A Stochastic Model for Particle Deposition in Turbulent Flows and Clogging Effects

Abstract

Particle deposition in turbulent flows is a phenomenon which can lead to fouling and affect normal operating conditions of key components of industrial processes. To explain the deposition mechanisms and predict the deposition rate, several models have been proposed in the literature. The model presented in this paper is based on a stochastic Lagrangian approach, where each particle is explicitly tracked, and where the velocity of the flow seen by particles is modeled by a stochastic process which depends on the mean fluid properties at particle locations. The interactions between particles and near-wall coherent structures are taken into account. Recent developments have shown that the model is not only able to reproduce single-particle deposition and resuspension but can also be applied to simulate the formation and the growth of multilayer deposits. Such deposits result from the competition between particle–fluid, particle–surface, and particle–particle interactions. Different morphologies of the deposit (monolayer, dendrites, multilayer) can exist according to the chemical properties of the particles and wall. A porous medium approach is used to take into account the effect of the deposit formed on the flow to obtain more realistic evolution.