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First Thermal and Fluids Engineering Summer Conference

ISSN: 2379-1748
ISBN: 978-1-56700-430-4

A PLATFORM THAT ACCEPTS SUB-GRID MODELS AS PLUGINS TO ENABLE THE TESTING OF LES MODELS AGAINST DNS DATA

DOI: 10.1615/TFESC1.cmd.012670
pages 275-288

Igor Grossman
Centre for Environmental Safety and Risk Engineering College of Engineering and Science, Victoria University, Melbourne, Australia 8001

Jun-De Li
Centre for Environmental Safety and Risk Engineering College of Engineering and Science, Victoria University, Melbourne, Australia 8001

Graham Thorpe
Centre for Environmental Safety and Risk Engineering College of Engineering and Science, Victoria University, Melbourne, Australia 8001


KEY WORDS: DNS, LES, Johns Hopkins Turbulence Databases, JHTDB, computational methods

Abstract

The Johns Hopkins Turbulent Databases (JHTDB) form a publicly accessible archive of solutions of the Navier-Stokes equations. The solutions are obtained by direct numerical simulation (DNS) are accurate to about six decimal places. However, the solution is obtained at 1024×1024×1024 points in space and 1024 time samples. This database contains 160 petabytes of information and it is a serious challenge if we wish to use it routinely for practical analyses. A natural answer to this challenge is to seek the application of 'database technology' in computational fluid dynamics (CFD) and turbulence research. Direct numerical solution (DNS) of the Navier-Stokes equation resolves all of the flow structures that influence turbulent flows, but in the case of LES the Navier-Stokes equation is spatially filtered so that it is expressed in terms of the velocities of larger scale structures. The rate of viscous dissipation is quantified by modelling the shear stress, and this process can lead to error. A means of rapid testing and evaluation of models is therefore required and this involves working with large data sets.
In this work we present a computational platform that allows LES models to be dynamically loaded, and to be rapidly evaluated against DNS data. An idea permeating the methodology is that a core is defined that contains the 'knowhow' associated with accessing and manipulating data, and which operates independently of a plugin. An example is presented that demonstrates how users can examine the accuracy of LES models and obtain results almost instantaneously.

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