Abstract

The demand for concrete production for civil construction promotes an investment by researchers and builders to find methodologies that improve their performance, the costs and less environmental degradation. Self-compacting concrete works it possible to offer a mixture with high flowability and compaction and good mechanical properties. For a better optimization of the mixtures, the statistical tool Design of Experiments (DoE) was used. Therefore, the objective of this research was to optimize an experimental dataset of high strength self-compacting mortars, through statistical analysis, using the Response Surface Methodology (RSM) for a Central Composite Design (CCD). The results showed a strong correlation between the D-Flow and T-funnel response factors, when compared with CS14h and CS28d models that showed moderate significance. The input variable w/c was the most significant model. Numerical optimization solutions showed good accuracy and high compliance for low cost and environmental impact, maintaining high performance in fresh and hardened properties.

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