Statistics – Computation
Scientific paper
Mar 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009jcoph.228.1541m&link_type=abstract
Journal of Computational Physics, Volume 228, Issue 5, p. 1541-1561.
Statistics
Computation
4
Scientific paper
A multiple-time step computational approach is presented for efficient discrete-element modeling of aerosol flows containing adhesive solid particles. Adhesive aerosol particulates are found in numerous dust and smoke contamination problems, including smoke particle transport in the lungs, particle clogging of heat exchangers in construction vehicles, industrial nanoparticle transport and filtration systems, and dust fouling of electronic systems and MEMS components. Dust fouling of equipment is of particular concern for potential human occupation on dusty planets, such as Mars. The discrete-element method presented in this paper can be used for prediction of aggregate structure and breakup, for prediction of the effect of aggregate formation on the bulk fluid flow, and for prediction of the effects of small-scale flow features (e.g., due to surface roughness or MEMS patterning) on the aggregate formation. After presentation of the overall computational structure, the forces and torques acting on the particles resulting from fluid motion, particle-particle collision, and adhesion under van der Waals forces are reviewed. The effect of various parameters of normal collision and adhesion of two particles are examined in detail. The method is then used to examine aggregate formation and particle clogging in pipe and channel flow.
No associations
LandOfFree
Discrete-element modeling of particulate aerosol flows does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Discrete-element modeling of particulate aerosol flows, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Discrete-element modeling of particulate aerosol flows will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1264280