Reconstruction of wall shear-stress fluctuations in a shallow tidal river

R. Mathis, I. Marusic, O. Cabrit, Nicole L. Jones, Gregory N. Ivey

Research output: Chapter in Book/Conference paperConference paperpeer-review


© Springer International Publishing Switzerland 2016.In this paper, we investigate the applicability of the predictive wall shearstress model, recently developed by Mathis et al. J. Fluid Mech. 715, 163-180, 2013, [17], to environmental flows where near-wall information is typically inaccessible. This wall-model, which embeds the scale interaction mechanisms of superposition and modulation, is able to reconstruct the instantaneous wall (bed) shear-stress fluctuations in turbulent boundary layers. The database considered here comes from field measurements using acoustic Doppler velocimeters carried out in a shallow tidal channel (Suisun Slough in North San Francisco Bay). The model is first applied to a selected subset of data sharing common properties with the canonical turbulent boundary layer. Statistics and energy content of these predictions are found to be consistent with laboratory predictions and DNS results. The model is then used on the whole dataset, whose some of them having properties far from the canonical case. Even for these situations, the model is able to preserve the overall Reynolds trend. This study shows the great capability of the model for environmental applications, which is the only one able to predict both the correct energetic content and probability density function.
Original languageEnglish
Title of host publicationProgress in Wall Turbulence 2
Subtitle of host publicationUnderstanding and Modelling
EditorsJavier Jimenez, Ivan Marusic, Michel Stanislas
Number of pages11
ISBN (Print)9783319203874
Publication statusPublished - 2016
Event2nd WALLTURB Workshop on Understanding and modelling of wall turbulence, 2014 - Lille, France
Duration: 18 Jun 201420 Jun 2014

Publication series

ISSN (Print)1382-4309
ISSN (Electronic)2215-1826


Conference2nd WALLTURB Workshop on Understanding and modelling of wall turbulence, 2014


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