Solid waste shape description and generation based on spherical harmonics and probability density function

Abstract

Transport and separation processes of solid waste can only be modelled successfully with discrete element methods in case the shape of the particles can be described accurately. The existing techniques for morphological data acquisition, such as computed tomography, laser scanning technique, optical interferometer, stereo photography and structured light technique, are laborious and require a large amount of realistic solid waste samples. Therefore, there is a pressing need for an alternative method to describe the shape of solid waste particles and to generate multiple variations of particles with almost similar shapes. In this paper, a new method to describe solid waste particles is proposed that is frequency-based and uses spherical harmonics (SHs). Additionally, a new shape generation method is introduced that uses the shape description of a single particle to generate an array of related shapes based on a probability density function with a dimensionless control factor η. The newly proposed methods were successfully applied to describe the complex shapes of pieces of metal and plastic scrap. The shapes of these pieces of scrap can be described adequately with 15° of SH expansion and the overall divergence is within 0.1 mm. Five different values for η were tested, which generated shapes with the same distribution as the original particle. Rising levels of η cause the morphological variation of the generated particles to increase. These new methods improve the modelling of transportation and separation processes.

Effects of rock types and crushing mechanism on the 3D morphological parameters of manufactured sands: a combination study of 3D scanning and spherical harmonic analysis

“…In recent years, the development of methods such as 3D scanning and X-ray tomography have provided powerful tools for obtaining the 3D morphology of particles. (Li et al, 2022;Wu et al, 2022). These methods have shown very excellent accuracy in particle morphology characterization, especially when solving threedimensional problems.…”