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Minimum-dissipation scalar transport model for large-eddy simulation of turbulent flows

Abkar, Mahdi and Bae, Hyun J. and Moin, Parviz (2016) Minimum-dissipation scalar transport model for large-eddy simulation of turbulent flows. Physical Review Fluids, 1 (4). Art. No. 041701. ISSN 2469-990X. doi:10.1103/physrevfluids.1.041701. https://resolver.caltech.edu/CaltechAUTHORS:20210315-142512722

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Abstract

Minimum-dissipation models are a simple alternative to the Smagorinsky-type approaches to parametrize the subfilter turbulent fluxes in large-eddy simulation. A recently derived model of this type for subfilter stress tensor is the anisotropic minimum-dissipation (AMD) model [Rozema et al., Phys. Fluids 27, 085107 (2015)], which has many desirable properties. It is more cost effective than the dynamic Smagorinsky model, it appropriately switches off in laminar and transitional flows, and it is consistent with the exact subfilter stress tensor on both isotropic and anisotropic grids. In this study, an extension of this approach to modeling the subfilter scalar flux is proposed. The performance of the AMD model is tested in the simulation of a high-Reynolds-number rough-wall boundary-layer flow with a constant and uniform surface scalar flux. The simulation results obtained from the AMD model show good agreement with well-established empirical correlations and theoretical predictions of the resolved flow statistics. In particular, the AMD model is capable of accurately predicting the expected surface-layer similarity profiles and power spectra for both velocity and scalar concentration.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1103/physrevfluids.1.041701DOIArticle
ORCID:
AuthorORCID
Abkar, Mahdi0000-0002-6220-870X
Bae, Hyun J.0000-0001-6789-6209
Moin, Parviz0000-0002-0491-7065
Additional Information:© 2016 American Physical Society. Received 11 April 2016; published 29 August 2016. The authors thank Professor John O. Dabiri for his insightful comments on the manuscript. M.A. was supported by the Swiss National Science Foundation.
Group:GALCIT
Funders:
Funding AgencyGrant Number
Swiss National Science Foundation (SNSF)UNSPECIFIED
Issue or Number:4
DOI:10.1103/physrevfluids.1.041701
Record Number:CaltechAUTHORS:20210315-142512722
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210315-142512722
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:108436
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:24 Mar 2021 20:18
Last Modified:24 Mar 2021 20:18

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