DNS Channel Data Re_tau=10000 high moments
Loading...
Date
2021-11-04
Type
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Description
This dataset contains the statistical moments based on the instantaneous velocities (H-moments) up to order 6 of a new Direct Numerical Simulation of a Poiseuille channel flow that has been conducted for a friction Reynolds number of 10000, using the pseudo-spectral code LISO.
Authors:
M. Oberlack, S. Kraheberger, J. Laux, TU Darmstadt.
S. Hoyas, F. Alcantara-Avila, Universitat Politècnica de València
References:
1. Turbulence Statistics of Arbitrary Moments of Wall-Bounded Shear Flows: A Symmetry Approach, M. Oberlack, S. Hoyas, S. Kraheberger, F. Alcantara-Avila and J. Laux, Phys. Rev. Lett. 128, 024502 – Published 10 January 2022.
2. Wall turbulence at high friction Reynolds numbers, S. Hoyas, M. Oberlack, S. Kraheberger, F. Alcantara-Avila and J. Laux, Phys. Rev. Fluids 7, 014602 – Published 10 January 2022.
Please check the final references before citing these papers
Data:
The data can be directly loaded in Matlab.
NOMENCLATURE:
x = streamwise coordinate
y = wall-normal coordinate
z = spanwise coordinate
h = channel half-width
U^n = nth-order moment of mean streamwise velocity
utau = friction velocity
(.)b = normalized by ubulk
nx = 6144 ny = 2101 nz = 6144
BOX SIZE in h (x,y,z): 2pi|2|1pi
FLOW CONDITIONS: Retau = 10049 (Re = 290000. Rebulk = 257143 ), utau = 0.034629, ubulk = 0.886746.
Files:
H_U1_Moments.txt: U_1 velocity moments of the instantaneous velocities (H-moments) up to order 6 of the Channel Flow DNS at Re_tau=10^4 as functions of the wall distance y (x_2).
Contact:
Email Sergio Hoyas, serhocal@mot.upv.es about any issue with the data.
The authors gratefully acknowledge computing time on the Gauss Centre for Supercomputing e.V. on the GCS Supercomputer SuperMUC-NG at Leibniz Supercomputing Centre under Project No. pr92la, on the supercomputer Lichtenberg II at TU Darmstadt under Project No. project00072, and on the supercomputer CLAIX-2018 at RWTH-Aachen under Project No. bund0008. S. V. K. gratefully acknowledges funding from projects OB96/39-1 and M.O. for partial funding from OB 96/48-1, both financed by the German Research Foundation (DFG). S. H. and F. A.-A. were supported by Contract No. RTI2018-102256-B-I00 of MINECO/FEDER. F. A.-A. is partially funded by GVA/FEDER project ACIF2018. Finally, the authors thank Paul Hollmann for help with the manuscript.
Authors:
M. Oberlack, S. Kraheberger, J. Laux, TU Darmstadt.
S. Hoyas, F. Alcantara-Avila, Universitat Politècnica de València
References:
1. Turbulence Statistics of Arbitrary Moments of Wall-Bounded Shear Flows: A Symmetry Approach, M. Oberlack, S. Hoyas, S. Kraheberger, F. Alcantara-Avila and J. Laux, Phys. Rev. Lett. 128, 024502 – Published 10 January 2022.
2. Wall turbulence at high friction Reynolds numbers, S. Hoyas, M. Oberlack, S. Kraheberger, F. Alcantara-Avila and J. Laux, Phys. Rev. Fluids 7, 014602 – Published 10 January 2022.
Please check the final references before citing these papers
Data:
The data can be directly loaded in Matlab.
NOMENCLATURE:
x = streamwise coordinate
y = wall-normal coordinate
z = spanwise coordinate
h = channel half-width
U^n = nth-order moment of mean streamwise velocity
utau = friction velocity
(.)b = normalized by ubulk
nx = 6144 ny = 2101 nz = 6144
BOX SIZE in h (x,y,z): 2pi|2|1pi
FLOW CONDITIONS: Retau = 10049 (Re = 290000. Rebulk = 257143 ), utau = 0.034629, ubulk = 0.886746.
Files:
H_U1_Moments.txt: U_1 velocity moments of the instantaneous velocities (H-moments) up to order 6 of the Channel Flow DNS at Re_tau=10^4 as functions of the wall distance y (x_2).
Contact:
Email Sergio Hoyas, serhocal@mot.upv.es about any issue with the data.
The authors gratefully acknowledge computing time on the Gauss Centre for Supercomputing e.V. on the GCS Supercomputer SuperMUC-NG at Leibniz Supercomputing Centre under Project No. pr92la, on the supercomputer Lichtenberg II at TU Darmstadt under Project No. project00072, and on the supercomputer CLAIX-2018 at RWTH-Aachen under Project No. bund0008. S. V. K. gratefully acknowledges funding from projects OB96/39-1 and M.O. for partial funding from OB 96/48-1, both financed by the German Research Foundation (DFG). S. H. and F. A.-A. were supported by Contract No. RTI2018-102256-B-I00 of MINECO/FEDER. F. A.-A. is partially funded by GVA/FEDER project ACIF2018. Finally, the authors thank Paul Hollmann for help with the manuscript.
Keywords
Citation
Endorsement
DFG Classification
Project(s)
Faculty
Collections
License
Except where otherwise noted, this license is described as Creative Commons Attribution-NonCommercial-NoDerivatives 4.0