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What can we learn from information‐entropy about turbulence and Large‐Eddy‐Simulation?

Title: What can we learn from information‐entropy about turbulence and Large‐Eddy‐Simulation?
Authors: Engelmann, Linus; Wlokas, Irenäus; Kempf, Andreas M.
Source: PAMM ; volume 19, issue 1 ; ISSN 1617-7061 1617-7061
Publisher Information: Wiley
Publication Year: 2019
Collection: Wiley Online Library (Open Access Articles via Crossref)
Description: The Shannon entropy is a rigorous measure of information that can be used to evaluate the properties of information in turbulent flows. In this study, the behavior of the Shannon entropy is investigated for LES of an incompressible turbulent channel flow based on the classical DNS of Moser et al.. The Shannon entropy is calculated from the velocity fluctuation fields and is compared to the turbulent kinetic energy. The quality and resolution of the LES calculations on different grids has been evaluated against DNS results. The Shannon entropy is calculated for velocities and the turbulent viscosity to observe how it behaves and how it is related to the simulation quality and grid resolution.
Document Type: article in journal/newspaper
Language: English
DOI: 10.1002/pamm.201900253
Availability: https://doi.org/10.1002/pamm.201900253; https://onlinelibrary.wiley.com/doi/pdf/10.1002/pamm.201900253
Rights: http://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.BD6C0EF1
Database: BASE