Predicting porosity of binary mixtures made out of irregular nonspherical particles: Application to natural sediments

• Published in: Advanced powder technology : the international journal of the Society of Powder Technology, Japan Vol. 30; no. 8; pp. 1558 - 1566
• Main Authors: El-Husseiny, Ammar, Vanorio, Tiziana, Mavko, Gary
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-08-2019
• Subjects: Binary mixtures; Packing theory; Particle size and shape; Porosity; Porosity; Packing theory; Binary mixtures; Particle size and shape
• ISSN: 0921-8831; 1568-5527
• DOI: 10.1016/j.apt.2019.05.001

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•An analytical model is developed to predict porosity of binary mixtures.•The effect of both particle size and shape on packing is incorporated into the model.•Porosity is expressed as function of end-members’ porosity and specific surface area.•The model is validated using published data for natural sediments.
Predicting porosity or packing density of sediments made of coarse and fine components of arbitrary geometry is critical to many science and engineering applications. Well-established analytical models for packing of spheres express porosity of the binary mixture as a function of fine-to-coarse particle size ratio. Nevertheless, the applicability of such models to natural granular materials is limited given the nonspherical and irregular nature of the particles whose packing depends on both particle size and shape. The objective of this study is to develop a model that predicts the porosity of binary mixtures made up of irregular nonspherical particles. We modified a previously developed linear sphere-packing model so that it takes into account the effect of both the particle size and shape. As an input, the modified model uses the coarse-to-fine particles specific surface area ratio instead of using the particle size ratio required by the sphere-packing model. We tested the modified model by predicting the porosities of a binary mixture composed of coarse and fine calcite aggregates. We further validate the model by using published data on the porosity of binary mixtures made of synthesized, cubical and cylindrical particles. Our model predictions show good agreement with the measured porosity.