3D meso-scale modeling of reinforcement concrete with high volume fraction of randomly distributed aggregates

Abstract

An effective numerical method is proposed in this paper to generate a meso-scale composite model of reinforcement concrete (RC) which contains aggregates with random size and shape based on Voronoi tessellation method. Besides the randomly distributed aggregates, the present model takes into account the reinforcement, compared with other conventional methods in finite element modeling of concrete. The shrinking algorithm with random shrinking factors is employed to generate graded aggregates. A simple and effective intersection detection is used for aggregate-reinforcement to prevent the aggregates from overlapping with preset reinforcements, but it is unnecessary for aggregate-aggregate due to the characteristic of Voronoi technique. The artificial layer with random offset distance is adopted to simulate the minimum gap between two adjacent aggregates, and the high-volume fraction model is obtained by the sinking process. In order to verify the reliability of the RC model, the numerical results of penetration are compared with the referenced experimental data, and good agreements are obtained. It is indicated that the proposed model can simulate and explain qualitatively the effects of the meso-scale structural properties on the macroscopic dynamic response of RC. Furthermore, this method has great significance in performance analysis, structural optimization and material design for RC composites.