Bulletin of the American Physical Society
71st Annual Meeting of the APS Division of Fluid Dynamics
Volume 63, Number 13
Sunday–Tuesday, November 18–20, 2018; Atlanta, Georgia
Session KP1: Poster Session (3:20-4:05pm)
3:20 PM,
Monday, November 19, 2018
Georgia World Congress Center
Room: Level 1, Exhibit Hall B2 by the GFM videos
Abstract ID: BAPS.2018.DFD.KP1.144
Abstract: KP1.00144 : LES/FDF studies of probability distribution of mixture fraction in inhomogeneous inlet turbulent jet flames*
Presenter:
Pei Zhang
(Purdue Univ)
Authors:
Haifeng Wang
(Purdue Univ)
Pei Zhang
(Purdue Univ)
Robert S. Barlow
(Sandia Natl Labs)
Assaad R. Masri
(The University of Sydney)
Mixture fraction is a key parameter that can be used for quantifying and modeling mixing in turbulent non-premixed, partially premixed, and stratified flames. It is a central quantity in many existing combustion models such as the flamelet models and the conditional moment closure. Developing capabilities to accurately predict mixture fraction is thus crucial for turbulent combustion modeling. Focus in the past has mainly been put on the prediction of the low-order moments such as the mean and variance of mixture fraction. The prediction of the full statistical information of mixture fraction has not been thoroughly studied. In this work, we examine the predictive capability of large-eddy simulation (LES)/filtered density function (FDF) for the probabilistic distribution of the mixture fraction. A series of piloted methane jet flames with inhomogeneous inlet flows is chosen as the test case which has detailed measurement data for the distribution of the mixture fraction. Different statistical distributions are examined such as the single-point PDF and the FDF. The capability of capturing these distributions by using LES/FDF is examined thoroughly.
*National Science Foundation under Grant no. CBET-1336075
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.DFD.KP1.144
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