In this paper, the mechanical behaviour and failure of porous additively manufactured (AM) polylactide (PLA) scaffolds based on the triply periodic minimal surfaces (TPMS) is investigated using numerical calculations of their unit cells and representative volumes. The strain-amplification factor is chosen as the main parameter, and the most critical locations for failure of different types of scaffold structures are evaluated. The results obtained are presented in comparison with a multiple-crack-growth algorithm using the extended finite element method (XFEM), underpinned by the experimentally obtained fracture properties of PLA. The effect of morphology of TPMS structures on the pre-critical, critical and post-critical behaviours of scaffolds under monotonic loading regimes is assessed. The results provide an understanding of the fracture behaviour and main risk points for crack initiation in structures of AM-PLA scaffolds based on typical commonly used types of TPMS, as well as the influence of structure type and external load on this behaviour.

Generative adversarial neural networks with a variational autoencoder (VAE-GANs) are actively used in the field of materials design. The synthesis of random structures with nonrepeated geometry and predetermined mechanical properties is important for solving various practical problems. Geometric parameters of such artificially generated random structures can vary within certain limits compared to the training dataset, causing unpredicted fluctuations in their resulting mechanical response. This study investigates the statistical variability of mechanical and morphological characteristics of random 3D models reconstructed from 2D images using a VAE-GAN neural network. A combined multitool method employing different mathematical and statistical instruments for comparison of the reconstructed models with their corresponding originals is proposed. It includes the analysis of statistical distributions of elastic properties, morphometric parameters, and stress values. The neural network was trained on two datasets, containing models created based on Gaussian random fields. Statistical fluctuations of the mechanical and morphological parameters of the reconstructed models are analyzed. The deviation of the effective elastic modulus of the reconstructed models from that of the original ones was less than 5.7% on average. The difference between the median values of ligament thickness and distance between ligaments ranged from 3.6 to 6.5% and 2.6 to 5.2%, respectively. The median value of the surface area of the reconstructed geometries was 4.6–8.1% higher compared to the original models. It is thus shown that mechanical properties of the NN-generated structures retain the statistical variability of the corresponding originals, while the variability of the morphology is highly affected by the training set and does not depend on the configuration of the input 2D image.

This study investigates strategies to enhance the structural integrity of 3D-printed orthopedic transtibial exoskeleton sockets by integrating non-planar reinforcement with structured prepreg rods composed of continuous carbon fibers, leveraging multi-axis additive manufacturing techniques. A prototype of a cylindrical polyamide 3D-printed exoskeleton socket is examined. Numerical modeling using progressive failure analysis, incorporating material property degradation models, successfully simulated damage accumulation in the studied 3D-printed structures. Numerical simulations revealed that crack formation initiates in the socket’s distal section, aligning with physical test observations. Targeted localized reinforcement with carbon rods effectively strengthened the high-load regions of the prosthetic devices. A method to improve product strength by optimization of the internal architecture of the embedded reinforcements in the local stress concentrator zones is proposed. The results demonstrate a reduction in stress concentrations within prostheses when using carbon fiber reinforcements. Multi-axis dual extrusion non-planar additive manufacturing techniques were used to produce the developed prototypes. Surface morphology was examined, and optimal process parameters were determined to enhance printing quality. The developed approach enables precise reinforcement of custom-shaped sockets with complex geometries.

In this work, representative volume elements (RVEs) of composites, consisting of nanoporous gold and polymer, were investigated. Gold is of great interest as a special case of nanoporous metals as it deforms to large plastic strains when compressed, whereas normally nanomaterials allow only small deformations. The nanocomposite is modeled as a nanoporous monocrystal filled with a polymer. Different models of the phase behavior of nanoporous metal composites with the addition of a polymer component were studied. Three models of the mechanical behavior of gold were implemented: elasticity, elastic-plasticity, and the model of fracture with the degradation of properties. Three types of polymers were considered: polypyrrole (PPy), epoxy resin, and polyaniline (PANI), for which elasticity and elastic-plasticity models were implemented. The effect of the morphology of the nanocomposite on their mechanical response was numerically investigated using finite element analysis.

This paper uses finite element analysis to investigate the mechanical behavior of elementary representative volumes of porous bone tissue structures and their artificial substitutes. New results have been obtained from numerical modelling of the mechanical behavior and failure of three-dimensional geometric models of trabecular bone microstructure and bone implant models based on random two-dimensional structures. The structure of the implants was selected according to the morphometric parameters of trabecular bone structures to ensure a similar volume fraction of pores, thickness of the interconnected lattice of solid material, and internal surface area. The properties of bone tissue and biocompatible polylactide PLA were selected as the properties of the solid phase material of the structures. The present study of the obtained scaffold structures did not always show their satisfactory correspondence with the original trabecular structures in terms of mechanical behavior. Auxiliary problems, such as determining the required volume fraction of pores in the scaffold structure made of PLA polylactide material to resemble the effective elastic properties of the reference trabecular bone structure and calculating the elastic modulus of the solid phase material of the scaffold structure have been solved. In the future, the problem of creating an optimal bone scaffold structure can be solved by optimizing morphometric parameters in conjunction with the selection or modification of a biocompatible polymer material used in additive manufacturing. The practical significance of this approach lies in the possibility of subsequent manufacture of personalized biomedical devices for the treatment of bone tissue diseases, adapted to a specific patient.

In this study, methods for enhancing the structural strength of conical orthopedic transtibial exoprosthetic sockets are investigated through the implementation of non-planar reinforcement using structured rods made of continuous carbon fiber. Numerical modeling based on progressive failure analysis according to an instantaneous damage law, incorporating material property degradation models, effectively demonstrated the damage accumulation process in the examined structures.