Large Eddy Simulation of soot evolution in turbulent reacting flows: Strain-Sensitive Transport Approach for Polycyclic Aromatic Hydrocarbons

Suo Yang, Jeffry K. Lew, Michael E. Mueller

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Polycyclic Aromatic Hydrocarbons (PAH) are confined to spatially intermittent regions of low scalar dissipation rates due to their slow formation chemistry. The length scales of these regions are on the order of the Kolmogorov scale or smaller, where molecular diffusion dominates over turbulent mixing irrespective of the large-scale turbulent Reynolds number. A strain-sensitivity parameter is proposed to identify such species. A Strain-Sensitive Transport Approach (SSTA) is then developed to model this differential transport in the nonpremixed flamelet equations. Specifically, the strain-sensitive species are modeled with their non-unity molecular effective Lewis numbers, while the remaining species are modeled with unity effective Lewis numbers. An a priori analysis of nonpremixed flamelet solutions reveals that the flame temperature and strain-insensitive species (e.g., major products of combustion, acetylene, etc.) profiles from the proposed SSTA closely match those from the unity effective Lewis number approach, but the mass fractions of strain-sensitive species (e.g., naphthalene) are significantly modified compared to the unity effective Lewis number approach and are consistent with Direct Numerical Simulation (DNS) data. This new SSTA model is implemented within a Large Eddy Simulation (LES) framework, applied to a series of laboratory-scale turbulent nonpremixed sooting jet flames, and validated via comparisons with experimental measurements of temperature and soot volume fraction. Both the unity effective Lewis number approach and SSTA model provide temperature predictions in good agreement with the experimental data, but the non-unity molecular effective Lewis number approach overpredicts the flame length. Compared to the unity effective Lewis number approach, the spatial distribution of soot volume fraction predicted by SSTA is in better agreement with the experimental measurements in terms of the upstream growth of the soot volume fraction and the location of its peak value along the centerline, both of which strongly depend on accurate predictions of the PAH mass fraction. The maximum soot volume fraction is minimally influenced and in good agreement with the experimental measurements. Finally, with this new SSTA model, the influence of global strain rate on turbulent nonpremixed sooting jet flames is analyzed to find that, even though PAH is inversely proportional to the global strain rate, the soot volume fraction may not be inversely proportional to the global strain rate due to an increase in the acetylene surface growth rate coefficient with global strain rate.

Original languageEnglish (US)
Pages (from-to)219-234
Number of pages16
JournalCombustion and Flame
Volume220
DOIs
StatePublished - Oct 2020

Bibliographical note

Funding Information:
The authors gratefully acknowledge funding from NASA under grant number NNX16AP90A . The authors also acknowledge valuable support in the form of computational time on the TIGRESS high performance computer center at Princeton University, which is jointly supported by the Princeton Institute for Computational Science and Engineering (PICSciE) and the Princeton University Office of Information Technology’s Research Computing Department.

Funding Information:
The authors gratefully acknowledge funding from NASA under grant number NNX16AP90A. The authors also acknowledge valuable support in the form of computational time on the TIGRESS high performance computer center at Princeton University, which is jointly supported by the Princeton Institute for Computational Science and Engineering (PICSciE) and the Princeton University Office of Information Technology's Research Computing Department.

Publisher Copyright:
© 2020 The Combustion Institute

Keywords

  • Differential diffusion
  • Effective Lewis numbers
  • Large Eddy Simulation (LES)
  • Polycyclic Aromatic Hydrocarbons (PAH)
  • Soot

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