## Abstract Literature offers several examples of application of neural networks to predict fresh and hardened properties of conventional and self‐compacting concretes. In this paper, these issues are addressed to a relatively recent computational scheme given by the functional networks, by proposi
Hardened properties of self-compacting concrete — A statistical approach
✍ Scribed by F.M. Almeida Filho; B.E. Barragán; J.R. Casas; A.L.H.C. El Debs
- Publisher
- Elsevier Science
- Year
- 2010
- Tongue
- English
- Weight
- 619 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0950-0618
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✦ Synopsis
This work presents a statistical study on the variability of the mechanical properties of hardened self-compacting concrete, including the compressive strength, splitting tensile strength and modulus of elasticity. The comparison of the experimental results with those derived from several codes and recommendations allows evaluating if the hardened behaviour of self-compacting concrete can be appropriately predicted by the existing formulations. The variables analyzed include the maximum size aggregate, paste and gravel content. Results from the analyzed self-compacting concretes presented variability measures in the same range than the expected for conventional vibrated concrete, with all the results within a confidence level of 95%. From several formulations for conventional concrete considered in this study, it was observed that a safe estimation of the modulus of elasticity can be obtained from the value of compressive strength; with lower strength self-compacting concretes presenting higher safety margins. However, most codes overestimate the material tensile strength.
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