Realistic soil particle generation based on limited morphological information by probability-based spherical harmonics

Abstract

Three-dimensional imaging techniques, such as X-ray computed tomography, have been used to scan realistic particle geometries. However, these techniques are labor intensive, time-consuming, and costly to obtain a large number of particles. Therefore, it is desirable if computers can be taught to generate realistic particles based on given morphological properties. This paper develops a particle generation technique by integrating spherical harmonics and probability functions. This technique only requires morphological information from one particle to generate a large number of particles and eliminates the need for scanning many particles for particle generation. The spherical harmonics coefficients of this particle are analog of the morphological gene. The probability function is used to add variances to spherical harmonics coefficients to simulate gene mutation. A dimensionless factor is developed to control degrees of gene mutation. The effectiveness and accuracy of the proposed technique are verified by particle shape descriptors computed by the computational geometry techniques.