Scholarly Works, Mechanical Engineering

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Browsing Scholarly Works, Mechanical Engineering by Author "Alemi, Mohammad Mehdi"

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    Modeling the Metabolic Reductions of a Passive Back-Support Exoskeleton
    Alemi, Mohammad Mehdi; Simon, Athulya A.; Geissinger, Jack H.; Asbeck, Alan T. (2022-01-13)
    Despite several attempts to quantify the metabolic savings resulting from the use of passive back-support exoskeletons (BSEs), no study has modeled the metabolic change while wearing an exoskeleton during lifting. The objectives of this study were to: 1) quantify the metabolic reductions due to the VT-Lowe's exoskeleton during lifting; and 2) provide a comprehensive model to estimate the metabolic reductions from using a passive BSE. In this study, 15 healthy adults (13M, 2F) of ages 20 to 34 years (mean=25.33, SD=4.43) performed repeated freestyle lifting and lowering of an empty box and a box with 20% of their bodyweight. Oxygen consumption and metabolic expenditure data were collected. A model for metabolic expenditure was developed and fitted with the experimental data of two prior studies and the without-exoskeleton experimental results. The metabolic cost model was then modified to reflect the effect of the exoskeleton. The experimental results revealed that VT-Lowe's exoskeleton significantly lowered the oxygen consumption by ~9% for an empty box and 8% for a 20% bodyweight box, which corresponds to a net metabolic cost reduction of ~12% and ~9%, respectively. The mean metabolic difference (i.e., without-exo minus with-exo) and the 95% confidence interval were 0.36 and (0.2-0.52) [Watts/kg] for 0% bodyweight, and 0.43 and (0.18-0.69) [Watts/kg] for 20% bodyweight. Our modeling predictions for with-exoskeleton conditions were precise, with absolute freestyle prediction errors of <2.1%. The model developed in this study can be modified based on different study designs, and can assist researchers in enhancing designs of future lifting exoskeletons.
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    Rail Surface Measurement And Multi-Scale Modeling Of Wheel-Rail Contact
    Alemi, Mohammad Mehdi; Taheri, Saied; Ahmadian, Mehdi (ASME, 2016-01-01)
    In railroad industries, one of the most important concepts is the ability to model and estimate the friction between the rail and the wheels. Overall, creating a general friction model is a challenging task because friction is influenced by different factors such as surface metrology, properties of materials in contact, surface contamination, flash temperature, normal load, sliding velocity, surface deformation, inter-surface adhesion, etc. Moreover, increase in the number of interfering factors in the process would add to the complexity of the friction model. Therefore, reliable prediction of the friction both theoretically and empirically is sensitive to how the model parameters are measured. Due to both safety and energy concerns, any attempts towards a better understanding of wheel/rail contact are considered important for the railroad industry. In this study, surface characteristics of four rail surfaces were measured at 20 microns over a rectangular area using a portable Nanovea Jr25 optical surface profilometer and the results were studied using various statistical procedures and Fractal theory. Furthermore, a 2D rectangular area was measured in this study because 1D height profile doesn’t capture all the necessary statistical properties of the surface. For surface roughness characterization, the 3D parameters such as root-mean-square (RMS) height, skewness, kurtosis and other important parameters were obtained according to ISO 25178 standard. To verify the statistical results and fractal analysis, a British Pendulum Skid Resistance Tester was used to measure the average sliding coefficients of friction based on several experiments over a 5 cm contact length for all four rail sections. The results supported this fact that the rail surface with lower fractal dimension number has the lower friction. In effect, the larger fractal dimension number simply would add more microtexture features to the contact surface which potentially increases the friction. This paper will discuss the results and the next steps towards a better understanding of the friction potential between the wheels and the track.