ELECTRO-ELASTICITY SENSING IN AXIALLY-LOADED CONCRETE USING RECYCLED STEEL RESIDUALS AS FUNCTIONAL FILL

1 online resource (399 pages) : PDF

2018

University of North Carolina at Charlotte

Self-sensing concrete is embedded with electrostrictive materials that provides indications of strain based on variations in electrical conductivity, or its inverse, resistance. Previous works includes embedded material that vary in size from nano-scale (a thousand times smaller than the diameter of a human hair) to as large as a coarse human hair. Materials used for creating self-sensing concrete include carbon tubes, graphite, crystals, or ceramics that are added in a solid phase to the other raw materials used to create concrete. Currently, these enhancing materials used to create self-sensing concrete are uniformly distributed while the concrete is being mixed. Research, testing, and analysis described herein investigates how steel shaving waste (or recycled steel residuals) of different sizes and aspect ratios (dust and fiber) can be segregated (graded) and mixed within fresh concrete to enhance its ability to be self-sensing. The study includes the development of concrete using the recycled steel residuals (RSR) for a specific application – nuclear power plants. To prevent disaster, nuclear power generation facilities utilize heavily reinforced, mass concrete, which presents a challenging scenario for conventional nondestructive evaluation (NDE) techniques. In this study, instead of developing a specific NDE technique(s) to be externally applied to the concrete, the proposed study will focus on exploring a fundamental understanding of the physics of electron flow through concrete that has incorporated recycled steel. Goals for this work include developing a structural health monitoring technique, as an alternative to nondestructive evaluation, by formulating the concrete material to itself become a sensor and transmitting data about the level of strain of the self-sensing concrete. This study will begin with review of existing embedded sensor technologies used for structural health monitoring of reinforced concrete to detect common types and levels of material degradation. This portion of the study will include providing aid to decision makers using decision making techniques – decision tree analysis and analytical hierarchy process. Following this, relationships between resistance, resistivity, Poisson’s ratio, modulus of elasticity (Young’s modulus), and orthogonal spatial representation will be theoretically developed. The theoretical development will also include continuum theory to relate axial stress with three-dimensional deformation as a function of Poisson’s ratio and shear modulus of concrete materials shaped as cylindrical specimens. Final stages of the study is empirical. It includes axial compression testing of concrete specimens and measuring the variations in strain and correlating strain with changes in electrical conductivity. The empirical testing includes concrete with varying mixture designs developed using criteria from the American Concrete Institute (ACI) and ASTM International, load concentrations of recycled steel residuals, and undergoing monotonic loading. The theoretical and experimental research reconciled electric, elastic, and material characterizations of concrete with recycled steel residuals; and, it showed that electric conductivity/resistivity is affected by strain and that an electro-elastic relationship exists in concrete containing recycled steel residuals.

doctoral dissertations

Materials science
Civil engineering

Ph.D.

Axial Concrete Compression
Electro-Elasticity
Recycled Steel Residuals
Resistance and Strain Relation
Self-Sensing Concrete
Strain Detection

Infrastructure & Environmental Systems

Chen, Shen-En

Gergely, Janos
Tempest, Brett
Wang, Peng
Nicholas, Tom

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2018.

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http://hdl.handle.net/20.500.13093/etd:1773