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

TL;DR

This paper introduces a publicly accessible DNS turbulence database system enabling remote analysis of large-scale turbulence data, facilitating studies on Lagrangian velocity increments and intermittency effects.

Contribution

The paper presents a novel web-based database system for large DNS turbulence data, allowing remote analysis and demonstrating its use in studying small-scale turbulence intermittency.

Findings

Pressure and viscous effects on velocity increments vary significantly.

The database enables detailed analysis of turbulence dynamics.

Different modeling strategies are needed for pressure and viscous effects.

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 $1024^3$ spatial points and 1024 time-samples spanning about one large-scale turn-over timescale. This complete $1024^4$ space-time 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 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.