In this paper, a shaft-bearing model is developed in order to investigate the rolling element vibrations for an angular contact ball bearing with and without defects. The shaft-bearing assembly is considered as a mass-spring system. The system shows a nonlinear characteristic under dynamic conditions. The equations of motion in radial and axial directions were obtained for shaft and rolling elements, and they were solved simultaneously with a computer simulation program. Additionally, the effect of localized defects on running surfaces (i.e., inner ring, outer ring, and ball) on the vibration of the balls is investigated. Vibration of rolling elements in the radial direction is analyzed in time and frequency domains. Characteristic defect frequencies and their components can be seen in the frequency spectra of rolling element vibrations. Comparison of the obtained results with similar studies available in literature showed reasonable qualitative agreement.

The synergistic integration of nanocomposites and 3D printing has opened a gateway to the future and is soon expected to surpass its rivalry with traditional manufacturing techniques. However, there is always a challenge associated with preparing a nanocomposite resin for polymerization-based 3D printing, which is the agglomeration of nanoparticles. Due to the high surface-area-to-volume ratio, the nanoparticles form clusters in the composite matrix, which affects the final properties. This paper aims to analyze the effects of graphene oxide (GO) dispersion on the mechanical and thermal properties of 3D-printed nanocomposites. In particular, a well-dispersed sonication dispersion route is employed for analyzing high and poor GO dispersions and their effects on different properties. After different microscopic analyses and testing, the optimum sonication condition was 30 min at an amplitude of 70%. In terms of mechanical properties, both tensile and compression strength first increased and then decreased gradually with different dispersions as well as varying GO concentrations. Furthermore, there was less or no effect on thermal stability. GO of 0.05 wt.% had the highest compression and tensile strength, while beyond 0.05 to 0.5 wt.%, both strengths reduced slowly. These 3D-printed nanocomposites have found their application in automotive, sports, and biomedical fields.

The vibrations of a shaft in rotary mechanical systems supported by angular contact ball bearings are investigated theoretically and experimentally for various preloads in this paper. In the theoretical part of the study, a dynamic bearing model is presented, a rigid shaft supported by EHL angular contact bearing has been modelled as 5 DoF. Non-linear equations of motion are solved numerically by the Runge–Kutta method. In the second part of the study, an experimental setup that enables performing different operating cases has been designed to validate the theoretical results. Theoretical and experimental data are investigated and compared in both time and frequency domains and the results are compared. It is observed from both the theoretical and experimental studies that preload has a significant effect on the vibration behaviour. Results show that the increase in preload reduces the amplitude of the variable compliance frequencies of bearing, the natural frequency of system is shifted to a higher value, and using signal processing with an envelope spectrum gives better results in spectral analysis; small deviations occur between the theoretical and the experimental data due to modulation and noise from machine elements such as gear, motor, misalignment, waviness, etc. Therefore, the presented dynamic bearing model can be used with a reasonable accuracy to examine effect of preload on the vibration of shaft-bearing system.

This study comprehensively investigates the frequency- and temperature-dependent viscoelastic properties of two elastomer materials, focusing on the comparison between experimental results and theoretical models derived from Prony series coefficients. Dynamic Mechanical Analysis (DMA) was performed across a broad temperature range of 0–100 °C and frequency range of 0.1–100 Hz to generate storage modulus and relaxation modulus data for both materials. Relaxation tests were conducted at 25 °C to further characterize the time-dependent behavior. Time–Temperature Superposition (TTS) was applied to the resultant shift factors used to fit both Williams–Landel–Ferry (WLF) and Arrhenius equations. Additionally, sinusoidal sweep tests were carried out at 0 °C, 25 °C, 50 °C, and 80 °C, with frequencies ranging from 1 Hz to 1000 Hz, to experimentally determine the natural frequencies of the elastomers. The findings demonstrate that Prony series coefficients derived from storage modulus data offer a more accurate prediction of the viscoelastic response and natural frequencies compared to those derived from relaxation modulus data. The storage modulus data closely match the experimentally observed natural frequencies, while the relaxation modulus data exhibit larger deviations, particularly at higher temperatures. The study also reveals temperature-dependent behavior, where increasing temperature reduces the stiffness of the materials, leading to lower natural frequencies. This comprehensive analysis highlights the importance of selecting appropriate modeling techniques and data sources, particularly when predicting dynamic responses under varying temperature and frequency conditions.