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Research Papers: Multiphase Flows

Particle Resuspension in a Wall-Bounded Turbulent Flow

[+] Author and Article Information
S. C. Fu

e-mail: mescfu@ust.hk

C. Y. H. Chao, W. T. Leung

Department of Mechanical Engineering,
The Hong Kong University of Science and Technology,
Clear Water Bay,
Hong Kong, 852, PRC

R. M. C. So

Department of Mechanical Engineering,
The Hong Kong Polytechnic University,
Hung Hom, Hong Kong, 852, PRC

1Corresponding author.

Manuscript received November 4, 2012; final manuscript received February 1, 2013; published online March 26, 2013. Assoc. Editor: John Abraham.

J. Fluids Eng 135(4), 041301 (Mar 26, 2013) (9 pages) Paper No: FE-12-1553; doi: 10.1115/1.4023660 History: Received November 04, 2012; Revised February 01, 2013

Resuspension is of common occurrence in a wide range of industrial and environmental processes. Excessive resuspension in these processes could have a severe impact on human safety and health. Therefore, it is necessary to develop a practical, yet reasonably accurate model to describe the resuspension phenomenon. It has been identified that rolling is the dominant mechanism for particle resuspension in the presence of an air stream, be it laminar or turbulent. Existing models predict the resuspension rate by regarding particles as being resuspended once they are set in motion; only a few of these models attempt to describe the full scenario, including rolling motion and the effect of turbulence. The objective of this paper is to propose a stochastic model to simulate the resuspension rate in the presence of a near-wall turbulent stream, and where the rolling mechanism is assumed to dominate the resuspension process. The fluctuating part of the angular velocity of a rolling particle is modeled by the Langevin equation (i.e., an Ornstein–Uhlenbeck process); thus, the overall angular velocity is modeled as a diffusion process. A free parameter of the proposed resuspension model is determined using data obtained from a Monte Carlo (MC) simulation of the problem. Once determined, the parameter is found to be universal for different materials and different sizes of particles tested. The modeling results obtained using this parameter are found to be in good agreement with experimental data, and the model performs better compared to other models.

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References

Figures

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Fig. 2

Algorithm of the MC simulation

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Fig. 3

Comparison of resuspension measurements (×) of Ref. [11] with model calculations for nominal 10 μm alumina spheres

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Fig. 4

Comparison of resuspension measurements (×) of Ref. [11] with model calculations for nominal 20 μm alumina spheres

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Fig. 5

Comparison of resuspension measurements (×) of Ref. [11] with model calculations for nominal 10 μm graphite spheres

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Fig. 6

Friction velocity to obtain 50% fraction remaining plotted against different Δt

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Fig. 7

Comparison of the resuspension rates with the long time 1/t decay

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Fig. 8

Probability of a single 10 μm alumina particle approaching resuspension

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Fig. 9

Probability of a single 10 μm alumina rolling particle approaching rest again

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