Model for the combination of diffusional and inertial particle deposition on inverse surfaces at low pressure

Abstract

A model was developed to estimate particle contamination probabilities on inverse surfaces at low pressure for inertial and diffusional particle deposition under the influence of gravity, drag, and thermophoresis. The model shows that contamination probabilities strongly depend on particle size, initial velocity, and initial distance between particle and surface. While thermophoresis effectively protects the surface against deposition of particles with 10mm (or more) initial distance and velocities below 1m∕s, the contamination probability of particles with an initial distance of 0.1mm is very high for small particles due to their high diffusivity and for fast particles due to inertia.

Gaussian diffusion sphere model to predict mass transfer due to diffusional particle deposition on a flat surface in laminar flow regime

“…The probability of the particle to be located at a certain distance away from the initial particle position can be weighted by a Gaussian probability density function with the standard deviation of = x rms . 5 Asbach et al 6,7 estimated the probability of an inverted critical surface to be contaminated by a diffusing particle which is initially positioned at a certain distance away from the inverted surface in a quiescent air at low pressure by calculating the volume of a sphere, of which radius is 5x rms , overlapping with the critical surface. In the present study, the concept of Asbach et al 6,7 was adopted and improved to predict mass transfer in a flow parallel to a flat surface.…”

“…5 Asbach et al 6,7 estimated the probability of an inverted critical surface to be contaminated by a diffusing particle which is initially positioned at a certain distance away from the inverted surface in a quiescent air at low pressure by calculating the volume of a sphere, of which radius is 5x rms , overlapping with the critical surface. In the present study, the concept of Asbach et al 6,7 was adopted and improved to predict mass transfer in a flow parallel to a flat surface. Figure 1 shows a schematic for calculating the probability-weighted volume fraction of a sphere, named as the Gaussian diffusion sphere ͑GDS͒ in the present study, overlapping with a flat surface.…”

A seemingly universal particle kinetic distribution in porous media

“…Computational details, including the validation of the algorithm, are presented in SM, Secs. IV through VII [40][41][42][43][44][45][46][47][48] .…”