Statistical Models to Predict Fresh Properties of Self-Consolidating Concrete

Abstract:

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In order to understand the influence of mixture parameters on concrete behaviour, a factorial design was employed in this investigation to identify the relative significance of primary mixture parameters and their coupled effects (interactions) on fresh properties of SCC that are of special interest to precast, prestressed applications. In addition to the 16 SCC mixtures employed, three SCC mixtures corresponding to the central point of the factorial design were prepared to estimate the degree of the experimental error for each of the modeled responses. The mixtures were evaluated to determine several key responses that affect the fresh properties of precast, prestressed concrete, including filling ability, passing ability, filling capacity, surface settlement, and column segregation. Mixture parameters modeled in this investigation included the binder content, binder type, w/cm, sand-to-total aggregate ratio (S/A), and dosage of thickening-type, viscosity-modifying admixture (VMA). The factorial design can identify potential mixtures with a given set of performance criteria that can be tried in the laboratory, hence simplifying the test protocol needed to optimize SCC.

Info:

Periodical:

Advanced Materials Research (Volumes 129-131)

Edited by:

Xie Yi and Li Mi

Pages:

853-856

DOI:

10.4028/www.scientific.net/AMR.129-131.853

Citation:

W. J. Long et al., "Statistical Models to Predict Fresh Properties of Self-Consolidating Concrete", Advanced Materials Research, Vols. 129-131, pp. 853-856, 2010

Online since:

August 2010

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Price:

$35.00

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