"Because of its unique ability to maintain high flow-ability and remain homogeneous, self-consolidating concrete (SCC) has the potential to significantly reduce the costs associated with civil infrastructure; however, the use of higher paste and lower coarse aggregate volumes than non-SCC concretes raises concerns about shear strength of SCC mixes. This research focused on the components that contribute to the concrete's ability to provide shear by aggregate interlock. Variables investigated by push-off tests included concrete compressive strength, coarse aggregate type , and volumetric content level of the coarse aggregate portion . Post-failure digital imaging software was used to confirm fresh concrete parameters in the hardened state. Additional attention was given to the global contributions of shear by the concrete in tests of pre-stressed beam members. The research suggests that SCC has advanced to the level that robust mix designs can, and have been, utilized for Civil infrastructure. Aggregate interlock results agree with previous researchers that increased concrete compressive strength and the use of river gravel rather than limestone aggregate improves shear resistance. A distinguishable trend was not identifiable for shear resistance with C.A. fraction. Digital imaging confirmed non-segregating mixtures. The precrack and push-off testing itself was analyzed and suggestions for future researchers were proposed. The SCC shear beams exhibited increased deflections, higher ultimate loads, and even different failure modes"--Abstract, page iii.
Volz, Jeffery S.
Schonberg, William P.
Civil, Architectural and Environmental Engineering
M.S. in Civil Engineering
Coreslab Structures, Inc.
Missouri. Department of Transportation
Missouri University of Science and Technology
xvii, 218 pages
© 2012 Eric B. Sells, All rights reserved.
Thesis - Open Access
Aggregates (Building materials)
Print OCLC #
Electronic OCLC #
Link to Catalog Record
Sells, Eric B., "Self-consolidating concrete for infrastructure elements shear characteristics" (2012). Masters Theses. 6931.