Aerosol Modeling of Soot Nanoparticles in a Turbulent Diffusion Flame Using an Extended Detailed Kinetic Scheme

摘要

In this work, a hybrid finite volume element FVE method is extended to simulate the evolution of soot nanoparticles in a turbulent axisymmetric confined diffusion flame. The FVE method can handle irregular-shaped solution domains and maintain the underlying physical conservation principles. To consider the evolutionary process of soot nanoparticles including nucleation, coagulation, surface growth, and oxidation, a two-variable approach is employed. In this approach, the soot mass fraction and soot number density transport equations are solved using an extended detailed chemical kinetics. Considering the phenyl route to describe the nucleation process, soot inception is based on the formation of two-ringed and three-ringed aromatics from acetylene, benzene, and phenyl radical. Considering the large detailed chemical kinetics, the flamelet combustion model is applied, in which the transport equations of mean mixture fraction and its variance are solved. Turbulence-chemistry interaction is taken into account by using a suitable probability density function. Applying two-equation standard k-ε turbulence model and suitable wall functions, the transport equations of turbulence kinetic energy and its dissipation rate are solved. Assuming optically-thin gases, radiation effects are taken into the account Soot radiation is considered in the optically thin limit, with soot nanoparticles assumed to be Rayleigh range absorber-emitters. To respect the physics of flow, we extend the physical influence scheme to approximate the soot mass fraction and soot number density fluxes over the cell faces via considering the related governing equations. Extending a bi-implicit strategy, the governing equations are solved thorough two different sequential matrices. Comparing with the measured data, the present solution successfully predicts the essential features and characteristics of combustion and soot nanoparticle formation phenomena.