Spherical harmonic-based random fields based on real particle 3-D data: Improved numerical algorithm and quantitative comparison to real particles

Published

October 23, 2010

Author(s)

Edward Garboczi, Sinan T. Erdogan, Yang Lu, Xuefeng Liu, Mircea Grigoriu

Abstract

The shape of particles often plays an important role in how they are used and in the properties of composite systems in which they are incorporated. When building models of systems that include real particles, it is often of interest to generate new, virtual particles whose three-dimensional (3-D) shape statistics are based on the 3-D shape statistics of a collection of real particles. A previous paper showed mathematically how this can be carried out, but only had a small set of real particle shape data to use and only made a limited amount of qualitative comparisons to the real particle data. The present paper shows how the numerical method used to create virtual particles has been improved and immensely accelerated, allowing the use of large particle data sets. Making use of several large particle shape data sets, the paper shows the effects of real particle number on the quality of the virtual particles generated by making quantitative comparisons to 3-D shape parameters. Several more real 3-D particle shape data sets are used to generate virtual particles that are compared to the real particles. The types of particles analyzed include two size ranges of crushed granite-hornblende rocks, silica sand, calcium carbonate powder, and ground granulated blast furnace slag.

Citation

Powder Technology

Volume

207

Pub Type

Journals

Download Paper

https://doi.org/10.1016/j.powtec.2010.10.012

Local Download

Keywords

particles, shape, virtual, statistics, three dimensional, rocks, sand, spherical harmonics

Citation

Garboczi, E. , Erdogan, S. , Lu, Y. , Liu, X. and Grigoriu, M. (2010), Spherical harmonic-based random fields based on real particle 3-D data: Improved numerical algorithm and quantitative comparison to real particles, Powder Technology, [online], https://doi.org/10.1016/j.powtec.2010.10.012, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=905390 (Accessed December 6, 2024)