Critical evaluation of strength prediction methods for alkali-activated fly ash
The literature contains many proposed methods for proportioning alkali-activated binders for maximum compressive strength. Many of these methods have been developed using metakaolin, which is a relatively pure aluminosilicate powder. In recent years, fly ash has become a more common aluminosilicate...
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| Published in: | Materials and structures Vol. 48; no. 3; pp. 607 - 620 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Dordrecht
Springer Netherlands
01-03-2015
Springer Nature B.V |
| Subjects: | |
| Online Access: | Get full text |
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| Summary: | The literature contains many proposed methods for proportioning alkali-activated binders for maximum compressive strength. Many of these methods have been developed using metakaolin, which is a relatively pure aluminosilicate powder. In recent years, fly ash has become a more common aluminosilicate source for alkali activation. However, fly ash is a more complex material than metakaolin, and activated fly ash may not follow the same trends as activated metakaolin. In this study, literature-recommended strength prediction methods for alkali-activated binders, using metakaolin and fly ash, are reviewed and compared with the compressive strengths measured for eight Class F fly ash-based binders made by activation with sodium hydroxide solution. Of the eight fly ash binders in the study, six had correct performance predictions considering SiO
2
/Al
2
O
3
and Na
2
O/Al
2
O
3
optimal ratios developed for metakaolin. A published empirical equation developed to predict alkali-activated fly ash concrete strength correctly predicted relative strengths for six of the eight fly ash binders. Modifier element content is another possible indicator of reactivity, and the fly ashes in this study generally showed that fly ashes with high contents of Ca
2+
, Mg
2+
, Na
+
, and K
+
were likely to produce strong binders, although the correlation shown here was not as strong as that shown in prior studies. This work demonstrates that, while the proposed prediction methods are generally adequate, they do not cover all fly ashes and more work is needed improve prediction methods and account for the behavior of outliers. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1359-5997 1871-6873 |
| DOI: | 10.1617/s11527-014-0496-z |