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    Analytical Modeling and Experimental Validation of Wear and Frictional Noise Under Lubricated Conditions
    (Asme, 2026) Kalifa, Mohamed; Khan, Muhammad; He, Feiyang; Basit, Kanza; Doganay Kati, Hilal
    Understanding the dynamics of friction, wear, and noise under lubricated conditions is crucial for the predictive maintenance of mechanical systems; however, existing models often overlook the role of lubrication in modulating these interactions. This research presents an analytical model that combines single-degree-of-freedom (SDOF) vibration theory, Hertz contact mechanics, the Archard wear model, and the principles governing acoustic emission to predict both wear depth and sound pressure level emitted in a lubricated pin-on-disc system. Contact stiffness and wear-induced geometric changes are dynamically updated by the model, considering viscous damping from thin-film lubrication. Experiments were conducted using an Anton Paar TRB3 tribometer under lubricated conditions at realistic loads of 15, 20, and 30 N and a rotational speed of 300 rpm (corresponding to a linear sliding velocity of approximately 0.314 m/s at a 10-mm track radius). The friction noise was recorded by a microphone that was free-standing. The analytical predictions were closely aligned with the measurements taken during the tests. For mild steel, wear depth errors remained below 22%, while sound pressure predictions deviated by 14-21%. Due to its softer nature, aluminum exhibited higher wear deviations (up to 32%). Track analyses showed that lubrication decreases wear depth compared to dry sliding, and sound pressure levels are closely related to wear depth. Track analysis revealed that lubrication decreases wear depth by up to 50% compared to dry sliding, and sound pressure levels closely follow wear progression. This work improves prognostic health management systems by incorporating lubrication dynamics and tribo-acoustic phenomena, which allow for effective real-time wear and noise monitoring in industrial applications.
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    Effect of Printing Parameters on the Dynamic Characteristics of Additively Manufactured ABS Beams: An Experimental Modal Analysis and Response Surface Methodology
    (Mdpi, 2025) Doganay Kati, Hilal; He, Feiyang; Khan, Muhammad; Gokdag, Hakan; Alshammari, Yousef Lafi A.
    This study investigates the dynamic characteristics of three-dimensional (3D) printed acrylonitrile butadiene styrene (ABS) cantilever beams using Experimental Modal Analysis (EMA). The effects of Fused Deposition Modelling (FDM) process parameters-specifically infill pattern, infill density, nozzle size, and raster angle-on the natural frequency, mode shapes, and damping ratio were examined. Although numerous studies have addressed the static mechanical behaviour of FDM parts, there remains a significant gap in understanding how internal structural features and porosity influence their vibrational response. To address this, a total of seventy-two specimens were fabricated with varying parameter combinations, and their dynamic responses were evaluated through frequency response functions (FRFs) obtained via the impact hammer test. Damping characteristics were extracted using the peak-picking (half power) method. Additionally, the influence of internal porosity on damping behaviour was assessed by comparing the actual and theoretical masses of the specimens. The findings indicate that both natural frequencies and damping ratios are strongly influenced by the internal structure of the printed components. In particular, gyroid and cubic infill patterns increased structural stiffness and resulted in higher resonant frequencies, while low infill densities and triangle patterns contributed to enhanced damping capacity. Response Surface Methodology (RSM) was employed to develop mathematical models describing the parameter effects, providing predictive tools for applications sensitive to vibration. The high R2 values obtained in the RSM models based on the input variables show that these variables explain the effects of these variables on both natural frequency and damping ratio with high accuracy. The models developed (with R2 values up to 0.98) enable the prediction of modal behaviour, providing a valuable design tool for engineers optimizing vibration-sensitive components in fields such as aerospace, automotive, and electronics.