Self-diffusion in unbounded rapid granular flows: a nonequilibrium approach
Payman Jalali,
, William Polashenski,
Piroz Zamankhan and
Pertti Sarkomaa
Physica A: Statistical Mechanics and its Applications, 2000, vol. 275, issue 3, 347-360
Abstract:
Using a nonequilibrium simulation scheme, the transverse diffusive motion has been investigated in unbounded shear flows of smooth, monodisperse, inelastic spherical particles. This scheme is used to obtain the concentration gradient due to the particle mass flux, which is extracted from the bulk flow using a certain labeling algorithm. The self-diffusion coefficient can then be obtained from Fick's law. Under steady conditions, the simulation results show that the particle diffusivity can be described by a linear law. This finding provides a justification for assuming a linear law relationship in the kinetic theory type derivation of an expression for self-diffusivity. Moreover, the values of self-diffusion coefficient from the computer simulations agree with those obtained using kinetic theory formulations for solid volume fractions less than 0.5.
Date: 2000
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437199003817
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:275:y:2000:i:3:p:347-360
DOI: 10.1016/S0378-4371(99)00381-7
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().