A computationally efficient approach for soot modeling with discrete sectional method and FGM chemistry

A novel approach for the prediction of soot formation in combustion simulations within the framework of discrete sectional method (DSM) based univariate soot model and Flamelet Generated Manifold (FGM) chemistry, referred to as FGM-CDSM, is proposed in this study. The FGM-CDSM considers the clustering of soot sections derived from the original soot particle size distribution function (PSDF) to minimize the computational cost. Unlike conventional DSM, in FGM-CDSM, governing equations for soot mass fractions are solved for the clusters, by using a pre-computed lookup table with tabulated soot source terms from the flamelet manifold, while the original soot PSDF is re-constructed in a post-processing stage. The flamelets employed for the manifold are computed with detailed chemistry and the complete sectional soot model. A comparative assessment of FGM-CDSM is conducted in laminar diffusion flames for its accuracy and computational performance against the detailed kinetics-based classical sectional model. Numerical results reveal that the FGM-CDSM can favorably reproduce the global soot quantities and capture their dynamic response predicted by detailed kinetics with a good qualitative agreement. Furthermore, compared to detailed kinetics, FGM-CDSM is shown to substantially reduce the computational cost of the complete reacting flow simulation with soot particle transport. Primarily, the use of FGM reduces the overall calculation by about two orders of magnitude compared to detailed kinetics, which is advanced further with the clustering of sections at a low memory footprint. Therefore, the present work demonstrates the promising capabilities of FGM-CDSM in the context of computationally efficient soot calculations and provides an excellent framework for extending its application to the simulations of turbulent sooting flames

Investigation of soot formation in n-dodecane spray flames using LES and a discrete sectional method

Considering stricter regulations on soot emissions, the detailed soot modeling approaches facilitating prediction of soot particle size distributions (PSD) are increasingly in demand. In this context, the transient evolution of soot is numerically investigated for two high-pressure turbulent sprays from the Engine Combustion Network (ECN), namely, Spray C (SC) and Spray D (SD). The 900-K ambient temperature (Tam) sprays are studied. This is because the two cases tend to produce a similar amount of soot at Tam=900K, despite the significantly different spray development. To predict the soot formation with information on PSD, a discrete sectional method is applied within the large-eddy simulation (LES) framework. The applied modeling strategy favorably captures the experimentally observed similar soot mass for SC and SD in the characteristic field-of-view (FOV) frustum. Moreover, the transient dynamics of soot within the FOV frustum is well captured, and the onset of soot is well predicted. It is observed that for SC and SD, soot formation is more prominent in fuel-rich (2&lt;π&lt;4) and high-temperature (T&gt;1500K) regions. Despite the stronger fuel dilution in the downstream area of the spray, soot is predominantly present in the head of the spray during the whole combustion progress, corresponding to larger particle sizes and higher soot number density. Although the spray development of SC and SD are different, the FOV approach bridges the two cases. The unique correlation between soot mass and FOV volume recognized in experiments was found to hold for the complete quasi-steady sooting region. Moreover, PSD analysis suggests very similar soot size and number density with respect to the FOV volume. This is attributed to the similar LOL for SC and SD in the normalized coordinates, and the same FOV volume corresponding to similar locations in the normalized coordinates.</p

An assessment of the sectional soot model and FGM tabulated chemistry coupling in laminar flame simulations

Discrete sectional method (DSM)-based soot models are computationally demanding since several transport equations are required to be solved for sectional soot variables using large chemical kinetic mechanisms. In this paper, the sectional soot model is coupled with Flamelet Generated Manifold (FGM) tabulated chemistry to achieve computationally efficient chemistry reduction for combustion simulations. Different approaches are explored for incorporating soot-gas phase coupling with FGM chemistry, and a comprehensive assessment of these FGM-DSM approaches is conducted for their predictive accuracy and computational performance in simulations of laminar ethylene counterflow flames. The accuracy of soot prediction with FGM chemistry is found to be sensitive to the tabulated concentrations of PAH species. An unaccounted consumption of PAH originating from PAH-based processes leads to significant overprediction of soot. In this context, the performance of two strategies (i) solving the transport equation of PAH species (ii) including a contribution of soot nucleation during the manifold generation stage is compared. The latter approach showed relatively better accuracy and computational efficiency than the former. Numerical results further reveal that the strategy of including the complete soot model during the manifold generation stage reproduces the detailed chemistry solutions most accurately. The influence of unsteadiness on predictive capabilities of FGM-DSM approaches is also investigated by imposing time-dependent strain rates in unsteady simulations. The computational performance analysis indicates that by adopting FGM chemistry, up to two orders of magnitude reduction in CPU time can be achieved, based on the choice of section number and simulation approach. Promising results obtained for FGM-DSM strategies in one-dimensional configuration, provide a good outset for extending the application of FGM for soot estimation in turbulent flames