OPTIMIZATION OF SELF-COMPACTING CONCRETE USING RESPONSE SURFACE METHODOLOGY

Abstract

The development of predicting models is necessary for an easier and more accurate design mix of self-compacting concrete. Due to the difficulty of test requirements for this type of concrete, a predicting model is useful and can be used to derive the optimum design mix. Different mixtures with varying cement, water, and superplasticizer content were created using a central composite design. A full quadratic model was chosen for all dependent variables considered such as flowability, passing ability, resistance to segregation, 28th-day compressive strength, and flexural strength. Water is the only significant factor that affects all of the rheological properties and compressive strength. Mixtures with high superplasticizer and water content show high segregation and bleeding but yield high compressive strength. Surface response and interaction profiles are developed to help the user of the models in modifying their design mix. Response surface methodology (RSM) was used to derive the optimum. The derived optimum design mix is as follows, cement is 483.72kg, 250kg for the water, and 1% for the superplasticizer The optimum design mix of SCC has a desirability of 0.812. The optimum design yield passing slump flow of 609.22mm (>550mm passing), passing l-box of 0.915 (>0.80 passing), -0.962% which can be assumed as equal to zero (<15% passing), 41.79Mpa for compressive strength and 10.33Mpa for flexural strength. The optimum design passes all rheological requirements and has acceptable compressive and flexural strengths. Although the mixture has high water content, this is due to the requirement of rheology. Low superplasticizer content is ideal for limiting segregation and bleeding.