Network simulation for deep bed filtration of Brownian particles

Abstract

The effect of different interaction energy curves of DLVO theory on the permeability reduction in a filter bed is investigated by using the Brownian dynamics simulation method and the modified square network model to track the individual particles movement through the filter bed. When energy barrier exists and both particle and pore size distributions are of the Raleigh type, it is found that particles with Brownian motion behavior are easier to get straining at small pores, and cause higher permeability reduction than those without considering the Brownian motion behavior. But, this result was not observed for the constant particle and pore sizes case. The permeability reduction for the Raleigh size distribution is higher than that of the constant size. Similar results are also obtained for the “barrierless” type interaction energy curve for the case of Raleigh type size distribution, with the exception that the decreasing rate of permeability reduction of Brownian particles is smaller than that without considering the Brownian motion behavior. When comparing with the permeability reduction experimental data, it is found that the present model shows fair agreement between the theory and the experimental results when the direct deposition mechanism is dominant.