Experimental dataset from a central composite design to develop mortars with self-compacting properties and high...

Area of Science:

• Materials Science
• Civil Engineering
• Construction Materials

Background:

• Concrete workability and compressive strength are key properties for fresh and hardened concrete.
• Optimizing concrete compositions, especially for self-compacting properties, requires scientific understanding and predictive models.
• Existing research highlights the need for systematic studies on mortar mix design to achieve desired performance characteristics.

Purpose of the Study:

• To present experimental data on mortar compositions for self-compacting concrete.
• To apply response models to experimental data for optimizing mortar mix designs.
• To investigate the relationship between mix proportions and key performance indicators of concrete.

Main Methods:

• Utilized a central composite design (CCD) with five independent variables: Water/Cement, Superplasticizer/Powder, Water/Powder, Sand/Mortar, and Fine Sand/Sand.
• Conducted 64 mortar trial mixes, including a 2^5 factorial design, axial runs, central runs, and validation mixes.
• Measured workability (D-flow, t-funnel) and mechanical properties (tensile and compressive strength at 24h) as dependent variables.

Main Results:

• The study generated a comprehensive dataset on mortar properties based on a CCD.
• Response models were developed and validated using the experimental data.
• The experimental framework allows for the identification of optimized mix compositions for self-compacting concrete.

Conclusions:

• The presented experimental approach and response modeling are effective for optimizing mortar mix designs.
• The findings contribute to a better scientific understanding of self-compacting concrete properties.
• The optimized compositions derived from this study can enhance the performance of fresh and hardened concrete.