Journal Published Online: 14 February 2019
Volume 8, Issue 1

Normality of Post-Crack Performance Data for Fiber-Reinforced Concrete

CODEN: ACEMF9

Abstract

With the increasing use of fiber-reinforced concrete (FRC) for civil infrastructure projects, challenges have become apparent in quality control (QC) testing for this material. The most common problem is high variability, but a secondary problem is identifying the most appropriate probability distribution function (PDF) for post-crack performance data. This article has examined the second of these challenges. It is widely assumed that the normal PDF most reliably describes the distribution of outcomes for many stochastic processes. Most of the conventions underlying probabilistic modeling of engineering processes are therefore predicated upon a normal distribution of material properties. However, evidence exists that other functions, such as the Weibull, lognormal, or gamma distribution functions, may be more appropriate representations of the distribution of test results for some post-crack performance parameters related to FRC, such as fatigue life. The present investigation has examined a large body of QC data to identify the most reliable function describing the probability distribution of post-crack performance of FRC as obtained from ASTM C1550, Standard Test Method for Flexural Toughness of Fiber Reinforced Concrete (Using Centrally Loaded Round Panel), and ASTM C1609/C1609M, Standard Test Method for Flexural Performance of Fiber-Reinforced Concrete (Using Beam with Third-Point Loading). The results demonstrate that the normal and lognormal functions model the distribution of post-crack performance data obtained for FRC equally well. However, the normal function produces the best fit for data assembled from multiple specimen sets, thereby confirming the validity of the central limit theorem. Moreover, a derivative of the normal function also reliably predicts the distribution of variances for data sets comprising a small number of replicate test results.

Author Information

Bernard, E. S.
Technologies in Structural Engineering Pty. Ltd., Penrith, NSW, Australia
Xu, G. G.
Technologies in Structural Engineering Pty. Ltd., Penrith, NSW, Australia
Pages: 13
Price: $25.00
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Details
Stock #: ACEM20180054
ISSN: 2379-1357
DOI: 10.1520/ACEM20180054