Statistics of the Navier-Stokes-alpha-beta regularization model for fluid turbulence
Denis F. Hinz, Tae-Yeon Kim, Eliot Fried

TL;DR
This paper analyzes the statistical properties of the Navier-Stokes-alpha-beta regularization model in turbulent flows, comparing it with other models and direct numerical simulations to assess its accuracy and usability.
Contribution
It provides a detailed statistical comparison of the Navier-Stokes-alpha-beta model with related models and DNS, highlighting differences in velocity field properties and the impact of the modified viscous term.
Findings
Filtered velocity fields yield more realistic probability density functions.
Unfiltered velocity fields have flatness factors close to DNS results.
The modified viscous term influences the statistical properties of the model.
Abstract
We explore one-point and two-point statistics of the Navier-Stokes-alpha-beta regularization model at moderate Reynolds number in homogeneous isotropic turbulence. The results are compared to the limit cases of the Navier-Stokes-alpha model and the Navier-Stokes-alpha-beta 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-alpha-beta model, the Navier-Stokes-alpha model, and Navier-Stokes-alpha-beta model without subrid-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…
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