Self-sensing Shape Memory Polymer Composites Reinforced with Piezoresistive Smart Fabrics

Student thesis: Master's Thesis

Abstract

In recent years, there has been interest in the field of utilizing the piezoresistive response of carbon nanomaterials coated fibers and fabrics for the purpose of structural health and process monitoring to provide cheap, accurate, and reliable in-situ monitoring of the composites during manufacturing and throughout their service life. Similarly, there is an unrelated interest in the field of utilizing multilayered shape memory polymer infused fiber reinforced composites to make deployable structures for satellites and other aerospace applications to provide a cheaper and lighter alternative to conventional methods. In this work, a new previously unstudied potential was seen in combining both fields of research to study the potential of utilizing carbon nanomaterials coated smart fabrics for in-situ thermal and shape memory effect monitoring of a shape memory polymer fiber reinforced composites. Initially rGO coated fabrics were produced via dip coating in fixed solution concentration while composite samples utilizing the coated fabrics and electrical connections for monitoring were made using a highly streamlined process. The produced fabrics, polymer, and composites were characterized via several methods to observe their quality, understand their properties, and observe changes they underwent. Initially the thermal response of the composite was compared using convective and direct heating across several levels where first the coated fabric was compared to its composite counterpart followed by comparing different fabric composites and finally the impact thermal cycling and variable heating voltages was studied. Thermal testing results found little impact of polymer presence and fabric architecture on the overall response of the fabric while thermal cyclic testing and variable voltage testing showed a highly stable thermal piezoresistive response across a large range of target temperatures and heat rates maintaining nearly stable TCR values regardless of the utilized heating voltage. The shape memory response was studied at a fixed bending angle and different heating voltages using several different samples to ensure the absence of outlier or lucky results. the shape memory piezoresistive response was successfully observed and characterized via direct comparison to rate of recovery obtained via video analysis across multiple cycles for single voltage testing. Direct comparison of static thermal testing and shape memory testing of the same composite also showed very clearly the differences training of the composite and its recovery has on the resistance change profile. Observation of the shape memory piezoresistive response variation with heating voltage and hence heating rate found close and logical correlation of all variables where it was also found that the results were heavily influenced by the Tg of the polymer further confirming their accuracy.
Date of AwardDec 2021
Original languageAmerican English

Keywords

  • shape memory polymers
  • reduced graphene oxide
  • structural health monitoring
  • temperature sensor
  • piezoresistive response
  • smart materials.

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