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

Yi Li Department of Mechanical Engineering, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA; Department of Applied Mathematics, University of Sheffield, UK

Eric Perlman Department of Computer Science, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA

Minping Wan Department of Mechanical Engineering, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA

Yunke Yang Department of Mechanical Engineering, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA

Charles Meneveau Department of Mechanical Engineering, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA

Randal Burns Department of Computer Science, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA

Shiyi Chen Department of Mechanical Engineering, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA

Alexander Szalay Department of Physics and Astronomy, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA

Gregory Eyink Department of Applied Mathematics and Statistics, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA

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Abstract

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.

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Acknowledgment

The authors thank Tamas Budavari, Ani Thakar, Jan Vandenberg and Alainna Wonders for their valuable help at various stages of development and maintenance of the database cluster. They also wish to acknowledge the National Science Foundation for funding through the ITR program, grant AST-0428325. The DNS was performed on a cluster supported by NSF through MRI grant CTS-0320907. Additional hardware support was provided by the Moore Foundation. Discussions with Professor Ethan Vishniac are also gratefully acknowledged.

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

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

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