Modeling Filtering Process Using Stochastic Simulations of Monte-Carlo Type

Filtration media have improved over the years to address a multitude of problems but continue to lose efficiency over a period of time due to membrane fouling which occurs even when the pores are much larger than the suspended particles via particle deposition on the pore interior walls. The focus of this research is to develop specifications for the optimal pore shape in the membrane media that maximize the filter lifetime, or the time at which pores of the membrane close fully, while ensuring adequate removal of impurities. For this purpose, we have developed stochastic simulations of Monte-Carlo type to simulate fouling and to study the effect of various parameters on the performance of the pore. We focus particularly on the probabilities of particles sticking to each other and to the pore walls, as well as on the influence of a cross-flow. Our model is used to investigate the performance of a membrane given multiple pores positioned next to each other. In this model, the parameters studied included the strength of the cross-flow along with the pore size variation, both in the depth of the membrane and in the direction of the cross-flow. We use our results to draw conclusions about optimal filtration scenarios.