(379a) Generalizing the Relationship between Inter-Particle Forces and Bulk Unconfined Yield Strength of Poly-Disperse Powders
AIChE Annual Meeting
2007
2007 Annual Meeting
Particle Technology Forum
Solids Handling and Processing
Wednesday, November 7, 2007 - 8:30am to 8:50am
Abstract:
Adhesion between particles is the driving force that produces strength in bulk powders and granulate systems. Understanding the dynamics of this adhesion process, and the relationship between shear and particle assembly structure, provides the basis of predicting bulk yield strength from inter-particle forces. These forces and particle structure depend on the particle size distribution, local inter-particle pore distribution, and pore size. The number and size of these pore structures depends on the cohesion of the bulk. Fine particles may occupy the pore structure in poly-disperse systems. Shear or yield occurs between particles in the particle assembly pulling adjacent particles apart. However, shear zones in poly-disperse systems do not cause inter-particle motion between all particles within these pore structures. Instead, some particles within the pore structure simply translate with the surrounding larger matrix of particles. Modeling bulk strength then depends on the number of particles that pull apart during a shear event. Combining the inter-particle forces with models describing the structure of poly-disperse powders allows prediction of bulk yield strength for real engineered particulate systems. The advantage of this approach is the ability to predict yield strength based on particle scale properties such as particle size, moisture content, and surface energy that can be controlled through processing. It allows engineers to estimate bulk behavior without doing extensive flow property testing. The effect of changes in processing can then be used to estimate the change in cohesive flow properties and, hence, to predict process behavior. This paper presents a model combining capillary, fracture, and Van der Waals forces with particle packing models to predict bulk yield strength estimates.
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