DNS Data for Turbulent Couette Flow

Three direct numerical simulations of fully developed flow at different Reynolds numbers in a plane Couette have been performed with POONGBACK code which uses the spectral numerical method of Kim, Moin and Moser (J. Fluid Mech. vol 177, page 133). The friction Reynolds numbers of the simulations are 93, 220, and 500. The data may be added to from time to time and corrections will be made if needed.

A comprehensive set of statistical data has been collected from these simulations and is available. It includes mean, Reynolds stress, terms in the Reynolds stress transport equations, etc. The data is in a series of text files.

Acknowledgement

When publishing results obtained using the Couette flow fields provided here, we ask you to cite the source of the data through the following publications

Myoungkyu Lee and Robert D. Moser "Extreme-scale motions in turbulent plane Couette flows", Journal of Fluid Mechanics, 2018, vol. 842, pp. 128-145 * The paper can be found at https://doi.org/10.1017/jfm.2018.131

Raw data of velocity fields

Please, contact us for raw data.

Reference for simulation detail

• Data analysis :
     Myoungkyu Lee and Robert D. Moser "Extreme-scale motions in turbulent plane Couette flows", Journal of Fluid Mechanics, 2018, vol. 842, pp. 128-145

• Code development & Optimization :
     Myoungkyu Lee, Nicholas Malaya and Robert D. Moser, 2013, "Petascale direct numerical simulation of turbulent Channel flow on up to 786K cores", Proc. SC13: Int’l Conf. for High-Performance Computing, Networking, Storage and Analysis

• Code verification, I/O, & Running simulation :
     Myoungkyu Lee, Rhys Ulerich, Nicholas Malaya, and Robert D. Moser, 2014, "Experiences from Leadership Computing in Simulations of Turbulent Fluid Flows", Computing in Sci & Eng

• Uncertainty estimation :
     Todd Oliver, Nicholas Malaya, Rhys Ulerich, Robert D. Moser, 2014, "Estimating uncertainties in statistics computed from direct numerical simulation", Physics of Fluids

Contact Information

Robert D. Moser rmoser@ices.utexas.edu Myoungkyu(M.K.) Lee mnlee@sandia.gov

*Preparing the data was supported by the National Science Foundation under Award Number [OCI-0749223] and the Argonne Leadership Computing Facility at Argonne National Laboratory under Early Science Program(ESP) and Innovative and Novel Computational Impact on Theory and Experiment Program(INCITE) 2013.