Modeling of aerosol dynamics in flames and exhaust plumes

Starting from the original physical model for aerosol coagulation, a sectional-nodal method was developed to conveniently simulate aerosol coagulation dynamics. The formulation for aerosol coagulation dynamics is represented by ordinary differential equations. These equations have been easily solved with arbitrary initial particle size distribution and arbitrary number of particle size bins. The computer code has been validated by reproducing the self-preserving particle size distribution. One important advantage of this model is its easiness to include complications such as time-dependent dilution, particle shape, particle growth/destruction, and particle charges.; One advantage of the above methodology is that it can be used to march back in time to estimate the initial particle size distribution (PSD). The criterion for marching back is that as long as the PSD has not fully evolved into self-preserving PSD, the initial PSD can be recovered by using the same sectional-nodal method but marching back in time.; The second application of the model is to include time-dependent dilution into the model. The equation describing the dilution of an aerosol system by ambient air was derived and incorporated into the model. Simulations were done by studying the effects of different streamlines, dilution rate, and ambient particles on the particle size distribution in exhaust plume.; Another application of the model is its extension to include the coagulation of charged particles with allowance of particle growth. Model and equations for the coagulation of charged particles were developed. The enhancement factors for the coagulation between neutral and charged particles and between like-charged particles have been computed. The enhancement factor for the like-charged particles is very small for small particles.; The model was then extended further to include oxidation and fragmentation with allowance of particle shape (agglomeration). Fragmentation equations were formulated and incorporated into the agglomeration equations. The fragmentation rate constant during soot oxidation was modeled by A = A′ f(Δ(d_p)/d_p). The soot fragmentation onset function f(Δ(d_p)/d_p) was determined by the experimental observations. The fragmentation rate magnitude A ′ was determined by fitting the simulation results to the experimental data, and correlations to the flame equivalence ratio and oxidation rate ratio were obtained respectively.