The present work contributes to the research on the damping properties of fibre composites through an experimental approach by using the free damped vibration measurement based on impulse-force system response, the developed measurement stand and laser Doppler vibrometry. Moreover, the influence of the material configuration on the damping properties was investigated and was compared with conventional homogeneous isotropic materials. The measurement was based on the analysis of flexural vibrations generated by the Dirac impulse force, as well as on the free decaying-vibrations response; the time- and frequency-domain modal identification was employed. The fibre composites were represented as layered bidirectional long carbon- and glass-fibre composites (laminates) with different material configurations and as short carbon-fibre composites.

In this paper, we present an extensive experimental study on the dynamic mechanical properties of composites with polymer matrices, as well as a quantification of the parameters that influence these properties. Polymer-composite matrices make it possible to form any reinforcement arrangement of fibres, particles, and layers, which makes it possible to form composite materials with certain dominant mechanical properties according to the internal arrangement for the application. In this study, we focused on the dynamic properties (i.e., damping parameters, such as the loss factor (tan d), logarithmic decrement (λ), storage modulus (E′), and loss modulus (E″)) of composites with polymer matrices, including parameters such as the fibre material, fabric weaving, fibre orientation, temperature, frequency, particle size, volume of short fibres, and epoxy resin type. If other articles focus on one type of composite and 1–2 parameters, then the benefit of this article lies in our analysis of 8 mentioned parameters in the experimental analysis of 27 different types of composites with polymer matrices. The tested fibre materials were glass, aramid, and carbon; the tested woven fabrics were twill, plain, unidirectional, and satin; the temperature range was from −50 to +230 °C; the frequency was 1 Hz and 10 Hz; the particle size was 0.1–16 mm; the volume percentages of the short fibres were 3, 6, and 12 vol.% of the hybrid polymer composites and the type of polymer matrix. We used the free-damped-vibration method with vibration dynamic signal analysis and the forced-damped vibration of dynamic mechanical thermal analysis for testing. We ranked the parameters that influence the dynamic vibration properties according to the effects. Among sets of results provided in the paper, considering the storage modulus, loss modulus, and loss factor, the best results of the fibre composites were for aramid-fibre-reinforced polymers, regardless of the weave type, with an advantage for unidirectional fabric. The best results of the particle composites were for those with fine filler sizes that incorporated the short fibres.

The study of press fit bearing‐shaft joint dimensional parameters by means of analytical and numerical calculations in order to identify those parameters of the press fit joints which significantly influence the life of the bearings fitted by pressing is dealt in this paper. The mounting and conditions of fit joint are the significant factors affecting the operability and life of the bearings and consequently that of rotating machines and the whole technical units. The aim of the analysis and study is to determine the tangential and radial stress, the radial displacement, and the influence of the shape features and the size of the interference on the change of the radii in the press fit bearing‐shaft joint, in particular, the ball bearings of 6014 2RSR C3 type. Moreover, on the basis of obtained results, the paper discusses the impact of shaft dimensional and geometrical accuracy on the bearing lifetime.

The present paper focuses on the configuration possibilities of post -processor influencing mechanical properties of a given test sample produced by the FDM printer from different materials. The research consists of assessing the composite material configurations through a static tensile test conducted on 80 samples produced. The samples were produced based on ISO 527-2 standard, type 1A, with a horizontal position and a layer height of 0.2 mm. The individual samples consisted of four basic groups of materials—the pure Polylactic acid (PLA) plastic (reference sample), and three composite samples with admixtures—PLA matrix with a copper admixture, PLA matrix with an iron admixture, and PLA matrix with a steel admixture. The static tensile test was conducted at a test speed of 5 mm/min. During the research, reference samples (pure PLA) were assessed in five orientations. Samples made of the PLA composite materials with admixtures were manufactured, tested, and evaluated only in the 0° orientation. The paper concludes by comparing the results of measurement with the original material, free from additives, and with the researched influence of the orientation of the prints on the resulting mechanical properties of shear samples and their surface structure. In the conducted experiments, the lowest tensile strength has been demonstrated in test samples the orbital transitions and the upper surface layers of which were parallel to the infill.

This paper addresses the regression modeling of local environmental pollution levels for electric power industry needs, which is fundamental for the proper design and maintenance of high-voltage transmission lines and insulators in order to prevent various hazards, such as accidental flashovers due to pollution and the resultant power outages. The primary goal of our study was to increase the precision of regression models for this application area by exploiting additional input attributes extracted from satellite imagery and adjusting the modeling methodology. Given that thousands of different attributes can be extracted from satellite images, of which only a few are likely to contain useful information, we also explored suitable feature selection procedures. We show that a suitable combination of attribute selection methods (relief, FSRF-Test, and forward selection), regression models (random forest models and M5P regression trees), and modeling methodology (estimating field-measured values of target variables rather than their upper bounds) can significantly increase the total modeling accuracy, measured by the correlation between the estimated and the true values of target variables. Specifically, the accuracies of our regression models dramatically rose from 0.12–0.23 to 0.40–0.64, while their relative absolute errors were conversely reduced (e.g., from 1.04 to 0.764 for the best model).