|M.Sc Student||Ben-Aarosh Stav|
|Subject||Concept Validation of Intelligent Sensory Carbon-Based TRC|
|Department||Department of Civil and Environmental Engineering||Supervisor||Dr. Yiska Goldfeld|
|Full Thesis text|
This thesis aims to take a step forward in the technology involved with an intelligent textile reinforced concrete (TRC) structure that uses an embedded high performance carbon based textile for both reinforcement as well as sensing capabilities. The technology is based on continuous carbon fiber rovings knitted into grid fabric with glass yarns that act as the structural reinforcement as well as the in situ health monitoring system. By taking advantage of carbon fiber’s piezoresistive properties, and monitoring the electrical resistance of the embedded rovings, the sensory textile has the ability to sense changes in strain, and damage. This ability eliminates the requirement for additional sensory systems. This thesis faces the challenge of understanding the correlation between changes in the electrical resistance of the carbon fiber rovings and changes in the mechanical or structural behavior of a 1D TRC beam. The study faces this challenge through an experimental investigation. The goal is to correlate structural behavior of the TRC beam with changes in electrical resistance of the carbon fiber tows. Therefore, temperature changes and Data Acquisition (DAQ) system drift were compensated from the electrical measurements. The obtainable correlations presented in this study may be used in future research to model intelligent TRC beam behavior through monitoring electrical changes in carbon fiber tows.