Browsing by Author "Pote, Timothy Ryan"

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    Engineering, Adoption, and Ethics of Lift-Assist Exoskeletons
    Pote, Timothy Ryan (Virginia Tech, 2022-02-01)
    Many occupations require workers to perform repetitive tasks such as lifting and bending that put significant strain on their bodies resulting in high levels of injury. Exoskeletons are one method of being able to decrease the forces on a worker while still allowing them to move. In this research, I propose a novel exoskeleton design that integrates the design process with an ethical understanding of how technology is used in society and a potential plan for an interdisciplinary approach to better adoption of this type of assistive technology. The exoskeleton is based around a novel differential that allows the exoskeleton legs to articulate during ambulatory motion while providing automatic lifting engagement by linking the force-generating mechanisms in each leg. Using a differential also allows the integration of a custom support level that can be changed during the design to better fit the varying motions found in different professions such as farming and manufacturing. Testing for this design was performed by using farming-related tasks in a laboratory to understand the level of support provided by the exoskeleton. Results show the exoskeleton provides significant support for these tasks. This validation helps build trust in the technology before it is tested on actual farmers in real-world situations and helps minimize ethical concerns regarding potential exoskeleton use. I also discuss the ethical concerns and how they can be mitigated during the design and implementation phases to ensure workers are protected and improve overall buy-in to exoskeleton technology in the workplace.
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    Optical Measurements of High-Viscosity Materials Using Variations of Laser Intensity Incident on a Semi-Rigid Vessel for use in Additive Manufacturing
    Pote, Timothy Ryan (Virginia Tech, 2016-12-12)
    Additive manufacturing is a growing field dominated by printing processes that soften and re-solidify material, depositing this material layer by layer to form the printed shape. Increasingly, researchers are pursuing new materials to enable fabrication of a wider variety of associated capabilities. This includes fabrication with high-viscosity materials of many new classes of material compositions, such as doping for magnetic or electrically conducting polymers. These additives complicate the materials deposition process by requiring complex, non-linear calibration to synchronize these new candidate materials with the additive manufacturing software and hardware. In essence, additive manufacturing is highly dependent on identifying the delicate balance between materials properties, hardware, and software-which is currently realized via a time-consuming and costly iterative calibration process. This thesis is concerned with reducing this cost of calibration, in particular by providing a time-based metric based on material viscosity for material retraction at the conclusion of each extrusion. It presents a novel non-contact method of determining the material retraction rate (during reversal of extrusion), by measuring the variation in laser intensity resulting from the deformation of the material reservoir due to change in material pressure. Commercially available laser measurement systems cost more than $20,000 and are limited to 1 μm at a 300 ms (3 Hz) sampling rate. The experimental setup presented in this thesis costs less than $100 and is capable of taking measurements of 1 - 2 μm at a 0.535 ms (1870 Hz) sampling rate. For comparison, the stepper motor driving the material extruder operates at 0.667 ms (1500 Hz). Using this experimental setup, an inverse correlation is shown to exist between the viscosity of a material and the rate at which the material is retracted. Using this correlation and a simplified material analysis process, one can approximate the retraction time necessary to calibrate new materials, thereby significantly improving initial estimated calibration settings, and thus reducing the number of calibration iterations required to ready a new material for additive manufacturing. In addition, the insight provided into the material response can also be used as the basis for future research into minimizing the calibration process.