Cement based brittle matrix composites that show deflection hardening called high performance fiber reinforced cementitious composites (HPFRCC) have the potential of offering high resiliency and environmentally sustainable benefits in numerous applications. However, more information is needed to fully understand, predict the behavior, and add functionality to HPFRCCs. This experimental research program aims to develop and characterize a new type of HPFRCC. This new HPFRCC is composed of polyvinyl alcohol (PVA) microfibers, carbon nanofibers (CNF), and a high volume of fly ash (HVA) to form a self-consolidating and self-sensing HPRFCC. The multi-functionality of the CNFs allow for increased mechanical properties and strain and damage sensing capabilities. The hybrid fiber reinforced cement composite developed is environmentally sound, due to the large amounts of recycled fly ash, with enhanced stiffness, and tensile strain capacity. This research considers the determination of fresh properties, hardened mechanical properties (elastic modulus, first cracking stress, ultimate stress, and maximum plastic strain), and electrical conductivity of the composite in response to strain, which is measured simultaneously through uniaxial tension tests. Digital Image Correlation (DIC) is used extensively to capture the tensile strain and provide a visualization of the behavior of the composite under increasing displacements. Results from this research program provide a preliminary understanding of the behavior of CNF HPFRCCs, which will aid in future research of similar composites. A standard mixing procedure is established that can be adopted in large scale processing of CNF HPFRCC. Increased mechanical properties and damage detection offers engineers with the ability to quantify structural health and optimize designs. The use of multi-functional self-sensing HPFRCCs is a step towards providing the public with a resilient and sustainable infrastructure for their communities.
|Commitee:||Carroll, J. C., Khattak, Mohammad J.|
|School:||University of Louisiana at Lafayette|
|School Location:||United States -- Louisiana|
|Source:||MAI 54/06M(E), Masters Abstracts International|
|Subjects:||Mechanics, Civil engineering, Materials science|
|Keywords:||Cnf, Hpfrcc, Hvfa, Self-sensing|
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