A microstructure-guided constitutive modeling approach for random heterogeneous materials: Application to structural binders

Abstract

This paper presents a microstructure-guided modeling approach to predict the effective elastic response of heterogeneous materials, and demonstrates its application towards two highly heterogeneous, unconventional structural binders, i.e., iron carbonate and fly ash geopolymer. Microstructural information from synchrotron x-ray tomography (XRT) and intrinsic elastic properties of component solid phases from statistical nanoindentation are used as the primary inputs. The virtual periodic 3D microstructure reconstructed using XRT, along with periodic boundary conditions is used as a basis for strain-controlled numerical simulation scheme in the linear elastic range to predict the elastic modulus as well as the stresses in the microstructural phases. The elastic modulus of the composite material predicted from the microstructure-based constitutive modeling approach correlates very well with experimental measurements for both the materials considered. This technique efficiently links the microstructure to mechanical properties of interest and helps develop material design guidelines for novel heterogeneous composites.

Microstructure-guided numerical simulations to predict the thermal performance of a hierarchical cement-based composite material

“…The formulations of particle growth rate, velocity of particles in the bounding box, and updating of the particle positions that are integral to the microstructure generation procedure, are extensively described in [20,[36][37][38][39]. The microstructural information thus obtained is implemented through a Python language script to enable it to be imported to a FE software such as ABAQUS TM .…”

“…The effective properties of hierarchical materials have been predicted using analytical schemes such as the Mori-Tanaka method [9][10][11], double inclusion method [11][12][13][14], and self-consistent schemes [15][16][17]. While popular because of their simplicity, these techniques are not adequately accurate when large contrast in constituent properties exist, or the volume fractions of the dispersed components are very high [18][19][20]. Computational techniques generally overcome these drawbacks [20][21][22][23][24][25][26].…”

“…While popular because of their simplicity, these techniques are not adequately accurate when large contrast in constituent properties exist, or the volume fractions of the dispersed components are very high [18][19][20]. Computational techniques generally overcome these drawbacks [20][21][22][23][24][25][26].…”

Influence of microencapsulated phase change materials (PCMs) on the chloride ion diffusivity of concretes exposed to Freeze-thaw cycles: Insights from multiscale numerical simulations

“…Such boundary conditions are computationally efficient and therefore suited for faster convergence in smaller analysis domains. [38]. For thermal analyses, the continuity of temperature/ heat flux is ensured by PBC across the neighboring unit cells boundaries.…”

“…Sizes of the RVEs adopted for the three length scales are 0.035 mm (Step-I), 12.75 mm (step-II) and 69.375 mm (step-III) respectively, obtained based on a sensitivity study. The numerical homogenization procedure is explained in detail in our previous publications [38,39].…”