NiCrBSi, WC-12Co and NiCrBSi with 30, 40 and 50 wt.% WC-12Co coatings were produced on low carbon steel by laser cladding with an Nd:YAG laser with a multi-jet coaxial cladding-nozzle. The microstructure properties after WC-12Co alloying were investigated by scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), electron backscatter diffraction (EBSD) and Vickers hardness tests. The resulting microstructures consisted of a γ-Ni and Ni₃B matrix, strengthened with Co and W, Ni₃Si, CrB, Cr₇C3, Cr₂₃C₆, WC/W₂C phases. In coatings with 30, 40 and 50 wt.% WC-12Co, a solid solution, strengthened multi-matrix NiCrWCo phase formed, which yielded a higher matrix hardness. Wear tests that monitored the friction coefficients were performed with a tribometer that contained a ball-on-disc configuration, Al₂O₃ counter-body and reciprocal sliding mode at room temperature. The major wear mode on the NiCrBSi coatings without the WC-12Co was adhesive with a high wear rate and visible material loss by flaking, delamination and micro-ploughing. The addition of WC-12Co to the NiCrBSi coating significantly increased the wear resistance and changed the major wear mechanism from adhesion to three-body abrasion and fatigue wear.

This paper proposes the study and implementation of a sensor with a metamaterial (MM) lens in electromagnetic nondestructive evaluation (eNDE). Thus, the use of a new type of MM, named Conical Swiss Rolls (CSR) has been proposed. These structures can serve as electromagnetic flux concentrators in the radiofrequency range. As a direct application, plates of composite materials with carbon fibers woven as reinforcement and polyphenylene sulphide as matrix with delaminations due to low energy impacts were examined. The evaluation method is based on the appearance of evanescent modes in the space between carbon fibers when the sample is excited with a transversal magnetic along z axis (TMz) polarized electromagnetic field. The MM lens allows the transmission and intensification of evanescent waves. The characteristics of carbon fibers woven structure became visible and delaminations are clearly emphasized. The flaws can be localized with spatial resolution better than λ/2000.

This paper investigated the effect of shot peening on the strength and corrosion properties of 6082-T651 aluminium alloy. The microstructure, surface roughness, microhardness, residual stresses, and corrosion behaviour were investigated and compared with those of untreated aluminium alloy. Cracks and delaminations in the surface layer could only be seen on the treated specimens at a working pressure of 4 bar and 8 bar, while no such effect was observed at a working pressure of 1.6 bar. The surface roughness was increased more than 15 times after shot peening at a working pressure of 8 bar. Shot peening resulted in an increase in microhardness of 27% and a deeper layer with higher compressive residual stresses compared to the untreated specimens. All treated specimens exhibited improved corrosion resistance with a lower degree of anodic dissolution. The current density of the treated specimen with the lowest surface roughness was more than two-fold lower than that of the untreated specimen.

This study presents the results of acoustic emission (AE) measurements and characterization in the loading of biocomposites at room and low temperatures that can be observed in the aviation industry. The fiber optic sensors (FOS) that can outperform electrical sensors in challenging operational environments were used. Standard features were extracted from AE measurements, and a convolutional autoencoder (CAE) was applied to extract deep features from AE signals. Different machine learning methods including discriminant analysis (DA), neural networks (NN), and extreme learning machines (ELM) were used for the construction of classifiers. The analysis is focused on the classification of extracted AE features to classify the source material, to evaluate the predictive importance of extracted features, and to evaluate the ability of used FOS for the evaluation of material behavior under challenging low-temperature environments. The results show the robustness of different CAE configurations for deep feature extraction. The combination of classic and deep features always significantly improves classification accuracy. The best classification accuracy (80.9%) was achieved with a neural network model and generally, more complex nonlinear models (NN, ELM) outperform simple models (DA). In all the considered models, the selected combined features always contain both classic and deep features.

This study focuses on investigating the fatigue and wear behaviour of carbon fibre reinforced polymer (CFRP) gears, which have shown promising potential as lightweight and high-performance alternatives to conventional gears. The gears were fabricated via an autoclave process using an 8-layer composite made of T300 plain weave carbon fabric and ET445 resin and were tested in pair with a 42CrMo4 steel pinion and under nominal tooth bending stress ranging from 60 to 150 MPa. In-situ temperature monitoring was performed, using an infrared camera, and wear rates were regularly assessed. The result of the wear test indicates adhesive wear and three-body abrasion wear mechanisms between the CFRP gears and the steel counterpart. A finite element analysis was performed to examine the in-mesh contact and root stress behaviour of both new and worn gears at various loads and a specified running time. The results point to a substantial divergence from ideal meshing and stress conditions as the wear level is increased. The fatigue results indicated that the CFRP gears exhibited superior performance compared to conventional plastic and composite short-fibrous polymer gears. The described composite gear material was additionally compared with two other composite configurations, including an autoclave-cured T700S plain weave prepreg with DT120 toughened resin and a vacuum-impregnated T300 spread plain weave carbon fabric with LG 900 UV resin. The study found that the use of the T700S-DT120 resulted in additional improvements.