Large eddy simulation subfilter modeling of soot-turbulence interactions

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Abstract

The small-scale interactions between turbulence, chemistry, and soot have a profound effect on the soot formation, growth, and destruction processes in turbulent reacting flows. In this work, the small-scale subfilter interactions between turbulence and soot are modeled using a presumed subfilter PDF for the statistical moments of the soot number density function. Due to a very large (infinite) Schmidt number, soot is confined to very thin structures. In addition, soot is formed initially from Polycyclic Aromatic Hydrocarbons, which exhibit a strong sensitivity to the local scalar dissipation rate in the flow field. These interactions of soot with the gas-phase chemistry, molecular transport, and turbulence result in very high spatial and temporal intermittency. Therefore, the soot subfilter PDF is presumed to be a pair of delta distributions with a sooting mode and a non-sooting mode. In addition to the mean values of the scalars, one additional parameter is needed to specify this distribution. The presumed soot subfilter PDF approach is evaluated a priori using a recent two-dimensional direct numerical simulation (DNS) database of soot evolution in a nonpremixed flame. The analysis shows that predictions of the soot intermittency as well as the soot source terms are improved with this presumed soot subfilter PDF approach compared to simply using the mean values of the soot scalars. Several choices for specifying the additional parameter of the PDF are also evaluated with the database. The results show that the parameter is best specified using the second moment of the soot number density. In addition, the transport equation for the second moment of the number density is briefly discussed. A model for the lone unclosed term is proposed and evaluated with the DNS data.

Original languageEnglish (US)
Article number115104
JournalPhysics of Fluids
Volume23
Issue number11
DOIs
StatePublished - Nov 29 2011

All Science Journal Classification (ASJC) codes

  • Computational Mechanics
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes

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