Abstract
Soot generally refers to carbonaceous particles formed during incomplete combustion of hydrocarbon fuels. A typical simulation of soot formation and evolution contains two parts: gas chemical kinetics, which models the chemical reaction from hydrocarbon fuels to soot precursors, that is, polycyclic aromatic hydrocarbons or PAHs, and soot dynamics, which models the soot formation from PAHs and evolution due to gas-soot and soot-soot interactions. In this study, two detailed gas kinetic mechanisms (ABF and KM2) have been compared during the simulation (using the solver Chemkin II) of ethylene combustion in counterflow diffusion flames. Subsequently, the operator splitting Monte Carlo method is used to simulate the soot dynamics. Both the simulated data from the two mechanisms for gas and soot particles are compared with experimental data available in the literature. It is found that both mechanisms predict similar profiles for the gas temperature and velocity, agreeing well with measurements. However, KM2 mechanism provides much closer prediction compared to measurements for soot gas precursors. Furthermore, KM2 also shows much better predictions for soot number density and volume fraction than ABF. The effect of nozzle exit velocity on soot dynamics has also been investigated. Higher nozzle exit velocity renders shorter residence time for soot particles, which reduces the soot number density and volume fraction accordingly.
Highlights
Around 80%–85% world energy comes from combustion of fossil fuel [1]. e formation and evolution of soot is an important and constantly studied field in combustion due to its practical significance in the production of technical carbon, as well as in the combustion efficiency and human health [2, 3]
Quantitative knowledge of soot formation has been largely derived from three types of work [4]: measurement of soot volume fraction, number density, and particle size distributions (PSDs); development of detailed chemical mechanisms for the formation of polycyclic aromatic hydrocarbons; and development of soot population dynamics models to describe the evolution of the particle ensemble
Methodology e simulation of soot formation and evolution in di usion ames are accomplished in two steps, that is, gaseous chemical kinetics simulation to determine the concentration of gaseous soot precursors and stochastic simulation for soot particle dynamics
Summary
Around 80%–85% world energy comes from combustion of fossil fuel [1]. e formation and evolution of soot (i.e., carbon particles resulting from incomplete combustion of hydrocarbons) is an important and constantly studied field in combustion due to its practical significance in the production of technical carbon (such as filler in rubber, component of printing paints), as well as in the combustion efficiency and human health [2, 3]. Been coupled with the chemical kinetics solver Chemkin II to simulate soot formation and evolution in a counter ow di usion ame [14]. Is work is to further explore the simulation framework of coupling the kinetics solver with the stochastic method and to provide more detailed simulation results on the soot dynamics in counter ow di usion ames, so as to investigate the e ects of di erent popular chemical kinetic mechanisms and nozzle exit velocity on the soot formation and evolution. 2. Methodology e simulation of soot formation and evolution in di usion ames are accomplished in two steps, that is, gaseous chemical kinetics simulation to determine the concentration of gaseous soot precursors (i.e., polycyclic aromatic hydrocarbons, PAHs) and stochastic simulation for soot particle dynamics. Oxidation is modelled by the reaction of soot particles with OH and O2 molecules
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