Statistics of the Navier-Stokes-alpha-beta regularization model for fluid turbulence

Denis F. Hinz, Tae Yeon Kim, Eliot Fried

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

We explore one-point and two-point statistics of the Navier-Stokes- αβ regularization model at moderate Reynolds number (Re ≈ 200) in homogeneous isotropic turbulence. The results are compared to the limit cases of the Navier-Stokes-α model and the Navier-Stokes-αβ model without subgrid-scale stress, as well as with high-resolution direct numerical simulation. After reviewing spectra of different energy norms of the Navier-Stokes-αβ model, the Navier-Stokes-α model, and Navier-Stokes-αβ model without subgrid-scale stress, we present probability density functions and normalized probability density functions of the filtered and unfiltered velocity increments along with longitudinal velocity structure functions of the regularization models and direct numerical simulation results. We highlight differences in the statistical properties of the unfiltered and filtered velocity fields entering the governing equations of the Navier-Stokes-α and Navier-Stokes-αβ models and discuss the usability of both velocity fields for realistic flow predictions. The influence of the modified viscous term in the Navier-Stokes-αβ model is studied through comparison to the case where the underlying subgrid-scale stress tensor is neglected. Whereas, the filtered velocity field is found to have physically more viable probability density functions and structure functions for the approximation of direct numerical simulation results, the unfiltered velocity field is found to have flatness factors close to direct numerical simulation results.

Original languageBritish English
Article number055501
JournalJournal of Physics A: Mathematical and Theoretical
Volume47
Issue number5
DOIs
StatePublished - 7 Feb 2014

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