Effects of particle clustering on the tensile properties and failure mechanisms of hollow spheres filled syntactic foams: A numerical investigation by microstructure based modeling

Particle clustering originated from manufacturing process is thought to be one of the critical factors to the mechanical performance of hollow spheres filled syntactic foams. Although experimental evidence provides a qualitative understanding of the effects of particle clustering on the mechanical properties of syntactic foams, a quantitative assessment cannot be made in the absence of an appropriate micromechanical modeling strategy. In this study, three-dimensional microstructures of syntactic foams with different degrees of particle clustering were reconstructed based on random sequential adsorption (RSA) method. Three-phase finite element models considering the progressive damage behavior of the microsphere–matrix interface were accordingly developed by means of representative volume element (RVE) to quantitatively investigate the effects of particle clustering on the tensile properties and failure mechanisms of syntactic foams. The simulation results indicate that the elastic behavior of syntactic foams is insensitive to the degree of particle clustering, but the strength properties as well as the failure mechanisms are significantly influenced by the degree of particle clustering. From the micromechanical viewpoint, the clustered regions containing higher concentration of microspheres than the average volume fraction would serve as crack initiation sites due to stress concentration, and consequently lead to a negative effect on tensile strength, fracture strain, and interfacial damage of syntactic foams.

► An algorithm was proposed to reconstruct microstructures with particle clustering. ► Three-phase FE model considering interface effect was developed. ► Effects of particle clustering on tensile properties were quantitatively investigated. ► The simulation results interpret the entire failure process from damage to fracture. ► The modeling strategy enables an estimation of clustering degree in real materials.