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In this study, a coarse-graining framework for discrete models is formulatedon the basis of multiscale homogenization. The discrete model considered inthis paper is the Lattice Discrete Particle Model (LDPM), which simulatesconcrete at the level of coarse aggregate pieces. In LDPM, the size of theaggregate particles follows the actual particle size distribution that is usedin experiment to produce concrete specimens. Consequently, modeling largestructural systems entirely with LDPM leads to a tremendous number of degreesof freedom and is not feasible with the currently available computationalresources. To overcome this limitation, this paper proposes the formulation ofa coarse-grained model obtained by (1) increasing the actual size of theparticles in the fine-scale model by a specific coarsening factor and (2)calibrating the parameters of the coarse grained model by best fitting themacroscopic, average response of the coarse grained model to the correspondingfine scale one for different loading conditions. A Representative VolumeElement (RVE) of LDPM is employed to obtain the macroscopic response of thefine scale and coarse grained models through a homogenization procedure.Accuracy and efficiency of the developed coarse graining method is verified bycomparing the response of fine scale and coarse grained simulations of severalreinforced concrete structural systems in terms of both accuracy of the resultsand computational cost.

Homogenization Coarse Graining (HCG) of the Lattice Discrete Particle Model (LDPM) for the Analysis of Reinforced Concrete Structures