Dynamics of particle loading in deep-bed filter. Transport, deposition and reentrainment

Abstract

Deep bed filtration is an effective method of submicron and micron particle removal from the fluid stream. There is an extensive body of literature regarding particle deposition in filters, often using the classical continuum approach. However, the approach is not convenient for studying the influence of particle deposition on filter performance (filtration efficiency, pressure drop) when nonsteady state boundary conditions have to be introduced. For the purposes of this work the latticeBoltzmann model describes fluid dynamics, while the solid particle motion is modeled by the Brownian dynamics. For aggregates the effect of their structure on displacement is taken into account. The possibility of particles rebound from the surface of collector or reentrainment of deposits to fluid stream is calculated by energy balanced oscillatory model derived from adhesion theory. The results show the evolution of filtration efficiency and pressure drop of filters with different internal structure described by the size of pores. The size of resuspended aggregates and volume distribution of deposits in filter were also analyzed. The model enables prediction of dynamic filter behavior. It can be a very useful tool for designing filter structures which optimize maximum lifetime with the acceptable values of filtration efficiency and pressure drop.

Eulerian Lagrangian Simulation of Particle Capture and Dendrite Formation on Binary Fibers

“…Furthermore, the necessary condition for recalculation of the flow filed was that the total volume of deposited particles to be close to 5 % of the fiber volume [18]. Rafał Przekop and Leon Gradoń [19] modeled the deep bed filtration considering the effect of particle growth on the filter structure and flow field. Their model was able to predict the dynamic filter behavior during instantaneous particle loading.…”