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Computational Thermal Sciences: An International Journal
ESCI SJR: 0.244 SNIP: 0.434 CiteScore™: 0.7

ISSN Imprimer: 1940-2503
ISSN En ligne: 1940-2554

Computational Thermal Sciences: An International Journal

DOI: 10.1615/ComputThermalScien.v1.i1.20
pages 37-53

MODELING OF A TURBULENT ETHYLENE/AIR JET FLAME USING HYBRID FINITE VOLUME/MONTE CARLO METHODS

Ranjan S. Mehta
Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
Anquan Wang
GE Global Research Center, One Research Circle, Niskayuna, NY 12309; Department of Mechanical Engineering, Pennsylvania State University, University Park, PA 16802, USA
Michael F. Modest
School of Engineering, University of California, Merced, California, USA, 95343
Daniel C. Haworth
Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA

RÉSUMÉ

Detailed modeling of an experimental ethylene/air jet flame is undertaken using the joint composition probability distribution function (PDF) method for gas-phase kinetics coupled with detailed models for soot formation and radiation from the flames. The gas-phase kinetics is modeled using a reduced mechanism for ethylene consisting of 33 species and 205 elementary reactions. The soot formation is modeled using the method of moments with a simplified nucleation mechanism and modified surface-HACA (Hydrogen abstraction acetylene addition) mechanism for surface growth and oxidation. The soot formation is coupled directly with a transported PDF approach to account for turbulence-chemistry interactions in gas-phase chemistry and the highly nonlinear soot formation processes. Radiation from soot and combustion gases is accounted for by using a photon Monte Carlo method coupled with nongray properties for soot and gases. Soot particles are assumed to be small, and scattering effects are neglected. Turbulence-radiation interactions are captured accurately. Simulation results are compared to experimental data, and also with less CPU-intensive radiation calculations using the optically thin approximation.


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