Kinetic modeling of soot formation in premixed burner-stabilized stagnation ethylene flames at heavily sooting condition. (15th December 2018)

• Record Type: Journal Article
• Authors: Pejpichestakul, Warumporn; Frassoldati, Alessio; Parente, Alessandro; Faravelli, Tiziano
• Is Part Of: Fuel. Volume 234(2018)
• Page Start: 199
• Page End: 206
• Publication Date: 2018-12-15
• Subjects: Soot -- Laminar premixed flame -- Particle size distribution functions -- Kinetic modeling; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2018.07.022
• Languages: English
• ISSNs: 0016-2361

Abstract

Abstract: A detailed kinetic mechanism of soot formation and oxidation is revised and extended to include temperature-dependent collision efficiencies. The collision efficiency for various particle size is studied and compared with experimental data and molecular dynamics simulations for the PAH dimerization where the experimental data are not available. This revised kinetic model is validated in comparison with the premixed burner-stabilized stagnation ethylene flames at heavily sooting conditions. The results showed that quasi-one-dimensional numerical simulations can capture the flame structure and predict soot formation quite satisfactorily. The predicted particle size distribution function (PSDF) is in reasonable agreement with experimental results, but the model only partially reproduces the distinct separation between nucleation and coagulation modes observed experimentally. This leads to some discrepancies in the prediction of soot number density, while the predicted soot volume fraction, which is dominated by the large particles of the PSDF, is in generally good agreement with the experimental data. There is an overestimation of the initial soot volume fraction in the flame region close to the burner, which is a consequence of the over-prediction of the amount of young particles. Therefore, the prediction of PAHs formation and their condensation on soot, which controls the nucleation rate, will require further attention. The comparison between the temperature-dependent model and the model neglecting the temperature dependency showed that the temperature-dependent model could improve the prediction of soot number density, which is controlled by small particles.