Abstract
High-Volume Fly Ash (HVFA) concretes are seen by many as a feasible solution for sustainable, low embodied carbon construction. At the moment, fly ash is classified as a waste by-product, primarily of thermal power stations. In this paper the authors experimentally and statistically investigated the effects of mix-design factors on the mechanical properties of high-volume class F fly ash concretes. A total of 240 and 32 samples were produced and tested in the laboratory to measure compressive strength and Young's modulus respectively. Applicability of the CEB-FIP (Comite Euro-international du Béton - Fédération Internationale de la Précontrainte) and ACI (American Concrete Institute) Building Model Code (Thomas, 2010; ACI Committee 209, 1982) [1,2] to the experimentally-derived mechanical property data for HVFA concretes was established. Furthermore, using multiple linear regression analysis, Mean Squared Residuals (MSRs) were obtained to determine whether a weight- or volume-based mix proportion is better to predict the mechanical properties of HVFA concrete. The significance levels of the design factors, which indicate how significantly the factors affect the HVFA concrete's mechanical properties, were determined using analysis of variance (ANOVA) tests. The results show that a weight-based mix proportion is a slightly better predictor of mechanical properties than volume-based one. The significance level of fly ash substitution rate was higher than that of w/b ratio initially but reduced over time. © 2014 Elsevier Ltd. All rights reserved.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 432-442 |
| Number of pages | 11 |
| Journal | Construction and Building Materials |
| Volume | 54 |
| DOIs | |
| State | Published - Mar 2014 |
| Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: The experimental data reported in this publication was obtained with the kind support of U C Berkeley research grant No. KUS-l1-004021, awarded by King Abdullah University of Science and Technology (KAUST). The processing and evaluation of this data was carried out with the kind support of University of Aberdeen research grant No. ENG016 RGG0593, awarded by the Gulf Organization of Research and Development (GORD), Qatar. Furthermore, we greatly appreciate to John Masson and Dougie Craighead for their experimental assistance.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.