Materials

This paper compares three nondestructive methods used to detect and locate defects such as delaminations or voids in externally bonded fiber reinforced polymer (FRP) concrete structures: infrared thermography, ground-penetrating radar, and measurement of acoustic wave velocity. One of the main goals was to check whether it was possible to distinguish overlapping defects. For this purpose, eight concrete samples were made with a bonded carbon fiber reinforced polymer (CFRP) strip with the following dimensions 100 × 100 × 500 mm. Two samples had no defects, four had single defects varying in location (at the edge of the strip or in the centre) simulating delamination or voids in the concrete cover, and the remaining samples had overlapping defects. Both infrared thermography and acoustic wave velocity measurement methods allow the detection of defects/voids in the adhesive layer and a concrete defect (void in the concrete cover). However, ground penetration failed to detect defects in the adhesive layer. Only infrared thermography allows for the differentiation of overlapping defects. On the basis of the conducted research, the methodology, differences, advantages, and limitations of each method were described, along with recommendations based on the authors’ experience.

Corrosion-induced cracking poses a significant threat to the longevity of reinforced concrete (RC) structures, yet precisely forecasting its advancement continues to be a considerable scientific obstacle. The principal shortcoming of current numerical models is their excessive simplification, frequently presuming totally saturated conditions and disregarding the dynamic interplay between environmental (hygro-thermal) variations and developing mesoscale damage. This study presents a thorough hygro-thermo-electro-chemo-mechanical (HTECM) phase-field model to fill this research need. The model uniquely combines dynamic unsaturated hygro-thermal transport with multi-ion reactive electrochemistry and meso-scale fracture mechanics. A rigorous comparison with published experimental data validates the model’s exceptional accuracy. The anticipated progression of fracture width exhibited remarkable concordance with experimental data, indicating a substantial enhancement in precision compared to uncoupled, saturated-state models. A key finding is the quantification of the damage-induced “transport-corrosion” positive feedback loop: initial corrosion-induced microcracks significantly expedite the transport of local moisture and corrosive agents, leading to nonlinear structural degradation. This work presents a high-fidelity numerical platform that enhances the understanding of linked deterioration in materials science and improves the durability design of reinforced concrete structures.

As the most commercially developed metal additive process, laser powder bed fusion (LPBF) is vital to advancing several industry sectors, enabling high-precision part production across aerospace, biomedical, and manufacturing industries. Al 7075 alloy offers low density and high-specific strength yet faces LPBF challenges such as hot cracking and porosity due to rapid solidification, thermal gradients, and a wide freezing range. To address these challenges, this study proposes an integrated computational and experimental framework to enhance the LPBF processability of Al 7xxx alloys by compositional modification. Using the Calculation of Phase Diagram approach, printable Al 7xxx compositions were designed by adding grain refiners (V and/or Ti) and a eutectic solidification enhancer (Mg) to Al 7075 alloy to enable grain refinement and eutectic solidification. Subsequent LPBF experiments and characterization tests, such as metallography (scanning electron microscopy), energy-dispersive X-ray spectroscopy, X-ray diffraction, and X-ray micro-computed tomography, confirmed the production of refined microstructures with reduced defects. This study contributes to existing approaches for producing high-quality Al 7xxx alloy parts without significant compositional deviations using an integrated computational and experimental approach. Finally, aligning with the Materials Genome Initiative, this study contributes to the development and industrial adoption of advanced materials.