A novel method for generation of particle packing model used in numerical simulation for the mechanical behavior of multi-component material. (April 2022)

• Record Type: Journal Article
• Authors: Ding, Yang; Lu, Qiang; Lu, Fangyun; Zhang, Xiangrong
• Is Part Of: Materials & design. Volume 216(2022)
• Publication Date: 2022-04
• Subjects: Particle reinforced composites -- Divide and fill -- Particle packing -- Affine transformation -- Voronoi tessellation; Materials -- Periodicals; Engineering design -- Periodicals; Matériaux -- Périodiques; Conception technique -- Périodiques; Electronic journals; 620.11
• DOI: 10.1016/j.matdes.2022.110554
• Languages: English
• ISSNs: 0264-1275

Abstract

Graphical abstract: Highlights: The particle size distributions include continuous gradation, discontinuous gradation and mixture of coarse and fine with large size ratio. Classical Voronoi, weighted Voronoi and two-scale Voronoi algorithms are used to build models with different particle size distributions. A Repulsion-Displacement method is proposed for the generation of discontinuous gradation particles. Abstract: This study presents a novel algorithm to establish a numerical model for the study of mechanical behavior of multi-component material such as particle reinforced metal matrix composites, concrete, particle filled polymers, etc. The algorithm consists of two steps, one is to divide the given region into sub-regions of a specified size distribution, and the other is to fill each sub-region with particles of specified shapes. During the filling process, the contact states between particles can be controlled by the number and positions of reference points. Taking the quasi-static uniaxial tensile simulation of concrete as a verification example, two concrete models with the same particle size distribution but different shapes have been established. Through the comparison of elastoplastic responses of different aggregate shape models in different tensile directions, it is concluded that the models meet the requirements of macroscopic uniformity, meso -scale randomness and statistical rationality. This verifies the feasibility of modeling method and its advantages in precise control of particle shape, distribution and other parameters.