Adhesion and detachment fluxes of micro-particles from a permeable wall under turbulent flow conditions

We report a numerical investigation of the deposition and re-entrainment of Brownian particles from a permeable plane wall. The tangential flow was turbulent. The suspension dynamics were obtained through direct numerical simulation of the Navier–Stokes equations coupled to the Lagrangian tracking of individual particles. Physical phenomena acting on the particles such as flow transport, adhesion, detachment and re-entrainment were considered. Brownian diffusion was accounted for in the trajectory computations by a stochastic model specifically adapted for use in the vicinity of the wall. Interactions between the particles and the wall such as adhesion forces and detachment were modeled. Validations of analytical solutions for simplified cases and comparisons with theoretical predictions are presented as well. Results are discussed focusing on the interplay between the distinct mechanisms occurring in the fouling of filtration devices. Particulate fluxes towards and away from the permeable wall are analyzed under different adhesion strengths

Modeling and simulation of inertial drop break-up in a turbulent pipe flow downstream of a restriction.

This work deals with the modeling of drop break-up in an inhomogeneous turbulent flow that develops downstream of a concentric restriction in a pipe. The proposed approach consists in coupling Euler–Lagrange simulations of the drop motion to an interface deformation model. First the turbulent flow downstream of the restriction is solved by means of direct numerical simulation. Single drop trajectories are then calculated from the instantaneous force balance acting on the drop within the turbulent field (one-way coupling). Concurrently, the interface deformation is computed assuming the drop to behave as a Rayleigh–Lamb type oscillator forced by the turbulent stress along its trajectory. Criterion for break-up is based upon a critical value of drop eformation. This model has been tested against experimental data. The flow conditions and fluids properties have been chosen to match those experimental investigations. Both turbulent flow statistics and break-up probability calculations are in good agreement with experimental data, strengthening the relevance of this approach for modeling break-up in complex unsteady flow

A model of fine particles deposition on smooth surfaces: II-comparison with experimental data and simplified models

The application of a model of fine particles initial deposition from a flowing suspension on smooth surfaces is discussed by comparison with literature experimental data and simplified models (Leveque equation). The model and its original features, including an accurate account of particle-surface interactions and ad hoc solution techniques, with special emphasis on the treatment of boundaries, have been thoroughly presented in Part I. The model demonstrates that in many circumstances diffusion is the limiting mechanism so that simple models based on a continuous approach (through particles concentration) together with perfect sink assumption are accurate enough. Departures from such circumstances are identified by means of a parametric study based on our model. The comparison with the experimental data also suggests additional characterizations needed for future experimental investigations. (c) 2007 Elsevier Ltd. All rights reserved

A model of fine particles deposition on smooth surfaces: I - Theoretical basis and model development

A model of fine particles deposition from a flowing suspension on smooth surfaces is developed. It is based on a common Eulerian-Lagrangian particle tracking approach, that allows a force-based description of the interactions between particles and surface. Hydrodynamics and particle-wall forces are included, with emphasis on a detailed account of Van der Waals forces. Diffusion has also been included and combined with the Lagrangian approach resulting in a stochastic process. Efficient and physically consistent techniques to solve the resulting stochastic differential equations are discussed, with specific algorithms to manage transition from small to extremely strong forcing function, and to precisely determine when and where particle trajectories reach the boundary. Quantitative evidences of the usefulness of techniques are shown. (c) 2006 Elsevier Ltd. All rights reserved