A soot particle surface reactivity model applied to a wide range of laminar ethylene/air flames

A novel soot concentration field estimator applied to sooting ethylene/air laminar flames

“…However, if the evolution is then seen from a historypoint-of-view, theoretically, soot concentration can be determined entirely by the history of a fluid parcel in which it is contained, from before inception to oxidation or smoke emission. This idea is supported by evidences shown in Veshkini, Dworkin, and Thomson (2014) and Kholghy, Veshkini, and Thomson (2016), in which it has been shown that soot evolution has a stronger dependency on the temperature history of soot particles than just particle size and local flame temperature. In Veshkini et al (2014) the concept of temperature aging was used to develop a new rate for soot growth processes; and in Kholghy et al (2016) important processes for soot maturity, such as the particle dehydrogenation, PAH molecular weight growth and shell formation, were regulated by temperature-time history of particles.…”

“…This idea is supported by evidences shown in Veshkini, Dworkin, and Thomson (2014) and Kholghy, Veshkini, and Thomson (2016), in which it has been shown that soot evolution has a stronger dependency on the temperature history of soot particles than just particle size and local flame temperature. In Veshkini et al (2014) the concept of temperature aging was used to develop a new rate for soot growth processes; and in Kholghy et al (2016) important processes for soot maturity, such as the particle dehydrogenation, PAH molecular weight growth and shell formation, were regulated by temperature-time history of particles. So, within the Soot Estimator technique, it is assumed that the local instantaneous soot volume fraction f v can be correlated to the history of thermo-chemical properties of a combustion system, or key parameters, to which a fluid parcel has been exposed as…”

“…The soot estimator consists of a library of a series of numerical solutions of well validated sooting flames. Sectional detailed soot modeling are employed as well as a detailed kinetic mechanism to predict PAHs, which are the gas species responsible for the nucleation of the soot particles (Eaves et al, 2012(Eaves et al, , 2016Saffaripour, Kholghy, Dworkin, & Thomson, 2013;Veshkini et al, 2014;Zhang, Thomson, Guo, Liu, & Smallwood, 2009). From these numerical solutions the Lagrangian histories of soot-containing fluid parcels are algorithmically gathered and stored in a library.…”

Experimental and numerical study of soot formation in laminar coflow diffusion flames of gasoline/ethanol blends

“…In previous numerical studies based on the CoFlame code [17,[20][21][22][23][24][25], the steric factor α, which represents the fraction of soot surface sites for HACA surface reactions (except oxidation by OH) [31,33], was considered as a model parameter, whose value was tuned to provide good agreement with available experimental data. Although various efforts have been made to correlate α as a function of temperature, particle size, and in a recent study as a function of thermal age [41], it is unlikely to establish a generic expression for α that can be applied for flames of different fuels. This is because there are currently large uncertainties in the PAH formation sub-mechanism, which has a significant influence on the soot inception rate and the subsequent surface growth modeling.…”

Sectional soot model coupled to tabulated chemistry for Diesel RANS simulations

“…It has been checked that these results were reproduced by the proposed model. Moreover, 30 or 35 sections are commonly used in 3-D simulations using soot sectional methods [32][33][34].…”