A method for evaluating relations of turbulent normal-stresses by experimental data over a wide range of Reynolds numbers

Abstract

Recently, Nagib et al (2024} utilized indicator functions of profiles of the streamwise normal stress to reveal the ranges of validity, in wall distance and Reynolds number, for each of two proposed models in DNS of channel and pipe flows. A method more suited to experimental data is proposed here, as establishing accurate indicator functions is a challenge. The new method is outlined and used with the two leading models that propose either a logarithmic or power trend, for the normal stresses of turbulence in a fitting region of wall-bounded flows. The method, which is simple and robust, is used to evaluate each model over a wide range of Reynolds numbers by applying it to two of the prominent experimental data sets in zero-pressure-gradient boundary layers (ZPG) and pipe flows. A somewhat larger exponent for the power trend equal to 0.28, instead of 0.25, is found to slightly extend its range of validity. Correcting for outer intermittency in ZPG data also extends validity of the power trend to around half the boundary layer thickness. Projecting near-wall peak normal-stress values using both models based on data from locations in the fitting region, yields nearly identical results up to the highest Re available from these two experiments.Neither model directly represents the inner peak values and differ by as much as 30%. However, the two relations provide projected values at Re=10M with a relative difference of approximately 6.2%; distinguishing between these values would require measurement accuracy well beyond our capabilities. Current results and those of Monkewitz and Nagib (2023) on the mean flow, suggest that considerations of nonlinear growth of eddies from the wall and accounting for some viscous effects, are important for modeling wall-bounded flows. Such effects also apply to potential refinements of the logarithmic trend along ideas advanced by Deshpande et al. (2021).