Convergence to a model in sparse-lagrangian FDF simulations

Klimenko, AY and Cleary, MJ (2010) Convergence to a model in sparse-lagrangian FDF simulations. Flow, Turbulence And Combustion, 85 3-4: 567-591. doi:10.1007/s10494-010-9301-4

Author Klimenko, AY
Cleary, MJ
Title Convergence to a model in sparse-lagrangian FDF simulations
Journal name Flow, Turbulence And Combustion   Check publisher's open access policy
ISSN 1386-6184
Publication date 2010-12
Sub-type Article (original research)
DOI 10.1007/s10494-010-9301-4
Volume 85
Issue 3-4
Start page 567
End page 591
Total pages 25
Place of publication Dordrecht, Netherlands
Publisher Springer Netherlands
Collection year 2011
Language eng
Abstract This work investigates the problem of distinguishing modelling assumptions and numerical errors in sparse-Lagrangian FDF (Filtered Density Function) methods. A new interpretation of sparse modelling with Curl’s mixing, which does not require an additional observation scale nor filtering, is given. The diffusion effects induced by mixing, which were previously interpreted as numerical errors, are now treated as modelling instruments. This ability of controlling numerical errors with the purpose of modelling physical quantities is one of the advantages of Lagrangian particle methods in turbulent reacting flows. The development of stochastic methods which use Lagrangian particles has been ongoing for many years, although the exact interpretation of the nature of such particles varies within the literature. Here we briefly discuss these interpretations and introduce the new term—“Pope particles”— to unify terminology used for the particle simulations of turbulent reacting flows. © Springer Science+Business Media B.V.
Keyword Turbulent reacting flows
PDF and FDF methods
Large-eddy simulation
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mechanical & Mining Engineering Publications
Official 2011 Collection
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 11 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 13 times in Scopus Article | Citations
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Created: Sun, 30 Jan 2011, 00:05:44 EST