| Description |
Soot is one of the most regulated pollutants in all the combustion applications like automotive engines, aviation engines, and industrial furnaces. Modeling soot formation is quite challenging due to the complex processes involved in the formation of the soot particulates. Empirical formulation based on two- equation soot models is commonly employed. However, they always need tuning for a given application and operational range. On the other hand, the sectional soot model is though highly accurate, has limitations in terms of calculation speed for industrial applications. The method of moment model offers an optimal combination of the efficiency of two-equation soot models and the fidelity of the sectional models. In this model, the soot particle size distribution (PSD) is modeled using the method of moments. In addition to the PSD, the other crucial aspect is the accurate modeling of the subprocess of soot formation like nucleation, surface growth, and oxidation. The modeling of each subprocess involves sensitive modeling parameters like the choice of nucleation precursors, the soot site density, the sticking coefficients, and the number of moments. In this work, a comprehensive investigation is carried out for modeling soot formation using the method of moments in Ansys Fluent software. The objective of the current investigation is to develop an optimal soot modeling strategy that minimizes the need for case-based tuning and applicable for a wide range of operating conditions and different fuels. In the current work, the soot is modeled using three moments with hydrogen abstraction carbon addition (HACA) based surface growth. The gas-phase mechanism, involving polycyclic aromatic hydrocarbon (PAH), is obtained from Ansys Models Fuel library. The results are compared with experimental data for different flames and modeling guidelines are proposed based on the model performance for the validation cases. |
