On the Mutual Effect of the Turbulent Dispersion Model and Thermophoresis on Nanoparticle Deposition

Abstract

Abstract Nanoparticles applications, whether for pharmaceuticals, for environmental assessment or for evaluation of global climatic has led to the use of CFD tools to improve the understanding of their dynamical behaviour (transport, deposition and coagulation). Due to small particle sizes and low Stokes numbers, nanoparticles are typically considered to deposit at the wall as a combined result of Brownian motion and turbulent dispersion. To simulate these mechanisms in this work, the two-phase flow is computed using a RANS model (Reynolds Averaged Navier-Stokes) for the mean fluid properties, and a Lagrangian tracking approach for the dispersed phase in which the fluctuating fluid velocity at particle location, that ensures the particle turbulent dispersion, is predicted through a user implemented Langevin-based dispersion model. When a temperature gradient is present, the aerosol particles experience a thermophoretic force in addition to the drag and the Brownian forces. Depending on the temperature gradient and particle size, the thermophoretic force could become the predominant deposition mechanism. This size dependence makes it important to appropriately choose the turbulent dispersion model in wall-bounded turbulent flows. Actually, in most commercial codes, the turbulent dispersion of particles is predicted using the so-called Eddy Interaction Model (EIM), whose major drawback is that it cannot account for turbulence non-homogeneity, thus leading to some unphysical accumulation of low-inertia particles near the wall and therefore to an overestimation of the deposition velocity which is accentuated by thermophoresis. This study shows that turbulent and thermophoretic depositions are not completely independent, since thermophoresis enhances the deposition of particles which are sensitive to the turbulent dispersion model.