Skeletonization-based beam finite element models for stochastic bicontinuous materials: Application to simulations of nanoporous gold

Abstract

An efficient representative volume element generation strategy is developed in modeling nanoporous materials. It uses periodic 3D beam finite element (FE) models derived from skeletonization of spinodal-like stochastic microstructures produced by a leveled random field. To mimic stiffening with agglomeration of the mass at junctions, an increased Young's modulus is assigned to the elements within the junction zone. The effective Young's modulus, Poisson's ratio, and universal anisotropy index are computed. A good agreement of the Young's modulus predictions with those obtained from experimental results for phase volume fractions 0.20 < phi(B) < 0.50 is observed. Moreover, the elastic anisotropy index of the generated beam networks shows sufficient proximity to isotropy. Finally, it is demonstrated that, as compared to the simulation statistics of voxel-FE models, for the beam-FE models over 500-fold computational acceleration with 250-fold less memory requirement is provided.