Appropriate drying shrinkage prediction models for lightweight concrete containing coarse agro-waste aggregate
Oil palm shell (OPS) agro-waste aggregate was successfully employed to produce lightweight aggregate concretes. However, the high rate of drying shrinkage for this type of concrete can impair the intended functionality of the structures or reduce service life. In this study, drying shrinkage strain...
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Veröffentlicht in: | Journal of Building Engineering 2020-05, Vol.29, p.101148, Article 101148 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Oil palm shell (OPS) agro-waste aggregate was successfully employed to produce lightweight aggregate concretes. However, the high rate of drying shrinkage for this type of concrete can impair the intended functionality of the structures or reduce service life. In this study, drying shrinkage strain behaviour of normal-weight and lightweight aggregate concretes was compared with prediction models. Twelve different mix proportions were designed by using of crushed granite (NWA) and OPS aggregates as replacement of the NWA at increasing intervals of 20%. Actual drying shrinkage at early and long-term ages (275 days) was compared against theoretical results from drying shrinkage prediction models such as ACI209R, EN1992, GL2000, B3 and SAK. Comparison between the test results and predicted results indicated that the EN1992 was the most precise model at early-ages as well as GL2000 at long-term ages. In contrast, B3 was found the least precise model at both early and long-term ages.
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•Addition of fly ash to the concrete mixtures generated higher drying shrinkage.•No suitable prediction model can be proposed for concretes containing high volume of oil palm shell lightweight aggregates.•EN1992 was the best model for prediction of drying shrinkage at early-ages as well as GL2000 at long-term ages.•B3 model was considered as a poor drying shrinkage prediction model for all mixes in both groups at early and long-term ages. |
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ISSN: | 2352-7102 2352-7102 |
DOI: | 10.1016/j.jobe.2019.101148 |