Computational Homogenization of Concrete in the Cyber Size-Resolution-Discretization (SRD) Parameter Space

TL;DR

This paper introduces a systematic approach to reduce computational complexity in 3D concrete microstructure analysis by balancing specimen size, resolution, and discretization within the SRD parameter space, ensuring controlled accuracy.

Contribution

It proposes a novel SRD parameter space framework for optimizing computational homogenization of concrete microstructures with validated accuracy measures.

Findings

Reduced computational complexity while maintaining accuracy in elastic deformation analysis.

Systematic exploration of SRD space for transferability from 2D to 3D structures.

Framework applicable to various heterogeneous materials beyond concrete.

Abstract

Micro- and mesostructures of multiphase materials obtained from tomography and image acquisition are an ever more important database for simulation analyses. Huge data sets for reconstructed 3d volumes typically as voxel grids call for criteria and measures to find an affordable balance of accuracy and efficiency. The present work shows for a 3d mesostructure of concrete in the elastic deformation range, how the computational complexity in analyses of numerical homogenization can be reduced at controlled errors. Reduction is systematically applied to specimen size S, resolution R, and discretization D, which span the newly introduced SRD parameter space. Key indicators for accuracy are (i) the phase fractions, (ii) the homogenized elasticity tensor, (iii) its invariance with respect to the applied boundary conditions and (iv) the total error as well as spatial error distributions, which are computed and estimated. Pre-analyses in the 2d SRD parameter sub-space explore the transferability to the 3d case. Beyond the concrete specimen undergoing elastic deformations in the present work, the proposed concept enables accuracy-efficiency balances for various classes of heterogeneous materials in different deformation regimes and thus contributes to build comprehensive digital twins of materials with validated attributes.