The statistical operators typically applied in postprocessing numerical databases for statistically steady turbulence are a mixture of physical averages in homogeneous spatial directions and in time. Alternative averaging operators may involve phase or ensemble averages over different simulations of the same flow. In this paper, we propose straightforward metrics to assess the relative importance of these averages, employing a mixed averaging analysis of the variance. We apply our novel indicators to two statistically steady turbulent flows that are homogeneous in the spanwise direction. In addition, this study highlights the local effectiveness of the averaging operator, which can vary significantly depending on the mean flow velocity and turbulent length scales. The work can be utilized to identify the most effective averaging procedure in flow configurations featuring at least two homogeneous directions. Thus, this will contribute to achieving better statistics for turbulent flow predictions or reducing computing time.

Mixed Averaging Procedures / Errante, M.; Klein, M.; Ferrero, A.; Larocca, F.; Scovazzi, G.; Germano, M.. - In: FLOW TURBULENCE AND COMBUSTION. - ISSN 1386-6184. - ELETTRONICO. - (2024). [10.1007/s10494-023-00527-x]

Mixed Averaging Procedures

Errante M.;Ferrero A.;Larocca F.;Germano M.
2024

Abstract

The statistical operators typically applied in postprocessing numerical databases for statistically steady turbulence are a mixture of physical averages in homogeneous spatial directions and in time. Alternative averaging operators may involve phase or ensemble averages over different simulations of the same flow. In this paper, we propose straightforward metrics to assess the relative importance of these averages, employing a mixed averaging analysis of the variance. We apply our novel indicators to two statistically steady turbulent flows that are homogeneous in the spanwise direction. In addition, this study highlights the local effectiveness of the averaging operator, which can vary significantly depending on the mean flow velocity and turbulent length scales. The work can be utilized to identify the most effective averaging procedure in flow configurations featuring at least two homogeneous directions. Thus, this will contribute to achieving better statistics for turbulent flow predictions or reducing computing time.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2985775