A microstructure-guided numerical approach to evaluate strain sensing and damage detection ability of random heterogeneous self-sensing structural materials

Abstract

Heterogeneous self-sensing materials that respond electrically to mechanical strains enable real time health monitoring of structures. To facilitate design and applicability of such smart materials with piezo-resistivity, a finite element-based numerical framework is being proposed in this paper for evaluation of electro-mechanical response and strain-sensing ability. Intrinsic heterogeneous nature of such composites warrants the need for microstructure-based study to have an insight into the effect of microstructural configuration on the macro-scale response. The microstructure-guided simulation framework, presented in this paper, implements interfacial debonding at the matrix-inclusion interface using a coupled interface damage-cohesive zone model and incorporates an isotropic damage model in the matrix under applied strain in the post-peak regime to obtain the deformed/damaged microstructure which is subjected to an electrical potential to simulate change in resistance due to applied strain. The applicability of the simulation framework is confirmed through its successful implementation on a smart structural material containing nano-engineered conductive coating at the inclusion-matrix interfaces. The predicted electro-mechanical responses correspond very well with the experimental observations and thus, the model has the potential to help develop design strategies to tailor the microstructure in these self-sensing materials for efficient performance.

A Peridynamics-Based Micromechanical Modeling Approach for Random Heterogeneous Structural Materials

“…The material input properties required for formulations in Sections 2.3.1 and 2.3.2 are the bulk and shear moduli for defining the linear peridynamic solid and the critical energy release rate to initialize the damage criterion. The input Young's modulus for the cement paste matrix, sand and iron particulates are 20, 70 and 200 GPa respectively [29,58]. A constant Poisson's ratio of 0.2 is considered for all the materials except the iron particles since a range of 0.17-0.22 for the same yields insignificant changes in the results [59,60].…”

Dynamic compressive behavior of metallic particulate-reinforced cementitious composites: SHPB experiments and numerical simulations

“…A hard particle contact model is implemented and particle overlaps are restricted in this algorithm. The algorithm has been rigorously implemented in [25,[41][42][43][44] towards unit cell generation and adequately detailed in [39,40].…”

“…Periodic boundary conditions (PBC) [41,43,45] are applied on the meshed unit cells. A python script handles the meshing.…”

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

“…The forward Euler scheme is used to update the positions of the particles with a time step that is minimized with events of possible collisions between particles. Detailed formulations of the iterative process where particles change positions in the bounding box, collide and grow to achieve the desired volume fraction are mentioned elsewhere [37]. Periodic boundary conditions (PBC) [29][30][31][32] are applied to the generated unit cells.…”

“…Where is the diffusion coefficient of the damaged element and is the diffusion coefficient of a crack (implying damage state 1) and is the progressive damage variable. Such proportional intrinsic properties has been successfully assigned to degraded materials for electromechanical [37] and thermomechanical [67] analysis.…”