Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/85250
Title: Statistical analysis of fine particle resuspension from rough surfaces by turbulent flows
Authors: You, Siming
Wan, Man Pun
Keywords: Fine Particles
DRNTU::Engineering::Mechanical engineering
Stochastic Analysis
Issue Date: 2017
Source: You, S., & Wan, M. P. (2017). Statistical analysis of fine particle resuspension from rough surfaces by turbulent flows. Aerosol and Air Quality Research, 17(4), 843-856. doi:10.4209/aaqr.2016.03.0106
Series/Report no.: Aerosol and Air Quality Research
Abstract: Particle resuspension plays a part in indoor aerosol dynamics and has received increasing attention due to its ability to prolong human exposure to airborne particles. A stochastic model of turbulence-induced particle resuspension from rough surfaces is proposed based on the statistical nature of the process. Deposited fine (micro- or nano-size) particles are generally immersed in the viscous sublayer of the incompressible turbulent boundary layer and are subjected to aerodynamic forces that can be approximated by log-normal distributions due to penetration of turbulent inrushes and bursts into the viscous sublayer. Similarly, the adhesion force between particles and surfaces could be approximated by statistical distributions according to the statistical nature of surface roughness. Three common types of adhesion force distributions, i.e. log-normal, Weibull, and Gaussian distributions, are specifically explored. Predicted resuspension fractions versus free stream velocity are in good agreement with experimental data reported in the literature. Using the proposed stochastic model, influences of various parameters (composite Young’s modulus, surface energy, adhesion force distribution, velocity distribution, fluid density, and particle diameter) on the threshold friction velocity (u*50) and friction velocity divergence (Δu*) are analysed. The information sheds light onto the controlling of the particle resuspension process. The proposed model extends the current capability of modeling particle resuspension by considering different types of adhesion force distributions.
URI: https://hdl.handle.net/10356/85250
http://hdl.handle.net/10220/48186
ISSN: 1680-8584
DOI: 10.4209/aaqr.2016.03.0106
Rights: © 2017 Taiwan Association for Aerosol Research. All rights reserved. This paper was published in Aerosol and Air Quality Research and is made available with permission of Taiwan Association for Aerosol Research.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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