in the viscous-convective subrange for turbulent mixing of high Schmidt number passive scalars

Abstract

In the present work, we investigate the possibility of performing velocity-resolved, scalar-filtered (VR-SF) numerical simulations of turbulent mixing of high Schmidt number scalars, by using a Large Eddy Simulation (LES)-type filter in the viscous-convective subrange. The only requirement for this technique is the large scale separation between the Kolmogorov and Batchelor length scales, which is a direct outcome of the high Schmidt number of the scalar. The present a priori analysis using high fidelity direct numerical simulation data leads to two main observations. First, the missing triadic interactions between (resolved) velocity and (filtered-out) scalar modes in the viscous-convective subrange do not affect directly the large scales. Second, the magnitude of the subgrid term is shown to be extremely small, which makes it particularly susceptible to numerical errors associated with the scalar transport scheme. A posteriori tests indicate that upwinded schemes, generally used for LES in complicated geometries, are sufficiently dissipative to overwhelm any contribution from the subgrid term. This renders the subgrid term superfluous, and as a result, VR-SF simulations run without subgrid scalar flux models are able to preserve large scale transport characteristics with remarkable accuracy.

Additional Information

© 2013 AIP Publishing LLC. Received 26 June 2012; accepted 11 April 2013; published online 24 May 2013. The authors are indebted to Dr. P.K. Yeung (Georgia Institute of Technology) for sharing his DNS data and providing valuable comments on the draft of the paper. The authors are grateful to the two anonymous reviewers for valuable comments that helped significantly improve the original manuscript. In addition, we wish to thank Kartik Iyer (Georgia Institute of Technology) for help with the retrieval and processing of data used for a priori analysis, and Dr. Dan Meiron (California Institute of Technology) for helpful discussions that were crucial to understanding the effect of various filtering kernels on the a priori analysis. The authors also gratefully acknowledge funding from the U.S. Department of Energy-Basic Energy Sciences (DE-SC0006591).

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