White Rose University Consortium logo
University of Leeds logo University of Sheffield logo York University logo

A public turbulence database cluster and applications to study Lagrangian evolution of velocity increments in turbulence

Li, Y., Perlman, E., Wan, M., Yang, Y., Meneveau, C., Burns, R., Chen, S., Szalay, A. and Eyink, G. (2008) A public turbulence database cluster and applications to study Lagrangian evolution of velocity increments in turbulence. Journal of Turbulence, 9. pp. 1-29. ISSN 1468-5248

Full text not available from this repository. (Request a copy)


A public database system archiving a direct numerical simulation (DNS) data set of isotropic, forced turbulence is described in this paper. The data set consists of the DNS output on 10243 spatial points and 1024 time samples spanning about one large-scale turnover time. This complete 10244 spacetime history of turbulence is accessible to users remotely through an interface that is based on the Web-services model. Users may write and execute analysis programs on their host computers, while the programs make subroutine-like calls that request desired parts of the data over the network. The users are thus able to perform numerical experiments by accessing the 27 terabytes (TB) of DNS data using regular platforms such as laptops. The architecture of the database is explained, as are some of the locally defined functions, such as differentiation and interpolation. Test calculations are performed to illustrate the usage of the system and to verify the accuracy of the methods. The database is then used to analyze a dynamical model for small-scale intermittency in turbulence. Specifically, the dynamical effects of pressure and viscous terms on the Lagrangian evolution of velocity increments are evaluated using conditional averages calculated from the DNS data in the database. It is shown that these effects differ considerably among themselves and thus require different modeling strategies in Lagrangian models of velocity increments and intermittency.

Item Type: Article
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield)
Depositing User: Mrs Megan Hobbs
Date Deposited: 23 Mar 2010 16:26
Last Modified: 16 Nov 2015 11:48
Published Version: http://dx.doi.org/10.1080/14685240802376389
Status: Published
Publisher: Taylor & Francis
Identification Number: 10.1080/14685240802376389
URI: http://eprints.whiterose.ac.uk/id/eprint/10574

Actions (repository staff only: login required)