Effects of non-unity Lewis number of gas-phase species in turbulent nonpremixed sooting flames
KAUST DepartmentClean Combustion Research Center
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AbstractTurbulence statistics from two three-dimensional direct numerical simulations of planar n-heptane/air turbulent jets are compared to assess the effect of the gas-phase species diffusion model on flame dynamics and soot formation. The Reynolds number based on the initial jet width and velocity is around 15, 000, corresponding to a Taylor scale Reynolds number in the range 100 ≤ Reλ ≤ 150. In one simulation, multicomponent transport based on a mixture-averaged approach is employed, while in the other the gas-phase species Lewis numbers are set equal to unity. The statistics of temperature and major species obtained with the mixture-averaged formulation are very similar to those in the unity Lewis number case. In both cases, the statistics of temperature are captured with remarkable accuracy by a laminar flamelet model with unity Lewis numbers. On the contrary, a flamelet with a mixture-averaged diffusion model, which corresponds to the model used in the multi-component diffusion three-dimensional DNS, produces significant differences with respect to the DNS results. The total mass of soot precursors decreases by 20-30% with the unity Lewis number approximation, and their distribution is more homogeneous in space and time. Due to the non-linearity of the soot growth rate with respect to the precursors' concentration, the soot mass yield decreases by a factor of two. Being strongly affected by coagulation, soot number density is not altered significantly if the unity Lewis number model is used rather than the mixture-averaged diffusion. The dominant role of turbulent transport over differential diffusion effects is expected to become more pronounced for higher Reynolds numbers. © 2016 The Combustion Institute.
CitationAttili A, Bisetti F, Mueller ME, Pitsch H (2016) Effects of non-unity Lewis number of gas-phase species in turbulent nonpremixed sooting flames. Combustion and Flame 166: 192–202. Available: http://dx.doi.org/10.1016/j.combustflame.2016.01.018.
SponsorsWe acknowledge valuable support from KAUST Supercomputing Laboratory (KSL) in the form of assistance with code development and computational time on the IBM System Blue Gene/P "Shaheen" at King Abdullah University of Science and Technology. H.P. acknowledges funding by Forschungsvereinigung Verbrennungsmotoren (FVV) and Deutsche Forschungsgemeinschaft (DFG) within the DFG/FVV project PI 368/6-1.
JournalCombustion and Flame