Iranian Journal of Chemical Engineering (IJChE)

Abstract In this work, a dynamic model has been developed for prediction of biofilters performance. The model includes most of the phenomena occurring in a biofilter. For biodegradation of pollutants in the biofilm, the Michaelis-Menten kinetic has been considered. The model equations including gas phase and biofilm partial differential equations were solved simultaneously using finite difference and method of lines. The model parameters were evaluated by sensitivity analysis to determine their respective effects on the model performance. The model predictions were validated by experimental data for mixture of methyl propyl ketone, toluene, p-Xylene and n-Butyl acetate. The simulation results of empty bed  residence times 30, 60, 90 seconds were compared with experimental data. The comparison of results showed the model
predictions had a good agreement with experimental data. The sensitivity analysis of the model parameters showed that Henry's constant and specific area of biofilter had the strongest influence on biofilter performance.

Abstract Prediction of particle removal efficiency in all kinds of dust collectors includes mathematical modeling of particle-laden flow. One of the main problems for such modeling is to find particle velocity distribution which can he predicted using a particle momentum balance equation. A common simple alternative is to use equilibrium or settling velocities. In this work, a comprehensive mathematical model for particle removal in double-stage electrostatic precipitators was developed. Analysing the results of this model shows that the equilibrium assumption can be considered as a reliable method for a Stokes number less than 0.001. Atm for a higher Stokes number, an explicit Eulerian method was developed for the evaluation of particle velocities explicitly. This method eliminates solving particle momentum balance equations which is a relatively time-consuming step in mathematical modeling of dust collectors.