Homogenization Coarse Graining (HCG) of the Lattice Discrete Particle Model (LDPM) for the Analysis of Reinforced Concrete Structures
Erol Lale, Roozbeh Rezakhani, Mohammed Alnaggar, Gianluca Cusatis

TL;DR
This paper introduces a multiscale homogenization-based coarse-graining framework for the Lattice Discrete Particle Model (LDPM) to enable efficient simulation of large reinforced concrete structures without significant loss of accuracy.
Contribution
It develops a novel coarse-grained LDPM by increasing particle size and calibrating parameters to match fine-scale responses, improving computational efficiency for structural analysis.
Findings
Coarse-grained LDPM accurately predicts structural responses.
Significant reduction in computational cost.
Validated on multiple reinforced concrete systems.
Abstract
In this study, a coarse-graining framework for discrete models is formulated on the basis of multiscale homogenization. The discrete model considered in this paper is the Lattice Discrete Particle Model (LDPM), which simulates concrete at the level of coarse aggregate pieces. In LDPM, the size of the aggregate particles follows the actual particle size distribution that is used in experiment to produce concrete specimens. Consequently, modeling large structural systems entirely with LDPM leads to a tremendous number of degrees of freedom and is not feasible with the currently available computational resources. To overcome this limitation, this paper proposes the formulation of a coarse-grained model obtained by (1) increasing the actual size of the particles in the fine-scale model by a specific coarsening factor and (2) calibrating the parameters of the coarse grained model by best…
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