Gaussian filtering method of evaluating the elastic/elasto-plastic properties of sintered nanocomposites with quasi-continuous volume distribution

In this work, combing the Gaussian filtering algorithm and the cutting quantile functions, a new technique is developed to efficiently generate the RVE of randomly distributed metal matrix nanocomposites (MMNCs) with quasi-continuous volume distribution. The procedures of filtering the random point matrix, generating the random field, separating the spatial points into constituents, and imposing the periodic boundary conditions are numerically implemented in detail. By contrasting the elastic/elasto-plastic properties of the sintered AgNPs composites with those determined by experimental measurements and analytical models, the proposed numerical homogenization model is verified. The results show that the proposed algorithm can control the distributions of the reinforcement size and the matrix volume fractions by tailoring the Gaussian widths and cutting levels. Meanwhile, the ratio of the Gaussian widths to the RVE length σ/L make influences on the resulting elastic/elasto-plastic properties of the MMNCs, and for the sintered AgNPs composites, σ/L = 2.5 is the critical value of its convergence. Additionally, the proposed method can be also extended to predict the other physical properties of MMNCs including conduction and diffusion.