Ln. Smith et Ps. Midha, COMPUTER-SIMULATION OF MORPHOLOGY AND PACKING BEHAVIOR OF IRREGULAR PARTICLES, FOR PREDICTING APPARENT POWDER DENSITIES, Computational materials science, 7(4), 1997, pp. 377-383
This paper describes a methodology for prediction of powder packing de
nsities which employs a new approach, designated as random sphere cons
truction (RSC), for modelling the shape of irregular particles such as
those produced by water atomization of iron. The approach involves mo
delling an irregular particle as a sphere which incorporates smaller c
orner spheres located randomly at its surface. The RSC modelling techn
ique has been combined with a previously developed particle packing al
gorithm (the random build algorithm), to provide a computer simulation
of irregular particle packings. Analysis of the simulation output dat
a has allowed relationships to be established between the particle mod
elling parameters employed by the RSC algorithm, and the density of th
e simulated packings. One such parameter is eta, which is the number o
f corner spheres per particle. A relationship was established between
eta (which was found to have a profound influence on packing density),
and the fractional density of the packing, fd. Vision system techniqu
es were used to measure the irregularity of the simulated particles, a
nd this was also related to eta. These two relationships were then com
bined to provide a plot of fractional density for a simulated packing
against irregularity of the simulated particles. A comparison was made
of these simulated packing densities and observed particle packing de
nsities for irregular particles, and a correlation coefficient of 0.96
was obtained. This relatively good correlation indicates that the mod
els developed are able to realistically simulate packing densities for
irregular particles, There are a considerable number of potential app
lications for such a model in powder metallurgy (PM), process control,
In combination with on-line particle image analysis, the model could
be used to automatically predict powder densities from particle morpho
logy.