An Improved Moving Sectional Aerosol Model of Soot Formation in a Plug Flow Reactor

Wen, John Z.; Thomson, Murray J.; Lightstone, M.F.; Park, S. H.; Rogak, Steven N.

doi:10.1080/00102200500270007

Cited by 19 publications

(13 citation statements)

References 28 publications

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“…Park and Rogak [118] employed it for the discretisation of the coagulation term, in conjunction with their method for discretisation of the growth term that will be discussed below, initially for modelling aerosol synthesis. Their overall approach was subsequently applied to soot modelling in several studies, including [119][120][121][122] in ideal reactors, [123][124][125][126][127] in laminar co-flow diffusion flames and [128] in laminar premixed flames.…”

Section: (Sections 32 and 33)mentioning

confidence: 99%

“…In these methods, special care must be taken for the nucleation term which is always active at the lowest end of the volume range, an issue that can be addressed by adding nodes at that range [142]. Moving grid methods were applied to soot by Park et al [120] and Wen et al [121,122]. A major issue with moving grids arises when the PBE is coupled with flow, as the distribution becomes spatially dependent and a different grid may be required at different locations.…”

Section: (Sections 32 and 33)mentioning

confidence: 99%

“…This model was subsequently applied to soot formation in a jet stirred reactor-plug flow reactor (JSR-PFR) combination by Park et al [120], where no sintering was considered. A number of further studies employed this approach for the JSR-PFR system [121,122] and laminar flames [125][126][127].…”

Section: (Sections 32 and 33)mentioning

confidence: 99%

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Modelling of Soot Aerosol Dynamics in Turbulent Flow

Rigopoulos

2019

Flow Turbulence Combust

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Aerosol dynamics plays an important role in the modelling of soot formation in combustion processes, as it is responsible for predicting the distribution of size and shape of soot particles. The distribution is required for the correct prediction of the rates of surface processes, such as growth and oxidation, and furthermore it is important on its own because new regulations on particulate emissions require control of the number of smaller particles. Soot formation is strongly dependent on the local chemical composition and thermodynamic conditions and is therefore coupled with fluid dynamics, chemical kinetics and transport phenomena. Comprehensive modelling of soot formation in combustion processes requires coupling of the population balance equation, which is the fundamental equation governing aerosol dynamics, with the equations of fluid dynamics. The presence of turbulence poses an additional challenge, due to the non-linear interactions between fluctuating velocity, temperature, concentrations and soot properties. The purpose of this work is to review the progress made in aerosol dynamics models, their integration with fluid dynamics and the models for addressing the turbulence-soot interaction.

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Section: (Sections 32 and 33)mentioning

confidence: 99%

Section: (Sections 32 and 33)mentioning

confidence: 99%

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Modelling of Soot Aerosol Dynamics in Turbulent Flow

Rigopoulos

2019

Flow Turbulence Combust

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“…Figure 7 shows the evolution of particle size distribution. The normalized particle size distributions as defined in the previous study [16] are used. At an earlier residence time when the nucleation process dominates, shown as 10 µs in the figure, the particle size distribution has a power law shape.…”

Section: Predictions Of Particle Size and Number Densitymentioning

confidence: 99%

“…This was attributed to a lack in the description of agglomerate structure of particles in those models [13]. Most recently, a fixed sectional aerosol dynamic model has been successfully implemented in studying the formation of soot agglomerates by simultaneous nucleation, coagulation, surface growth and condensation, and was valid over the entire Knudson number regime [15,16]. The model has its advantages of decreasing numerical diffusion and increasing the computational stability [17].…”

Section: Introductionmentioning

confidence: 99%

Numerical study of carbonaceous nanoparticle formation behind shock waves

Wen

Thomson

Lightstone

2006

Combustion Theory and Modelling

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By incorporating complex chemical kinetics for both gaseous and particulate phases with a fixed sectional aerosol dynamics model, a detailed description of the properties of carbonaceous nanoparticles formed in the pyrolysis of carbon suboxide behind a reflected shock wave can be obtained. The model successfully predicted the induction time, growth rate and particle yield for the shock tube experiment. The calculated time-dependent particle volume fractions were in good agreement with the measured optical densities, and the averaged particle diameters were in reasonable agreement with the measured particle size using LII (laser-induced incandescence) and TEM (transmission electron microscope). The predicted particle size distribution as a function of residence time showed an evolution from the power law shape to a bi-modal shape. The temperature dependence of particle properties has been also investigated. The second bell at the high temperature range, which has been argued as resulting from particle nucleation behind the incident wave during the experiment, was found in the numerical simulation of particle formation behind the reflected shock wave where no incident wave is included. Analysis of the simulation results showed that the double bell-shaped particle yield arises from the different particle nucleation timescales and the changing surface growth rates at different temperatures.

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