Architected piezoelectric composites (PCs) have recently gained interest in designing transducers and nondestructive testing devices. The current analytical modeling approach cannot be readily applied to design architected periodic PCs exhibiting elastic anisotropy and piezoelectric activity. This study presents a micromechanical (MM)-model based finite element (FE) modeling framework to predict the electromechanical properties (EMPs) of the architected PCs. As an example, the microstructure with one-dimensional (1–3 PCs) connectivity is considered with different cross-sections of fibers. 3D FE models are developed. The intrinsic symmetry of architected composite is used to derive boundary conditions (BCs) equivalent to periodic BCs (PBCs). The proposed approach is simple and eliminates the need for a tedious mesh generation process on opposite boundary faces on the MM model of architected PCs. The EMPs of 1–3 PCs calculated from the proposed micromechanics-FE models were compared with those obtained from analytical solutions (i.e. based on micromechanics theories), and FE homogenization (i.e. obtained by employing the PBCs available in the literature). A quite good agreement between the proposed modeling approach and the ones obtained using the analytical model was observed. However, an excellent agreement is observed with the MM results that employed PBCs. Hence, we have concluded that the proposed MM modeling approach is equivalent to MM models that employed PBCs. The computed enhanced effective elastic, piezoelectric, and dielectric properties and corresponding figure of merit revealed that 1–3 PCs are suitable in transducer applications.

Highly conductive composites have found applications in thermal management, and the effective thermal conductivity plays a vital role in understanding the thermo-mechanical behavior of advanced composites. Experimental studies show that when highly conductive inclusions embedded in a polymeric matrix the particle forms conductive chain that drastically increase the effective thermal conductivity of two-phase particulate composites. In this study, we introduce a random network three dimensional (3D) percolation model which closely represent the experimentally observed scenario of the formation of the conductive chain by spherical particles. The prediction of the effective thermal conductivity obtained from percolation models is compared with the conventional micromechanical models of particulate composites having the cubical arrangement, the hexagonal arrangement and the random distribution of the spheres. In addition to that, the capabilities of predicting the effective thermal conductivity of a composite by different analytical models, micromechanical models, and, numerical models are also discussed and compared with the experimental data available in the literature. The results showed that random network percolation models give reasonable estimates of the effective thermal conductivity of the highly conductive particulate composites only in some cases. It is found that the developed percolation models perfectly represent the case of conduction through a composite containing randomly suspended interacting spheres and yield effective thermal conductivity results close to Jeffery's model. It is concluded that a more refined random network percolation model with the directional conductive chain of spheres should be developed to predict the effective thermal conductivity of advanced composites containing highly conductive inclusions.