Determining random packing density and equivalent packing size of superballs via binary mixtures with spheres. (20th July 2019)
- Record Type:
- Journal Article
- Title:
- Determining random packing density and equivalent packing size of superballs via binary mixtures with spheres. (20th July 2019)
- Main Title:
- Determining random packing density and equivalent packing size of superballs via binary mixtures with spheres
- Authors:
- Liu, Lufeng
Yuan, Ye
Deng, Wei
Li, Shuixiang - Abstract:
- Graphical abstract: Highlights: A new approach to determining the random packing densities via binary mixtures with spheres. We obtain the equivalent packing diameters of superballs. The random packing densities of superballs obtained are surprisingly close to those of the MDRPs. The linear fitting method can be used to verify the randomicity of non-spherical particle packings. Abstract: We propose a new approach to determining the random packing densities of superballs via binary mixtures with spheres. The main idea of the approach is to suppress order formations in non-spherical particle packings via the polydispersity of particle shapes, which avoids using order metrics. The packing density of superballs in a mixture can be segregated using a linear fitting method with the concept of equivalent packing size (or size ratio with unit spheres) which represents the effective size (or volume) of a non-spherical particle in a binary mixture with spheres. We systemically study the packing properties of binary mixtures consisting of spheres and superballs and obtain the equivalent packing sizes of superballs. Our results show that the equivalent packing size ratio always corresponds to the minimal packing density or specific volume (reciprocal of packing densities) variation, and is independent of the solid volume fraction. The specific volumes of mixtures with the equivalent packing size ratio are always the upper bound for all the solid volume fractions. The linear relationshipGraphical abstract: Highlights: A new approach to determining the random packing densities via binary mixtures with spheres. We obtain the equivalent packing diameters of superballs. The random packing densities of superballs obtained are surprisingly close to those of the MDRPs. The linear fitting method can be used to verify the randomicity of non-spherical particle packings. Abstract: We propose a new approach to determining the random packing densities of superballs via binary mixtures with spheres. The main idea of the approach is to suppress order formations in non-spherical particle packings via the polydispersity of particle shapes, which avoids using order metrics. The packing density of superballs in a mixture can be segregated using a linear fitting method with the concept of equivalent packing size (or size ratio with unit spheres) which represents the effective size (or volume) of a non-spherical particle in a binary mixture with spheres. We systemically study the packing properties of binary mixtures consisting of spheres and superballs and obtain the equivalent packing sizes of superballs. Our results show that the equivalent packing size ratio always corresponds to the minimal packing density or specific volume (reciprocal of packing densities) variation, and is independent of the solid volume fraction. The specific volumes of mixtures with the equivalent packing size ratio are always the upper bound for all the solid volume fractions. The linear relationship between the specific volume and solid volume fraction is only observed in the mixtures with superballs of small surface shape parameters (shapes close to a sphere), which results from the highly disordered nature in the mixtures. Moreover, the ideal random packing densities of mono-sized superballs obtained via the linear fitting method are surprisingly close to those of the MDRPs (maximally dense random packings), further verifying that the MDRPs of non-spherical particles correspond to the ideal random packings whose degrees of order are at the same level with that of the random close packing of spheres. Our work leads to a better understanding towards the random and binary packings and sheds new light on the essence of the MDRP. Our work also guides the optimal particle size distributions of powders in chemical engineering process. … (more)
- Is Part Of:
- Chemical engineering science. Volume 202(2019)
- Journal:
- Chemical engineering science
- Issue:
- Volume 202(2019)
- Issue Display:
- Volume 202, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 202
- Issue:
- 2019
- Issue Sort Value:
- 2019-0202-2019-0000
- Page Start:
- 270
- Page End:
- 281
- Publication Date:
- 2019-07-20
- Subjects:
- Superball -- Maximally dense random packing -- Binary mixture -- Equivalent packing size
Chemical engineering -- Periodicals
Génie chimique -- Périodiques
Chemical engineering
Periodicals
Electronic journals
660 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00092509 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ces.2019.03.041 ↗
- Languages:
- English
- ISSNs:
- 0009-2509
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3146.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9908.xml