A-priori Analysis of the LMSE Micromixing Model for Filtered-Density Function Simulation in High Schmidt Number Flows

F. Schwertfirm () and M. Manhart ()
Additional contact information
F. Schwertfirm: Fachgebiet Hydromechanik
M. Manhart: Fachgebiet Hydromechanik

A chapter in High Performance Computing in Science and Engineering, Garching/Munich 2007, 2009, pp 303-314 from Springer

Abstract: Abstract An attractive method for dealing with turbulent reacting flows are Filtered-Density Function simulations (FDF) (Colucci et al., Phys. Fluids 12(2): 499–515, 1998; Raman et al., Combust. Flame 143:56–78, 2005), where the transport equations of the FDF are directly solved via a Monte-Carlo Method (Heinz, Statistical Mechanics of Turbulent Flows, 2003; Pope, Turbulent Flows, 2000) in conjunction with a Large-Eddy-Simulation (LES) of the flow field. The great advantage of these methods is that the chemical source term is closed, the difficulties lie in the modeling of the unclosed conditional diffusion term. In this work we adopt the FDF method to treat high Schmidt (Sc) number flows in combination with a Direct Numerical Simulation (DNS) of the flow field. Due to the high Sc number, the micromixing takes place on scales beyond the Kolmogorov scale η K and these scales are therefore described and modeled with the FDF method. In this paper we conduct an a-priori analysis of a standard micromixing model for the conditional diffusion term in the framework of fully resolved flow field (DNS) and an unresolved scalar field at high Sc number.

Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-69182-2_24

Ordering information: This item can be ordered from
http://www.springer.com/9783540691822

DOI: 10.1007/978-3-540-69182-2_24

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().