Characterization of packing structures

Particle size distributions often produce denser packing structures because smaller particles may fill void spaces between larger ones. Based on this assumption several researchers have described densest packings. Table 6 shows porosities that can be obtained with binary or ternary particle mixtures (i.e. consisting of two or three particle sizes). Recently, a geometrical mathematical model for calculating the porosity of randomly packed binary mixtures of spherical particles has been developed. It could be shown that the absolute deviation between theoretical and experimentally obtained data 

For particle size distributions of any type the optimal (i.e. densest) packing is obtained if it becomes random. A random packing of particles is characterized by the condition that the structure of an arbitrary volume element must not be different from that of any other volume element. Therefore, a sufficiently large volume element of a random packing features homogeneous structure and, respectively, constant porosity. 

Debbas determined the distribution of the volume porosity of packings by saturating the pores with a filler material that hardens without shrinkage. The solid sample was then machined step by step in a lathe. The porosity of the concentric volume elements was calculated from the volume and weight of each portion thus removed and the densities of particles as well as filler material. Debbas found that it is easier to produce random packings by vibration with wide particle size distributions than with narrower ones it was most difficult with monosized particles. 

The assumption that the liquid does not penetrate into the porous agglomerate yields Kl= Kaggi and A =A/l. Thus  

Agglomerates often contain moisture. If this is the case they must be dried prior to determination of the solid mass and density. The solid mass of a dry agglomerate is 

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