What can we learn from information‐entropy about turbulence and Large‐Eddy‐Simulation?. Issue 1 (18th November 2019)

• Record Type: Journal Article
• Authors: Engelmann, Linus; Wlokas, Irenäus; Kempf, Andreas M.
• Other Names: Eberhardsteiner J. guestEditor.; Schöberl M. guestEditor.
• Is Part Of: Proceedings in applied mathematics and mechanics. Volume 19:Issue 1(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-11-18
• Subjects: Applied mathematics -- Periodicals; Engineering mathematics -- Periodicals; Mathematical physics -- Periodicals; 519
• DOI: 10.1002/pamm.201900253
• Languages: English
• ISSNs: 1617-7061

Abstract

Abstract: 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.