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Time-Dependent Strain-Resistance Relationships in Silicone Nanocomposite Sensors

Flexible high-deflection strain gauges have been demonstrated as cost-effective and accessible sensors for capturing human biomechanical deformations. However, the interpretation of these sensors is notably more complex compared to conventional strain gauges, partially owing to the viscoelastic nature of the strain gauges. On top of the non-linear viscoelastic behavior, dynamic resistance response is even more difficult to capture due to spikes in resistance during strain changes. This research examines the relationships between stress, strain, and resistance in nanocomposite sensors during dynamic strain situations. Under the assumption that both macroscopic stress and resistance are governed by microscopic stress concentrations at the junctions between nanoparticles and silicone matrix, the stress-resistance relationship is analyzed. Both stress and resistance are found to exhibit aspects of viscoelastic behavior, including creep decay and relaxation during constant strains. However, the resistance spikes are found to be more complex than a simple stress-resistance model can capture. This research then develops a model that captures the strain-resistance relationship of the sensors, including resistance spikes, during cyclical movements. The forward model, which converts strain to resistance, is comprised of four parts to accurately capture the different aspects of the sensor response: a quasi-static linear model, a spike magnitude model, a long-term creep decay model, and a short-term decay model. An inverse problem approach is used to create an inverse model, which predicts the strain vs time data that would result in the observed resistance data. The model is calibrated for a particular sensor from a small amount of cyclic data from a single test. The resulting sensor-specific model is able to accurately predict the resistance output with an R-squared value of 0.90. The inverse model is able to accurately predict key strain characteristics with a percent error of 0.5. The model can be used in a wide range of applications, including biomechanical modeling and analysis. It is found that the resistance spikes are directly correlated to the strain acceleration in terms of timing and in terms of magnitude. Poisson contraction rates and voids in the material are possible causes for resistance spikes during dynamic strain movements.

Identiferoai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-11294
Date12 April 2024
CreatorsWonnacott, Alex Mikal
PublisherBYU ScholarsArchive
Source SetsBrigham Young University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations
Rightshttps://lib.byu.edu/about/copyright/

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