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Optimizing Electrical snd Mechanical Properties of a Polymer-Based Composite High-Deflection Strain Gauge Using Mutli-Objective Bayesian Optimization


Title: Optimizing Electrical snd Mechanical Properties of a Polymer-Based Composite High-Deflection Strain Gauge Using Mutli-Objective Bayesian Optimization

Authors: David S Wood, David Fullwood, William Christensen, Anton Bowden

DOI: 10.33599/nasampe/s.21.0511

Abstract: Polymer-based composite strain gauges are a quickly expanding technology area that exhibits advantages such as large strain capacity and high sensitivity to changes in strain. These strain gauges use an inert matrix embedded with one or more conductive fillers to exploit the elasticity of the matrix and the electrical conducting properties of the filler materials. However, determining the optimal composition of the filler materials for a particular application can be a challenging and iterative process. In the present work, the composition of a nano-nickel/silicone composite gauge was optimized based on four independent design parameters related to both mechanical and electrical performance of the gauge. Specifically, the critical impedance, critical strain, strain to failure, and initial impedance of the gauges were optimized by varying the weight ratios of Libra Gloss silicone base material, nickel nanostrands, and nickel-coated carbon fibers. The approach leveraged a combination of black-box design space modeling and multi-objective Bayesian optimization algorithm. The data from tensile tests were analyzed and compositions for a new optimal combination of parameters were found. This methodology was used to find transducer compositions that were appropriate for high strain, low-cycle wearable applications in biomechanical measurement.

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Conference: SAMPE NEXUS 2021

Publication Date: 2021/06/29

SKU: TP21-0000000511

Pages: 11

Price: FREE

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