Numerical Investigation of Soot Dynamics at Engine-Relevant Conditions

Formation of soot in an auto-igniting n-dodecane spray under diesel engine relevant conditions has been investigated numerically. As opposed to research addressing turbulence-chemistry interaction (TCI) by coupling diffusive turbulence models with more sophisticated models in the context of Reynolds-Averaged Navier-Stokes equations (RANS), this study employs the advanced sub-grid scale k-equation model in the framework of a Large Eddy Simulation (LES) together with the uninvolved Direct Integration (DI) approach. A reduced n-heptane chemical mechanism has been employed and artificially accelerated in order to predict the ignition for n-dodecane accurately. Soot processes have been modelled with an extended version of the semi-empirical, two-equation model of Leung, which considers C2H2 as the soot precursor and accounts for particle inception, surface growth by C2H2 addition, oxidation by O2, oxidation by OH and particle coagulation. A full spray event has been simulated and statistics have been collected over the quasi-steady state of the spray. The results are compared to experimental data from the Engine Combustion Network in terms of vapor penetration, global soot mass and distribution of soot volume fraction. They are also compared to - RANS computations in terms of time-averaged fields related to flame structure and soot kinetics. Both turbulence modelling frameworks are shown to successfully predict the position of the soot cloud in physical space. LES additionally succeeds at capturing the intermittency in soot formation and oxidation, although a smaller filter width would be required to bring soot kinetic processes to the resolved scales. Comparison between terms in the soot mass fraction transport equation provides insight into the origin of the qualitative differences between RANS and LES.


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  • Accession Number: 01690107
  • Record Type: Publication
  • Source Agency: SAE International
  • Report/Paper Numbers: 2018-01-0204
  • Files: TRIS, SAE
  • Created Date: Dec 27 2018 5:05PM