Stochastic modeling of soot particle size and age distributions in laminar premixed flames

Singh, Jasdeep; Balthasar, Michael; Kraft, Markus; Wagner, Wolfgang

doi:10.1016/j.proci.2004.08.120

Cited by 88 publications

(53 citation statements)

References 32 publications

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“…The formation and growth of soot particles are described by collision-induced coalescence, surface reaction/oxidation, and surface condensation, and, when particles exceed a certain size, by particle-particle agglomeration, leading to fractal-like aggregates. Several methods of solution of aerosol dynamics have been proposed, including the moment [39,40], sectional [45], Galerkin [46], and stochastic methods [44,47,48]. Because of limitations on the number of species and variables high-fidelity LES models are able to handle, the moment method remains the most promising near-term solution to soot aerosol dynamics and was used in this project.…”

Section: Soot Chemistry Modelmentioning

confidence: 99%

Understanding and predicting soot generation in turbulent non-premixed jet flames.

Wang

Kook²,

Doom³

et al. 2010

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This report documents the results of a project funded by DoD's Strategic Environmental Research and Development Program (SERDP) on the science behind development of predictive models for soot emission from gas turbine engines. Measurements of soot formation were performed in laminar flat premixed flames and turbulent non-premixed jet flames at 1 atm pressure and in turbulent liquid spray flames under representative conditions for takeoff in a gas turbine engine. The laminar flames and open jet flames used both ethylene and a prevaporized JP-8 surrogate fuel composed of n-dodecane and m-xylene. The pressurized turbulent jet flame measurements used the JP-8 surrogate fuel and compared its combustion and sooting characteristics to a world-average JP-8 fuel sample. The pressurized jet flame measurements demonstrated that the surrogate was representative of JP-8, with a somewhat higher tendency to soot formation. The premixed flame measurements revealed that flame temperature has a strong impact on the rate of soot nucleation and particle coagulation, but little sensitivity in the overall trends was found with different fuels. An extensive array of non-intrusive optical and laser-based measurements was performed in turbulent non-premixed jet flames established on specially designed piloted burners. Soot concentration data was collected throughout the flames, together with instantaneous images showing the relationship between soot and the OH radical and soot and PAH. A detailed chemical kinetic mechanism for ethylene combustion, including fuel-rich chemistry and benzene formation steps, was compiled, validated, and reduced. The reduced ethylene mechanism was incorporated into a high-fidelity LES code, together with a momentbased soot model and models for thermal radiation, to evaluate the ability of the chemistry and soot models to predict soot formation in the jet diffusion flame. The LES results highlight the importance of including an optically-thick radiation model to accurately predict gas temperatures and thus soot formation rates. When including such a radiation model, the LES model predicts mean soot concentrations within 30% in the ethylene jet flame. 3This page left intentionally blank.

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Section: Soot Chemistry Modelmentioning

confidence: 99%

Understanding and predicting soot generation in turbulent non-premixed jet flames.

Wang

Kook²,

Doom³

et al. 2010

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“…Likewise, little is known about the internal structure of soot other than from HRTEM images [1,2] and the results of some numerical studies of PAH interactions which have investigated clustering and the dynamics of the molecular interactions [3][4][5][6][7]. Developing an understanding of the internal structure of soot particles is essential to improve our current soot models [8][9][10][11][12][13][14][15][16][17]. In particular it is vital to establish how molecules arrange locally and how mobile they are within a particle to properly understand the time evolution of soot particles in flame environments.…”

Section: Introductionmentioning

confidence: 99%

Modelling the internal structure of nascent soot particles

Totton

Chakrabarti

Misquitta

et al. 2010

Combustion and Flame

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“…Kinetic data for gas phase reactions are not precise and the processes on the surface of soot particles are barely understood at all. In particular, the surface activity of soot particles is known to decrease as particles move through flames but no physical model is available and some sort of correlation with size [13] or age [15] has to be used instead. Also while the MoMIC and the stochastic data are qualitatively the same and close on a log scale there are some differences.…”

Section: Application To Flamesmentioning

confidence: 99%

“…Second, the representation of the particle distribution by a sample of particles means that simulation of processes at the individual particle level is possible. Interactions between particles and the surrounding system may be simulated using the kinetics for those particular particles rather than average quantities as in moment-based methods; see for example [15]. Within the DSA framework extremely complex descriptions of the internal particle structure can also be used, e.g., [16].…”

Section: Application To Flamesmentioning

confidence: 99%