Numerical simulations of soot aggregation in premixed laminar flames

Morgan, Neal; Kraft, Markus; Balthasar, Michael; Wong, David Y.; Frenklach, Michael; Mitchell, Pablo

doi:10.1016/j.proci.2006.08.021

Cited by 84 publications

(43 citation statements)

References 30 publications

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“…Initiation of the process of soot and hydrocarbon fuels is not only related to the thermal solution, but also with a specific precursor-related chemical processes. Results show [16,17], that flame and carbon-related intermediate species, mainly PAH and polyacetylene, play an equally important role in soot particle nucleation, which would follow Equations (6) and (7):…”

Section: Soot Source Termmentioning

confidence: 95%

A Phenomenological Model for Prediction Auto-Ignition and Soot Formation of Turbulent Diffusion Combustion in a High Pressure Common Rail Diesel Engine

et al. 2011

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Abstract:A new phenomenological model, the TP (Temperature Phase) model, is presented to carry out optimization calculations for turbulent diffusion combustion in a high-pressure common rail diesel engine. Temperature is the most important parameter in the TP model, which includes two parts: an auto-ignition and a soot model. In the auto-ignition phase, different reaction mechanisms are built for different zones. For the soot model, different methods are used for different temperatures. The TP model is then implemented in KIVA code instead of original model to carry out optimization. The results of cylinder pressures, the corresponding heat release rates, and soot with variation of injection time, variation of rail pressure and variation of speed among TP model, KIVA standard model and experimental data are analyzed. The results indicate that the TP model can carry out optimization and CFD (computational fluid dynamics) and can be a useful tool to study turbulent diffusion combustion.

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Section: Soot Source Termmentioning

confidence: 95%

A Phenomenological Model for Prediction Auto-Ignition and Soot Formation of Turbulent Diffusion Combustion in a High Pressure Common Rail Diesel Engine

et al. 2011

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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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“…Other researchers have explored hybrid solution methods, for example integrating discrete relations for small clusters (i = 1 to 20) with sectional relations for the larger clusters (Gelbard et al 1980;Wu and Flagan 1988;Langrebe and Pratsinis 1990). Mathematical modeling of agglomeration has also been carried out using finite element (Das and Bhattacharjee 2003), Monte Carlo (Sinyagin et al 2005;Balthasar et al 2005), and stochastic methods (Morgan et al 2005(Morgan et al , 2007.…”

Section: Particle Formation and Growth Modelsmentioning

confidence: 99%

Image Analysis and Computer Simulation of Nanoparticle Clustering in Combustion Systems

Chen

Bakrania

Wooldridge

et al. 2010

Aerosol Science and Technology

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The current work presents a new method to model and characterize the formation and growth of nanoparticles clusters which includes the three dimensional geometric properties of the clusters, such as aspect ratios, main chain length, radius of gyration, fractal dimension and fractal prefactor. In the model, semi-stochastic mathematics is used to represent varying levels of Coulomb and van der Waals forces during clustering of monodisperse particles. Parametric studies of the relative particle interactions are conducted to evaluate the effects on cluster geometry. Radius of gyration and main chain length were identified as the geometric properties with the greatest sensitivity to changes in the interparticle forces. To demonstrate the analytical capability of the approach, clusters of combustion-generated tin dioxide (SnO 2 ) nanoparticles were imaged and evaluated to identify the dominant forces controlling cluster morphology. The results show the geometry of the SnO 2 clusters is a result of strong Coulomb interactions.

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Numerical simulations of soot aggregation in premixed laminar flames

Cited by 84 publications

References 30 publications

A Phenomenological Model for Prediction Auto-Ignition and Soot Formation of Turbulent Diffusion Combustion in a High Pressure Common Rail Diesel Engine

A Phenomenological Model for Prediction Auto-Ignition and Soot Formation of Turbulent Diffusion Combustion in a High Pressure Common Rail Diesel Engine

Modelling the internal structure of nascent soot particles

Image Analysis and Computer Simulation of Nanoparticle Clustering in Combustion Systems

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