Statistical simulation of particle deposition on the wall from turbulent dispersed pipe flow

Citation
Ea. Matida et al., Statistical simulation of particle deposition on the wall from turbulent dispersed pipe flow, INT J HEA F, 21(4), 2000, pp. 389-402
Citations number
37
Categorie Soggetti
Mechanical Engineering
Journal title
INTERNATIONAL JOURNAL OF HEAT AND FLUID FLOW
ISSN journal
0142727X → ACNP
Volume
21
Issue
4
Year of publication
2000
Pages
389 - 402
Database
ISI
SICI code
0142-727X(200008)21:4<389:SSOPDO>2.0.ZU;2-D
Abstract
Deposition of particles towards the wall from a turbulent dispersed flow in a vertical pipe has been studied numerically. A fully developed turbulent pipe flow of air is chosen as the primary flow, and it is represented by th e law-of-the-wall relations and the average turbulence statistics obtained from a direct numerical simulation reported in the literature. Trajectories and velocities of the particles are calculated, using a one-way coupling L agrangian eddy-particle interaction model. Thousands of individual particle s (typically 930 kg/m(3) in density) of various diameters (2.0-68.5 mu m) a re released in the represented flow, and deposition velocities are evaluate d. It is shown that the deposition velocities predicted are in good agreeme nt with experimental data available in the literature. The influence of som e forces in the particle equation of motion (i.e., the Saffman lift force, the centrifugal force, the conservation of angular momentum and the buoyanc y force) on the prediction of the deposition velocities is examined. Also e xamined is the influence of the inlet particle concentration profile. on wh ich little attention has been paid so far. The unique phenomenon of 'near-w all build-up' of small particles, which has been reported in some previous simulations and experiments, was also observed in the present simulation wh ile the result for very small particles (tau(p)(+) < 3) should be accepted with reservation due to their possible spurious build-up associated with th e random-walk approach. (C) 2000 Elsevier Science Inc. All rights reserved.