Behavioral assessment of intrinsically formed smart concrete using steel fibre and carbon black composite

In recent years, health monitoring consists of the periodic observation and analysis of existing systems to predict and avoid structural breakdown, thereby saving lives and significantly lowering the cost of structural maintenance and repair. Normally, non-destructive testing techniques and sensor technology are used to detect damage in concrete structures are expensive in nature. Self-diagnosing or smart concrete has emerged a new paradigm in concrete research for damage detection. Smart concrete was cast by blending functional fillers such as carbon black, and steel fibers with concrete to improve the performance. Under various load conditions, the mechanical properties of the proposed smart concrete were examined. The electrical resistance of smart concrete was measured using the Four Probe Method and the Arduino UNO software. SEM and XRD were used to investigate the microstructures of intrinsically smart concrete. Thermogravimetric analysis was employed as a Non-Destructive Testing method to observe the hydration process. Furthermore, the obtained data were linked with the electrical resistivity of the smart concrete to assess corrosion damage. The electrical resistivity method is also an economical method and effective method to monitor the rate of corrosion.